shitton

Add explicit chat capability tracking, expose formatted runtime capabilities
in the info command, and support a max context size option for user AI settings.

Also update Ollama base URL resolution to use OLLAMA_ADDRESS and simplify
provider chat command execution.

.env.example

@@ -11,18 +11,6 @@ BOT_TOKEN=your_bot_token_here
 # To get your ID: send /id command to the bot and use the "from id" value
 CREATOR_ID=your_user_id_here
 
-# Database connection
-# Leave empty for local SQLite in ~/.local/share/tg-chat-bot/database.db.
-# Set DATA_PATH=data if you want to keep files inside the repo.
-# Set to postgres://... for PostgreSQL.
-# Set to :memory: for ephemeral in-memory SQLite.
-DATABASE_URL=
-DATA_PATH=
-
-# Docker Compose image tag override
-# Used by docker-compose.yml when pulling ghcr.io/melod1n/tg-chat-bot
-IMAGE_TAG=1.0.0
-
 # ============================================
 # BOT SETTINGS (Optional)
 # ============================================
@@ -43,27 +31,9 @@ ONLY_FOR_CREATOR_MODE=false
 # Use user names in AI prompts
 USE_NAMES_IN_PROMPT=true
 
-# Disable all built-in local tools and keep only MCP tools
-DISABLE_LOCAL_TOOLS=false
-
-# Filter built-in local tools by name.
-# LOCAL_TOOL_ALLOWLIST lets through only the listed tools.
-# LOCAL_TOOL_DENYLIST removes the listed tools.
-# Examples:
-# LOCAL_TOOL_ALLOWLIST=get_datetime,web_search
-# LOCAL_TOOL_DENYLIST=shell_execute,python_interpreter
-LOCAL_TOOL_ALLOWLIST=
-LOCAL_TOOL_DENYLIST=
-
 # Custom system prompt for AI (or put it into data/SYSTEM_PROMPT.md)
 SYSTEM_PROMPT=
 
-# Tool ranker fallback policy:
-# MAIN_MODEL - rank tools through the provider's chat model if a dedicated ranker target is missing or fails
-# ALL_TOOLS - skip ranker fallback and allow all tools
-# NO_TOOLS - skip ranker fallback and allow no tools
-TOOL_RANKER_FALLBACK_POLICY=ALL_TOOLS
-
 # Maximum photo size in pixels
 MAX_PHOTO_SIZE=1280
 
@@ -74,6 +44,17 @@ LOCALES_DIR=locales
 # AI MODELS CONFIGURATION (Optional)
 # ============================================
 
+# Google Gemini
+GEMINI_API_KEY=
+# google: official Gemini API via @google/genai; openai: OpenAI-compatible Gemini endpoint; auto: infer from GEMINI_BASE_URL
+GEMINI_API_MODE=google
+GEMINI_MODEL=gemini-2.5-flash
+GEMINI_IMAGE_MODEL=gemini-2.5-flash-image
+GEMINI_TRANSCRIPTION_MODEL=gemini-2.5-flash
+GEMINI_TTS_MODEL=gemini-2.5-flash-preview-tts
+GEMINI_TTS_VOICE=Kore
+GEMINI_MAX_CONCURRENT_REQUESTS=3
+
 # Mistral AI
 MISTRAL_API_KEY=
 MISTRAL_MODEL=mistral-small-latest
@@ -103,10 +84,6 @@ OLLAMA_MAX_CONCURRENT_REQUESTS=1
 # OpenAI
 OPENAI_API_KEY=
 OPENAI_BASE_URL=
-# Backend mode:
-# official = OpenAI responses API
-# compatible = OpenAI-compatible chat.completions servers like llama.cpp
-OPENAI_BACKEND=official
 OPENAI_MODEL=gpt-4.1-nano
 OPENAI_IMAGE_MODEL=gpt-image-1-mini
 OPENAI_TRANSCRIPTION_MODEL=gpt-4o-mini-transcribe
@@ -115,29 +92,20 @@ OPENAI_TTS_VOICE=alloy
 OPENAI_TTS_INSTRUCTIONS=
 OPENAI_MAX_CONCURRENT_REQUESTS=3
 
-# MCP servers
-# JSON array or {"mcpServers": {"name": {...}}}
-# Stdio example:
-# MCP_SERVERS=[{"name":"local-tools","transport":"stdio","command":"node","args":["./mcp-server.js"]}]
-# HTTP example:
-# MCP_SERVERS=[{"name":"remote-tools","transport":"http","url":"https://example.com/mcp"}]
-MCP_SERVERS=
-
 # Per-capability AI endpoint overrides
 # Pattern:
 # <PROVIDER>_<CAPABILITY>_MODEL=
 # <PROVIDER>_<CAPABILITY>_BASE_URL=
 # <PROVIDER>_<CAPABILITY>_API_KEY=
 #
-# Providers: OLLAMA, MISTRAL, OPENAI
+# Providers: OLLAMA, GEMINI, MISTRAL, OPENAI
 # Capabilities: CHAT, VISION, OCR, THINKING, EXTENDED_THINKING, TOOLS, AUDIO,
 # DOCUMENTS, OUTPUT_IMAGES, SPEECH_TO_TEXT, TEXT_TO_SPEECH
 # Endpoint aliases are also supported: *_ENDPOINT and *_ADDRESS.
 # Provider-wide fallback endpoints: OPENAI_BASE_URL, MISTRAL_BASE_URL,
-# OLLAMA_ADDRESS or OLLAMA_BASE_URL.
+# GEMINI_BASE_URL, OLLAMA_ADDRESS or OLLAMA_BASE_URL.
 # Capability aliases are also supported: IMAGE, THINK, RAG, EMBEDDING,
 # TRANSCRIPTION, STT, TTS.
-# Backend override: OPENAI_BACKEND=official|compatible.
 #
 # Examples:
 # OPENAI_SPEECH_TO_TEXT_MODEL=gpt-4o-mini-transcribe

.github/workflows/ci.yml

@@ -1,55 +0,0 @@
-name: CI
-
-on:
-  push:
-  pull_request:
-
-jobs:
-  node:
-    runs-on: ubuntu-latest
-
-    steps:
-      - name: Checkout
-        uses: actions/checkout@v4
-
-      - name: Set up Node.js
-        uses: actions/setup-node@v4
-        with:
-          node-version: 20.19.0
-          cache: npm
-
-      - name: Install dependencies
-        run: npm ci
-
-      - name: Lint
-        run: npm run lint
-
-      - name: Typecheck
-        run: npm run typecheck
-
-      - name: Build
-        run: npm run build
-
-  bun:
-    runs-on: ubuntu-latest
-
-    steps:
-      - name: Checkout
-        uses: actions/checkout@v4
-
-      - name: Set up Bun
-        uses: oven-sh/setup-bun@v2
-        with:
-          bun-version: latest
-
-      - name: Install dependencies
-        run: bun install --frozen-lockfile
-
-      - name: Lint
-        run: bun run lint
-
-      - name: Typecheck
-        run: bun run typecheck
-
-      - name: Build
-        run: bun run build

OPENAI_COMPATIBLE_TARGET_IMPLEMENTATION.md

@@ -1,314 +0,0 @@
-# OPENAI Compatible Target Implementation
-
-## Purpose
-
-Add a separate execution path for OpenAI-compatible backends such as `llama.cpp`, while keeping the current official OpenAI path unchanged.
-
-## Checklist
-
-- [x] Add explicit OpenAI backend mode in config
-- [x] Route OpenAI requests to separate official and compatible runners
-- [x] Keep official OpenAI on `responses.create(...)`
-- [x] Add compatible `chat.completions.create(...)` runner
-- [x] Add compatible tool-call extractors
-- [x] Add backend selection tests
-- [x] Add basic memory/config regression coverage
-- [x] Normalize compatible streaming tool-call assembly
-- [x] Preserve file upload behavior in compatible backend
-- [x] Guard unsupported OpenAI-only tools for compatible backend
-- [x] Add environment docs and example config entries
-- [x] Add real-server integration coverage for compatible backend
-- [x] Revisit shared orchestration extraction for further deduplication
-
-## Non-Goals
-
-1. Do not change the current official OpenAI `responses.create(...)` behavior.
-2. Do not auto-switch behavior only because `OPENAI_BASE_URL` is set.
-3. Do not merge compatible backend quirks into the official OpenAI runner.
-4. Do not remove or weaken existing tool ranking, memory, RAG, logging, or upload behavior.
-
-## Current State
-
-1. `src/ai/unified-ai-runner.openai.ts` currently uses the official `responses` API.
-2. `src/ai/provider-adapters.ts` already has provider-specific adapters and tool/result mapping.
-3. `src/ai/provider-adapter-contract.ts` already contains `responses`-style extractors.
-4. `src/ai/openai-chat-message.ts` currently models `responses`-style messages, not `chat.completions` tool messages.
-5. `src/ai/unified-ai-request-pipeline.ts` prepares chat context and runtime state before the model call.
-6. `src/ai/ai-runtime-target.ts` resolves provider targets, base URLs, models, and keys.
-7. `src/ai/unified-ai-runner.tool-ranker.ts` already uses a `chat.completions`-style call path, which is closer to compatible backends.
-
-## Target Architecture
-
-1. Official OpenAI backend stays on `responses.create(...)`.
-2. Compatible OpenAI backend uses `chat.completions.create(...)`.
-3. Backend selection is explicit through config, for example `OPENAI_BACKEND=official|compatible`.
-4. Shared preparation logic remains common.
-5. Transport-specific request formatting and response parsing are split.
-
-## Configuration Design
-
-1. Add a new config value `OPENAI_BACKEND`.
-2. Allowed values should be `official` and `compatible`.
-3. Default must be `official`.
-4. Keep `OPENAI_BASE_URL` as a transport setting only.
-5. `OPENAI_BASE_URL` must not imply compatible mode by itself.
-6. Extend environment schema and runtime config to expose this value.
-7. Update env docs and example env files.
-
-## Step 1: Config and Target Selection
-
-1. Update `src/common/environment.ts`.
-2. Add a new environment field for backend mode.
-3. Add setters if the codebase uses runtime env mutation in tests.
-4. Update the startup schema and runtime snapshot.
-5. Add tests for default value and explicit `compatible` selection.
-
-Expected result:
-- Official OpenAI stays unchanged by default.
-- Explicit `OPENAI_BACKEND=compatible` selects the new execution path.
-
-## Step 2: Split Runner Selection
-
-1. Update the unified AI execution entry point.
-2. Add a small backend selector for OpenAI targets.
-3. Route official mode to the current runner.
-4. Route compatible mode to a new compatible runner.
-5. Keep other providers untouched.
-
-Expected result:
-- One codepath for official OpenAI.
-- One codepath for OpenAI-compatible servers.
-
-## Step 3: Shared Orchestration Extraction
-
-1. Identify logic that is identical for both OpenAI branches.
-2. Extract common orchestration into a shared helper where possible.
-3. Keep these pieces shared:
-   - memory prompt injection
-   - tool ranking
-   - tool loop control
-   - logging and timing
-   - cancellation handling
-   - file upload post-processing
-   - document RAG preparation and cleanup
-4. Keep transport-specific pieces separate:
-   - request shape
-   - response parsing
-   - tool result message shape
-   - streaming event parsing
-
-Expected result:
-- Less duplicate logic.
-- Cleaner separation between official and compatible behavior.
-
-## Step 4: Compatible Message Model
-
-1. Update `src/ai/openai-chat-message.ts` or create a sibling type file for compatible chat messages.
-2. Model `system`, `user`, `assistant`, and `tool` roles explicitly.
-3. Support `tool_calls` on assistant messages.
-4. Support `tool_call_id` on tool result messages.
-5. Preserve support for text and multimodal user content where the backend supports it.
-6. Avoid forcing `responses` output types into `chat.completions`.
-
-Expected result:
-- Compatible runner can build valid `chat.completions` message arrays.
-
-## Step 5: Compatible Contract Extractors
-
-1. Extend `src/ai/provider-adapter-contract.ts`.
-2. Add extractors for `chat.completions` tool calls.
-3. Add extractors for `chat.completions` streaming tool call deltas.
-4. Keep existing `responses` extractors intact.
-5. Normalize tool call IDs, names, and argument text the same way as existing extractors.
-6. Ensure arguments are always represented as JSON text for the tool loop.
-
-Expected result:
-- Compatible runner can parse tool calls from both normal and streaming responses.
-
-## Step 6: Compatible Provider Adapter
-
-1. Update `src/ai/provider-adapters.ts`.
-2. Add a separate adapter or branch for OpenAI-compatible chat.completions behavior.
-3. Reuse existing tool ranking where safe.
-4. Make `appendToolResults(...)` emit `role: "tool"` messages with `tool_call_id`.
-5. Keep official OpenAI adapter outputting `function_call_output`.
-6. Keep Mistral and Ollama unchanged.
-
-Expected result:
-- Each backend uses the tool result shape it expects.
-
-## Step 7: Compatible Runner Implementation
-
-1. Create a new file such as `src/ai/unified-ai-runner.openai-compatible.ts`.
-2. Use `openai.chat.completions.create(...)`.
-3. Pass `messages`, `tools`, `model`, `stream`, and `signal`.
-4. Map system prompt and memory prompt into the `messages` array correctly.
-5. Keep the tool loop structure from the current runner.
-6. Append assistant tool-call messages and tool result messages between rounds.
-7. Continue until no tool calls remain or max rounds is reached.
-
-Expected result:
-- Compatible backends can complete multi-round tool flows.
-
-## Step 8: Tool Call Loop Semantics
-
-1. Preserve `MAX_TOOL_ROUNDS`.
-2. Preserve tool ranking before each round.
-3. Preserve memory tool selection.
-4. Preserve file search injection when document RAG is active.
-5. Preserve file upload post-processing.
-6. Preserve max-rounds warnings and continuation decisions.
-7. Keep the final text visible in the stream message exactly as today.
-
-Expected result:
-- Compatible backend behaves like the current runner from the user’s perspective.
-
-## Step 9: Streaming Behavior
-
-1. Implement streaming event handling for `chat.completions`.
-2. Parse text deltas and append them to `TelegramStreamMessage`.
-3. Parse `delta.tool_calls` and keep incremental tool-call state.
-4. Update status text when tool usage starts and ends.
-5. Keep image generation and file-search status handling if the backend emits compatible signals.
-6. Finalize the stream only after the terminal completion event.
-
-Expected result:
-- Streaming works without losing tool call state.
-
-## Step 10: Tool Result Handling
-
-1. After each tool execution round, append tool results using the compatible message format.
-2. Ensure each tool result keeps the correct `tool_call_id`.
-3. Preserve the existing file upload hook.
-4. If upload fails, convert the failure into a tool result error string.
-5. Preserve the same tool memory map behavior.
-
-Expected result:
-- The backend receives a valid message history for the next round.
-
-## Step 11: Prompt and Memory Injection
-
-1. Keep `buildSystemInstruction(...)` as the source of system prompt assembly.
-2. Keep `buildUserMemoryPrompt(...)` injected as a separate block.
-3. Preserve the explicit separation between assistant memory and user memory.
-4. Preserve the `user.md` and `system.md` memory layout.
-5. Ensure compatible backend receives the same semantic prompt content.
-
-Expected result:
-- Memory behavior stays identical across official and compatible backends.
-
-## Step 12: Tool Ranking Compatibility
-
-1. Review `src/ai/unified-ai-runner.tool-ranker.ts`.
-2. Verify whether the current JSON response handling is safe for compatible backends.
-3. If a backend cannot guarantee strict JSON mode, add a fallback parser.
-4. Keep ranking inputs and outputs consistent across both branches.
-5. Do not weaken tool selection heuristics.
-
-Expected result:
-- Tool ranking remains deterministic enough for both branches.
-
-## Step 13: File Search and RAG
-
-1. Keep document RAG preparation in the request pipeline.
-2. Keep vector store preparation for official OpenAI.
-3. Decide whether compatible backend supports file search or needs a no-op fallback.
-4. If unsupported, guard the tool list so the compatible backend never receives unsupported tools.
-5. Keep cleanup behavior for temporary artifacts.
-
-Expected result:
-- Compatible backend does not receive tools it cannot execute.
-
-## Step 14: Error Handling
-
-1. Preserve abort handling.
-2. Preserve response failure handling.
-3. Preserve stream error handling.
-4. Surface backend-specific incompatibilities as explicit errors.
-5. Do not silently fall back from compatible to official mode.
-6. Keep logs actionable.
-
-Expected result:
-- Failures are obvious and debuggable.
-
-## Step 15: Logging and Observability
-
-1. Keep the current AI logs and duration tracking.
-2. Add backend mode to log metadata.
-3. Log tool calls, tool outputs, and round transitions in both branches.
-4. Preserve existing observability hooks.
-5. Add explicit labels for official vs compatible runs.
-
-Expected result:
-- Debugging remains easy after the split.
-
-## Step 16: Tests
-
-1. Add unit tests for backend selection.
-2. Add unit tests for compatible message conversion.
-3. Add unit tests for compatible tool call extraction.
-4. Add integration tests for a tool-call round trip using mocked `chat.completions`.
-5. Add tests proving the official `responses` path is unchanged.
-6. Add tests for streaming tool call parsing if the backend supports it.
-7. Add tests for fallback behavior in the tool ranker if needed.
-
-Expected result:
-- Both branches are covered and regressions are visible quickly.
-
-## Step 17: Suggested File Changes
-
-1. `src/common/environment.ts`
-2. `src/ai/ai-runtime-target.ts`
-3. `src/ai/unified-ai-request-pipeline.ts`
-4. `src/ai/unified-ai-runner.openai.ts`
-5. `src/ai/unified-ai-runner.openai-compatible.ts`
-6. `src/ai/provider-adapter-contract.ts`
-7. `src/ai/provider-adapters.ts`
-8. `src/ai/openai-chat-message.ts`
-9. `src/ai/unified-ai-runner.tool-ranker.ts`
-10. `test/*.test.mjs`
-11. `.env.example`
-12. Documentation files for backend selection
-
-## Implementation Order
-
-1. [x] Add config flag and wire it through environment parsing.
-2. [x] Add backend selection logic.
-3. [x] Add compatible message and extractor support.
-4. [x] Create the compatible runner.
-5. [x] Reuse shared orchestration where possible.
-6. [x] Wire tests.
-7. [x] Verify official behavior is unchanged.
-8. [x] Verify compatible backend works with a real OpenAI-compatible server.
-
-## Verification Plan
-
-1. Run unit tests.
-2. Run integration tests.
-3. Verify official OpenAI path still uses `responses.create(...)`.
-4. Verify compatible path uses `chat.completions.create(...)`.
-5. Verify a `llama.cpp`-style server can complete a tool loop.
-6. Verify memory tools still work.
-7. Verify document RAG and file upload behavior do not regress.
-
-## Risks
-
-1. Some OpenAI-compatible servers do not support every official OpenAI feature.
-2. Streaming tool call deltas may differ across providers.
-3. JSON-mode assumptions in the ranker may not hold for all compatible servers.
-4. Tool schema filtering may need backend-specific allowlists.
-5. Message conversion mistakes can break tool loops silently if not tested.
-
-## Acceptance Criteria
-
-1. Official OpenAI behavior is unchanged.
-2. Compatible backend can run a full chat loop with tools.
-3. Tool calls are correctly extracted and executed.
-4. Tool results are appended in the correct format.
-5. Memory injection still works.
-6. Document RAG and file upload behavior remain functional or fail explicitly.
-7. Tests cover both branches.
-
-## Final Note
-
-The key design rule is simple: keep official OpenAI `responses` behavior intact, and introduce OpenAI-compatible `chat.completions` behavior as a separate backend mode with its own parsing and message shape.

README.md

@@ -1,50 +1,12 @@
 # Telegram Chat Bot
 
-Bot for Telegram with a lot of commands and AI (Ollama/Mistral/OpenAI) written in TypeScript + NodeJS/Bun runtime + SQLite/PostgreSQL/in-memory storage
+Bot for Telegram with a lot of commands and AI (Ollama/Gemini/Mistral) written in TypeScript + NodeJS/Bun runtime + Drizzle ORM (SQLite DB)
 
 ## Quick Start
 
 ```bash
 cp .env.example .env
-# Edit .env: add BOT_TOKEN, CREATOR_ID and configure optional AI models (MISTRAL_API_KEY, OPENAI_API_KEY, OLLAMA_ADDRESS)
-# For OpenAI-compatible servers (llama.cpp, etc.), set OPENAI_BACKEND=compatible and OPENAI_BASE_URL.
-# Optional: set DATABASE_URL to postgres://... for PostgreSQL or :memory: for ephemeral SQLite.
-# Optional: set DATA_PATH if you want to override the default local storage directory.
-```
-
-**With Bun (Recommended):**
-```bash
-bun install
-bun run build && bun start
-```
-
-**With Node.js:**
-```bash
-npm install
-npm run build && npm start
-```
-
-The bot initializes and migrates its database schema automatically on startup.
-`/exportdb` sends the SQLite file when available, plus a `.sql` dump and a JSON backup.
-`/importdb` restores the database from the JSON backup format.
-
-MCP tool servers can be configured through `MCP_SERVERS` in `.env`. Use a JSON array with `stdio` or `http` transports. Example:
-
-```bash
-MCP_SERVERS=[{"name":"local-tools","transport":"stdio","command":"node","args":["./mcp-server.js"]}]
-```
-
-If you want to disable all built-in local tools and use only MCP tools, set:
-
-```bash
-DISABLE_LOCAL_TOOLS=true
-```
-
-If you want a partial filter instead, use tool names:
-
-```bash
-LOCAL_TOOL_ALLOWLIST=get_datetime,web_search
-LOCAL_TOOL_DENYLIST=shell_execute,python_interpreter
+# Edit .env: add BOT_TOKEN, CREATOR_ID and configure optional AI models (GEMINI_API_KEY, MISTRAL_API_KEY, OLLAMA_ADDRESS)
 ```
 
 For local Ollama document RAG, install an embedding model locally and set it in `.env`:
@@ -54,19 +16,24 @@ ollama pull nomic-embed-text
 OLLAMA_EMBEDDING_MODEL=nomic-embed-text
 ```
 
-Tool ranker fallback is configurable via `TOOL_RANKER_FALLBACK_POLICY`:
+**With Bun (Recommended):**
+```bash
+bun install
+bunx drizzle-kit generate && bunx drizzle-kit migrate
+bun run build && bun start
+```
 
-- `MAIN_MODEL` - use the provider's main chat model to rank tools if a dedicated ranker target is missing or fails
-- `ALL_TOOLS` - skip tool ranking fallback and allow all tools
-- `NO_TOOLS` - skip tool ranking fallback and allow no tools
-
-The default is `ALL_TOOLS`.
+**With Node.js:**
+```bash
+npm install
+npx drizzle-kit generate && npx drizzle-kit migrate
+npm run build && npm start
+```
 
 **With Docker Compose:**
 ```bash
 docker compose up -d
 ```
-Set `IMAGE_TAG` in `.env` if you want to override the pinned release tag used by `docker-compose.yml`.
 
 **With Docker:**
 ```bash
@@ -82,13 +49,13 @@ docker run -d --env-file .env -v $(pwd)/data:/config/data tg-bot-bun
 
 ## Requirements
 
-- Node.js >= 20.19 OR Bun >= 1.0
+- Node.js >= 20 OR Bun >= 1.0
 - Docker (optional)
 
 
 ## Features
 
-- AI chat (Mistral, Ollama, OpenAI)
+- AI chat (Gemini, Mistral, Ollama)
 - Local document RAG for Ollama without third-party providers
 - Custom answers and commands
 - Admin management

bun.lock

@@ -5,17 +5,17 @@
     "": {
       "name": "tg-chat-bot",
       "dependencies": {
+        "@google/genai": "^2.0.0",
         "@libsql/client": "^0.17.3",
         "@mistralai/mistralai": "^2.2.1",
         "@napi-rs/canvas": "^1.0.0",
-        "axios": "^1.16.1",
+        "axios": "^1.16.0",
         "dotenv": "^17.4.2",
         "drizzle-orm": "0.45.2",
         "emoji-regex": "^10.6.0",
         "fluent-ffmpeg": "^2.1.3",
         "ollama": "^0.6.3",
-        "openai": "^6.38.0",
-        "pg": "^8.21.0",
+        "openai": "^6.37.0",
         "qrcode": "^1.5.4",
         "sharp": "^0.34.5",
         "systeminformation": "^5.31.6",
@@ -24,48 +24,77 @@
         "zod": "^4.4.3",
       },
       "devDependencies": {
-        "@eslint/js": "^9.39.4",
-        "@types/bun": "^1.3.14",
+        "@types/bun": "^1.3.13",
         "@types/fluent-ffmpeg": "^2.1.28",
-        "@types/node": "^25.9.1",
-        "@types/pg": "^8.20.0",
+        "@types/node": "^25.6.1",
         "@types/qrcode": "^1.5.6",
-        "eslint": "^9.39.4",
+        "drizzle-kit": "^0.31.10",
         "typescript": "^6.0.3",
-        "typescript-eslint": "^8.59.4",
       },
     },
   },
   "packages": {
+    "@drizzle-team/brocli": ["@drizzle-team/brocli@0.10.2", "", {}, "sha512-z33Il7l5dKjUgGULTqBsQBQwckHh5AbIuxhdsIxDDiZAzBOrZO6q9ogcWC65kU382AfynTfgNumVcNIjuIua6w=="],
+
     "@emnapi/runtime": ["@emnapi/runtime@1.7.1", "", { "dependencies": { "tslib": "^2.4.0" } }, "sha512-PVtJr5CmLwYAU9PZDMITZoR5iAOShYREoR45EyyLrbntV50mdePTgUn4AmOw90Ifcj+x2kRjdzr1HP3RrNiHGA=="],
 
-    "@eslint-community/eslint-utils": ["@eslint-community/eslint-utils@4.9.1", "", { "dependencies": { "eslint-visitor-keys": "^3.4.3" }, "peerDependencies": { "eslint": "^6.0.0 || ^7.0.0 || >=8.0.0" } }, "sha512-phrYmNiYppR7znFEdqgfWHXR6NCkZEK7hwWDHZUjit/2/U0r6XvkDl0SYnoM51Hq7FhCGdLDT6zxCCOY1hexsQ=="],
+    "@esbuild-kit/core-utils": ["@esbuild-kit/core-utils@3.3.2", "", { "dependencies": { "esbuild": "~0.18.20", "source-map-support": "^0.5.21" } }, "sha512-sPRAnw9CdSsRmEtnsl2WXWdyquogVpB3yZ3dgwJfe8zrOzTsV7cJvmwrKVa+0ma5BoiGJ+BoqkMvawbayKUsqQ=="],
 
-    "@eslint-community/regexpp": ["@eslint-community/regexpp@4.12.2", "", {}, "sha512-EriSTlt5OC9/7SXkRSCAhfSxxoSUgBm33OH+IkwbdpgoqsSsUg7y3uh+IICI/Qg4BBWr3U2i39RpmycbxMq4ew=="],
+    "@esbuild-kit/esm-loader": ["@esbuild-kit/esm-loader@2.6.5", "", { "dependencies": { "@esbuild-kit/core-utils": "^3.3.2", "get-tsconfig": "^4.7.0" } }, "sha512-FxEMIkJKnodyA1OaCUoEvbYRkoZlLZ4d/eXFu9Fh8CbBBgP5EmZxrfTRyN0qpXZ4vOvqnE5YdRdcrmUUXuU+dA=="],
 
-    "@eslint/config-array": ["@eslint/config-array@0.21.2", "", { "dependencies": { "@eslint/object-schema": "^2.1.7", "debug": "^4.3.1", "minimatch": "^3.1.5" } }, "sha512-nJl2KGTlrf9GjLimgIru+V/mzgSK0ABCDQRvxw5BjURL7WfH5uoWmizbH7QB6MmnMBd8cIC9uceWnezL1VZWWw=="],
+    "@esbuild/aix-ppc64": ["@esbuild/aix-ppc64@0.25.12", "", { "os": "aix", "cpu": "ppc64" }, "sha512-Hhmwd6CInZ3dwpuGTF8fJG6yoWmsToE+vYgD4nytZVxcu1ulHpUQRAB1UJ8+N1Am3Mz4+xOByoQoSZf4D+CpkA=="],
 
-    "@eslint/config-helpers": ["@eslint/config-helpers@0.4.2", "", { "dependencies": { "@eslint/core": "^0.17.0" } }, "sha512-gBrxN88gOIf3R7ja5K9slwNayVcZgK6SOUORm2uBzTeIEfeVaIhOpCtTox3P6R7o2jLFwLFTLnC7kU/RGcYEgw=="],
+    "@esbuild/android-arm": ["@esbuild/android-arm@0.25.12", "", { "os": "android", "cpu": "arm" }, "sha512-VJ+sKvNA/GE7Ccacc9Cha7bpS8nyzVv0jdVgwNDaR4gDMC/2TTRc33Ip8qrNYUcpkOHUT5OZ0bUcNNVZQ9RLlg=="],
 
-    "@eslint/core": ["@eslint/core@0.17.0", "", { "dependencies": { "@types/json-schema": "^7.0.15" } }, "sha512-yL/sLrpmtDaFEiUj1osRP4TI2MDz1AddJL+jZ7KSqvBuliN4xqYY54IfdN8qD8Toa6g1iloph1fxQNkjOxrrpQ=="],
+    "@esbuild/android-arm64": ["@esbuild/android-arm64@0.25.12", "", { "os": "android", "cpu": "arm64" }, "sha512-6AAmLG7zwD1Z159jCKPvAxZd4y/VTO0VkprYy+3N2FtJ8+BQWFXU+OxARIwA46c5tdD9SsKGZ/1ocqBS/gAKHg=="],
 
-    "@eslint/eslintrc": ["@eslint/eslintrc@3.3.5", "", { "dependencies": { "ajv": "^6.14.0", "debug": "^4.3.2", "espree": "^10.0.1", "globals": "^14.0.0", "ignore": "^5.2.0", "import-fresh": "^3.2.1", "js-yaml": "^4.1.1", "minimatch": "^3.1.5", "strip-json-comments": "^3.1.1" } }, "sha512-4IlJx0X0qftVsN5E+/vGujTRIFtwuLbNsVUe7TO6zYPDR1O6nFwvwhIKEKSrl6dZchmYBITazxKoUYOjdtjlRg=="],
+    "@esbuild/android-x64": ["@esbuild/android-x64@0.25.12", "", { "os": "android", "cpu": "x64" }, "sha512-5jbb+2hhDHx5phYR2By8GTWEzn6I9UqR11Kwf22iKbNpYrsmRB18aX/9ivc5cabcUiAT/wM+YIZ6SG9QO6a8kg=="],
 
-    "@eslint/js": ["@eslint/js@9.39.4", "", {}, "sha512-nE7DEIchvtiFTwBw4Lfbu59PG+kCofhjsKaCWzxTpt4lfRjRMqG6uMBzKXuEcyXhOHoUp9riAm7/aWYGhXZ9cw=="],
+    "@esbuild/darwin-arm64": ["@esbuild/darwin-arm64@0.25.12", "", { "os": "darwin", "cpu": "arm64" }, "sha512-N3zl+lxHCifgIlcMUP5016ESkeQjLj/959RxxNYIthIg+CQHInujFuXeWbWMgnTo4cp5XVHqFPmpyu9J65C1Yg=="],
 
-    "@eslint/object-schema": ["@eslint/object-schema@2.1.7", "", {}, "sha512-VtAOaymWVfZcmZbp6E2mympDIHvyjXs/12LqWYjVw6qjrfF+VK+fyG33kChz3nnK+SU5/NeHOqrTEHS8sXO3OA=="],
+    "@esbuild/darwin-x64": ["@esbuild/darwin-x64@0.25.12", "", { "os": "darwin", "cpu": "x64" }, "sha512-HQ9ka4Kx21qHXwtlTUVbKJOAnmG1ipXhdWTmNXiPzPfWKpXqASVcWdnf2bnL73wgjNrFXAa3yYvBSd9pzfEIpA=="],
 
-    "@eslint/plugin-kit": ["@eslint/plugin-kit@0.4.1", "", { "dependencies": { "@eslint/core": "^0.17.0", "levn": "^0.4.1" } }, "sha512-43/qtrDUokr7LJqoF2c3+RInu/t4zfrpYdoSDfYyhg52rwLV6TnOvdG4fXm7IkSB3wErkcmJS9iEhjVtOSEjjA=="],
+    "@esbuild/freebsd-arm64": ["@esbuild/freebsd-arm64@0.25.12", "", { "os": "freebsd", "cpu": "arm64" }, "sha512-gA0Bx759+7Jve03K1S0vkOu5Lg/85dou3EseOGUes8flVOGxbhDDh/iZaoek11Y8mtyKPGF3vP8XhnkDEAmzeg=="],
 
-    "@humanfs/core": ["@humanfs/core@0.19.2", "", { "dependencies": { "@humanfs/types": "^0.15.0" } }, "sha512-UhXNm+CFMWcbChXywFwkmhqjs3PRCmcSa/hfBgLIb7oQ5HNb1wS0icWsGtSAUNgefHeI+eBrA8I1fxmbHsGdvA=="],
+    "@esbuild/freebsd-x64": ["@esbuild/freebsd-x64@0.25.12", "", { "os": "freebsd", "cpu": "x64" }, "sha512-TGbO26Yw2xsHzxtbVFGEXBFH0FRAP7gtcPE7P5yP7wGy7cXK2oO7RyOhL5NLiqTlBh47XhmIUXuGciXEqYFfBQ=="],
 
-    "@humanfs/node": ["@humanfs/node@0.16.8", "", { "dependencies": { "@humanfs/core": "^0.19.2", "@humanfs/types": "^0.15.0", "@humanwhocodes/retry": "^0.4.0" } }, "sha512-gE1eQNZ3R++kTzFUpdGlpmy8kDZD/MLyHqDwqjkVQI0JMdI1D51sy1H958PNXYkM2rAac7e5/CnIKZrHtPh3BQ=="],
+    "@esbuild/linux-arm": ["@esbuild/linux-arm@0.25.12", "", { "os": "linux", "cpu": "arm" }, "sha512-lPDGyC1JPDou8kGcywY0YILzWlhhnRjdof3UlcoqYmS9El818LLfJJc3PXXgZHrHCAKs/Z2SeZtDJr5MrkxtOw=="],
 
-    "@humanfs/types": ["@humanfs/types@0.15.0", "", {}, "sha512-ZZ1w0aoQkwuUuC7Yf+7sdeaNfqQiiLcSRbfI08oAxqLtpXQr9AIVX7Ay7HLDuiLYAaFPu8oBYNq/QIi9URHJ3Q=="],
+    "@esbuild/linux-arm64": ["@esbuild/linux-arm64@0.25.12", "", { "os": "linux", "cpu": "arm64" }, "sha512-8bwX7a8FghIgrupcxb4aUmYDLp8pX06rGh5HqDT7bB+8Rdells6mHvrFHHW2JAOPZUbnjUpKTLg6ECyzvas2AQ=="],
 
-    "@humanwhocodes/module-importer": ["@humanwhocodes/module-importer@1.0.1", "", {}, "sha512-bxveV4V8v5Yb4ncFTT3rPSgZBOpCkjfK0y4oVVVJwIuDVBRMDXrPyXRL988i5ap9m9bnyEEjWfm5WkBmtffLfA=="],
+    "@esbuild/linux-ia32": ["@esbuild/linux-ia32@0.25.12", "", { "os": "linux", "cpu": "ia32" }, "sha512-0y9KrdVnbMM2/vG8KfU0byhUN+EFCny9+8g202gYqSSVMonbsCfLjUO+rCci7pM0WBEtz+oK/PIwHkzxkyharA=="],
 
-    "@humanwhocodes/retry": ["@humanwhocodes/retry@0.4.3", "", {}, "sha512-bV0Tgo9K4hfPCek+aMAn81RppFKv2ySDQeMoSZuvTASywNTnVJCArCZE2FWqpvIatKu7VMRLWlR1EazvVhDyhQ=="],
+    "@esbuild/linux-loong64": ["@esbuild/linux-loong64@0.25.12", "", { "os": "linux", "cpu": "none" }, "sha512-h///Lr5a9rib/v1GGqXVGzjL4TMvVTv+s1DPoxQdz7l/AYv6LDSxdIwzxkrPW438oUXiDtwM10o9PmwS/6Z0Ng=="],
+
+    "@esbuild/linux-mips64el": ["@esbuild/linux-mips64el@0.25.12", "", { "os": "linux", "cpu": "none" }, "sha512-iyRrM1Pzy9GFMDLsXn1iHUm18nhKnNMWscjmp4+hpafcZjrr2WbT//d20xaGljXDBYHqRcl8HnxbX6uaA/eGVw=="],
+
+    "@esbuild/linux-ppc64": ["@esbuild/linux-ppc64@0.25.12", "", { "os": "linux", "cpu": "ppc64" }, "sha512-9meM/lRXxMi5PSUqEXRCtVjEZBGwB7P/D4yT8UG/mwIdze2aV4Vo6U5gD3+RsoHXKkHCfSxZKzmDssVlRj1QQA=="],
+
+    "@esbuild/linux-riscv64": ["@esbuild/linux-riscv64@0.25.12", "", { "os": "linux", "cpu": "none" }, "sha512-Zr7KR4hgKUpWAwb1f3o5ygT04MzqVrGEGXGLnj15YQDJErYu/BGg+wmFlIDOdJp0PmB0lLvxFIOXZgFRrdjR0w=="],
+
+    "@esbuild/linux-s390x": ["@esbuild/linux-s390x@0.25.12", "", { "os": "linux", "cpu": "s390x" }, "sha512-MsKncOcgTNvdtiISc/jZs/Zf8d0cl/t3gYWX8J9ubBnVOwlk65UIEEvgBORTiljloIWnBzLs4qhzPkJcitIzIg=="],
+
+    "@esbuild/linux-x64": ["@esbuild/linux-x64@0.25.12", "", { "os": "linux", "cpu": "x64" }, "sha512-uqZMTLr/zR/ed4jIGnwSLkaHmPjOjJvnm6TVVitAa08SLS9Z0VM8wIRx7gWbJB5/J54YuIMInDquWyYvQLZkgw=="],
+
+    "@esbuild/netbsd-arm64": ["@esbuild/netbsd-arm64@0.25.12", "", { "os": "none", "cpu": "arm64" }, "sha512-xXwcTq4GhRM7J9A8Gv5boanHhRa/Q9KLVmcyXHCTaM4wKfIpWkdXiMog/KsnxzJ0A1+nD+zoecuzqPmCRyBGjg=="],
+
+    "@esbuild/netbsd-x64": ["@esbuild/netbsd-x64@0.25.12", "", { "os": "none", "cpu": "x64" }, "sha512-Ld5pTlzPy3YwGec4OuHh1aCVCRvOXdH8DgRjfDy/oumVovmuSzWfnSJg+VtakB9Cm0gxNO9BzWkj6mtO1FMXkQ=="],
+
+    "@esbuild/openbsd-arm64": ["@esbuild/openbsd-arm64@0.25.12", "", { "os": "openbsd", "cpu": "arm64" }, "sha512-fF96T6KsBo/pkQI950FARU9apGNTSlZGsv1jZBAlcLL1MLjLNIWPBkj5NlSz8aAzYKg+eNqknrUJ24QBybeR5A=="],
+
+    "@esbuild/openbsd-x64": ["@esbuild/openbsd-x64@0.25.12", "", { "os": "openbsd", "cpu": "x64" }, "sha512-MZyXUkZHjQxUvzK7rN8DJ3SRmrVrke8ZyRusHlP+kuwqTcfWLyqMOE3sScPPyeIXN/mDJIfGXvcMqCgYKekoQw=="],
+
+    "@esbuild/openharmony-arm64": ["@esbuild/openharmony-arm64@0.25.12", "", { "os": "none", "cpu": "arm64" }, "sha512-rm0YWsqUSRrjncSXGA7Zv78Nbnw4XL6/dzr20cyrQf7ZmRcsovpcRBdhD43Nuk3y7XIoW2OxMVvwuRvk9XdASg=="],
+
+    "@esbuild/sunos-x64": ["@esbuild/sunos-x64@0.25.12", "", { "os": "sunos", "cpu": "x64" }, "sha512-3wGSCDyuTHQUzt0nV7bocDy72r2lI33QL3gkDNGkod22EsYl04sMf0qLb8luNKTOmgF/eDEDP5BFNwoBKH441w=="],
+
+    "@esbuild/win32-arm64": ["@esbuild/win32-arm64@0.25.12", "", { "os": "win32", "cpu": "arm64" }, "sha512-rMmLrur64A7+DKlnSuwqUdRKyd3UE7oPJZmnljqEptesKM8wx9J8gx5u0+9Pq0fQQW8vqeKebwNXdfOyP+8Bsg=="],
+
+    "@esbuild/win32-ia32": ["@esbuild/win32-ia32@0.25.12", "", { "os": "win32", "cpu": "ia32" }, "sha512-HkqnmmBoCbCwxUKKNPBixiWDGCpQGVsrQfJoVGYLPT41XWF8lHuE5N6WhVia2n4o5QK5M4tYr21827fNhi4byQ=="],
+
+    "@esbuild/win32-x64": ["@esbuild/win32-x64@0.25.12", "", { "os": "win32", "cpu": "x64" }, "sha512-alJC0uCZpTFrSL0CCDjcgleBXPnCrEAhTBILpeAp7M/OFgoqtAetfBzX0xM00MUsVVPpVjlPuMbREqnZCXaTnA=="],
+
+    "@google/genai": ["@google/genai@2.0.0", "", { "dependencies": { "google-auth-library": "^10.3.0", "p-retry": "^4.6.2", "protobufjs": "^7.5.4", "ws": "^8.18.0" }, "peerDependencies": { "@modelcontextprotocol/sdk": "^1.25.2" }, "optionalPeers": ["@modelcontextprotocol/sdk"] }, "sha512-6XpO+YbGutXkm5QgR7NZktISxSz0dw3pSs9NtCUQwvhJc1eyA3KhdKhE/0Uaxp3a6eul3LC0SKau1bXymjOKUg=="],
 
     "@img/colour": ["@img/colour@1.0.0", "", {}, "sha512-A5P/LfWGFSl6nsckYtjw9da+19jB8hkJ6ACTGcDfEJ0aE+l2n2El7dsVM7UVHZQ9s2lmYMWlrS21YLy2IR1LUw=="],
 
@@ -117,6 +146,8 @@
 
     "@img/sharp-win32-x64": ["@img/sharp-win32-x64@0.34.5", "", { "os": "win32", "cpu": "x64" }, "sha512-+29YMsqY2/9eFEiW93eqWnuLcWcufowXewwSNIT6UwZdUUCrM3oFjMWH/Z6/TMmb4hlFenmfAVbpWeup2jryCw=="],
 
+    "@isaacs/cliui": ["@isaacs/cliui@8.0.2", "", { "dependencies": { "string-width": "^5.1.2", "string-width-cjs": "npm:string-width@^4.2.0", "strip-ansi": "^7.0.1", "strip-ansi-cjs": "npm:strip-ansi@^6.0.1", "wrap-ansi": "^8.1.0", "wrap-ansi-cjs": "npm:wrap-ansi@^7.0.0" } }, "sha512-O8jcjabXaleOG9DQ0+ARXWZBTfnP4WNAqzuiJK7ll44AmxGKv/J2M4TPjxjY3znBCfvBXFzucm1twdyFybFqEA=="],
+
     "@libsql/client": ["@libsql/client@0.17.3", "", { "dependencies": { "@libsql/core": "^0.17.3", "@libsql/hrana-client": "^0.10.0", "js-base64": "^3.7.5", "libsql": "^0.5.28", "promise-limit": "^2.7.0" } }, "sha512-HXk9wiAoJbKFbyBH4O+aEhN6ir5ERXuXvwE5OD2eR4/5RUa3Pw/8L9zrnVdU+iNJitRvisPWaIwmhkO3bH7giA=="],
 
     "@libsql/core": ["@libsql/core@0.17.3", "", { "dependencies": { "js-base64": "^3.7.5" } }, "sha512-2UjK1i7JBkMduJo4WdvvBxMMvVJ31pArBZNONyz/GCJJAH+1UHat2X6vn10S/WpY5fKzIT98WqYFl2vzWRLOfg=="],
@@ -171,76 +202,70 @@
 
     "@neon-rs/load": ["@neon-rs/load@0.0.4", "", {}, "sha512-kTPhdZyTQxB+2wpiRcFWrDcejc4JI6tkPuS7UZCG4l6Zvc5kU/gGQ/ozvHTh1XR5tS+UlfAfGuPajjzQjCiHCw=="],
 
-    "@types/bun": ["@types/bun@1.3.14", "", { "dependencies": { "bun-types": "1.3.14" } }, "sha512-h1hFqFVcvAvD9j9K7ZW7vd82aSA+rTdznZa+5bwvCwqSB1jmmfLcbIWhOLx1/+boy/xmjgCs/OMUL8hRJSmnPw=="],
+    "@pkgjs/parseargs": ["@pkgjs/parseargs@0.11.0", "", {}, "sha512-+1VkjdD0QBLPodGrJUeqarH8VAIvQODIbwh9XpP5Syisf7YoQgsJKPNFoqqLQlu+VQ/tVSshMR6loPMn8U+dPg=="],
 
-    "@types/estree": ["@types/estree@1.0.9", "", {}, "sha512-GhdPgy1el4/ImP05X05Uw4cw2/M93BCUmnEvWZNStlCzEKME4Fkk+YpoA5OiHNQmoS7Cafb8Xa3Pya8m1Qrzeg=="],
+    "@protobufjs/aspromise": ["@protobufjs/aspromise@1.1.2", "", {}, "sha512-j+gKExEuLmKwvz3OgROXtrJ2UG2x8Ch2YZUxahh+s1F2HZ+wAceUNLkvy6zKCPVRkU++ZWQrdxsUeQXmcg4uoQ=="],
+
+    "@protobufjs/base64": ["@protobufjs/base64@1.1.2", "", {}, "sha512-AZkcAA5vnN/v4PDqKyMR5lx7hZttPDgClv83E//FMNhR2TMcLUhfRUBHCmSl0oi9zMgDDqRUJkSxO3wm85+XLg=="],
+
+    "@protobufjs/codegen": ["@protobufjs/codegen@2.0.4", "", {}, "sha512-YyFaikqM5sH0ziFZCN3xDC7zeGaB/d0IUb9CATugHWbd1FRFwWwt4ld4OYMPWu5a3Xe01mGAULCdqhMlPl29Jg=="],
+
+    "@protobufjs/eventemitter": ["@protobufjs/eventemitter@1.1.0", "", {}, "sha512-j9ednRT81vYJ9OfVuXG6ERSTdEL1xVsNgqpkxMsbIabzSo3goCjDIveeGv5d03om39ML71RdmrGNjG5SReBP/Q=="],
+
+    "@protobufjs/fetch": ["@protobufjs/fetch@1.1.0", "", { "dependencies": { "@protobufjs/aspromise": "^1.1.1", "@protobufjs/inquire": "^1.1.0" } }, "sha512-lljVXpqXebpsijW71PZaCYeIcE5on1w5DlQy5WH6GLbFryLUrBD4932W/E2BSpfRJWseIL4v/KPgBFxDOIdKpQ=="],
+
+    "@protobufjs/float": ["@protobufjs/float@1.0.2", "", {}, "sha512-Ddb+kVXlXst9d+R9PfTIxh1EdNkgoRe5tOX6t01f1lYWOvJnSPDBlG241QLzcyPdoNTsblLUdujGSE4RzrTZGQ=="],
+
+    "@protobufjs/inquire": ["@protobufjs/inquire@1.1.0", "", {}, "sha512-kdSefcPdruJiFMVSbn801t4vFK7KB/5gd2fYvrxhuJYg8ILrmn9SKSX2tZdV6V+ksulWqS7aXjBcRXl3wHoD9Q=="],
+
+    "@protobufjs/path": ["@protobufjs/path@1.1.2", "", {}, "sha512-6JOcJ5Tm08dOHAbdR3GrvP+yUUfkjG5ePsHYczMFLq3ZmMkAD98cDgcT2iA1lJ9NVwFd4tH/iSSoe44YWkltEA=="],
+
+    "@protobufjs/pool": ["@protobufjs/pool@1.1.0", "", {}, "sha512-0kELaGSIDBKvcgS4zkjz1PeddatrjYcmMWOlAuAPwAeccUrPHdUqo/J6LiymHHEiJT5NrF1UVwxY14f+fy4WQw=="],
+
+    "@protobufjs/utf8": ["@protobufjs/utf8@1.1.0", "", {}, "sha512-Vvn3zZrhQZkkBE8LSuW3em98c0FwgO4nxzv6OdSxPKJIEKY2bGbHn+mhGIPerzI4twdxaP8/0+06HBpwf345Lw=="],
+
+    "@types/bun": ["@types/bun@1.3.13", "", { "dependencies": { "bun-types": "1.3.13" } }, "sha512-9fqXWk5YIHGGnUau9TEi+qdlTYDAnOj+xLCmSTwXfAIqXr2x4tytJb43E9uCvt09zJURKXwAtkoH4nLQfzeTXw=="],
 
     "@types/fluent-ffmpeg": ["@types/fluent-ffmpeg@2.1.28", "", { "dependencies": { "@types/node": "*" } }, "sha512-5ovxsDwBcPfJ+eYs1I/ZpcYCnkce7pvH9AHSvrZllAp1ZPpTRDZAFjF3TRFbukxSgIYTTNYePbS0rKUmaxVbXw=="],
 
-    "@types/json-schema": ["@types/json-schema@7.0.15", "", {}, "sha512-5+fP8P8MFNC+AyZCDxrB2pkZFPGzqQWUzpSeuuVLvm8VMcorNYavBqoFcxK8bQz4Qsbn4oUEEem4wDLfcysGHA=="],
-
-    "@types/node": ["@types/node@25.9.1", "", { "dependencies": { "undici-types": ">=7.24.0 <7.24.7" } }, "sha512-xfrlY7UD5rMJk3ZVJP8BNzS28J36YJg+xp+LPXV1TdWxr8uMH5A860QNxYDGQe/ylDSgjxE52Q9VnO7p75tJxg=="],
-
-    "@types/pg": ["@types/pg@8.20.0", "", { "dependencies": { "@types/node": "*", "pg-protocol": "*", "pg-types": "^2.2.0" } }, "sha512-bEPFOaMAHTEP1EzpvHTbmwR8UsFyHSKsRisLIHVMXnpNefSbGA1bD6CVy+qKjGSqmZqNqBDV2azOBo8TgkcVow=="],
+    "@types/node": ["@types/node@25.6.1", "", { "dependencies": { "undici-types": "~7.19.0" } }, "sha512-coJCN8O1q4AGyyqCAUSP06P+SrMTu18BkEj3NVAK07q6QUneD2wzj3CLv9+yP+BMeZQlMvneXqqvDe3w+xcq7g=="],
 
     "@types/qrcode": ["@types/qrcode@1.5.6", "", { "dependencies": { "@types/node": "*" } }, "sha512-te7NQcV2BOvdj2b1hCAHzAoMNuj65kNBMz0KBaxM6c3VGBOhU0dURQKOtH8CFNI/dsKkwlv32p26qYQTWoB5bw=="],
 
+    "@types/retry": ["@types/retry@0.12.0", "", {}, "sha512-wWKOClTTiizcZhXnPY4wikVAwmdYHp8q6DmC+EJUzAMsycb7HB32Kh9RN4+0gExjmPmZSAQjgURXIGATPegAvA=="],
+
     "@types/ws": ["@types/ws@8.18.1", "", { "dependencies": { "@types/node": "*" } }, "sha512-ThVF6DCVhA8kUGy+aazFQ4kXQ7E1Ty7A3ypFOe0IcJV8O/M511G99AW24irKrW56Wt44yG9+ij8FaqoBGkuBXg=="],
 
-    "@typescript-eslint/eslint-plugin": ["@typescript-eslint/eslint-plugin@8.59.4", "", { "dependencies": { "@eslint-community/regexpp": "^4.12.2", "@typescript-eslint/scope-manager": "8.59.4", "@typescript-eslint/type-utils": "8.59.4", "@typescript-eslint/utils": "8.59.4", "@typescript-eslint/visitor-keys": "8.59.4", "ignore": "^7.0.5", "natural-compare": "^1.4.0", "ts-api-utils": "^2.5.0" }, "peerDependencies": { "@typescript-eslint/parser": "^8.59.4", "eslint": "^8.57.0 || ^9.0.0 || ^10.0.0", "typescript": ">=4.8.4 <6.1.0" } }, "sha512-PegsU+XfyJJNjd4+u/k6f9yTyp0lEXXiPopUNobZcIAUJFGICFLN+sP0Rb3JehVmiij1Ph0dFGYqODoRo/2+6A=="],
-
-    "@typescript-eslint/parser": ["@typescript-eslint/parser@8.59.4", "", { "dependencies": { "@typescript-eslint/scope-manager": "8.59.4", "@typescript-eslint/types": "8.59.4", "@typescript-eslint/typescript-estree": "8.59.4", "@typescript-eslint/visitor-keys": "8.59.4", "debug": "^4.4.3" }, "peerDependencies": { "eslint": "^8.57.0 || ^9.0.0 || ^10.0.0", "typescript": ">=4.8.4 <6.1.0" } }, "sha512-zORHqO/tuhxY1zWuTvMUqddRxpiFJ72xVfcNoWpqdLjs6lfPbuQBJuW4pk+49/uBMy7Ssr4bzgjiKmmDB1UbZQ=="],
-
-    "@typescript-eslint/project-service": ["@typescript-eslint/project-service@8.59.4", "", { "dependencies": { "@typescript-eslint/tsconfig-utils": "^8.59.4", "@typescript-eslint/types": "^8.59.4", "debug": "^4.4.3" }, "peerDependencies": { "typescript": ">=4.8.4 <6.1.0" } }, "sha512-Ly00Vu4oAacfDeHp2Zg85ioNG6l8HG+tN1D7J+xTHSxu9y0awYKJ2zH1rFBn8ZSfuGK+7FxK3Cgl3uAz0aZZLg=="],
-
-    "@typescript-eslint/scope-manager": ["@typescript-eslint/scope-manager@8.59.4", "", { "dependencies": { "@typescript-eslint/types": "8.59.4", "@typescript-eslint/visitor-keys": "8.59.4" } }, "sha512-mUeR/3H1WrTAddJrwut8OoPjfauaztMQmRwV5fQTUyNVJCLiUXXe4lGEyYIL2oFDpP7UtgbGJXCt72wT0z2S3Q=="],
-
-    "@typescript-eslint/tsconfig-utils": ["@typescript-eslint/tsconfig-utils@8.59.4", "", { "peerDependencies": { "typescript": ">=4.8.4 <6.1.0" } }, "sha512-DLCpnKgD4alVxTBSKulK+gU1KCqOgUXfDRDXh2mZgzokQKa/70ax93I2uVO3m/LLvIAtWZIFoiifudmIqAxpMA=="],
-
-    "@typescript-eslint/type-utils": ["@typescript-eslint/type-utils@8.59.4", "", { "dependencies": { "@typescript-eslint/types": "8.59.4", "@typescript-eslint/typescript-estree": "8.59.4", "@typescript-eslint/utils": "8.59.4", "debug": "^4.4.3", "ts-api-utils": "^2.5.0" }, "peerDependencies": { "eslint": "^8.57.0 || ^9.0.0 || ^10.0.0", "typescript": ">=4.8.4 <6.1.0" } }, "sha512-uonTuPAAKr9XaBGqJ3LjYTh72zy5DyGesljO9gtmk/eFW0W1fRHjnwVYKB35Lm8d5Q5CluEW3gPHjTvZTmgrfA=="],
-
-    "@typescript-eslint/types": ["@typescript-eslint/types@8.59.4", "", {}, "sha512-F1o7WJcCq+bc8dwcO/YsSEOudAH8RDtaOhM6wcAQhcUsFhnWQl81JKy48q1hoxAU0qrzM89+31GYh1515Zde3Q=="],
-
-    "@typescript-eslint/typescript-estree": ["@typescript-eslint/typescript-estree@8.59.4", "", { "dependencies": { "@typescript-eslint/project-service": "8.59.4", "@typescript-eslint/tsconfig-utils": "8.59.4", "@typescript-eslint/types": "8.59.4", "@typescript-eslint/visitor-keys": "8.59.4", "debug": "^4.4.3", "minimatch": "^10.2.2", "semver": "^7.7.3", "tinyglobby": "^0.2.15", "ts-api-utils": "^2.5.0" }, "peerDependencies": { "typescript": ">=4.8.4 <6.1.0" } }, "sha512-F+RuOmcDXo4+TPdfd/TCLS3m2nw8gE9XXyZLrA3JBfaA5tz9TtdkyD3YJFmPxulyc2cKbEok/CvFE3MgSLWnag=="],
-
-    "@typescript-eslint/utils": ["@typescript-eslint/utils@8.59.4", "", { "dependencies": { "@eslint-community/eslint-utils": "^4.9.1", "@typescript-eslint/scope-manager": "8.59.4", "@typescript-eslint/types": "8.59.4", "@typescript-eslint/typescript-estree": "8.59.4" }, "peerDependencies": { "eslint": "^8.57.0 || ^9.0.0 || ^10.0.0", "typescript": ">=4.8.4 <6.1.0" } }, "sha512-cYXeNAUsG4lJo5dbc1FcKm+JwIWrj1/UpTORsC6tGMjEZ81DYcvIr9/ueikhMa/Y/gDQYGp+YX9/xQrXje5BJw=="],
-
-    "@typescript-eslint/visitor-keys": ["@typescript-eslint/visitor-keys@8.59.4", "", { "dependencies": { "@typescript-eslint/types": "8.59.4", "eslint-visitor-keys": "^5.0.0" } }, "sha512-U3gxVaDVnuZKhSspW/MzMxE1kq7zOdc072FcSNoqA1I9p8HyKbBFfEHoWckBAMgNMph4MamwS5iTVzFmrnt8TQ=="],
-
-    "acorn": ["acorn@8.16.0", "", { "bin": { "acorn": "bin/acorn" } }, "sha512-UVJyE9MttOsBQIDKw1skb9nAwQuR5wuGD3+82K6JgJlm/Y+KI92oNsMNGZCYdDsVtRHSak0pcV5Dno5+4jh9sw=="],
-
-    "acorn-jsx": ["acorn-jsx@5.3.2", "", { "peerDependencies": { "acorn": "^6.0.0 || ^7.0.0 || ^8.0.0" } }, "sha512-rq9s+JNhf0IChjtDXxllJ7g41oZk5SlXtp0LHwyA5cejwn7vKmKp4pPri6YEePv2PU65sAsegbXtIinmDFDXgQ=="],
-
-    "agent-base": ["agent-base@6.0.2", "", { "dependencies": { "debug": "4" } }, "sha512-RZNwNclF7+MS/8bDg70amg32dyeZGZxiDuQmZxKLAlQjr3jGyLx+4Kkk58UO7D2QdgFIQCovuSuZESne6RG6XQ=="],
-
-    "ajv": ["ajv@6.15.0", "", { "dependencies": { "fast-deep-equal": "^3.1.1", "fast-json-stable-stringify": "^2.0.0", "json-schema-traverse": "^0.4.1", "uri-js": "^4.2.2" } }, "sha512-fgFx7Hfoq60ytK2c7DhnF8jIvzYgOMxfugjLOSMHjLIPgenqa7S7oaagATUq99mV6IYvN2tRmC0wnTYX6iPbMw=="],
+    "agent-base": ["agent-base@7.1.4", "", {}, "sha512-MnA+YT8fwfJPgBx3m60MNqakm30XOkyIoH1y6huTQvC0PwZG7ki8NacLBcrPbNoo8vEZy7Jpuk7+jMO+CUovTQ=="],
 
     "ansi-regex": ["ansi-regex@5.0.1", "", {}, "sha512-quJQXlTSUGL2LH9SUXo8VwsY4soanhgo6LNSm84E1LBcE8s3O0wpdiRzyR9z/ZZJMlMWv37qOOb9pdJlMUEKFQ=="],
 
     "ansi-styles": ["ansi-styles@4.3.0", "", { "dependencies": { "color-convert": "^2.0.1" } }, "sha512-zbB9rCJAT1rbjiVDb2hqKFHNYLxgtk8NURxZ3IZwD3F6NtxbXZQCnnSi1Lkx+IDohdPlFp222wVALIheZJQSEg=="],
 
-    "argparse": ["argparse@2.0.1", "", {}, "sha512-8+9WqebbFzpX9OR+Wa6O29asIogeRMzcGtAINdpMHHyAg10f05aSFVBbcEqGf/PXw1EjAZ+q2/bEBg3DvurK3Q=="],
-
     "async": ["async@0.2.10", "", {}, "sha512-eAkdoKxU6/LkKDBzLpT+t6Ff5EtfSF4wx1WfJiPEEV7WNLnDaRXk0oVysiEPm262roaachGexwUv94WhSgN5TQ=="],
 
     "asynckit": ["asynckit@0.4.0", "", {}, "sha1-x57Zf380y48robyXkLzDZkdLS3k="],
 
-    "axios": ["axios@1.16.1", "", { "dependencies": { "follow-redirects": "^1.16.0", "form-data": "^4.0.5", "https-proxy-agent": "^5.0.1", "proxy-from-env": "^2.1.0" } }, "sha512-caYkukvroVPO8KrzuJEb50Hm07KwfBZPEC3VeFHTsqWHvKTsy54hjJz9BS/cdaypROE2rH6xvm9mHX4fgWkr3A=="],
+    "axios": ["axios@1.16.0", "", { "dependencies": { "follow-redirects": "^1.16.0", "form-data": "^4.0.5", "proxy-from-env": "^2.1.0" } }, "sha512-6hp5CwvTPlN2A31g5dxnwAX0orzM7pmCRDLnZSX772mv8WDqICwFjowHuPs04Mc8deIld1+ejhtaMn5vp6b+1w=="],
 
     "balanced-match": ["balanced-match@1.0.2", "", {}, "sha512-3oSeUO0TMV67hN1AmbXsK4yaqU7tjiHlbxRDZOpH0KW9+CeX4bRAaX0Anxt0tx2MrpRpWwQaPwIlISEJhYU5Pw=="],
 
-    "brace-expansion": ["brace-expansion@1.1.14", "", { "dependencies": { "balanced-match": "^1.0.0", "concat-map": "0.0.1" } }, "sha512-MWPGfDxnyzKU7rNOW9SP/c50vi3xrmrua/+6hfPbCS2ABNWfx24vPidzvC7krjU/RTo235sV776ymlsMtGKj8g=="],
+    "base64-js": ["base64-js@1.5.1", "", {}, "sha512-AKpaYlHn8t4SVbOHCy+b5+KKgvR4vrsD8vbvrbiQJps7fKDTkjkDry6ji0rUJjC0kzbNePLwzxq8iypo41qeWA=="],
 
-    "bun-types": ["bun-types@1.3.14", "", { "dependencies": { "@types/node": "*" } }, "sha512-4N0ig0fEomHt5R0KCFWjovxow98rIoRwKolrYdCcknNwMekCXRnWEUvgu5soYV8QXtVsrUD8B95MBOZGPvr6KQ=="],
+    "bignumber.js": ["bignumber.js@9.3.1", "", {}, "sha512-Ko0uX15oIUS7wJ3Rb30Fs6SkVbLmPBAKdlm7q9+ak9bbIeFf0MwuBsQV6z7+X768/cHsfg+WlysDWJcmthjsjQ=="],
+
+    "brace-expansion": ["brace-expansion@2.0.2", "", { "dependencies": { "balanced-match": "^1.0.0" } }, "sha512-Jt0vHyM+jmUBqojB7E1NIYadt0vI0Qxjxd2TErW94wDz+E2LAm5vKMXXwg6ZZBTHPuUlDgQHKXvjGBdfcF1ZDQ=="],
+
+    "buffer-equal-constant-time": ["buffer-equal-constant-time@1.0.1", "", {}, "sha512-zRpUiDwd/xk6ADqPMATG8vc9VPrkck7T07OIx0gnjmJAnHnTVXNQG3vfvWNuiZIkwu9KrKdA1iJKfsfTVxE6NA=="],
+
+    "buffer-from": ["buffer-from@1.1.2", "", {}, "sha512-E+XQCRwSbaaiChtv6k6Dwgc+bx+Bs6vuKJHHl5kox/BaKbhiXzqQOwK4cO22yElGp2OCmjwVhT3HmxgyPGnJfQ=="],
+
+    "bun-types": ["bun-types@1.3.13", "", { "dependencies": { "@types/node": "*" } }, "sha512-QXKeHLlOLqQX9LgYaHJfzdBaV21T63HhFJnvuRCcjZiaUDpbs5ED1MgxbMra71CsryN/1dAoXuJJJwIv/2drVA=="],
 
     "call-bind-apply-helpers": ["call-bind-apply-helpers@1.0.2", "", { "dependencies": { "es-errors": "^1.3.0", "function-bind": "^1.1.2" } }, "sha512-Sp1ablJ0ivDkSzjcaJdxEunN5/XvksFJ2sMBFfq6x0ryhQV/2b/KwFe21cMpmHtPOSij8K99/wSfoEuTObmuMQ=="],
 
-    "callsites": ["callsites@3.1.0", "", {}, "sha512-P8BjAsXvZS+VIDUI11hHCQEv74YT67YUi5JJFNWIqL235sBmjX4+qx9Muvls5ivyNENctx46xQLQ3aTuE7ssaQ=="],
-
     "camelcase": ["camelcase@5.3.1", "", {}, "sha512-L28STB170nwWS63UjtlEOE3dldQApaJXZkOI1uMFfzf3rRuPegHaHesyee+YxQ+W6SvRDQV6UrdOdRiR153wJg=="],
 
-    "chalk": ["chalk@4.1.2", "", { "dependencies": { "ansi-styles": "^4.1.0", "supports-color": "^7.1.0" } }, "sha512-oKnbhFyRIXpUuez8iBMmyEa4nbj4IOQyuhc/wy9kY7/WVPcwIO9VA668Pu8RkO7+0G76SLROeyw9CpQ061i4mA=="],
-
     "cliui": ["cliui@6.0.0", "", { "dependencies": { "string-width": "^4.2.0", "strip-ansi": "^6.0.0", "wrap-ansi": "^6.2.0" } }, "sha512-t6wbgtoCXvAzst7QgXxJYqPt0usEfbgQdftEPbLL/cvv6HPE5VgvqCuAIDR0NgU52ds6rFwqrgakNLrHEjCbrQ=="],
 
     "color-convert": ["color-convert@2.0.1", "", { "dependencies": { "color-name": "~1.1.4" } }, "sha512-RRECPsj7iu/xb5oKYcsFHSppFNnsj/52OVTRKb4zP5onXwVF3zVmmToNcOfGC+CRDpfK/U584fMg38ZHCaElKQ=="],
@@ -249,16 +274,14 @@
 
     "combined-stream": ["combined-stream@1.0.8", "", { "dependencies": { "delayed-stream": "~1.0.0" } }, "sha512-FQN4MRfuJeHf7cBbBMJFXhKSDq+2kAArBlmRBvcvFE5BB1HZKXtSFASDhdlz9zOYwxh8lDdnvmMOe/+5cdoEdg=="],
 
-    "concat-map": ["concat-map@0.0.1", "", {}, "sha512-/Srv4dswyQNBfohGpz9o6Yb3Gz3SrUDqBH5rTuhGR7ahtlbYKnVxw2bCFMRljaA7EXHaXZ8wsHdodFvbkhKmqg=="],
-
     "cross-spawn": ["cross-spawn@7.0.6", "", { "dependencies": { "path-key": "^3.1.0", "shebang-command": "^2.0.0", "which": "^2.0.1" } }, "sha512-uV2QOWP2nWzsy2aMp8aRibhi9dlzF5Hgh5SHaB9OiTGEyDTiJJyx0uy51QXdyWbtAHNua4XJzUKca3OzKUd3vA=="],
 
+    "data-uri-to-buffer": ["data-uri-to-buffer@4.0.1", "", {}, "sha512-0R9ikRb668HB7QDxT1vkpuUBtqc53YyAwMwGeUFKRojY/NWKvdZ+9UYtRfGmhqNbRkTSVpMbmyhXipFFv2cb/A=="],
+
     "debug": ["debug@4.4.3", "", { "dependencies": { "ms": "^2.1.3" } }, "sha512-RGwwWnwQvkVfavKVt22FGLw+xYSdzARwm0ru6DhTVA3umU5hZc28V3kO4stgYryrTlLpuvgI9GiijltAjNbcqA=="],
 
     "decamelize": ["decamelize@1.2.0", "", {}, "sha512-z2S+W9X73hAUUki+N+9Za2lBlun89zigOyGrsax+KUQ6wKW4ZoWpEYBkGhQjwAjjDCkWxhY0VKEhk8wzY7F5cA=="],
 
-    "deep-is": ["deep-is@0.1.4", "", {}, "sha512-oIPzksmTg4/MriiaYGO+okXDT7ztn/w3Eptv/+gSIdMdKsJo0u4CfYNFJPy+4SKMuCqGw2wxnA+URMg3t8a/bQ=="],
-
     "delayed-stream": ["delayed-stream@1.0.0", "", {}, "sha1-3zrhmayt+31ECqrgsp4icrJOxhk="],
 
     "detect-libc": ["detect-libc@2.1.2", "", {}, "sha512-Btj2BOOO83o3WyH59e8MgXsxEQVcarkUOpEYrubB0urwnN10yQ364rsiByU11nZlqWYZm05i/of7io4mzihBtQ=="],
@@ -267,10 +290,16 @@
 
     "dotenv": ["dotenv@17.4.2", "", {}, "sha512-nI4U3TottKAcAD9LLud4Cb7b2QztQMUEfHbvhTH09bqXTxnSie8WnjPALV/WMCrJZ6UV/qHJ6L03OqO3LcdYZw=="],
 
+    "drizzle-kit": ["drizzle-kit@0.31.10", "", { "dependencies": { "@drizzle-team/brocli": "^0.10.2", "@esbuild-kit/esm-loader": "^2.5.5", "esbuild": "^0.25.4", "tsx": "^4.21.0" }, "bin": { "drizzle-kit": "bin.cjs" } }, "sha512-7OZcmQUrdGI+DUNNsKBn1aW8qSoKuTH7d0mYgSP8bAzdFzKoovxEFnoGQp2dVs82EOJeYycqRtciopszwUf8bw=="],
+
     "drizzle-orm": ["drizzle-orm@0.45.2", "", { "peerDependencies": { "@aws-sdk/client-rds-data": ">=3", "@cloudflare/workers-types": ">=4", "@electric-sql/pglite": ">=0.2.0", "@libsql/client": ">=0.10.0", "@libsql/client-wasm": ">=0.10.0", "@neondatabase/serverless": ">=0.10.0", "@op-engineering/op-sqlite": ">=2", "@opentelemetry/api": "^1.4.1", "@planetscale/database": ">=1.13", "@prisma/client": "*", "@tidbcloud/serverless": "*", "@types/better-sqlite3": "*", "@types/pg": "*", "@types/sql.js": "*", "@upstash/redis": ">=1.34.7", "@vercel/postgres": ">=0.8.0", "@xata.io/client": "*", "better-sqlite3": ">=7", "bun-types": "*", "expo-sqlite": ">=14.0.0", "gel": ">=2", "knex": "*", "kysely": "*", "mysql2": ">=2", "pg": ">=8", "postgres": ">=3", "sql.js": ">=1", "sqlite3": ">=5" }, "optionalPeers": ["@aws-sdk/client-rds-data", "@cloudflare/workers-types", "@electric-sql/pglite", "@libsql/client", "@libsql/client-wasm", "@neondatabase/serverless", "@op-engineering/op-sqlite", "@opentelemetry/api", "@planetscale/database", "@prisma/client", "@tidbcloud/serverless", "@types/better-sqlite3", "@types/pg", "@types/sql.js", "@upstash/redis", "@vercel/postgres", "@xata.io/client", "better-sqlite3", "bun-types", "expo-sqlite", "gel", "knex", "kysely", "mysql2", "pg", "postgres", "sql.js", "sqlite3"] }, "sha512-kY0BSaTNYWnoDMVoyY8uxmyHjpJW1geOmBMdSSicKo9CIIWkSxMIj2rkeSR51b8KAPB7m+qysjuHme5nKP+E5Q=="],
 
     "dunder-proto": ["dunder-proto@1.0.1", "", { "dependencies": { "call-bind-apply-helpers": "^1.0.1", "es-errors": "^1.3.0", "gopd": "^1.2.0" } }, "sha512-KIN/nDJBQRcXw0MLVhZE9iQHmG68qAVIBg9CqmUYjmQIhgij9U5MFvrqkUL5FbtyyzZuOeOt0zdeRe4UY7ct+A=="],
 
+    "eastasianwidth": ["eastasianwidth@0.2.0", "", {}, "sha512-I88TYZWc9XiYHRQ4/3c5rjjfgkjhLyW2luGIheGERbNQ6OY7yTybanSpDXZa8y7VUP9YmDcYa+eyq4ca7iLqWA=="],
+
+    "ecdsa-sig-formatter": ["ecdsa-sig-formatter@1.0.11", "", { "dependencies": { "safe-buffer": "^5.0.1" } }, "sha512-nagl3RYrbNv6kQkeJIpt6NJZy8twLB/2vtz6yN9Z4vRKHN4/QZJIEbqohALSgwKdnksuY3k5Addp5lg8sVoVcQ=="],
+
     "emoji-regex": ["emoji-regex@10.6.0", "", {}, "sha512-toUI84YS5YmxW219erniWD0CIVOo46xGKColeNQRgOzDorgBi1v4D71/OFzgD9GO2UGKIv1C3Sp8DAn0+j5w7A=="],
 
     "es-define-property": ["es-define-property@1.0.1", "", {}, "sha512-e3nRfgfUZ4rNGL232gUgX06QNyyez04KdjFrF+LTRoOXmrOgFKDg4BCdsjW8EnT69eqdYGmRpJwiPVYNrCaW3g=="],
@@ -281,65 +310,53 @@
 
     "es-set-tostringtag": ["es-set-tostringtag@2.1.0", "", { "dependencies": { "es-errors": "^1.3.0", "get-intrinsic": "^1.2.6", "has-tostringtag": "^1.0.2", "hasown": "^2.0.2" } }, "sha512-j6vWzfrGVfyXxge+O0x5sh6cvxAog0a/4Rdd2K36zCMV5eJ+/+tOAngRO8cODMNWbVRdVlmGZQL2YS3yR8bIUA=="],
 
-    "escape-string-regexp": ["escape-string-regexp@4.0.0", "", {}, "sha512-TtpcNJ3XAzx3Gq8sWRzJaVajRs0uVxA2YAkdb1jm2YkPz4G6egUFAyA3n5vtEIZefPk5Wa4UXbKuS5fKkJWdgA=="],
+    "esbuild": ["esbuild@0.25.12", "", { "optionalDependencies": { "@esbuild/aix-ppc64": "0.25.12", "@esbuild/android-arm": "0.25.12", "@esbuild/android-arm64": "0.25.12", "@esbuild/android-x64": "0.25.12", "@esbuild/darwin-arm64": "0.25.12", "@esbuild/darwin-x64": "0.25.12", "@esbuild/freebsd-arm64": "0.25.12", "@esbuild/freebsd-x64": "0.25.12", "@esbuild/linux-arm": "0.25.12", "@esbuild/linux-arm64": "0.25.12", "@esbuild/linux-ia32": "0.25.12", "@esbuild/linux-loong64": "0.25.12", "@esbuild/linux-mips64el": "0.25.12", "@esbuild/linux-ppc64": "0.25.12", "@esbuild/linux-riscv64": "0.25.12", "@esbuild/linux-s390x": "0.25.12", "@esbuild/linux-x64": "0.25.12", "@esbuild/netbsd-arm64": "0.25.12", "@esbuild/netbsd-x64": "0.25.12", "@esbuild/openbsd-arm64": "0.25.12", "@esbuild/openbsd-x64": "0.25.12", "@esbuild/openharmony-arm64": "0.25.12", "@esbuild/sunos-x64": "0.25.12", "@esbuild/win32-arm64": "0.25.12", "@esbuild/win32-ia32": "0.25.12", "@esbuild/win32-x64": "0.25.12" }, "bin": { "esbuild": "bin/esbuild" } }, "sha512-bbPBYYrtZbkt6Os6FiTLCTFxvq4tt3JKall1vRwshA3fdVztsLAatFaZobhkBC8/BrPetoa0oksYoKXoG4ryJg=="],
 
-    "eslint": ["eslint@9.39.4", "", { "dependencies": { "@eslint-community/eslint-utils": "^4.8.0", "@eslint-community/regexpp": "^4.12.1", "@eslint/config-array": "^0.21.2", "@eslint/config-helpers": "^0.4.2", "@eslint/core": "^0.17.0", "@eslint/eslintrc": "^3.3.5", "@eslint/js": "9.39.4", "@eslint/plugin-kit": "^0.4.1", "@humanfs/node": "^0.16.6", "@humanwhocodes/module-importer": "^1.0.1", "@humanwhocodes/retry": "^0.4.2", "@types/estree": "^1.0.6", "ajv": "^6.14.0", "chalk": "^4.0.0", "cross-spawn": "^7.0.6", "debug": "^4.3.2", "escape-string-regexp": "^4.0.0", "eslint-scope": "^8.4.0", "eslint-visitor-keys": "^4.2.1", "espree": "^10.4.0", "esquery": "^1.5.0", "esutils": "^2.0.2", "fast-deep-equal": "^3.1.3", "file-entry-cache": "^8.0.0", "find-up": "^5.0.0", "glob-parent": "^6.0.2", "ignore": "^5.2.0", "imurmurhash": "^0.1.4", "is-glob": "^4.0.0", "json-stable-stringify-without-jsonify": "^1.0.1", "lodash.merge": "^4.6.2", "minimatch": "^3.1.5", "natural-compare": "^1.4.0", "optionator": "^0.9.3" }, "peerDependencies": { "jiti": "*" }, "optionalPeers": ["jiti"], "bin": { "eslint": "bin/eslint.js" } }, "sha512-XoMjdBOwe/esVgEvLmNsD3IRHkm7fbKIUGvrleloJXUZgDHig2IPWNniv+GwjyJXzuNqVjlr5+4yVUZjycJwfQ=="],
+    "extend": ["extend@3.0.2", "", {}, "sha512-fjquC59cD7CyW6urNXK0FBufkZcoiGG80wTuPujX590cB5Ttln20E2UB4S/WARVqhXffZl2LNgS+gQdPIIim/g=="],
 
-    "eslint-scope": ["eslint-scope@8.4.0", "", { "dependencies": { "esrecurse": "^4.3.0", "estraverse": "^5.2.0" } }, "sha512-sNXOfKCn74rt8RICKMvJS7XKV/Xk9kA7DyJr8mJik3S7Cwgy3qlkkmyS2uQB3jiJg6VNdZd/pDBJu0nvG2NlTg=="],
+    "fetch-blob": ["fetch-blob@3.2.0", "", { "dependencies": { "node-domexception": "^1.0.0", "web-streams-polyfill": "^3.0.3" } }, "sha512-7yAQpD2UMJzLi1Dqv7qFYnPbaPx7ZfFK6PiIxQ4PfkGPyNyl2Ugx+a/umUonmKqjhM4DnfbMvdX6otXq83soQQ=="],
 
-    "eslint-visitor-keys": ["eslint-visitor-keys@4.2.1", "", {}, "sha512-Uhdk5sfqcee/9H/rCOJikYz67o0a2Tw2hGRPOG2Y1R2dg7brRe1uG0yaNQDHu+TO/uQPF/5eCapvYSmHUjt7JQ=="],
-
-    "espree": ["espree@10.4.0", "", { "dependencies": { "acorn": "^8.15.0", "acorn-jsx": "^5.3.2", "eslint-visitor-keys": "^4.2.1" } }, "sha512-j6PAQ2uUr79PZhBjP5C5fhl8e39FmRnOjsD5lGnWrFU8i2G776tBK7+nP8KuQUTTyAZUwfQqXAgrVH5MbH9CYQ=="],
-
-    "esquery": ["esquery@1.7.0", "", { "dependencies": { "estraverse": "^5.1.0" } }, "sha512-Ap6G0WQwcU/LHsvLwON1fAQX9Zp0A2Y6Y/cJBl9r/JbW90Zyg4/zbG6zzKa2OTALELarYHmKu0GhpM5EO+7T0g=="],
-
-    "esrecurse": ["esrecurse@4.3.0", "", { "dependencies": { "estraverse": "^5.2.0" } }, "sha512-KmfKL3b6G+RXvP8N1vr3Tq1kL/oCFgn2NYXEtqP8/L3pKapUA4G8cFVaoF3SU323CD4XypR/ffioHmkti6/Tag=="],
-
-    "estraverse": ["estraverse@5.3.0", "", {}, "sha512-MMdARuVEQziNTeJD8DgMqmhwR11BRQ/cBP+pLtYdSTnf3MIO8fFeiINEbX36ZdNlfU/7A9f3gUw49B3oQsvwBA=="],
-
-    "esutils": ["esutils@2.0.3", "", {}, "sha512-kVscqXk4OCp68SZ0dkgEKVi6/8ij300KBWTJq32P/dYeWTSwK41WyTxalN1eRmA5Z9UU/LX9D7FWSmV9SAYx6g=="],
-
-    "fast-deep-equal": ["fast-deep-equal@3.1.3", "", {}, "sha512-f3qQ9oQy9j2AhBe/H9VC91wLmKBCCU/gDOnKNAYG5hswO7BLKj09Hc5HYNz9cGI++xlpDCIgDaitVs03ATR84Q=="],
-
-    "fast-json-stable-stringify": ["fast-json-stable-stringify@2.1.0", "", {}, "sha512-lhd/wF+Lk98HZoTCtlVraHtfh5XYijIjalXck7saUtuanSDyLMxnHhSXEDJqHxD7msR8D0uCmqlkwjCV8xvwHw=="],
-
-    "fast-levenshtein": ["fast-levenshtein@2.0.6", "", {}, "sha512-DCXu6Ifhqcks7TZKY3Hxp3y6qphY5SJZmrWMDrKcERSOXWQdMhU9Ig/PYrzyw/ul9jOIyh0N4M0tbC5hodg8dw=="],
-
-    "fdir": ["fdir@6.5.0", "", { "peerDependencies": { "picomatch": "^3 || ^4" }, "optionalPeers": ["picomatch"] }, "sha512-tIbYtZbucOs0BRGqPJkshJUYdL+SDH7dVM8gjy+ERp3WAUjLEFJE+02kanyHtwjWOnwrKYBiwAmM0p4kLJAnXg=="],
-
-    "file-entry-cache": ["file-entry-cache@8.0.0", "", { "dependencies": { "flat-cache": "^4.0.0" } }, "sha512-XXTUwCvisa5oacNGRP9SfNtYBNAMi+RPwBFmblZEF7N7swHYQS6/Zfk7SRwx4D5j3CH211YNRco1DEMNVfZCnQ=="],
-
-    "find-up": ["find-up@5.0.0", "", { "dependencies": { "locate-path": "^6.0.0", "path-exists": "^4.0.0" } }, "sha512-78/PXT1wlLLDgTzDs7sjq9hzz0vXD+zn+7wypEe4fXQxCmdmqfGsEPQxmiCSQI3ajFV91bVSsvNtrJRiW6nGng=="],
-
-    "flat-cache": ["flat-cache@4.0.1", "", { "dependencies": { "flatted": "^3.2.9", "keyv": "^4.5.4" } }, "sha512-f7ccFPK3SXFHpx15UIGyRJ/FJQctuKZ0zVuN3frBo4HnK3cay9VEW0R6yPYFHC0AgqhukPzKjq22t5DmAyqGyw=="],
-
-    "flatted": ["flatted@3.4.2", "", {}, "sha512-PjDse7RzhcPkIJwy5t7KPWQSZ9cAbzQXcafsetQoD7sOJRQlGikNbx7yZp2OotDnJyrDcbyRq3Ttb18iYOqkxA=="],
+    "find-up": ["find-up@4.1.0", "", { "dependencies": { "locate-path": "^5.0.0", "path-exists": "^4.0.0" } }, "sha512-PpOwAdQ/YlXQ2vj8a3h8IipDuYRi3wceVQQGYWxNINccq40Anw7BlsEXCMbt1Zt+OLA6Fq9suIpIWD0OsnISlw=="],
 
     "fluent-ffmpeg": ["fluent-ffmpeg@2.1.3", "", { "dependencies": { "async": "^0.2.9", "which": "^1.1.1" } }, "sha512-Be3narBNt2s6bsaqP6Jzq91heDgOEaDCJAXcE3qcma/EJBSy5FB4cvO31XBInuAuKBx8Kptf8dkhjK0IOru39Q=="],
 
     "follow-redirects": ["follow-redirects@1.16.0", "", {}, "sha512-y5rN/uOsadFT/JfYwhxRS5R7Qce+g3zG97+JrtFZlC9klX/W5hD7iiLzScI4nZqUS7DNUdhPgw4xI8W2LuXlUw=="],
 
+    "foreground-child": ["foreground-child@3.3.1", "", { "dependencies": { "cross-spawn": "^7.0.6", "signal-exit": "^4.0.1" } }, "sha512-gIXjKqtFuWEgzFRJA9WCQeSJLZDjgJUOMCMzxtvFq/37KojM1BFGufqsCy0r4qSQmYLsZYMeyRqzIWOMup03sw=="],
+
     "form-data": ["form-data@4.0.5", "", { "dependencies": { "asynckit": "^0.4.0", "combined-stream": "^1.0.8", "es-set-tostringtag": "^2.1.0", "hasown": "^2.0.2", "mime-types": "^2.1.12" } }, "sha512-8RipRLol37bNs2bhoV67fiTEvdTrbMUYcFTiy3+wuuOnUog2QBHCZWXDRijWQfAkhBj2Uf5UnVaiWwA5vdd82w=="],
 
+    "formdata-polyfill": ["formdata-polyfill@4.0.10", "", { "dependencies": { "fetch-blob": "^3.1.2" } }, "sha512-buewHzMvYL29jdeQTVILecSaZKnt/RJWjoZCF5OW60Z67/GmSLBkOFM7qh1PI3zFNtJbaZL5eQu1vLfazOwj4g=="],
+
     "fs-extra": ["fs-extra@8.1.0", "", { "dependencies": { "graceful-fs": "^4.2.0", "jsonfile": "^4.0.0", "universalify": "^0.1.0" } }, "sha512-yhlQgA6mnOJUKOsRUFsgJdQCvkKhcz8tlZG5HBQfReYZy46OwLcY+Zia0mtdHsOo9y/hP+CxMN0TU9QxoOtG4g=="],
 
+    "fsevents": ["fsevents@2.3.3", "", { "os": "darwin" }, "sha512-5xoDfX+fL7faATnagmWPpbFtwh/R77WmMMqqHGS65C3vvB0YHrgF+B1YmZ3441tMj5n63k0212XNoJwzlhffQw=="],
+
     "function-bind": ["function-bind@1.1.2", "", {}, "sha512-7XHNxH7qX9xG5mIwxkhumTox/MIRNcOgDrxWsMt2pAr23WHp6MrRlN7FBSFpCpr+oVO0F744iUgR82nJMfG2SA=="],
 
+    "gaxios": ["gaxios@7.1.3", "", { "dependencies": { "extend": "^3.0.2", "https-proxy-agent": "^7.0.1", "node-fetch": "^3.3.2", "rimraf": "^5.0.1" } }, "sha512-YGGyuEdVIjqxkxVH1pUTMY/XtmmsApXrCVv5EU25iX6inEPbV+VakJfLealkBtJN69AQmh1eGOdCl9Sm1UP6XQ=="],
+
+    "gcp-metadata": ["gcp-metadata@8.1.2", "", { "dependencies": { "gaxios": "^7.0.0", "google-logging-utils": "^1.0.0", "json-bigint": "^1.0.0" } }, "sha512-zV/5HKTfCeKWnxG0Dmrw51hEWFGfcF2xiXqcA3+J90WDuP0SvoiSO5ORvcBsifmx/FoIjgQN3oNOGaQ5PhLFkg=="],
+
     "get-caller-file": ["get-caller-file@2.0.5", "", {}, "sha512-DyFP3BM/3YHTQOCUL/w0OZHR0lpKeGrxotcHWcqNEdnltqFwXVfhEBQ94eIo34AfQpo0rGki4cyIiftY06h2Fg=="],
 
     "get-intrinsic": ["get-intrinsic@1.3.0", "", { "dependencies": { "call-bind-apply-helpers": "^1.0.2", "es-define-property": "^1.0.1", "es-errors": "^1.3.0", "es-object-atoms": "^1.1.1", "function-bind": "^1.1.2", "get-proto": "^1.0.1", "gopd": "^1.2.0", "has-symbols": "^1.1.0", "hasown": "^2.0.2", "math-intrinsics": "^1.1.0" } }, "sha512-9fSjSaos/fRIVIp+xSJlE6lfwhES7LNtKaCBIamHsjr2na1BiABJPo0mOjjz8GJDURarmCPGqaiVg5mfjb98CQ=="],
 
     "get-proto": ["get-proto@1.0.1", "", { "dependencies": { "dunder-proto": "^1.0.1", "es-object-atoms": "^1.0.0" } }, "sha512-sTSfBjoXBp89JvIKIefqw7U2CCebsc74kiY6awiGogKtoSGbgjYE/G/+l9sF3MWFPNc9IcoOC4ODfKHfxFmp0g=="],
 
-    "glob-parent": ["glob-parent@6.0.2", "", { "dependencies": { "is-glob": "^4.0.3" } }, "sha512-XxwI8EOhVQgWp6iDL+3b0r86f4d6AX6zSU55HfB4ydCEuXLXc5FcYeOu+nnGftS4TEju/11rt4KJPTMgbfmv4A=="],
+    "get-tsconfig": ["get-tsconfig@4.14.0", "", { "dependencies": { "resolve-pkg-maps": "^1.0.0" } }, "sha512-yTb+8DXzDREzgvYmh6s9vHsSVCHeC0G3PI5bEXNBHtmshPnO+S5O7qgLEOn0I5QvMy6kpZN8K1NKGyilLb93wA=="],
 
-    "globals": ["globals@14.0.0", "", {}, "sha512-oahGvuMGQlPw/ivIYBjVSrWAfWLBeku5tpPE2fOPLi+WHffIWbuh2tCjhyQhTBPMf5E9jDEH4FOmTYgYwbKwtQ=="],
+    "glob": ["glob@10.5.0", "", { "dependencies": { "foreground-child": "^3.1.0", "jackspeak": "^3.1.2", "minimatch": "^9.0.4", "minipass": "^7.1.2", "package-json-from-dist": "^1.0.0", "path-scurry": "^1.11.1" }, "bin": { "glob": "dist/esm/bin.mjs" } }, "sha512-DfXN8DfhJ7NH3Oe7cFmu3NCu1wKbkReJ8TorzSAFbSKrlNaQSKfIzqYqVY8zlbs2NLBbWpRiU52GX2PbaBVNkg=="],
+
+    "google-auth-library": ["google-auth-library@10.5.0", "", { "dependencies": { "base64-js": "^1.3.0", "ecdsa-sig-formatter": "^1.0.11", "gaxios": "^7.0.0", "gcp-metadata": "^8.0.0", "google-logging-utils": "^1.0.0", "gtoken": "^8.0.0", "jws": "^4.0.0" } }, "sha512-7ABviyMOlX5hIVD60YOfHw4/CxOfBhyduaYB+wbFWCWoni4N7SLcV46hrVRktuBbZjFC9ONyqamZITN7q3n32w=="],
+
+    "google-logging-utils": ["google-logging-utils@1.1.3", "", {}, "sha512-eAmLkjDjAFCVXg7A1unxHsLf961m6y17QFqXqAXGj/gVkKFrEICfStRfwUlGNfeCEjNRa32JEWOUTlYXPyyKvA=="],
 
     "gopd": ["gopd@1.2.0", "", {}, "sha512-ZUKRh6/kUFoAiTAtTYPZJ3hw9wNxx+BIBOijnlG9PnrJsCcSjs1wyyD6vJpaYtgnzDrKYRSqf3OO6Rfa93xsRg=="],
 
     "graceful-fs": ["graceful-fs@4.2.11", "", {}, "sha512-RbJ5/jmFcNNCcDV5o9eTnBLJ/HszWV0P73bc+Ff4nS/rJj+YaS6IGyiOL0VoBYX+l1Wrl3k63h/KrH+nhJ0XvQ=="],
 
-    "has-flag": ["has-flag@4.0.0", "", {}, "sha512-EykJT/Q1KjTWctppgIAgfSO0tKVuZUjhgMr17kqTumMl6Afv3EISleU7qZUzoXDFTAHTDC4NOoG/ZxU3EvlMPQ=="],
+    "gtoken": ["gtoken@8.0.0", "", { "dependencies": { "gaxios": "^7.0.0", "jws": "^4.0.0" } }, "sha512-+CqsMbHPiSTdtSO14O51eMNlrp9N79gmeqmXeouJOhfucAedHw9noVe/n5uJk3tbKE6a+6ZCQg3RPhVhHByAIw=="],
 
     "has-symbols": ["has-symbols@1.1.0", "", {}, "sha512-1cDNdwJ2Jaohmb3sg4OmKaMBwuC48sYni5HUw2DvsC8LjGTLK9h+eb1X6RyuOHe4hT0ULCW68iomhjUoKUqlPQ=="],
 
@@ -347,43 +364,31 @@
 
     "hasown": ["hasown@2.0.2", "", { "dependencies": { "function-bind": "^1.1.2" } }, "sha512-0hJU9SCPvmMzIBdZFqNPXWa6dqh7WdH0cII9y+CyS8rG3nL48Bclra9HmKhVVUHyPWNH5Y7xDwAB7bfgSjkUMQ=="],
 
-    "https-proxy-agent": ["https-proxy-agent@5.0.1", "", { "dependencies": { "agent-base": "6", "debug": "4" } }, "sha512-dFcAjpTQFgoLMzC2VwU+C/CbS7uRL0lWmxDITmqm7C+7F0Odmj6s9l6alZc6AELXhrnggM2CeWSXHGOdX2YtwA=="],
-
-    "ignore": ["ignore@5.3.2", "", {}, "sha512-hsBTNUqQTDwkWtcdYI2i06Y/nUBEsNEDJKjWdigLvegy8kDuJAS8uRlpkkcQpyEXL0Z/pjDy5HBmMjRCJ2gq+g=="],
-
-    "import-fresh": ["import-fresh@3.3.1", "", { "dependencies": { "parent-module": "^1.0.0", "resolve-from": "^4.0.0" } }, "sha512-TR3KfrTZTYLPB6jUjfx6MF9WcWrHL9su5TObK4ZkYgBdWKPOFoSoQIdEuTuR82pmtxH2spWG9h6etwfr1pLBqQ=="],
-
-    "imurmurhash": ["imurmurhash@0.1.4", "", {}, "sha512-JmXMZ6wuvDmLiHEml9ykzqO6lwFbof0GG4IkcGaENdCRDDmMVnny7s5HsIgHCbaq0w2MyPhDqkhTUgS2LU2PHA=="],
-
-    "is-extglob": ["is-extglob@2.1.1", "", {}, "sha512-SbKbANkN603Vi4jEZv49LeVJMn4yGwsbzZworEoyEiutsN3nJYdbO36zfhGJ6QEDpOZIFkDtnq5JRxmvl3jsoQ=="],
+    "https-proxy-agent": ["https-proxy-agent@7.0.6", "", { "dependencies": { "agent-base": "^7.1.2", "debug": "4" } }, "sha512-vK9P5/iUfdl95AI+JVyUuIcVtd4ofvtrOr3HNtM2yxC9bnMbEdp3x01OhQNnjb8IJYi38VlTE3mBXwcfvywuSw=="],
 
     "is-fullwidth-code-point": ["is-fullwidth-code-point@3.0.0", "", {}, "sha512-zymm5+u+sCsSWyD9qNaejV3DFvhCKclKdizYaJUuHA83RLjb7nSuGnddCHGv0hk+KY7BMAlsWeK4Ueg6EV6XQg=="],
 
-    "is-glob": ["is-glob@4.0.3", "", { "dependencies": { "is-extglob": "^2.1.1" } }, "sha512-xelSayHH36ZgE7ZWhli7pW34hNbNl8Ojv5KVmkJD4hBdD3th8Tfk9vYasLM+mXWOZhFkgZfxhLSnrwRr4elSSg=="],
-
     "isexe": ["isexe@2.0.0", "", {}, "sha512-RHxMLp9lnKHGHRng9QFhRCMbYAcVpn69smSGcq3f36xjgVVWThj4qqLbTLlq7Ssj8B+fIQ1EuCEGI2lKsyQeIw=="],
 
+    "jackspeak": ["jackspeak@3.4.3", "", { "dependencies": { "@isaacs/cliui": "^8.0.2" }, "optionalDependencies": { "@pkgjs/parseargs": "^0.11.0" } }, "sha512-OGlZQpz2yfahA/Rd1Y8Cd9SIEsqvXkLVoSw/cgwhnhFMDbsQFeZYoJJ7bIZBS9BcamUW96asq/npPWugM+RQBw=="],
+
     "js-base64": ["js-base64@3.7.8", "", {}, "sha512-hNngCeKxIUQiEUN3GPJOkz4wF/YvdUdbNL9hsBcMQTkKzboD7T/q3OYOuuPZLUE6dBxSGpwhk5mwuDud7JVAow=="],
 
-    "js-yaml": ["js-yaml@4.1.1", "", { "dependencies": { "argparse": "^2.0.1" }, "bin": { "js-yaml": "bin/js-yaml.js" } }, "sha512-qQKT4zQxXl8lLwBtHMWwaTcGfFOZviOJet3Oy/xmGk2gZH677CJM9EvtfdSkgWcATZhj/55JZ0rmy3myCT5lsA=="],
-
-    "json-buffer": ["json-buffer@3.0.1", "", {}, "sha512-4bV5BfR2mqfQTJm+V5tPPdf+ZpuhiIvTuAB5g8kcrXOZpTT/QwwVRWBywX1ozr6lEuPdbHxwaJlm9G6mI2sfSQ=="],
-
-    "json-schema-traverse": ["json-schema-traverse@0.4.1", "", {}, "sha512-xbbCH5dCYU5T8LcEhhuh7HJ88HXuW3qsI3Y0zOZFKfZEHcpWiHU/Jxzk629Brsab/mMiHQti9wMP+845RPe3Vg=="],
-
-    "json-stable-stringify-without-jsonify": ["json-stable-stringify-without-jsonify@1.0.1", "", {}, "sha512-Bdboy+l7tA3OGW6FjyFHWkP5LuByj1Tk33Ljyq0axyzdk9//JSi2u3fP1QSmd1KNwq6VOKYGlAu87CisVir6Pw=="],
+    "json-bigint": ["json-bigint@1.0.0", "", { "dependencies": { "bignumber.js": "^9.0.0" } }, "sha512-SiPv/8VpZuWbvLSMtTDU8hEfrZWg/mH/nV/b4o0CYbSxu1UIQPLdwKOCIyLQX+VIPO5vrLX3i8qtqFyhdPSUSQ=="],
 
     "jsonfile": ["jsonfile@5.0.0", "", { "dependencies": { "universalify": "^0.1.2" }, "optionalDependencies": { "graceful-fs": "^4.1.6" } }, "sha512-NQRZ5CRo74MhMMC3/3r5g2k4fjodJ/wh8MxjFbCViWKFjxrnudWSY5vomh+23ZaXzAS7J3fBZIR2dV6WbmfM0w=="],
 
-    "keyv": ["keyv@4.5.4", "", { "dependencies": { "json-buffer": "3.0.1" } }, "sha512-oxVHkHR/EJf2CNXnWxRLW6mg7JyCCUcG0DtEGmL2ctUo1PNTin1PUil+r/+4r5MpVgC/fn1kjsx7mjSujKqIpw=="],
+    "jwa": ["jwa@2.0.1", "", { "dependencies": { "buffer-equal-constant-time": "^1.0.1", "ecdsa-sig-formatter": "1.0.11", "safe-buffer": "^5.0.1" } }, "sha512-hRF04fqJIP8Abbkq5NKGN0Bbr3JxlQ+qhZufXVr0DvujKy93ZCbXZMHDL4EOtodSbCWxOqR8MS1tXA5hwqCXDg=="],
 
-    "levn": ["levn@0.4.1", "", { "dependencies": { "prelude-ls": "^1.2.1", "type-check": "~0.4.0" } }, "sha512-+bT2uH4E5LGE7h/n3evcS/sQlJXCpIp6ym8OWJ5eV6+67Dsql/LaaT7qJBAt2rzfoa/5QBGBhxDix1dMt2kQKQ=="],
+    "jws": ["jws@4.0.1", "", { "dependencies": { "jwa": "^2.0.1", "safe-buffer": "^5.0.1" } }, "sha512-EKI/M/yqPncGUUh44xz0PxSidXFr/+r0pA70+gIYhjv+et7yxM+s29Y+VGDkovRofQem0fs7Uvf4+YmAdyRduA=="],
 
     "libsql": ["libsql@0.5.29", "", { "dependencies": { "@neon-rs/load": "^0.0.4", "detect-libc": "2.0.2" }, "optionalDependencies": { "@libsql/darwin-arm64": "0.5.29", "@libsql/darwin-x64": "0.5.29", "@libsql/linux-arm-gnueabihf": "0.5.29", "@libsql/linux-arm-musleabihf": "0.5.29", "@libsql/linux-arm64-gnu": "0.5.29", "@libsql/linux-arm64-musl": "0.5.29", "@libsql/linux-x64-gnu": "0.5.29", "@libsql/linux-x64-musl": "0.5.29", "@libsql/win32-x64-msvc": "0.5.29" }, "os": [ "linux", "win32", "darwin", ], "cpu": [ "arm", "x64", "arm64", ] }, "sha512-8lMP8iMgiBzzoNbAPQ59qdVcj6UaE/Vnm+fiwX4doX4Narook0a4GPKWBEv+CR8a1OwbfkgL18uBfBjWdF0Fzg=="],
 
-    "locate-path": ["locate-path@6.0.0", "", { "dependencies": { "p-locate": "^5.0.0" } }, "sha512-iPZK6eYjbxRu3uB4/WZ3EsEIMJFMqAoopl3R+zuq0UjcAm/MO6KCweDgPfP3elTztoKP3KtnVHxTn2NHBSDVUw=="],
+    "locate-path": ["locate-path@5.0.0", "", { "dependencies": { "p-locate": "^4.1.0" } }, "sha512-t7hw9pI+WvuwNJXwk5zVHpyhIqzg2qTlklJOf0mVxGSbe3Fp2VieZcduNYjaLDoy6p9uGpQEGWG87WpMKlNq8g=="],
 
-    "lodash.merge": ["lodash.merge@4.6.2", "", {}, "sha512-0KpjqXRVvrYyCsX1swR/XTK0va6VQkQM6MNo7PqW77ByjAhoARA8EfrP1N4+KlKj8YS0ZUCtRT/YUuhyYDujIQ=="],
+    "long": ["long@5.3.2", "", {}, "sha512-mNAgZ1GmyNhD7AuqnTG3/VQ26o760+ZYBPKjPvugO8+nLbYfX6TVpJPseBvopbdY+qpZ/lKUnmEc1LeZYS3QAA=="],
+
+    "lru-cache": ["lru-cache@10.4.3", "", {}, "sha512-JNAzZcXrCt42VGLuYz0zfAzDfAvJWW6AfYlDBQyDV5DClI2m5sAmK+OIO7s59XfsRsWHp02jAJrRadPRGTt6SQ=="],
 
     "math-intrinsics": ["math-intrinsics@1.1.0", "", {}, "sha512-/IXtbwEk5HTPyEwyKX6hGkYXxM9nbj64B+ilVJnC/R6B0pH5G4V3b0pVbL7DBj4tkhBAppbQUlf6F6Xl9LHu1g=="],
 
@@ -391,65 +396,43 @@
 
     "mime-types": ["mime-types@2.1.29", "", { "dependencies": { "mime-db": "1.46.0" } }, "sha512-Y/jMt/S5sR9OaqteJtslsFZKWOIIqMACsJSiHghlCAyhf7jfVYjKBmLiX8OgpWeW+fjJ2b+Az69aPFPkUOY6xQ=="],
 
-    "minimatch": ["minimatch@3.1.5", "", { "dependencies": { "brace-expansion": "^1.1.7" } }, "sha512-VgjWUsnnT6n+NUk6eZq77zeFdpW2LWDzP6zFGrCbHXiYNul5Dzqk2HHQ5uFH2DNW5Xbp8+jVzaeNt94ssEEl4w=="],
+    "minimatch": ["minimatch@9.0.5", "", { "dependencies": { "brace-expansion": "^2.0.1" } }, "sha512-G6T0ZX48xgozx7587koeX9Ys2NYy6Gmv//P89sEte9V9whIapMNF4idKxnW2QtCcLiTWlb/wfCabAtAFWhhBow=="],
+
+    "minipass": ["minipass@7.1.2", "", {}, "sha512-qOOzS1cBTWYF4BH8fVePDBOO9iptMnGUEZwNc/cMWnTV2nVLZ7VoNWEPHkYczZA0pdoA7dl6e7FL659nX9S2aw=="],
 
     "ms": ["ms@2.1.3", "", {}, "sha512-6FlzubTLZG3J2a/NVCAleEhjzq5oxgHyaCU9yYXvcLsvoVaHJq/s5xXI6/XXP6tz7R9xAOtHnSO/tXtF3WRTlA=="],
 
-    "natural-compare": ["natural-compare@1.4.0", "", {}, "sha512-OWND8ei3VtNC9h7V60qff3SVobHr996CTwgxubgyQYEpg290h9J0buyECNNJexkFm5sOajh5G116RYA1c8ZMSw=="],
+    "node-domexception": ["node-domexception@1.0.0", "", {}, "sha512-/jKZoMpw0F8GRwl4/eLROPA3cfcXtLApP0QzLmUT/HuPCZWyB7IY9ZrMeKw2O/nFIqPQB3PVM9aYm0F312AXDQ=="],
+
+    "node-fetch": ["node-fetch@3.3.2", "", { "dependencies": { "data-uri-to-buffer": "^4.0.0", "fetch-blob": "^3.1.4", "formdata-polyfill": "^4.0.10" } }, "sha512-dRB78srN/l6gqWulah9SrxeYnxeddIG30+GOqK/9OlLVyLg3HPnr6SqOWTWOXKRwC2eGYCkZ59NNuSgvSrpgOA=="],
 
     "ollama": ["ollama@0.6.3", "", { "dependencies": { "whatwg-fetch": "^3.6.20" } }, "sha512-KEWEhIqE5wtfzEIZbDCLH51VFZ6Z3ZSa6sIOg/E/tBV8S51flyqBOXi+bRxlOYKDf8i327zG9eSTb8IJxvm3Zg=="],
 
-    "openai": ["openai@6.38.0", "", { "peerDependencies": { "ws": "^8.18.0", "zod": "^3.25 || ^4.0" }, "optionalPeers": ["ws", "zod"], "bin": { "openai": "bin/cli" } }, "sha512-AoMplt2UalrpgUDMh3L09QWjNRlgJPipclQvA6sYAaeF6nHNBMgmikAZGmcYLn8on4d9sQY9Q8bOLfrBS7Lc8g=="],
+    "openai": ["openai@6.37.0", "", { "peerDependencies": { "ws": "^8.18.0", "zod": "^3.25 || ^4.0" }, "optionalPeers": ["ws", "zod"], "bin": { "openai": "bin/cli" } }, "sha512-0H5dEGFmmLv6KSd0W1w2nyL8WsLkX6yoLeQpU+dZAOuGcany5qkYQMmj35ZrKgb6yiyYqpUzFOpR8mZQkgqeEQ=="],
 
-    "optionator": ["optionator@0.9.4", "", { "dependencies": { "deep-is": "^0.1.3", "fast-levenshtein": "^2.0.6", "levn": "^0.4.1", "prelude-ls": "^1.2.1", "type-check": "^0.4.0", "word-wrap": "^1.2.5" } }, "sha512-6IpQ7mKUxRcZNLIObR0hz7lxsapSSIYNZJwXPGeF0mTVqGKFIXj1DQcMoT22S3ROcLyY/rz0PWaWZ9ayWmad9g=="],
+    "p-limit": ["p-limit@2.3.0", "", { "dependencies": { "p-try": "^2.0.0" } }, "sha512-//88mFWSJx8lxCzwdAABTJL2MyWB12+eIY7MDL2SqLmAkeKU9qxRvWuSyTjm3FUmpBEMuFfckAIqEaVGUDxb6w=="],
 
-    "p-limit": ["p-limit@3.1.0", "", { "dependencies": { "yocto-queue": "^0.1.0" } }, "sha512-TYOanM3wGwNGsZN2cVTYPArw454xnXj5qmWF1bEoAc4+cU/ol7GVh7odevjp1FNHduHc3KZMcFduxU5Xc6uJRQ=="],
+    "p-locate": ["p-locate@4.1.0", "", { "dependencies": { "p-limit": "^2.2.0" } }, "sha512-R79ZZ/0wAxKGu3oYMlz8jy/kbhsNrS7SKZ7PxEHBgJ5+F2mtFW2fK2cOtBh1cHYkQsbzFV7I+EoRKe6Yt0oK7A=="],
 
-    "p-locate": ["p-locate@5.0.0", "", { "dependencies": { "p-limit": "^3.0.2" } }, "sha512-LaNjtRWUBY++zB5nE/NwcaoMylSPk+S+ZHNB1TzdbMJMny6dynpAGt7X/tl/QYq3TIeE6nxHppbo2LGymrG5Pw=="],
+    "p-retry": ["p-retry@4.6.2", "", { "dependencies": { "@types/retry": "0.12.0", "retry": "^0.13.1" } }, "sha512-312Id396EbJdvRONlngUx0NydfrIQ5lsYu0znKVUzVvArzEIt08V1qhtyESbGVd1FGX7UKtiFp5uwKZdM8wIuQ=="],
 
     "p-try": ["p-try@2.2.0", "", {}, "sha512-R4nPAVTAU0B9D35/Gk3uJf/7XYbQcyohSKdvAxIRSNghFl4e71hVoGnBNQz9cWaXxO2I10KTC+3jMdvvoKw6dQ=="],
 
-    "parent-module": ["parent-module@1.0.1", "", { "dependencies": { "callsites": "^3.0.0" } }, "sha512-GQ2EWRpQV8/o+Aw8YqtfZZPfNRWZYkbidE9k5rpl/hC3vtHHBfGm2Ifi6qWV+coDGkrUKZAxE3Lot5kcsRlh+g=="],
+    "package-json-from-dist": ["package-json-from-dist@1.0.1", "", {}, "sha512-UEZIS3/by4OC8vL3P2dTXRETpebLI2NiI5vIrjaD/5UtrkFX/tNbwjTSRAGC/+7CAo2pIcBaRgWmcBBHcsaCIw=="],
 
     "path-exists": ["path-exists@4.0.0", "", {}, "sha512-ak9Qy5Q7jYb2Wwcey5Fpvg2KoAc/ZIhLSLOSBmRmygPsGwkVVt0fZa0qrtMz+m6tJTAHfZQ8FnmB4MG4LWy7/w=="],
 
     "path-key": ["path-key@3.1.1", "", {}, "sha512-ojmeN0qd+y0jszEtoY48r0Peq5dwMEkIlCOu6Q5f41lfkswXuKtYrhgoTpLnyIcHm24Uhqx+5Tqm2InSwLhE6Q=="],
 
-    "pg": ["pg@8.21.0", "", { "dependencies": { "pg-connection-string": "^2.13.0", "pg-pool": "^3.14.0", "pg-protocol": "^1.14.0", "pg-types": "2.2.0", "pgpass": "1.0.5" }, "optionalDependencies": { "pg-cloudflare": "^1.4.0" }, "peerDependencies": { "pg-native": ">=3.0.1" }, "optionalPeers": ["pg-native"] }, "sha512-AUP1EYJuHraQGsVoCQVIcM7TEJVGtDzxWtGFZd8rds9d+CCXlU5Js1rYgfLNvxy9iJrpHjGrRjoi/3BT9fRyiA=="],
-
-    "pg-cloudflare": ["pg-cloudflare@1.4.0", "", {}, "sha512-Vo7z/6rrQYxpNRylp4Tlob2elzbh+N/MOQbxFVWCxS7oEx6jF53GTJFxK2WWpKuBRkmiin4Mt+xofFDjx09R0A=="],
-
-    "pg-connection-string": ["pg-connection-string@2.13.0", "", {}, "sha512-EMnU9E2fSULdsbErBbMaXJvFeD9B4+nPcM3f+4lsiCR0BHLPrLVjv3DbyM2hgQQviKJaTWIRRTjKjWlHg3p2ig=="],
-
-    "pg-int8": ["pg-int8@1.0.1", "", {}, "sha512-WCtabS6t3c8SkpDBUlb1kjOs7l66xsGdKpIPZsg4wR+B3+u9UAum2odSsF9tnvxg80h4ZxLWMy4pRjOsFIqQpw=="],
-
-    "pg-pool": ["pg-pool@3.14.0", "", { "peerDependencies": { "pg": ">=8.0" } }, "sha512-gKtPkFdQPU3DksooVLi9LsjZxrsBUZIpa+7aVx+LV5pNh0KzP4Zleud2po+ConrxbuXGBJ6Hfer6hdgpIBpBaw=="],
-
-    "pg-protocol": ["pg-protocol@1.13.0", "", {}, "sha512-zzdvXfS6v89r6v7OcFCHfHlyG/wvry1ALxZo4LqgUoy7W9xhBDMaqOuMiF3qEV45VqsN6rdlcehHrfDtlCPc8w=="],
-
-    "pg-types": ["pg-types@2.2.0", "", { "dependencies": { "pg-int8": "1.0.1", "postgres-array": "~2.0.0", "postgres-bytea": "~1.0.0", "postgres-date": "~1.0.4", "postgres-interval": "^1.1.0" } }, "sha512-qTAAlrEsl8s4OiEQY69wDvcMIdQN6wdz5ojQiOy6YRMuynxenON0O5oCpJI6lshc6scgAY8qvJ2On/p+CXY0GA=="],
-
-    "pgpass": ["pgpass@1.0.5", "", { "dependencies": { "split2": "^4.1.0" } }, "sha512-FdW9r/jQZhSeohs1Z3sI1yxFQNFvMcnmfuj4WBMUTxOrAyLMaTcE1aAMBiTlbMNaXvBCQuVi0R7hd8udDSP7ug=="],
-
-    "picomatch": ["picomatch@4.0.4", "", {}, "sha512-QP88BAKvMam/3NxH6vj2o21R6MjxZUAd6nlwAS/pnGvN9IVLocLHxGYIzFhg6fUQ+5th6P4dv4eW9jX3DSIj7A=="],
+    "path-scurry": ["path-scurry@1.11.1", "", { "dependencies": { "lru-cache": "^10.2.0", "minipass": "^5.0.0 || ^6.0.2 || ^7.0.0" } }, "sha512-Xa4Nw17FS9ApQFJ9umLiJS4orGjm7ZzwUrwamcGQuHSzDyth9boKDaycYdDcZDuqYATXw4HFXgaqWTctW/v1HA=="],
 
     "pngjs": ["pngjs@5.0.0", "", {}, "sha512-40QW5YalBNfQo5yRYmiw7Yz6TKKVr3h6970B2YE+3fQpsWcrbj1PzJgxeJ19DRQjhMbKPIuMY8rFaXc8moolVw=="],
 
-    "postgres-array": ["postgres-array@2.0.0", "", {}, "sha512-VpZrUqU5A69eQyW2c5CA1jtLecCsN2U/bD6VilrFDWq5+5UIEVO7nazS3TEcHf1zuPYO/sqGvUvW62g86RXZuA=="],
-
-    "postgres-bytea": ["postgres-bytea@1.0.1", "", {}, "sha512-5+5HqXnsZPE65IJZSMkZtURARZelel2oXUEO8rH83VS/hxH5vv1uHquPg5wZs8yMAfdv971IU+kcPUczi7NVBQ=="],
-
-    "postgres-date": ["postgres-date@1.0.7", "", {}, "sha512-suDmjLVQg78nMK2UZ454hAG+OAW+HQPZ6n++TNDUX+L0+uUlLywnoxJKDou51Zm+zTCjrCl0Nq6J9C5hP9vK/Q=="],
-
-    "postgres-interval": ["postgres-interval@1.2.0", "", { "dependencies": { "xtend": "^4.0.0" } }, "sha512-9ZhXKM/rw350N1ovuWHbGxnGh/SNJ4cnxHiM0rxE4VN41wsg8P8zWn9hv/buK00RP4WvlOyr/RBDiptyxVbkZQ=="],
-
-    "prelude-ls": ["prelude-ls@1.2.1", "", {}, "sha512-vkcDPrRZo1QZLbn5RLGPpg/WmIQ65qoWWhcGKf/b5eplkkarX0m9z8ppCat4mlOqUsWpyNuYgO3VRyrYHSzX5g=="],
-
     "promise-limit": ["promise-limit@2.7.0", "", {}, "sha512-7nJ6v5lnJsXwGprnGXga4wx6d1POjvi5Qmf1ivTRxTjH4Z/9Czja/UCMLVmB9N93GeWOU93XaFaEt6jbuoagNw=="],
 
-    "proxy-from-env": ["proxy-from-env@2.1.0", "", {}, "sha512-cJ+oHTW1VAEa8cJslgmUZrc+sjRKgAKl3Zyse6+PV38hZe/V6Z14TbCuXcan9F9ghlz4QrFr2c92TNF82UkYHA=="],
+    "protobufjs": ["protobufjs@7.5.4", "", { "dependencies": { "@protobufjs/aspromise": "^1.1.2", "@protobufjs/base64": "^1.1.2", "@protobufjs/codegen": "^2.0.4", "@protobufjs/eventemitter": "^1.1.0", "@protobufjs/fetch": "^1.1.0", "@protobufjs/float": "^1.0.2", "@protobufjs/inquire": "^1.1.0", "@protobufjs/path": "^1.1.2", "@protobufjs/pool": "^1.1.0", "@protobufjs/utf8": "^1.1.0", "@types/node": ">=13.7.0", "long": "^5.0.0" } }, "sha512-CvexbZtbov6jW2eXAvLukXjXUW1TzFaivC46BpWc/3BpcCysb5Vffu+B3XHMm8lVEuy2Mm4XGex8hBSg1yapPg=="],
 
-    "punycode": ["punycode@2.3.1", "", {}, "sha512-vYt7UD1U9Wg6138shLtLOvdAu+8DsC/ilFtEVHcH+wydcSpNE20AfSOduf6MkRFahL5FY7X1oU7nKVZFtfq8Fg=="],
+    "proxy-from-env": ["proxy-from-env@2.1.0", "", {}, "sha512-cJ+oHTW1VAEa8cJslgmUZrc+sjRKgAKl3Zyse6+PV38hZe/V6Z14TbCuXcan9F9ghlz4QrFr2c92TNF82UkYHA=="],
 
     "qrcode": ["qrcode@1.5.4", "", { "dependencies": { "dijkstrajs": "^1.0.1", "pngjs": "^5.0.0", "yargs": "^15.3.1" }, "bin": { "qrcode": "bin/qrcode" } }, "sha512-1ca71Zgiu6ORjHqFBDpnSMTR2ReToX4l1Au1VFLyVeBTFavzQnv5JxMFr3ukHVKpSrSA2MCk0lNJSykjUfz7Zg=="],
 
@@ -457,7 +440,13 @@
 
     "require-main-filename": ["require-main-filename@2.0.0", "", {}, "sha512-NKN5kMDylKuldxYLSUfrbo5Tuzh4hd+2E8NPPX02mZtn1VuREQToYe/ZdlJy+J3uCpfaiGF05e7B8W0iXbQHmg=="],
 
-    "resolve-from": ["resolve-from@4.0.0", "", {}, "sha512-pb/MYmXstAkysRFx8piNI1tGFNQIFA3vkE3Gq4EuA1dF6gHp/+vgZqsCGJapvy8N3Q+4o7FwvquPJcnZ7RYy4g=="],
+    "resolve-pkg-maps": ["resolve-pkg-maps@1.0.0", "", {}, "sha512-seS2Tj26TBVOC2NIc2rOe2y2ZO7efxITtLZcGSOnHHNOQ7CkiUBfw0Iw2ck6xkIhPwLhKNLS8BO+hEpngQlqzw=="],
+
+    "retry": ["retry@0.13.1", "", {}, "sha512-XQBQ3I8W1Cge0Seh+6gjj03LbmRFWuoszgK9ooCpwYIrhhoO80pfq4cUkU5DkknwfOfFteRwlZ56PYOGYyFWdg=="],
+
+    "rimraf": ["rimraf@5.0.10", "", { "dependencies": { "glob": "^10.3.7" }, "bin": { "rimraf": "dist/esm/bin.mjs" } }, "sha512-l0OE8wL34P4nJH/H2ffoaniAokM2qSmrtXHmlpvYr5AVVX8msAyW0l8NVJFDxlSK4u3Uh/f41cQheDVdnYijwQ=="],
+
+    "safe-buffer": ["safe-buffer@5.2.1", "", {}, "sha512-rp3So07KcdmmKbGvgaNxQSJr7bGVSVk5S9Eq1F+ppbRo70+YeaDxkw5Dd8NPN+GD6bjnYm2VuPuCXmpuYvmCXQ=="],
 
     "semver": ["semver@7.7.3", "", { "bin": { "semver": "bin/semver.js" } }, "sha512-SdsKMrI9TdgjdweUSR9MweHA4EJ8YxHn8DFaDisvhVlUOe4BF1tLD7GAj0lIqWVl+dPb/rExr0Btby5loQm20Q=="],
 
@@ -469,41 +458,39 @@
 
     "shebang-regex": ["shebang-regex@3.0.0", "", {}, "sha512-7++dFhtcx3353uBaq8DDR4NuxBetBzC7ZQOhmTQInHEd6bSrXdiEyzCvG07Z44UYdLShWUyXt5M/yhz8ekcb1A=="],
 
-    "split2": ["split2@4.2.0", "", {}, "sha512-UcjcJOWknrNkF6PLX83qcHM6KHgVKNkV62Y8a5uYDVv9ydGQVwAHMKqHdJje1VTWpljG0WYpCDhrCdAOYH4TWg=="],
+    "signal-exit": ["signal-exit@4.1.0", "", {}, "sha512-bzyZ1e88w9O1iNJbKnOlvYTrWPDl46O1bG0D3XInv+9tkPrxrN8jUUTiFlDkkmKWgn1M6CfIA13SuGqOa9Korw=="],
+
+    "source-map": ["source-map@0.6.1", "", {}, "sha512-UjgapumWlbMhkBgzT7Ykc5YXUT46F0iKu8SGXq0bcwP5dz/h0Plj6enJqjz1Zbq2l5WaqYnrVbwWOWMyF3F47g=="],
+
+    "source-map-support": ["source-map-support@0.5.21", "", { "dependencies": { "buffer-from": "^1.0.0", "source-map": "^0.6.0" } }, "sha512-uBHU3L3czsIyYXKX88fdrGovxdSCoTGDRZ6SYXtSRxLZUzHg5P/66Ht6uoUlHu9EZod+inXhKo3qQgwXUT/y1w=="],
 
     "string-width": ["string-width@4.2.3", "", { "dependencies": { "emoji-regex": "^8.0.0", "is-fullwidth-code-point": "^3.0.0", "strip-ansi": "^6.0.1" } }, "sha512-wKyQRQpjJ0sIp62ErSZdGsjMJWsap5oRNihHhu6G7JVO/9jIB6UyevL+tXuOqrng8j/cxKTWyWUwvSTriiZz/g=="],
 
+    "string-width-cjs": ["string-width@4.2.3", "", { "dependencies": { "emoji-regex": "^8.0.0", "is-fullwidth-code-point": "^3.0.0", "strip-ansi": "^6.0.1" } }, "sha512-wKyQRQpjJ0sIp62ErSZdGsjMJWsap5oRNihHhu6G7JVO/9jIB6UyevL+tXuOqrng8j/cxKTWyWUwvSTriiZz/g=="],
+
     "strip-ansi": ["strip-ansi@6.0.1", "", { "dependencies": { "ansi-regex": "^5.0.1" } }, "sha512-Y38VPSHcqkFrCpFnQ9vuSXmquuv5oXOKpGeT6aGrr3o3Gc9AlVa6JBfUSOCnbxGGZF+/0ooI7KrPuUSztUdU5A=="],
 
-    "strip-json-comments": ["strip-json-comments@3.1.1", "", {}, "sha512-6fPc+R4ihwqP6N/aIv2f1gMH8lOVtWQHoqC4yK6oSDVVocumAsfCqjkXnqiYMhmMwS/mEHLp7Vehlt3ql6lEig=="],
-
-    "supports-color": ["supports-color@7.2.0", "", { "dependencies": { "has-flag": "^4.0.0" } }, "sha512-qpCAvRl9stuOHveKsn7HncJRvv501qIacKzQlO/+Lwxc9+0q2wLyv4Dfvt80/DPn2pqOBsJdDiogXGR9+OvwRw=="],
+    "strip-ansi-cjs": ["strip-ansi@6.0.1", "", { "dependencies": { "ansi-regex": "^5.0.1" } }, "sha512-Y38VPSHcqkFrCpFnQ9vuSXmquuv5oXOKpGeT6aGrr3o3Gc9AlVa6JBfUSOCnbxGGZF+/0ooI7KrPuUSztUdU5A=="],
 
     "systeminformation": ["systeminformation@5.31.6", "", { "os": "!aix", "bin": { "systeminformation": "lib/cli.js" } }, "sha512-Uv2b2uGGM6ns+26czgW2cYRabYdnswM0ddSOOlryHOaelzsmDSet1iM/NT7VOYxW8x/BW+HkY+b1Ve2pLTSGSA=="],
 
-    "tinyglobby": ["tinyglobby@0.2.16", "", { "dependencies": { "fdir": "^6.5.0", "picomatch": "^4.0.4" } }, "sha512-pn99VhoACYR8nFHhxqix+uvsbXineAasWm5ojXoN8xEwK5Kd3/TrhNn1wByuD52UxWRLy8pu+kRMniEi6Eq9Zg=="],
-
-    "ts-api-utils": ["ts-api-utils@2.5.0", "", { "peerDependencies": { "typescript": ">=4.8.4" } }, "sha512-OJ/ibxhPlqrMM0UiNHJ/0CKQkoKF243/AEmplt3qpRgkW8VG7IfOS41h7V8TjITqdByHzrjcS/2si+y4lIh8NA=="],
-
     "tslib": ["tslib@2.8.1", "", {}, "sha512-oJFu94HQb+KVduSUQL7wnpmqnfmLsOA/nAh6b6EH0wCEoK0/mPeXU6c3wKDV83MkOuHPRHtSXKKU99IBazS/2w=="],
 
+    "tsx": ["tsx@4.21.0", "", { "dependencies": { "esbuild": "~0.27.0", "get-tsconfig": "^4.7.5" }, "optionalDependencies": { "fsevents": "~2.3.3" }, "bin": { "tsx": "dist/cli.mjs" } }, "sha512-5C1sg4USs1lfG0GFb2RLXsdpXqBSEhAaA/0kPL01wxzpMqLILNxIxIOKiILz+cdg/pLnOUxFYOR5yhHU666wbw=="],
+
     "twemoji": ["twemoji@14.0.2", "", { "dependencies": { "fs-extra": "^8.0.1", "jsonfile": "^5.0.0", "twemoji-parser": "14.0.0", "universalify": "^0.1.2" } }, "sha512-BzOoXIe1QVdmsUmZ54xbEH+8AgtOKUiG53zO5vVP2iUu6h5u9lN15NcuS6te4OY96qx0H7JK9vjjl9WQbkTRuA=="],
 
     "twemoji-parser": ["twemoji-parser@14.0.0", "", {}, "sha512-9DUOTGLOWs0pFWnh1p6NF+C3CkQ96PWmEFwhOVmT3WbecRC+68AIqpsnJXygfkFcp4aXbOp8Dwbhh/HQgvoRxA=="],
 
-    "type-check": ["type-check@0.4.0", "", { "dependencies": { "prelude-ls": "^1.2.1" } }, "sha512-XleUoc9uwGXqjWwXaUTZAmzMcFZ5858QA2vvx1Ur5xIcixXIP+8LnFDgRplU30us6teqdlskFfu+ae4K79Ooew=="],
-
     "typescript": ["typescript@6.0.3", "", { "bin": { "tsc": "bin/tsc", "tsserver": "bin/tsserver" } }, "sha512-y2TvuxSZPDyQakkFRPZHKFm+KKVqIisdg9/CZwm9ftvKXLP8NRWj38/ODjNbr43SsoXqNuAisEf1GdCxqWcdBw=="],
 
-    "typescript-eslint": ["typescript-eslint@8.59.4", "", { "dependencies": { "@typescript-eslint/eslint-plugin": "8.59.4", "@typescript-eslint/parser": "8.59.4", "@typescript-eslint/typescript-estree": "8.59.4", "@typescript-eslint/utils": "8.59.4" }, "peerDependencies": { "eslint": "^8.57.0 || ^9.0.0 || ^10.0.0", "typescript": ">=4.8.4 <6.1.0" } }, "sha512-Rw6+44QNFaXtgHSjPy+Kw8hrJniMYzR85E9yLmOLcfZ91/rz+JXQbDTCmc6ccxMPY6K6PgAq26f0JCBfR7LIPQ=="],
-
     "typescript-telegram-bot-api": ["typescript-telegram-bot-api@0.16.0", "", { "dependencies": { "axios": "^1.7.7", "form-data": "^4.0.1" } }, "sha512-NaAjXucQiZ87U8La/IMaWDOghbMlJzfMbU4rG8ppFpgPOvEwat/zfN5BM+J2QDvKVGN87qJ+1nELnkm3ctSLnQ=="],
 
-    "undici-types": ["undici-types@7.24.6", "", {}, "sha512-WRNW+sJgj5OBN4/0JpHFqtqzhpbnV0GuB+OozA9gCL7a993SmU+1JBZCzLNxYsbMfIeDL+lTsphD5jN5N+n0zg=="],
+    "undici-types": ["undici-types@7.19.2", "", {}, "sha512-qYVnV5OEm2AW8cJMCpdV20CDyaN3g0AjDlOGf1OW4iaDEx8MwdtChUp4zu4H0VP3nDRF/8RKWH+IPp9uW0YGZg=="],
 
     "universalify": ["universalify@0.1.2", "", {}, "sha512-rBJeI5CXAlmy1pV+617WB9J63U6XcazHHF2f2dbJix4XzpUF0RS3Zbj0FGIOCAva5P/d/GBOYaACQ1w+0azUkg=="],
 
-    "uri-js": ["uri-js@4.4.1", "", { "dependencies": { "punycode": "^2.1.0" } }, "sha512-7rKUyy33Q1yc98pQ1DAmLtwX109F7TIfWlW1Ydo8Wl1ii1SeHieeh0HHfPeL2fMXK6z0s8ecKs9frCuLJvndBg=="],
+    "web-streams-polyfill": ["web-streams-polyfill@3.3.3", "", {}, "sha512-d2JWLCivmZYTSIoge9MsgFCZrt571BikcWGYkjC1khllbTeDlGqZ2D8vD8E/lJa8WGWbb7Plm8/XJYV7IJHZZw=="],
 
     "whatwg-fetch": ["whatwg-fetch@3.6.20", "", {}, "sha512-EqhiFU6daOA8kpjOWTL0olhVOF3i7OrFzSYiGsEMB8GcXS+RrzauAERX65xMeNWVqxA6HXH2m69Z9LaKKdisfg=="],
 
@@ -511,13 +498,11 @@
 
     "which-module": ["which-module@2.0.1", "", {}, "sha512-iBdZ57RDvnOR9AGBhML2vFZf7h8vmBjhoaZqODJBFWHVtKkDmKuHai3cx5PgVMrX5YDNp27AofYbAwctSS+vhQ=="],
 
-    "word-wrap": ["word-wrap@1.2.5", "", {}, "sha512-BN22B5eaMMI9UMtjrGd5g5eCYPpCPDUy0FJXbYsaT5zYxjFOckS53SQDE3pWkVoWpHXVb3BrYcEN4Twa55B5cA=="],
-
     "wrap-ansi": ["wrap-ansi@6.2.0", "", { "dependencies": { "ansi-styles": "^4.0.0", "string-width": "^4.1.0", "strip-ansi": "^6.0.0" } }, "sha512-r6lPcBGxZXlIcymEu7InxDMhdW0KDxpLgoFLcguasxCaJ/SOIZwINatK9KY/tf+ZrlywOKU0UDj3ATXUBfxJXA=="],
 
-    "ws": ["ws@8.19.0", "", { "peerDependencies": { "bufferutil": "^4.0.1", "utf-8-validate": ">=5.0.2" }, "optionalPeers": ["bufferutil", "utf-8-validate"] }, "sha512-blAT2mjOEIi0ZzruJfIhb3nps74PRWTCz1IjglWEEpQl5XS/UNama6u2/rjFkDDouqr4L67ry+1aGIALViWjDg=="],
+    "wrap-ansi-cjs": ["wrap-ansi@7.0.0", "", { "dependencies": { "ansi-styles": "^4.0.0", "string-width": "^4.1.0", "strip-ansi": "^6.0.0" } }, "sha512-YVGIj2kamLSTxw6NsZjoBxfSwsn0ycdesmc4p+Q21c5zPuZ1pl+NfxVdxPtdHvmNVOQ6XSYG4AUtyt/Fi7D16Q=="],
 
-    "xtend": ["xtend@4.0.2", "", {}, "sha512-LKYU1iAXJXUgAXn9URjiu+MWhyUXHsvfp7mcuYm9dSUKK0/CjtrUwFAxD82/mCWbtLsGjFIad0wIsod4zrTAEQ=="],
+    "ws": ["ws@8.19.0", "", { "peerDependencies": { "bufferutil": "^4.0.1", "utf-8-validate": ">=5.0.2" }, "optionalPeers": ["bufferutil", "utf-8-validate"] }, "sha512-blAT2mjOEIi0ZzruJfIhb3nps74PRWTCz1IjglWEEpQl5XS/UNama6u2/rjFkDDouqr4L67ry+1aGIALViWjDg=="],
 
     "y18n": ["y18n@4.0.3", "", {}, "sha512-JKhqTOwSrqNA1NY5lSztJ1GrBiUodLMmIZuLiDaMRJ+itFd+ABVE8XBjOvIWL+rSqNDC74LCSFmlb/U4UZ4hJQ=="],
 
@@ -525,13 +510,17 @@
 
     "yargs-parser": ["yargs-parser@18.1.3", "", { "dependencies": { "camelcase": "^5.0.0", "decamelize": "^1.2.0" } }, "sha512-o50j0JeToy/4K6OZcaQmW6lyXXKhq7csREXcDwk2omFPJEwUNOVtJKvmDr9EI1fAJZUyZcRF7kxGBWmRXudrCQ=="],
 
-    "yocto-queue": ["yocto-queue@0.1.0", "", {}, "sha512-rVksvsnNCdJ/ohGc6xgPwyN8eheCxsiLM8mxuE/t/mOVqJewPuO1miLpTHQiRgTKCLexL4MeAFVagts7HmNZ2Q=="],
-
     "zod": ["zod@4.4.3", "", {}, "sha512-ytENFjIJFl2UwYglde2jchW2Hwm4GJFLDiSXWdTrJQBIN9Fcyp7n4DhxJEiWNAJMV1/BqWfW/kkg71UDcHJyTQ=="],
 
     "zod-to-json-schema": ["zod-to-json-schema@3.25.1", "", { "peerDependencies": { "zod": "^3.25 || ^4" } }, "sha512-pM/SU9d3YAggzi6MtR4h7ruuQlqKtad8e9S0fmxcMi+ueAK5Korys/aWcV9LIIHTVbj01NdzxcnXSN+O74ZIVA=="],
 
-    "@eslint-community/eslint-utils/eslint-visitor-keys": ["eslint-visitor-keys@3.4.3", "", {}, "sha512-wpc+LXeiyiisxPlEkUzU6svyS1frIO3Mgxj1fdy7Pm8Ygzguax2N3Fa/D/ag1WqbOprdI+uY6wMUl8/a2G+iag=="],
+    "@esbuild-kit/core-utils/esbuild": ["esbuild@0.18.20", "", { "optionalDependencies": { "@esbuild/android-arm": "0.18.20", "@esbuild/android-arm64": "0.18.20", "@esbuild/android-x64": "0.18.20", "@esbuild/darwin-arm64": "0.18.20", "@esbuild/darwin-x64": "0.18.20", "@esbuild/freebsd-arm64": "0.18.20", "@esbuild/freebsd-x64": "0.18.20", "@esbuild/linux-arm": "0.18.20", "@esbuild/linux-arm64": "0.18.20", "@esbuild/linux-ia32": "0.18.20", "@esbuild/linux-loong64": "0.18.20", "@esbuild/linux-mips64el": "0.18.20", "@esbuild/linux-ppc64": "0.18.20", "@esbuild/linux-riscv64": "0.18.20", "@esbuild/linux-s390x": "0.18.20", "@esbuild/linux-x64": "0.18.20", "@esbuild/netbsd-x64": "0.18.20", "@esbuild/openbsd-x64": "0.18.20", "@esbuild/sunos-x64": "0.18.20", "@esbuild/win32-arm64": "0.18.20", "@esbuild/win32-ia32": "0.18.20", "@esbuild/win32-x64": "0.18.20" }, "bin": { "esbuild": "bin/esbuild" } }, "sha512-ceqxoedUrcayh7Y7ZX6NdbbDzGROiyVBgC4PriJThBKSVPWnnFHZAkfI1lJT8QFkOwH4qOS2SJkS4wvpGl8BpA=="],
+
+    "@isaacs/cliui/string-width": ["string-width@5.1.2", "", { "dependencies": { "eastasianwidth": "^0.2.0", "emoji-regex": "^9.2.2", "strip-ansi": "^7.0.1" } }, "sha512-HnLOCR3vjcY8beoNLtcjZ5/nxn2afmME6lhrDrebokqMap+XbeW8n9TXpPDOqdGK5qcI3oT0GKTW6wC7EMiVqA=="],
+
+    "@isaacs/cliui/strip-ansi": ["strip-ansi@7.1.2", "", { "dependencies": { "ansi-regex": "^6.0.1" } }, "sha512-gmBGslpoQJtgnMAvOVqGZpEz9dyoKTCzy2nfz/n8aIFhN/jCE/rCmcxabB6jOOHV+0WNnylOxaxBQPSvcWklhA=="],
+
+    "@isaacs/cliui/wrap-ansi": ["wrap-ansi@8.1.0", "", { "dependencies": { "ansi-styles": "^6.1.0", "string-width": "^5.0.1", "strip-ansi": "^7.0.1" } }, "sha512-si7QWI6zUMq56bESFvagtmzMdGOtoxfR+Sez11Mobfc7tm+VkUckk9bW2UeffTGVUbOksxmSw0AA2gs8g71NCQ=="],
 
     "@libsql/isomorphic-ws/ws": ["ws@8.18.3", "", { "peerDependencies": { "bufferutil": "^4.0.1", "utf-8-validate": ">=5.0.2" }, "optionalPeers": ["bufferutil", "utf-8-validate"] }, "sha512-PEIGCY5tSlUt50cqyMXfCzX+oOPqN0vuGqWzbcJ2xvnkzkq46oOpz7dQaTDBdfICb4N14+GARUDw2XV2N4tvzg=="],
 
@@ -539,19 +528,11 @@
 
     "@types/fluent-ffmpeg/@types/node": ["@types/node@25.2.3", "", { "dependencies": { "undici-types": "~7.16.0" } }, "sha512-m0jEgYlYz+mDJZ2+F4v8D1AyQb+QzsNqRuI7xg1VQX/KlKS0qT9r1Mo16yo5F/MtifXFgaofIFsdFMox2SxIbQ=="],
 
-    "@types/pg/@types/node": ["@types/node@25.6.1", "", { "dependencies": { "undici-types": "~7.19.0" } }, "sha512-coJCN8O1q4AGyyqCAUSP06P+SrMTu18BkEj3NVAK07q6QUneD2wzj3CLv9+yP+BMeZQlMvneXqqvDe3w+xcq7g=="],
-
     "@types/qrcode/@types/node": ["@types/node@25.0.3", "", { "dependencies": { "undici-types": "~7.16.0" } }, "sha512-W609buLVRVmeW693xKfzHeIV6nJGGz98uCPfeXI1ELMLXVeKYZ9m15fAMSaUPBHYLGFsVRcMmSCksQOrZV9BYA=="],
 
     "@types/ws/@types/node": ["@types/node@25.0.3", "", { "dependencies": { "undici-types": "~7.16.0" } }, "sha512-W609buLVRVmeW693xKfzHeIV6nJGGz98uCPfeXI1ELMLXVeKYZ9m15fAMSaUPBHYLGFsVRcMmSCksQOrZV9BYA=="],
 
-    "@typescript-eslint/eslint-plugin/ignore": ["ignore@7.0.5", "", {}, "sha512-Hs59xBNfUIunMFgWAbGX5cq6893IbWg4KnrjbYwX3tx0ztorVgTDA6B2sxf8ejHJ4wz8BqGUMYlnzNBer5NvGg=="],
-
-    "@typescript-eslint/typescript-estree/minimatch": ["minimatch@10.2.5", "", { "dependencies": { "brace-expansion": "^5.0.5" } }, "sha512-MULkVLfKGYDFYejP07QOurDLLQpcjk7Fw+7jXS2R2czRQzR56yHRveU5NDJEOviH+hETZKSkIk5c+T23GjFUMg=="],
-
-    "@typescript-eslint/visitor-keys/eslint-visitor-keys": ["eslint-visitor-keys@5.0.1", "", {}, "sha512-tD40eHxA35h0PEIZNeIjkHoDR4YjjJp34biM0mDvplBe//mB+IHCqHDGV7pxF+7MklTvighcCPPZC7ynWyjdTA=="],
-
-    "bun-types/@types/node": ["@types/node@25.8.0", "", { "dependencies": { "undici-types": ">=7.24.0 <7.24.7" } }, "sha512-TCFSk8IZh+iLX1xtksoBVtdmgL+1IX0fC9BeU4QqFSuNdN/K+HUlhqOzEmSYYpZUVsLYcPqc9KX+60iDuninSQ=="],
+    "bun-types/@types/node": ["@types/node@25.6.0", "", { "dependencies": { "undici-types": "~7.19.0" } }, "sha512-+qIYRKdNYJwY3vRCZMdJbPLJAtGjQBudzZzdzwQYkEPQd+PJGixUL5QfvCLDaULoLv+RhT3LDkwEfKaAkgSmNQ=="],
 
     "cross-spawn/which": ["which@2.0.2", "", { "dependencies": { "isexe": "^2.0.0" }, "bin": { "node-which": "./bin/node-which" } }, "sha512-BLI3Tl1TW3Pvl70l3yq3Y64i+awpwXqsGBYWkkqMtnbXgrMD+yj7rhW0kuEDxzJaYXGjEW5ogapKNMEKNMjibA=="],
 
@@ -559,30 +540,124 @@
 
     "libsql/detect-libc": ["detect-libc@2.0.2", "", {}, "sha512-UX6sGumvvqSaXgdKGUsgZWqcUyIXZ/vZTrlRT/iobiKhGL0zL4d3osHj3uqllWJK+i+sixDS/3COVEOFbupFyw=="],
 
-    "pg/pg-protocol": ["pg-protocol@1.14.0", "", {}, "sha512-n5taZ1kO3s9ngDTVxsEznOqCyToTgz0FLuPq0B33COy5pPpuWJpY3/2oRBVETuOgzdqRXfWpM9HIhp2LBBT1BA=="],
+    "protobufjs/@types/node": ["@types/node@25.0.10", "", { "dependencies": { "undici-types": "~7.16.0" } }, "sha512-zWW5KPngR/yvakJgGOmZ5vTBemDoSqF3AcV/LrO5u5wTWyEAVVh+IT39G4gtyAkh3CtTZs8aX/yRM82OfzHJRg=="],
 
     "string-width/emoji-regex": ["emoji-regex@8.0.0", "", {}, "sha512-MSjYzcWNOA0ewAHpz0MxpYFvwg6yjy1NG3xteoqz644VCo/RPgnr1/GGt+ic3iJTzQ8Eu3TdM14SawnVUmGE6A=="],
 
-    "typescript-telegram-bot-api/axios": ["axios@1.16.0", "", { "dependencies": { "follow-redirects": "^1.16.0", "form-data": "^4.0.5", "proxy-from-env": "^2.1.0" } }, "sha512-6hp5CwvTPlN2A31g5dxnwAX0orzM7pmCRDLnZSX772mv8WDqICwFjowHuPs04Mc8deIld1+ejhtaMn5vp6b+1w=="],
+    "string-width-cjs/emoji-regex": ["emoji-regex@8.0.0", "", {}, "sha512-MSjYzcWNOA0ewAHpz0MxpYFvwg6yjy1NG3xteoqz644VCo/RPgnr1/GGt+ic3iJTzQ8Eu3TdM14SawnVUmGE6A=="],
 
-    "yargs/find-up": ["find-up@4.1.0", "", { "dependencies": { "locate-path": "^5.0.0", "path-exists": "^4.0.0" } }, "sha512-PpOwAdQ/YlXQ2vj8a3h8IipDuYRi3wceVQQGYWxNINccq40Anw7BlsEXCMbt1Zt+OLA6Fq9suIpIWD0OsnISlw=="],
+    "tsx/esbuild": ["esbuild@0.27.2", "", { "optionalDependencies": { "@esbuild/aix-ppc64": "0.27.2", "@esbuild/android-arm": "0.27.2", "@esbuild/android-arm64": "0.27.2", "@esbuild/android-x64": "0.27.2", "@esbuild/darwin-arm64": "0.27.2", "@esbuild/darwin-x64": "0.27.2", "@esbuild/freebsd-arm64": "0.27.2", "@esbuild/freebsd-x64": "0.27.2", "@esbuild/linux-arm": "0.27.2", "@esbuild/linux-arm64": "0.27.2", "@esbuild/linux-ia32": "0.27.2", "@esbuild/linux-loong64": "0.27.2", "@esbuild/linux-mips64el": "0.27.2", "@esbuild/linux-ppc64": "0.27.2", "@esbuild/linux-riscv64": "0.27.2", "@esbuild/linux-s390x": "0.27.2", "@esbuild/linux-x64": "0.27.2", "@esbuild/netbsd-arm64": "0.27.2", "@esbuild/netbsd-x64": "0.27.2", "@esbuild/openbsd-arm64": "0.27.2", "@esbuild/openbsd-x64": "0.27.2", "@esbuild/openharmony-arm64": "0.27.2", "@esbuild/sunos-x64": "0.27.2", "@esbuild/win32-arm64": "0.27.2", "@esbuild/win32-ia32": "0.27.2", "@esbuild/win32-x64": "0.27.2" }, "bin": { "esbuild": "bin/esbuild" } }, "sha512-HyNQImnsOC7X9PMNaCIeAm4ISCQXs5a5YasTXVliKv4uuBo1dKrG0A+uQS8M5eXjVMnLg3WgXaKvprHlFJQffw=="],
+
+    "tsx/get-tsconfig": ["get-tsconfig@4.13.0", "", { "dependencies": { "resolve-pkg-maps": "^1.0.0" } }, "sha512-1VKTZJCwBrvbd+Wn3AOgQP/2Av+TfTCOlE4AcRJE72W1ksZXbAx8PPBR9RzgTeSPzlPMHrbANMH3LbltH73wxQ=="],
+
+    "@esbuild-kit/core-utils/esbuild/@esbuild/android-arm": ["@esbuild/android-arm@0.18.20", "", { "os": "android", "cpu": "arm" }, "sha512-fyi7TDI/ijKKNZTUJAQqiG5T7YjJXgnzkURqmGj13C6dCqckZBLdl4h7bkhHt/t0WP+zO9/zwroDvANaOqO5Sw=="],
+
+    "@esbuild-kit/core-utils/esbuild/@esbuild/android-arm64": ["@esbuild/android-arm64@0.18.20", "", { "os": "android", "cpu": "arm64" }, "sha512-Nz4rJcchGDtENV0eMKUNa6L12zz2zBDXuhj/Vjh18zGqB44Bi7MBMSXjgunJgjRhCmKOjnPuZp4Mb6OKqtMHLQ=="],
+
+    "@esbuild-kit/core-utils/esbuild/@esbuild/android-x64": ["@esbuild/android-x64@0.18.20", "", { "os": "android", "cpu": "x64" }, "sha512-8GDdlePJA8D6zlZYJV/jnrRAi6rOiNaCC/JclcXpB+KIuvfBN4owLtgzY2bsxnx666XjJx2kDPUmnTtR8qKQUg=="],
+
+    "@esbuild-kit/core-utils/esbuild/@esbuild/darwin-arm64": ["@esbuild/darwin-arm64@0.18.20", "", { "os": "darwin", "cpu": "arm64" }, "sha512-bxRHW5kHU38zS2lPTPOyuyTm+S+eobPUnTNkdJEfAddYgEcll4xkT8DB9d2008DtTbl7uJag2HuE5NZAZgnNEA=="],
+
+    "@esbuild-kit/core-utils/esbuild/@esbuild/darwin-x64": ["@esbuild/darwin-x64@0.18.20", "", { "os": "darwin", "cpu": "x64" }, "sha512-pc5gxlMDxzm513qPGbCbDukOdsGtKhfxD1zJKXjCCcU7ju50O7MeAZ8c4krSJcOIJGFR+qx21yMMVYwiQvyTyQ=="],
+
+    "@esbuild-kit/core-utils/esbuild/@esbuild/freebsd-arm64": ["@esbuild/freebsd-arm64@0.18.20", "", { "os": "freebsd", "cpu": "arm64" }, "sha512-yqDQHy4QHevpMAaxhhIwYPMv1NECwOvIpGCZkECn8w2WFHXjEwrBn3CeNIYsibZ/iZEUemj++M26W3cNR5h+Tw=="],
+
+    "@esbuild-kit/core-utils/esbuild/@esbuild/freebsd-x64": ["@esbuild/freebsd-x64@0.18.20", "", { "os": "freebsd", "cpu": "x64" }, "sha512-tgWRPPuQsd3RmBZwarGVHZQvtzfEBOreNuxEMKFcd5DaDn2PbBxfwLcj4+aenoh7ctXcbXmOQIn8HI6mCSw5MQ=="],
+
+    "@esbuild-kit/core-utils/esbuild/@esbuild/linux-arm": ["@esbuild/linux-arm@0.18.20", "", { "os": "linux", "cpu": "arm" }, "sha512-/5bHkMWnq1EgKr1V+Ybz3s1hWXok7mDFUMQ4cG10AfW3wL02PSZi5kFpYKrptDsgb2WAJIvRcDm+qIvXf/apvg=="],
+
+    "@esbuild-kit/core-utils/esbuild/@esbuild/linux-arm64": ["@esbuild/linux-arm64@0.18.20", "", { "os": "linux", "cpu": "arm64" }, "sha512-2YbscF+UL7SQAVIpnWvYwM+3LskyDmPhe31pE7/aoTMFKKzIc9lLbyGUpmmb8a8AixOL61sQ/mFh3jEjHYFvdA=="],
+
+    "@esbuild-kit/core-utils/esbuild/@esbuild/linux-ia32": ["@esbuild/linux-ia32@0.18.20", "", { "os": "linux", "cpu": "ia32" }, "sha512-P4etWwq6IsReT0E1KHU40bOnzMHoH73aXp96Fs8TIT6z9Hu8G6+0SHSw9i2isWrD2nbx2qo5yUqACgdfVGx7TA=="],
+
+    "@esbuild-kit/core-utils/esbuild/@esbuild/linux-loong64": ["@esbuild/linux-loong64@0.18.20", "", { "os": "linux", "cpu": "none" }, "sha512-nXW8nqBTrOpDLPgPY9uV+/1DjxoQ7DoB2N8eocyq8I9XuqJ7BiAMDMf9n1xZM9TgW0J8zrquIb/A7s3BJv7rjg=="],
+
+    "@esbuild-kit/core-utils/esbuild/@esbuild/linux-mips64el": ["@esbuild/linux-mips64el@0.18.20", "", { "os": "linux", "cpu": "none" }, "sha512-d5NeaXZcHp8PzYy5VnXV3VSd2D328Zb+9dEq5HE6bw6+N86JVPExrA6O68OPwobntbNJ0pzCpUFZTo3w0GyetQ=="],
+
+    "@esbuild-kit/core-utils/esbuild/@esbuild/linux-ppc64": ["@esbuild/linux-ppc64@0.18.20", "", { "os": "linux", "cpu": "ppc64" }, "sha512-WHPyeScRNcmANnLQkq6AfyXRFr5D6N2sKgkFo2FqguP44Nw2eyDlbTdZwd9GYk98DZG9QItIiTlFLHJHjxP3FA=="],
+
+    "@esbuild-kit/core-utils/esbuild/@esbuild/linux-riscv64": ["@esbuild/linux-riscv64@0.18.20", "", { "os": "linux", "cpu": "none" }, "sha512-WSxo6h5ecI5XH34KC7w5veNnKkju3zBRLEQNY7mv5mtBmrP/MjNBCAlsM2u5hDBlS3NGcTQpoBvRzqBcRtpq1A=="],
+
+    "@esbuild-kit/core-utils/esbuild/@esbuild/linux-s390x": ["@esbuild/linux-s390x@0.18.20", "", { "os": "linux", "cpu": "s390x" }, "sha512-+8231GMs3mAEth6Ja1iK0a1sQ3ohfcpzpRLH8uuc5/KVDFneH6jtAJLFGafpzpMRO6DzJ6AvXKze9LfFMrIHVQ=="],
+
+    "@esbuild-kit/core-utils/esbuild/@esbuild/linux-x64": ["@esbuild/linux-x64@0.18.20", "", { "os": "linux", "cpu": "x64" }, "sha512-UYqiqemphJcNsFEskc73jQ7B9jgwjWrSayxawS6UVFZGWrAAtkzjxSqnoclCXxWtfwLdzU+vTpcNYhpn43uP1w=="],
+
+    "@esbuild-kit/core-utils/esbuild/@esbuild/netbsd-x64": ["@esbuild/netbsd-x64@0.18.20", "", { "os": "none", "cpu": "x64" }, "sha512-iO1c++VP6xUBUmltHZoMtCUdPlnPGdBom6IrO4gyKPFFVBKioIImVooR5I83nTew5UOYrk3gIJhbZh8X44y06A=="],
+
+    "@esbuild-kit/core-utils/esbuild/@esbuild/openbsd-x64": ["@esbuild/openbsd-x64@0.18.20", "", { "os": "openbsd", "cpu": "x64" }, "sha512-e5e4YSsuQfX4cxcygw/UCPIEP6wbIL+se3sxPdCiMbFLBWu0eiZOJ7WoD+ptCLrmjZBK1Wk7I6D/I3NglUGOxg=="],
+
+    "@esbuild-kit/core-utils/esbuild/@esbuild/sunos-x64": ["@esbuild/sunos-x64@0.18.20", "", { "os": "sunos", "cpu": "x64" }, "sha512-kDbFRFp0YpTQVVrqUd5FTYmWo45zGaXe0X8E1G/LKFC0v8x0vWrhOWSLITcCn63lmZIxfOMXtCfti/RxN/0wnQ=="],
+
+    "@esbuild-kit/core-utils/esbuild/@esbuild/win32-arm64": ["@esbuild/win32-arm64@0.18.20", "", { "os": "win32", "cpu": "arm64" }, "sha512-ddYFR6ItYgoaq4v4JmQQaAI5s7npztfV4Ag6NrhiaW0RrnOXqBkgwZLofVTlq1daVTQNhtI5oieTvkRPfZrePg=="],
+
+    "@esbuild-kit/core-utils/esbuild/@esbuild/win32-ia32": ["@esbuild/win32-ia32@0.18.20", "", { "os": "win32", "cpu": "ia32" }, "sha512-Wv7QBi3ID/rROT08SABTS7eV4hX26sVduqDOTe1MvGMjNd3EjOz4b7zeexIR62GTIEKrfJXKL9LFxTYgkyeu7g=="],
+
+    "@esbuild-kit/core-utils/esbuild/@esbuild/win32-x64": ["@esbuild/win32-x64@0.18.20", "", { "os": "win32", "cpu": "x64" }, "sha512-kTdfRcSiDfQca/y9QIkng02avJ+NCaQvrMejlsB3RRv5sE9rRoeBPISaZpKxHELzRxZyLvNts1P27W3wV+8geQ=="],
+
+    "@isaacs/cliui/string-width/emoji-regex": ["emoji-regex@9.2.2", "", {}, "sha512-L18DaJsXSUk2+42pv8mLs5jJT2hqFkFE4j21wOmgbUqsZ2hL72NsUU785g9RXgo3s0ZNgVl42TiHp3ZtOv/Vyg=="],
+
+    "@isaacs/cliui/strip-ansi/ansi-regex": ["ansi-regex@6.2.2", "", {}, "sha512-Bq3SmSpyFHaWjPk8If9yc6svM8c56dB5BAtW4Qbw5jHTwwXXcTLoRMkpDJp6VL0XzlWaCHTXrkFURMYmD0sLqg=="],
+
+    "@isaacs/cliui/wrap-ansi/ansi-styles": ["ansi-styles@6.2.3", "", {}, "sha512-4Dj6M28JB+oAH8kFkTLUo+a2jwOFkuqb3yucU0CANcRRUbxS0cP0nZYCGjcc3BNXwRIsUVmDGgzawme7zvJHvg=="],
 
     "@types/fluent-ffmpeg/@types/node/undici-types": ["undici-types@7.16.0", "", {}, "sha512-Zz+aZWSj8LE6zoxD+xrjh4VfkIG8Ya6LvYkZqtUQGJPZjYl53ypCaUwWqo7eI0x66KBGeRo+mlBEkMSeSZ38Nw=="],
 
-    "@types/pg/@types/node/undici-types": ["undici-types@7.19.2", "", {}, "sha512-qYVnV5OEm2AW8cJMCpdV20CDyaN3g0AjDlOGf1OW4iaDEx8MwdtChUp4zu4H0VP3nDRF/8RKWH+IPp9uW0YGZg=="],
-
     "@types/qrcode/@types/node/undici-types": ["undici-types@7.16.0", "", {}, "sha512-Zz+aZWSj8LE6zoxD+xrjh4VfkIG8Ya6LvYkZqtUQGJPZjYl53ypCaUwWqo7eI0x66KBGeRo+mlBEkMSeSZ38Nw=="],
 
     "@types/ws/@types/node/undici-types": ["undici-types@7.16.0", "", {}, "sha512-Zz+aZWSj8LE6zoxD+xrjh4VfkIG8Ya6LvYkZqtUQGJPZjYl53ypCaUwWqo7eI0x66KBGeRo+mlBEkMSeSZ38Nw=="],
 
-    "@typescript-eslint/typescript-estree/minimatch/brace-expansion": ["brace-expansion@5.0.6", "", { "dependencies": { "balanced-match": "^4.0.2" } }, "sha512-kLpxurY4Z4r9sgMsyG0Z9uzsBlgiU/EFKhj/h91/8yHu0edo7XuixOIH3VcJ8kkxs6/jPzoI6U9Vj3WqbMQ94g=="],
+    "protobufjs/@types/node/undici-types": ["undici-types@7.16.0", "", {}, "sha512-Zz+aZWSj8LE6zoxD+xrjh4VfkIG8Ya6LvYkZqtUQGJPZjYl53ypCaUwWqo7eI0x66KBGeRo+mlBEkMSeSZ38Nw=="],
 
-    "yargs/find-up/locate-path": ["locate-path@5.0.0", "", { "dependencies": { "p-locate": "^4.1.0" } }, "sha512-t7hw9pI+WvuwNJXwk5zVHpyhIqzg2qTlklJOf0mVxGSbe3Fp2VieZcduNYjaLDoy6p9uGpQEGWG87WpMKlNq8g=="],
+    "tsx/esbuild/@esbuild/aix-ppc64": ["@esbuild/aix-ppc64@0.27.2", "", { "os": "aix", "cpu": "ppc64" }, "sha512-GZMB+a0mOMZs4MpDbj8RJp4cw+w1WV5NYD6xzgvzUJ5Ek2jerwfO2eADyI6ExDSUED+1X8aMbegahsJi+8mgpw=="],
 
-    "@typescript-eslint/typescript-estree/minimatch/brace-expansion/balanced-match": ["balanced-match@4.0.4", "", {}, "sha512-BLrgEcRTwX2o6gGxGOCNyMvGSp35YofuYzw9h1IMTRmKqttAZZVU67bdb9Pr2vUHA8+j3i2tJfjO6C6+4myGTA=="],
+    "tsx/esbuild/@esbuild/android-arm": ["@esbuild/android-arm@0.27.2", "", { "os": "android", "cpu": "arm" }, "sha512-DVNI8jlPa7Ujbr1yjU2PfUSRtAUZPG9I1RwW4F4xFB1Imiu2on0ADiI/c3td+KmDtVKNbi+nffGDQMfcIMkwIA=="],
 
-    "yargs/find-up/locate-path/p-locate": ["p-locate@4.1.0", "", { "dependencies": { "p-limit": "^2.2.0" } }, "sha512-R79ZZ/0wAxKGu3oYMlz8jy/kbhsNrS7SKZ7PxEHBgJ5+F2mtFW2fK2cOtBh1cHYkQsbzFV7I+EoRKe6Yt0oK7A=="],
+    "tsx/esbuild/@esbuild/android-arm64": ["@esbuild/android-arm64@0.27.2", "", { "os": "android", "cpu": "arm64" }, "sha512-pvz8ZZ7ot/RBphf8fv60ljmaoydPU12VuXHImtAs0XhLLw+EXBi2BLe3OYSBslR4rryHvweW5gmkKFwTiFy6KA=="],
 
-    "yargs/find-up/locate-path/p-locate/p-limit": ["p-limit@2.3.0", "", { "dependencies": { "p-try": "^2.0.0" } }, "sha512-//88mFWSJx8lxCzwdAABTJL2MyWB12+eIY7MDL2SqLmAkeKU9qxRvWuSyTjm3FUmpBEMuFfckAIqEaVGUDxb6w=="],
+    "tsx/esbuild/@esbuild/android-x64": ["@esbuild/android-x64@0.27.2", "", { "os": "android", "cpu": "x64" }, "sha512-z8Ank4Byh4TJJOh4wpz8g2vDy75zFL0TlZlkUkEwYXuPSgX8yzep596n6mT7905kA9uHZsf/o2OJZubl2l3M7A=="],
+
+    "tsx/esbuild/@esbuild/darwin-arm64": ["@esbuild/darwin-arm64@0.27.2", "", { "os": "darwin", "cpu": "arm64" }, "sha512-davCD2Zc80nzDVRwXTcQP/28fiJbcOwvdolL0sOiOsbwBa72kegmVU0Wrh1MYrbuCL98Omp5dVhQFWRKR2ZAlg=="],
+
+    "tsx/esbuild/@esbuild/darwin-x64": ["@esbuild/darwin-x64@0.27.2", "", { "os": "darwin", "cpu": "x64" }, "sha512-ZxtijOmlQCBWGwbVmwOF/UCzuGIbUkqB1faQRf5akQmxRJ1ujusWsb3CVfk/9iZKr2L5SMU5wPBi1UWbvL+VQA=="],
+
+    "tsx/esbuild/@esbuild/freebsd-arm64": ["@esbuild/freebsd-arm64@0.27.2", "", { "os": "freebsd", "cpu": "arm64" }, "sha512-lS/9CN+rgqQ9czogxlMcBMGd+l8Q3Nj1MFQwBZJyoEKI50XGxwuzznYdwcav6lpOGv5BqaZXqvBSiB/kJ5op+g=="],
+
+    "tsx/esbuild/@esbuild/freebsd-x64": ["@esbuild/freebsd-x64@0.27.2", "", { "os": "freebsd", "cpu": "x64" }, "sha512-tAfqtNYb4YgPnJlEFu4c212HYjQWSO/w/h/lQaBK7RbwGIkBOuNKQI9tqWzx7Wtp7bTPaGC6MJvWI608P3wXYA=="],
+
+    "tsx/esbuild/@esbuild/linux-arm": ["@esbuild/linux-arm@0.27.2", "", { "os": "linux", "cpu": "arm" }, "sha512-vWfq4GaIMP9AIe4yj1ZUW18RDhx6EPQKjwe7n8BbIecFtCQG4CfHGaHuh7fdfq+y3LIA2vGS/o9ZBGVxIDi9hw=="],
+
+    "tsx/esbuild/@esbuild/linux-arm64": ["@esbuild/linux-arm64@0.27.2", "", { "os": "linux", "cpu": "arm64" }, "sha512-hYxN8pr66NsCCiRFkHUAsxylNOcAQaxSSkHMMjcpx0si13t1LHFphxJZUiGwojB1a/Hd5OiPIqDdXONia6bhTw=="],
+
+    "tsx/esbuild/@esbuild/linux-ia32": ["@esbuild/linux-ia32@0.27.2", "", { "os": "linux", "cpu": "ia32" }, "sha512-MJt5BRRSScPDwG2hLelYhAAKh9imjHK5+NE/tvnRLbIqUWa+0E9N4WNMjmp/kXXPHZGqPLxggwVhz7QP8CTR8w=="],
+
+    "tsx/esbuild/@esbuild/linux-loong64": ["@esbuild/linux-loong64@0.27.2", "", { "os": "linux", "cpu": "none" }, "sha512-lugyF1atnAT463aO6KPshVCJK5NgRnU4yb3FUumyVz+cGvZbontBgzeGFO1nF+dPueHD367a2ZXe1NtUkAjOtg=="],
+
+    "tsx/esbuild/@esbuild/linux-mips64el": ["@esbuild/linux-mips64el@0.27.2", "", { "os": "linux", "cpu": "none" }, "sha512-nlP2I6ArEBewvJ2gjrrkESEZkB5mIoaTswuqNFRv/WYd+ATtUpe9Y09RnJvgvdag7he0OWgEZWhviS1OTOKixw=="],
+
+    "tsx/esbuild/@esbuild/linux-ppc64": ["@esbuild/linux-ppc64@0.27.2", "", { "os": "linux", "cpu": "ppc64" }, "sha512-C92gnpey7tUQONqg1n6dKVbx3vphKtTHJaNG2Ok9lGwbZil6DrfyecMsp9CrmXGQJmZ7iiVXvvZH6Ml5hL6XdQ=="],
+
+    "tsx/esbuild/@esbuild/linux-riscv64": ["@esbuild/linux-riscv64@0.27.2", "", { "os": "linux", "cpu": "none" }, "sha512-B5BOmojNtUyN8AXlK0QJyvjEZkWwy/FKvakkTDCziX95AowLZKR6aCDhG7LeF7uMCXEJqwa8Bejz5LTPYm8AvA=="],
+
+    "tsx/esbuild/@esbuild/linux-s390x": ["@esbuild/linux-s390x@0.27.2", "", { "os": "linux", "cpu": "s390x" }, "sha512-p4bm9+wsPwup5Z8f4EpfN63qNagQ47Ua2znaqGH6bqLlmJ4bx97Y9JdqxgGZ6Y8xVTixUnEkoKSHcpRlDnNr5w=="],
+
+    "tsx/esbuild/@esbuild/linux-x64": ["@esbuild/linux-x64@0.27.2", "", { "os": "linux", "cpu": "x64" }, "sha512-uwp2Tip5aPmH+NRUwTcfLb+W32WXjpFejTIOWZFw/v7/KnpCDKG66u4DLcurQpiYTiYwQ9B7KOeMJvLCu/OvbA=="],
+
+    "tsx/esbuild/@esbuild/netbsd-arm64": ["@esbuild/netbsd-arm64@0.27.2", "", { "os": "none", "cpu": "arm64" }, "sha512-Kj6DiBlwXrPsCRDeRvGAUb/LNrBASrfqAIok+xB0LxK8CHqxZ037viF13ugfsIpePH93mX7xfJp97cyDuTZ3cw=="],
+
+    "tsx/esbuild/@esbuild/netbsd-x64": ["@esbuild/netbsd-x64@0.27.2", "", { "os": "none", "cpu": "x64" }, "sha512-HwGDZ0VLVBY3Y+Nw0JexZy9o/nUAWq9MlV7cahpaXKW6TOzfVno3y3/M8Ga8u8Yr7GldLOov27xiCnqRZf0tCA=="],
+
+    "tsx/esbuild/@esbuild/openbsd-arm64": ["@esbuild/openbsd-arm64@0.27.2", "", { "os": "openbsd", "cpu": "arm64" }, "sha512-DNIHH2BPQ5551A7oSHD0CKbwIA/Ox7+78/AWkbS5QoRzaqlev2uFayfSxq68EkonB+IKjiuxBFoV8ESJy8bOHA=="],
+
+    "tsx/esbuild/@esbuild/openbsd-x64": ["@esbuild/openbsd-x64@0.27.2", "", { "os": "openbsd", "cpu": "x64" }, "sha512-/it7w9Nb7+0KFIzjalNJVR5bOzA9Vay+yIPLVHfIQYG/j+j9VTH84aNB8ExGKPU4AzfaEvN9/V4HV+F+vo8OEg=="],
+
+    "tsx/esbuild/@esbuild/openharmony-arm64": ["@esbuild/openharmony-arm64@0.27.2", "", { "os": "none", "cpu": "arm64" }, "sha512-LRBbCmiU51IXfeXk59csuX/aSaToeG7w48nMwA6049Y4J4+VbWALAuXcs+qcD04rHDuSCSRKdmY63sruDS5qag=="],
+
+    "tsx/esbuild/@esbuild/sunos-x64": ["@esbuild/sunos-x64@0.27.2", "", { "os": "sunos", "cpu": "x64" }, "sha512-kMtx1yqJHTmqaqHPAzKCAkDaKsffmXkPHThSfRwZGyuqyIeBvf08KSsYXl+abf5HDAPMJIPnbBfXvP2ZC2TfHg=="],
+
+    "tsx/esbuild/@esbuild/win32-arm64": ["@esbuild/win32-arm64@0.27.2", "", { "os": "win32", "cpu": "arm64" }, "sha512-Yaf78O/B3Kkh+nKABUF++bvJv5Ijoy9AN1ww904rOXZFLWVc5OLOfL56W+C8F9xn5JQZa3UX6m+IktJnIb1Jjg=="],
+
+    "tsx/esbuild/@esbuild/win32-ia32": ["@esbuild/win32-ia32@0.27.2", "", { "os": "win32", "cpu": "ia32" }, "sha512-Iuws0kxo4yusk7sw70Xa2E2imZU5HoixzxfGCdxwBdhiDgt9vX9VUCBhqcwY7/uh//78A1hMkkROMJq9l27oLQ=="],
+
+    "tsx/esbuild/@esbuild/win32-x64": ["@esbuild/win32-x64@0.27.2", "", { "os": "win32", "cpu": "x64" }, "sha512-sRdU18mcKf7F+YgheI/zGf5alZatMUTKj/jNS6l744f9u3WFu4v7twcUI9vu4mknF4Y9aDlblIie0IM+5xxaqQ=="],
   }
 }

docker-compose.yml

@@ -1,7 +1,7 @@
 services:
  tgchatbot:
     container_name: tgchatbot
-    image: ghcr.io/melod1n/tg-chat-bot:${IMAGE_TAG:-1.0.0}
+    image: ghcr.io/melod1n/tg-chat-bot:latest
     restart: unless-stopped
     env_file:
       - .env

drizzle.config.ts

@@ -0,0 +1,17 @@
+import "dotenv/config";
+import {defineConfig} from "drizzle-kit";
+import path from "node:path";
+
+const dataPath = process.env.DATA_PATH
+    ?? (process.env.IS_DOCKER === "true" ? "/" + path.join("config", "data") : "data");
+const dbFileName = process.env.DB_FILE_NAME ?? "database.db";
+
+export default defineConfig({
+    out: "./drizzle",
+    schema: "./src/db/schema.ts",
+    dialect: "sqlite",
+    dbCredentials: {
+        url: process.env.DB_FILE_NAME
+        // url: process.env.DB_PATH ? "file:" + process.env.DB_PATH : "file:" + path.join(dataPath, dbFileName),
+    },
+});

eslint.config.js

@@ -1,42 +1,31 @@
-import js from "@eslint/js";
-import {defineConfig} from "eslint/config";
-import tseslint from "typescript-eslint";
+const tsParser = require("@typescript-eslint/parser");
+const tsPlugin = require("@typescript-eslint/eslint-plugin");
 
-export default defineConfig(
+module.exports = [
     {
         ignores: [
             "dist/**",
-            "data/**",
             "node_modules/**",
-            "**/*.tsbuildinfo",
         ],
     },
-    js.configs.recommended,
-    tseslint.configs.recommended,
     {
-        files: ["src/**/*.ts"],
+        files: ["**/*.ts"],
+        languageOptions: {
+            parser: tsParser,
+            ecmaVersion: "latest",
+            sourceType: "module",
+        },
         linterOptions: {
             reportUnusedDisableDirectives: "off",
         },
+        plugins: {
+            "@typescript-eslint": tsPlugin,
+        },
         rules: {
-            "no-console": "error",
-            "no-control-regex": "off",
-            "no-case-declarations": "off",
-            "no-useless-escape": "off",
-            "no-extra-boolean-cast": "off",
-            "quotes": ["error", "double", {avoidEscape: true}],
-            "semi": ["error", "always"],
-            "prefer-const": "off",
-            "@typescript-eslint/ban-ts-comment": "off",
-            "@typescript-eslint/no-explicit-any": "off",
             "@typescript-eslint/no-unused-vars": "off",
             "no-unused-vars": "off",
+            "quotes": "warn",
+            "semi": "error",
         },
     },
-    {
-        files: ["src/logging/logger.ts"],
-        rules: {
-            "no-console": "off",
-        },
-    },
-);
+];

locales/en.json

@@ -8,13 +8,6 @@
   },
   "providerChoice.default": "Default",
   "errorText": "⚠️ An error occurred.",
-  "pipelineFallback.generic": "⚠️ I had to skip part of the request, but I can continue.",
-  "pipelineFallback.notifyUser": "⚠️ I hit a problem and need to continue with a fallback.",
-  "pipelineFallback.failRequest": "⚠️ I could not finish this request.",
-  "pipelineFallback.documentRag": "⚠️ Document retrieval failed, so I will answer without RAG.",
-  "pipelineFallback.speechToText": "⚠️ Speech transcription failed, so I will continue without the audio transcript.",
-  "pipelineFallback.textToSpeech": "⚠️ Text-to-speech failed, so I will continue without audio output.",
-  "pipelineFallback.toolLoop": "⚠️ Tool execution failed, so I will continue without that tool.",
   "waitThinkText": "⏳ Let me think...",
   "analyzingPictureText": "🔍 Analyzing the image...",
   "analyzingPicturesText": "🔍 Analyzing the images...",
@@ -69,21 +62,18 @@
   "userSettingsResponseLanguageSelectionTitle": "Response Language Selection",
   "userSettingsContextSizeSelectionTitle": "Context Size Selection",
   "userSettingsVoiceModeSelectionTitle": "Voice Message Mode Selection",
-  "userSettingsImageOutputSelectionTitle": "Image Output Mode Selection",
   "userSettingsTierLabel": "Tier",
   "userSettingsAiProviderLabel": "AI provider",
   "userSettingsInterfaceLanguageLabel": "Interface language",
   "userSettingsResponseLanguageLabel": "LLM response language",
   "userSettingsContextSizeLabel": "Context size",
   "userSettingsVoiceModeLabel": "Voice messages",
-  "userSettingsImageOutputLabel": "Image output",
   "userSettingsBackButtonText": "Back",
   "userSettingsAiProviderButtonPrefix": "AI provider",
   "userSettingsInterfaceLanguageButtonPrefix": "Interface language",
   "userSettingsResponseLanguageButtonPrefix": "Response language",
   "userSettingsContextSizeButtonPrefix": "Context",
   "userSettingsVoiceModeButtonPrefix": "Voice",
-  "userSettingsImageOutputButtonPrefix": "Image output",
   "userSettingsCreatorTierText": "Creator",
   "userSettingsAdminTierText": "Admin",
   "userSettingsUserTierText": "User",
@@ -91,8 +81,6 @@
   "userSettingsContextSizeDefaultText": "Default",
   "userSettingsVoiceModeExecuteText": "Run through AI",
   "userSettingsVoiceModeTranscriptText": "Show transcript only",
-  "userSettingsImageOutputPhotoText": "As photo",
-  "userSettingsImageOutputDocumentText": "As document",
   "startingImageGenText": "🌈 Starting image generation...",
   "imageGenText": "🌈 Generating image...",
   "finalizingImageGenText": "🌈 Finalizing image generation...",
@@ -148,7 +136,6 @@
   "getPreparingRAGText.default": "🔍 Preparing RAG for the document...",
   "getPreparingRAGText.single": "🔍 Preparing RAG for document: `{name}`",
   "getPreparingRAGText.many": "🔍 Preparing RAG for documents: {names}",
-  "getSelectingToolsText": "🧩 Choosing the right tools...",
   "getBuildingRAGIndexText.default": "🧠 Building RAG index...",
   "getBuildingRAGIndexText.withModel": "🧠 Building RAG index: `{modelName}`.",
   "queueNoneText": "none",
@@ -183,9 +170,6 @@
   "getWhenPluralUnitText": "{unit}s",
   "getWhenDurationText": "{prefix}{value} {unit}",
   "commandDescriptions": {
-    "aiAudit": "Inspect AI request audit and artifacts",
-    "aiMetrics": "Show AI observability counters",
-    "aiRequests": "Show recent AI requests",
     "ae": "evaluation",
     "adminsAdd": "Add user to admins",
     "adminsRemove": "Remove user from admins",
@@ -195,6 +179,10 @@
     "debug": "Returns msg (or reply) as json",
     "dice": "Sends random or specific dice",
     "distort": "Distortion of picture",
+    "geminiChat": "Chat with AI (Gemini)",
+    "geminiGetModel": "Get current Gemini model",
+    "geminiListModels": "List all Gemini models",
+    "geminiSetModel": "Set Gemini model",
     "help": "Show list of commands",
     "id": "ID of chat, user and reply (if replied to any message)",
     "ignore": "Bot will ignore user",

locales/ru.json

@@ -8,13 +8,6 @@
   },
   "providerChoice.default": "По умолчанию",
   "errorText": "⚠️ Произошла ошибка.",
-  "pipelineFallback.generic": "⚠️ Мне пришлось пропустить часть запроса, но я могу продолжить.",
-  "pipelineFallback.notifyUser": "⚠️ Возникла проблема, и я продолжу с запасным вариантом.",
-  "pipelineFallback.failRequest": "⚠️ Я не смог завершить этот запрос.",
-  "pipelineFallback.documentRag": "⚠️ Не удалось получить документы, поэтому я отвечу без RAG.",
-  "pipelineFallback.speechToText": "⚠️ Не удалось распознать речь, поэтому я продолжу без расшифровки аудио.",
-  "pipelineFallback.textToSpeech": "⚠️ Не удалось выполнить синтез речи, поэтому я продолжу без аудио.",
-  "pipelineFallback.toolLoop": "⚠️ Не удалось выполнить инструменты, поэтому я продолжу без них.",
   "waitThinkText": "⏳ Дайте-ка подумать...",
   "analyzingPictureText": "🔍 Анализирую изображение...",
   "analyzingPicturesText": "🔍 Анализирую изображения...",
@@ -95,21 +88,18 @@
   "userSettingsResponseLanguageSelectionTitle": "Выбор языка ответов",
   "userSettingsContextSizeSelectionTitle": "Выбор размера контекста",
   "userSettingsVoiceModeSelectionTitle": "Режим голосовых сообщений",
-  "userSettingsImageOutputSelectionTitle": "Режим отправки изображений",
   "userSettingsTierLabel": "Уровень",
   "userSettingsAiProviderLabel": "AI-провайдер",
   "userSettingsInterfaceLanguageLabel": "Язык интерфейса",
   "userSettingsResponseLanguageLabel": "Язык ответов LLM",
   "userSettingsContextSizeLabel": "Размер контекста",
   "userSettingsVoiceModeLabel": "Голосовые сообщения",
-  "userSettingsImageOutputLabel": "Изображения",
   "userSettingsBackButtonText": "Назад",
   "userSettingsAiProviderButtonPrefix": "AI-провайдер",
   "userSettingsInterfaceLanguageButtonPrefix": "Язык интерфейса",
   "userSettingsResponseLanguageButtonPrefix": "Язык ответов",
   "userSettingsContextSizeButtonPrefix": "Контекст",
   "userSettingsVoiceModeButtonPrefix": "Голосовые",
-  "userSettingsImageOutputButtonPrefix": "Изображения",
   "userSettingsCreatorTierText": "Создатель",
   "userSettingsAdminTierText": "Админ",
   "userSettingsUserTierText": "Пользователь",
@@ -117,8 +107,6 @@
   "userSettingsContextSizeDefaultText": "По умолчанию",
   "userSettingsVoiceModeExecuteText": "Выполнять через ИИ",
   "userSettingsVoiceModeTranscriptText": "Только расшифровка",
-  "userSettingsImageOutputPhotoText": "Как фото",
-  "userSettingsImageOutputDocumentText": "Как документ",
   "startingImageGenText": "🌈 Запускаю генерацию изображения...",
   "imageGenText": "🌈 Генерирую изображение...",
   "finalizingImageGenText": "🌈 Завершаю генерацию изображения...",
@@ -174,7 +162,6 @@
   "getPreparingRAGText.default": "🔍 Готовлю RAG для документа...",
   "getPreparingRAGText.single": "🔍 Готовлю RAG для документа: `{name}`",
   "getPreparingRAGText.many": "🔍 Готовлю RAG для документов: {names}",
-  "getSelectingToolsText": "🧩 Выбираю подходящие инструменты...",
   "getBuildingRAGIndexText.default": "🧠 Строю RAG-индекс...",
   "getBuildingRAGIndexText.withModel": "🧠 Строю RAG-индекс: `{modelName}`.",
   "queueNoneText": "нет",
@@ -209,9 +196,6 @@
   "getWhenPluralUnitText": "{unit}",
   "getWhenDurationText": "{prefix}{value} {unit}",
   "commandDescriptions": {
-    "aiRequests": "Показать последние AI-запросы",
-    "aiAudit": "Показать аудит AI-запроса и артефакты",
-    "aiMetrics": "Показать счётчики AI-обсервабилити",
     "ae": "вычисление",
     "adminsAdd": "Добавить пользователя в администраторы",
     "adminsRemove": "Удалить пользователя из администраторов",
@@ -221,6 +205,10 @@
     "debug": "Вернуть msg или reply в JSON",
     "dice": "Отправить случайный или конкретный дайс",
     "distort": "Искажение изображения",
+    "geminiChat": "Чат с AI (Gemini)",
+    "geminiGetModel": "Показать текущую модель Gemini",
+    "geminiListModels": "Показать все модели Gemini",
+    "geminiSetModel": "Установить модель Gemini",
     "help": "Показать список команд",
     "id": "ID чата, пользователя и ответа",
     "ignore": "Бот будет игнорировать пользователя",

locales/ua.json

@@ -8,13 +8,6 @@
   },
   "providerChoice.default": "За замовчуванням",
   "errorText": "⚠️ Сталася помилка.",
-  "pipelineFallback.generic": "⚠️ Мені довелося пропустити частину запиту, але я можу продовжити.",
-  "pipelineFallback.notifyUser": "⚠️ Виникла проблема, і я продовжу із запасним варіантом.",
-  "pipelineFallback.failRequest": "⚠️ Я не зміг завершити цей запит.",
-  "pipelineFallback.documentRag": "⚠️ Не вдалося отримати документи, тому я відповім без RAG.",
-  "pipelineFallback.speechToText": "⚠️ Не вдалося розпізнати мовлення, тому я продовжу без розшифровки аудіо.",
-  "pipelineFallback.textToSpeech": "⚠️ Не вдалося виконати синтез мовлення, тому я продовжу без аудіо.",
-  "pipelineFallback.toolLoop": "⚠️ Не вдалося виконати інструменти, тому я продовжу без них.",
   "waitThinkText": "⏳ Дайте-но подумати...",
   "analyzingPictureText": "🔍 Аналізую зображення...",
   "analyzingPicturesText": "🔍 Аналізую зображення...",
@@ -94,21 +87,18 @@
   "userSettingsResponseLanguageSelectionTitle": "Вибір мови відповідей",
   "userSettingsContextSizeSelectionTitle": "Вибір розміру контексту",
   "userSettingsVoiceModeSelectionTitle": "Режим голосових повідомлень",
-  "userSettingsImageOutputSelectionTitle": "Режим надсилання зображень",
   "userSettingsTierLabel": "Рівень",
   "userSettingsAiProviderLabel": "AI-провайдер",
   "userSettingsInterfaceLanguageLabel": "Мова інтерфейсу",
   "userSettingsResponseLanguageLabel": "Мова відповідей LLM",
   "userSettingsContextSizeLabel": "Розмір контексту",
   "userSettingsVoiceModeLabel": "Голосові повідомлення",
-  "userSettingsImageOutputLabel": "Зображення",
   "userSettingsBackButtonText": "Назад",
   "userSettingsAiProviderButtonPrefix": "AI-провайдер",
   "userSettingsInterfaceLanguageButtonPrefix": "Мова інтерфейсу",
   "userSettingsResponseLanguageButtonPrefix": "Мова відповідей",
   "userSettingsContextSizeButtonPrefix": "Контекст",
   "userSettingsVoiceModeButtonPrefix": "Голосові",
-  "userSettingsImageOutputButtonPrefix": "Зображення",
   "userSettingsCreatorTierText": "Творець",
   "userSettingsAdminTierText": "Адмін",
   "userSettingsUserTierText": "Користувач",
@@ -116,8 +106,6 @@
   "userSettingsContextSizeDefaultText": "За замовчуванням",
   "userSettingsVoiceModeExecuteText": "Виконувати через AI",
   "userSettingsVoiceModeTranscriptText": "Лише розшифровка",
-  "userSettingsImageOutputPhotoText": "Як фото",
-  "userSettingsImageOutputDocumentText": "Як документ",
   "startingImageGenText": "🌈 Запускаю генерацію зображення...",
   "imageGenText": "🌈 Генерую зображення...",
   "finalizingImageGenText": "🌈 Завершую генерацію зображення...",
@@ -173,7 +161,6 @@
   "getPreparingRAGText.default": "🔍 Готую RAG для документа...",
   "getPreparingRAGText.single": "🔍 Готую RAG для документа: `{name}`",
   "getPreparingRAGText.many": "🔍 Готую RAG для документів: {names}",
-  "getSelectingToolsText": "🧩 Вибираю підхожі інструменти...",
   "getBuildingRAGIndexText.default": "🧠 Будую RAG-індекс...",
   "getBuildingRAGIndexText.withModel": "🧠 Будую RAG-індекс: `{modelName}`.",
   "queueNoneText": "немає",
@@ -208,9 +195,6 @@
   "getWhenPluralUnitText": "{unit}",
   "getWhenDurationText": "{prefix}{value} {unit}",
   "commandDescriptions": {
-    "aiRequests": "Показати останні AI-запити",
-    "aiAudit": "Показати аудит AI-запиту та артефакти",
-    "aiMetrics": "Показати лічильники AI-спостережуваності",
     "help": "Показати список команд",
     "settings": "Налаштування користувача",
     "start": "Запустити бота",

package.json

@@ -4,42 +4,35 @@
   "version": "1.0.0",
   "type": "module",
   "scripts": {
-    "build": "tsc -p tsconfig.build.json",
-    "test": "npm run build && node --test test/*.test.mjs",
-    "typecheck": "tsc --noEmit -p tsconfig.json",
-    "lint": "eslint .",
-    "lint:fix": "eslint . --fix",
+    "build": "tsgo -p tsconfig.json",
     "start": "node dist/index.js",
     "bun:start": "bun run src/index.ts"
   },
   "dependencies": {
-    "@libsql/client": "^0.17.3",
+    "@google/genai": "^2.0.0",
     "@mistralai/mistralai": "^2.2.1",
+    "openai": "^6.37.0",
+    "ollama": "^0.6.3",
+    "typescript-telegram-bot-api": "^0.16.0",
+    "@libsql/client": "^0.17.3",
     "@napi-rs/canvas": "^1.0.0",
-    "axios": "^1.16.1",
+    "axios": "^1.16.0",
     "dotenv": "^17.4.2",
     "drizzle-orm": "0.45.2",
     "emoji-regex": "^10.6.0",
     "fluent-ffmpeg": "^2.1.3",
-    "ollama": "^0.6.3",
-    "openai": "^6.38.0",
-    "pg": "^8.21.0",
     "qrcode": "^1.5.4",
     "sharp": "^0.34.5",
     "systeminformation": "^5.31.6",
     "twemoji": "^14.0.2",
-    "typescript-telegram-bot-api": "^0.16.0",
     "zod": "^4.4.3"
   },
   "devDependencies": {
-    "@eslint/js": "^9.39.4",
-    "@types/bun": "^1.3.14",
+    "@types/bun": "^1.3.13",
     "@types/fluent-ffmpeg": "^2.1.28",
-    "@types/node": "^25.9.1",
-    "@types/pg": "^8.20.0",
+    "@types/node": "^25.6.1",
     "@types/qrcode": "^1.5.6",
-    "eslint": "^9.39.4",
-    "typescript": "^6.0.3",
-    "typescript-eslint": "^8.59.4"
+    "drizzle-kit": "^0.31.10",
+    "typescript": "^6.0.3"
   }
 }

src/ai/ai-runtime-target.ts

@@ -1,12 +1,13 @@
 import {Mistral} from "@mistralai/mistralai";
+import {GoogleGenAI} from "@google/genai";
 import {Ollama} from "ollama";
 import {OpenAI} from "openai";
-import {Environment} from "../common/environment.js";
-import {AiModelCapabilities} from "../model/ai-model-capabilities.js";
-import {AiProvider} from "../model/ai-provider.js";
+import {Environment} from "../common/environment";
+import {AiModelCapabilities} from "../model/ai-model-capabilities";
+import {AiProvider} from "../model/ai-provider";
 
 export type AiCapabilityName = keyof AiModelCapabilities;
-export type AiRuntimePurpose = AiCapabilityName | "chat" | "memoryCompress";
+export type AiRuntimePurpose = AiCapabilityName | "chat";
 
 export type AiRuntimeTarget = {
     provider: AiProvider;
@@ -14,9 +15,12 @@ export type AiRuntimeTarget = {
     model: string;
     baseUrl?: string;
     apiKey?: string;
-    systemPromptAdditions?: string | null;
 };
 
+export type GeminiApiMode = "google" | "openai";
+
+const GEMINI_OPENAI_BASE_URL = "https://generativelanguage.googleapis.com/v1beta/openai/";
+
 const PURPOSE_SUFFIXES: Record<AiRuntimePurpose, string[]> = {
     chat: ["CHAT"],
     vision: ["VISION", "IMAGE"],
@@ -24,7 +28,6 @@ const PURPOSE_SUFFIXES: Record<AiRuntimePurpose, string[]> = {
     thinking: ["THINKING", "THINK"],
     extendedThinking: ["EXTENDED_THINKING", "THINKING", "THINK"],
     tools: ["TOOLS", "CHAT"],
-    memoryCompress: ["MEMORY_COMPRESS"],
     toolRank: ["TOOL_RANK", "TOOL_RANKER"],
     audio: ["AUDIO"],
     documents: ["DOCUMENTS", "RAG", "EMBEDDING"],
@@ -69,18 +72,13 @@ function modelEnvNames(provider: AiProvider, purpose: AiRuntimePurpose): string[
     return PURPOSE_SUFFIXES[purpose].map(suffix => `${prefix}_${suffix}_MODEL`);
 }
 
-function systemPromptEnvNames(provider: AiProvider, purpose: AiRuntimePurpose): string[] {
-    const prefix = providerPrefix(provider);
-    return PURPOSE_SUFFIXES[purpose].flatMap(suffix => [
-        `${prefix}_${suffix}_SYSTEM_PROMPT_ADDITIONS`,
-        `${prefix}_${suffix}_SYSTEM_PROMPT`,
-    ]);
-}
-
 export function getProviderBaseUrl(provider: AiProvider): string | undefined {
     switch (provider) {
         case AiProvider.OLLAMA:
             return env("OLLAMA_ADDRESS");
+        case AiProvider.GEMINI:
+            return env("GEMINI_BASE_URL") ?? env("GEMINI_ENDPOINT")
+                ?? (Environment.GEMINI_API_MODE === "openai" ? GEMINI_OPENAI_BASE_URL : undefined);
         case AiProvider.MISTRAL:
             return env("MISTRAL_BASE_URL") ?? env("MISTRAL_ENDPOINT");
         case AiProvider.OPENAI:
@@ -92,6 +90,8 @@ export function getProviderApiKey(provider: AiProvider): string | undefined {
     switch (provider) {
         case AiProvider.OLLAMA:
             return Environment.OLLAMA_API_KEY;
+        case AiProvider.GEMINI:
+            return Environment.GEMINI_API_KEY;
         case AiProvider.MISTRAL:
             return Environment.MISTRAL_API_KEY;
         case AiProvider.OPENAI:
@@ -118,6 +118,19 @@ export function getDefaultModelForPurpose(provider: AiProvider, purpose: AiRunti
                 default:
                     return Environment.OLLAMA_CHAT_MODEL;
             }
+        case AiProvider.GEMINI:
+            switch (purpose) {
+                case "vision":
+                case "ocr":
+                case "outputImages":
+                    return Environment.GEMINI_IMAGE_MODEL;
+                case "speechToText":
+                    return Environment.GEMINI_TRANSCRIPTION_MODEL;
+                case "textToSpeech":
+                    return Environment.GEMINI_TTS_MODEL;
+                default:
+                    return Environment.GEMINI_MODEL;
+            }
         case AiProvider.MISTRAL:
             switch (purpose) {
                 case "speechToText":
@@ -151,28 +164,8 @@ export function resolveAiRuntimeTarget(
         ?? getDefaultModelForPurpose(provider, purpose);
     const baseUrl = firstEnv(endpointEnvNames(provider, purpose)) ?? getProviderBaseUrl(provider);
     const apiKey = firstEnv(apiKeyEnvNames(provider, purpose)) ?? getProviderApiKey(provider);
-    const systemPromptAdditions = firstEnv(systemPromptEnvNames(provider, purpose));
 
-    return {provider, purpose, model, baseUrl, apiKey, systemPromptAdditions};
-}
-
-function hasExplicitTargetConfig(provider: AiProvider, purpose: AiRuntimePurpose): boolean {
-    const prefix = providerPrefix(provider);
-    return [
-        ...endpointEnvNames(provider, purpose),
-        ...apiKeyEnvNames(provider, purpose),
-        ...modelEnvNames(provider, purpose),
-        ...systemPromptEnvNames(provider, purpose),
-    ].some(name => !!env(name)) || !!env(`${prefix}_${PURPOSE_SUFFIXES[purpose][0]}_MODEL`);
-}
-
-export function resolveOptionalAiRuntimeTarget(
-    provider: AiProvider,
-    purpose: AiRuntimePurpose,
-    modelOverride?: string,
-): AiRuntimeTarget | undefined {
-    if (!hasExplicitTargetConfig(provider, purpose)) return undefined;
-    return resolveAiRuntimeTarget(provider, purpose, modelOverride);
+    return {provider, purpose, model, baseUrl, apiKey};
 }
 
 export function sameRuntimeEndpoint(left: AiRuntimeTarget, right: AiRuntimeTarget): boolean {
@@ -188,6 +181,26 @@ export function createOpenAiClient(target: AiRuntimeTarget): OpenAI {
     });
 }
 
+export function getGeminiApiMode(target?: AiRuntimeTarget): GeminiApiMode {
+    if (Environment.GEMINI_API_MODE === "openai") return "openai";
+    if (Environment.GEMINI_API_MODE === "google") return "google";
+    if ((target?.baseUrl ?? "").includes("/openai")) return "openai";
+    return "google";
+}
+
+export function createGeminiOpenAiClient(target: AiRuntimeTarget): OpenAI {
+    return createOpenAiClient({
+        ...target,
+        baseUrl: target.baseUrl ?? GEMINI_OPENAI_BASE_URL,
+    });
+}
+
+export function createGoogleGenAiClient(target: AiRuntimeTarget): GoogleGenAI {
+    return new GoogleGenAI({
+        apiKey: target.apiKey,
+    });
+}
+
 export function createMistralClient(target: AiRuntimeTarget): Mistral {
     return new Mistral({
         apiKey: target.apiKey,

src/ai/chat-messages-types.ts

@@ -1,5 +1,6 @@
 import {AiToolCall} from "./tool-types";
 import {OllamaChatMessage} from "./ollama-chat-message";
+import {GeminiMessage} from "./gemini-chat-message";
 import {MistralChatMessage} from "./mistral-chat-message";
 import {MessageAudioPart, MessageImagePart} from "../common/message-part";
 import {OpenAIChatMessage} from "./openai-chat-message";
@@ -30,6 +31,27 @@ export function asOllamaChatMessage(message: ChatMessage): OllamaChatMessage {
     };
 }
 
+// export function asGeminiChatMessage(message: ChatMessage): GeminiMessage {
+//     if (message.images) {
+//         return {
+//             role: message.role,
+//             content: message.images.map(() => {
+//                 return {
+//                     type: "image",
+//                 };
+//             })
+//         };
+//     }
+//
+//     return {
+//         role: message.role,
+//         content: {
+//             type: "text",
+//             text: message.content,
+//         },
+//     };
+// }
+
 export function asMistralChatMessage(message: ChatMessage): MistralChatMessage {
     return {
         role: message.role,
@@ -42,4 +64,6 @@ export function asMistralChatMessage(message: ChatMessage): MistralChatMessage {
 //
 //     }
 // }
-export type AiChatMessage = OpenAIChatMessage | OllamaChatMessage | MistralChatMessage;
+
+
+export type AiChatMessage = | OpenAIChatMessage | OllamaChatMessage | MistralChatMessage | GeminiMessage;

src/ai/conversation-pipeline.ts

@@ -1,358 +0,0 @@
-import {Message} from "typescript-telegram-bot-api";
-import type {
-    ResponseInputMessageContentList,
-    ResponseOutputMessage,
-    ResponseOutputText,
-} from "openai/resources/responses/responses";
-import {AiProvider} from "../model/ai-provider";
-import {MessageStore} from "../common/message-store";
-import {collectReplyChainText} from "../util/utils";
-import type {AiDownloadedFile} from "./telegram-attachments";
-import type {MessageAudioPart, MessageImagePart, MessagePart} from "../common/message-part";
-import type {UserAiResponseLanguage} from "../common/user-ai-settings";
-import {getResponseLanguageInstruction} from "../common/user-ai-settings";
-import {pythonInterpreterToolPrompt} from "./tools/python-interpretator";
-import type {AttachmentKind, AiRuntimeTarget, RuntimeConfigSnapshot} from "./unified-ai-runner.shared";
-import type {OpenAIChatMessage} from "./openai-chat-message";
-import type {MistralChatMessage} from "./mistral-chat-message";
-import type {OllamaChatMessage} from "./ollama-chat-message";
-import {buildUserMemoryPrompt} from "./tools/user-memory.js";
-
-export type ConversationAttachment = {
-    kind: AttachmentKind;
-    data: string;
-    mimeType: string;
-    fileName?: string;
-};
-
-export type ConversationTurn = {
-    bot: boolean;
-    name?: string;
-    langCode?: string;
-    userName?: string;
-    content: string;
-    deletedByBotAt?: number | null;
-    attachments: ConversationAttachment[];
-    documentNames?: string[];
-};
-
-export type ConversationSnapshot = {
-    turns: ConversationTurn[];
-    imageCount: number;
-    systemInstruction: string;
-};
-
-function buildAttachmentFromImage(image: MessageImagePart): ConversationAttachment {
-    return {
-        kind: "image",
-        data: image.data,
-        mimeType: image.mimeType || "image/jpeg",
-        fileName: "image.jpg",
-    };
-}
-
-function buildAttachmentFromAudio(audio: MessageAudioPart): ConversationAttachment {
-    return {
-        kind: "audio",
-        data: audio.data,
-        mimeType: audio.mimeType || "audio/mpeg",
-        fileName: "audio.bin",
-    };
-}
-
-function buildConversationAttachments(part: MessagePart): ConversationAttachment[] {
-    const attachments: ConversationAttachment[] = [];
-
-    for (const image of part.imageParts ?? []) {
-        attachments.push(buildAttachmentFromImage(image));
-    }
-
-    for (const audio of part.audioParts ?? []) {
-        attachments.push(buildAttachmentFromAudio(audio));
-    }
-
-    for (const document of part.documents ?? []) {
-        attachments.push({
-            kind: "document",
-            data: document,
-            mimeType: "application/octet-stream",
-            fileName: "document.bin",
-        });
-    }
-
-    for (const video of part.videos ?? []) {
-        attachments.push({
-            kind: "video",
-            data: video,
-            mimeType: "video/mp4",
-            fileName: "video.mp4",
-        });
-    }
-
-    for (const videoNote of part.videoNotes ?? []) {
-        attachments.push({
-            kind: "video-note",
-            data: videoNote,
-            mimeType: "video/mp4",
-            fileName: "video-note.mp4",
-        });
-    }
-
-    return attachments;
-}
-
-function attachmentCounts(attachments: ConversationAttachment[]): Record<AttachmentKind, number> {
-    return attachments.reduce<Record<AttachmentKind, number>>((counts, attachment) => {
-        counts[attachment.kind] += 1;
-        return counts;
-    }, {
-        image: 0,
-        document: 0,
-        audio: 0,
-        video: 0,
-        "video-note": 0,
-    });
-}
-
-function attachmentSummary(attachments: ConversationAttachment[]): string {
-    const counts = attachmentCounts(attachments);
-    const lines = Object.entries(counts)
-        .filter(([, count]) => count > 0)
-        .map(([kind, count]) => `- ${kind}: ${count}`);
-
-    if (!lines.length) return "";
-
-    return ["[attachments]:", ...lines].join("\n");
-}
-
-function namesSummary(kind: string, names: string[]): string {
-    const filtered = names.map(name => name.trim()).filter(Boolean);
-    if (!filtered.length) return "";
-
-    return [`[${kind}]:`, ...filtered.map(name => `- ${name}`)].join("\n");
-}
-
-function supportedAttachmentKinds(provider: AiProvider, bot: boolean): Set<AttachmentKind> {
-    if (bot) return new Set<AttachmentKind>();
-
-    switch (provider) {
-        case AiProvider.OPENAI:
-            return new Set<AttachmentKind>(["image", "audio", "document", "video", "video-note"]);
-        case AiProvider.MISTRAL:
-            return new Set<AttachmentKind>(["image"]);
-        case AiProvider.OLLAMA:
-            return new Set<AttachmentKind>();
-    }
-
-    return new Set<AttachmentKind>();
-}
-
-function renderContentText(
-    turn: ConversationTurn,
-    provider: AiProvider,
-    includeNames: boolean,
-): string {
-    const parts = [turn.content.trim()];
-    const supported = supportedAttachmentKinds(provider, turn.bot);
-    const unsupported = turn.attachments.filter(attachment => !supported.has(attachment.kind));
-
-    if (includeNames && !turn.bot) {
-        parts.unshift([
-            "[user_info]:",
-            `name: ${turn.name ?? ""}`.trimEnd(),
-            `username: @${turn.userName ?? ""}`.trimEnd(),
-            "",
-        ].join("\n"));
-    }
-
-    if (turn.bot && turn.deletedByBotAt) {
-        parts.push("[message_state]: deleted_by_bot");
-    }
-
-    if (turn.documentNames?.length) {
-        parts.push(namesSummary("documents", turn.documentNames));
-    }
-
-    if (unsupported.length) {
-        parts.push(attachmentSummary(unsupported));
-    }
-
-    return parts.filter(part => part.trim().length > 0).join("\n\n").trim();
-}
-
-function buildOpenAiOutputText(text: string): ResponseOutputText {
-    return {
-        type: "output_text",
-        text,
-        annotations: [],
-    };
-}
-
-function buildOpenAiInputMessage(turn: ConversationTurn, provider: AiProvider, includeNames: boolean): OpenAIChatMessage {
-    const text = renderContentText(turn, provider, includeNames);
-    const content: ResponseInputMessageContentList = [
-        {
-            type: "input_text",
-            text,
-        },
-    ];
-
-    for (const attachment of turn.attachments.filter(item => item.kind === "image")) {
-        content.push({
-            type: "input_image",
-            image_url: `data:${attachment.mimeType};base64,${attachment.data}`,
-            detail: "auto",
-        });
-    }
-
-    return {
-        type: "message",
-        role: "user",
-        content,
-    };
-}
-
-function buildOpenAiAssistantMessage(turn: ConversationTurn, provider: AiProvider, includeNames: boolean): ResponseOutputMessage {
-    const text = renderContentText(turn, provider, includeNames);
-    return {
-        id: `msg_${Date.now()}`,
-        type: "message",
-        role: "assistant",
-        status: "completed",
-        phase: "final_answer",
-        content: [buildOpenAiOutputText(text)],
-    };
-}
-
-function buildOpenAiMessage(turn: ConversationTurn, provider: AiProvider, includeNames: boolean): OpenAIChatMessage {
-    return turn.bot
-        ? buildOpenAiAssistantMessage(turn, provider, includeNames)
-        : buildOpenAiInputMessage(turn, provider, includeNames);
-}
-
-function buildMistralMessage(turn: ConversationTurn, provider: AiProvider, includeNames: boolean): MistralChatMessage {
-    const text = renderContentText(turn, provider, includeNames);
-
-    if (turn.bot) {
-        return {
-            role: "assistant",
-            content: [{type: "text", text}],
-        };
-    }
-
-    return {
-        role: "user",
-        content: [
-            {type: "text", text},
-            ...turn.attachments
-                .filter(attachment => attachment.kind === "image")
-                .map(attachment => ({
-                    type: "image_url" as const,
-                    imageUrl: `data:${attachment.mimeType};base64,${attachment.data}`,
-                })),
-        ],
-    };
-}
-
-function buildOllamaMessage(turn: ConversationTurn, provider: AiProvider, includeNames: boolean): OllamaChatMessage {
-    const text = renderContentText(turn, provider, includeNames);
-    return {
-        role: turn.bot ? "assistant" : "user",
-        content: text,
-        images: turn.bot ? undefined : turn.attachments.filter(attachment => attachment.kind === "image").map(attachment => attachment.data),
-    };
-}
-
-function buildSystemInstruction(
-    config: RuntimeConfigSnapshot,
-    responseLanguage: UserAiResponseLanguage,
-    includePythonToolPrompt: boolean,
-    additions?: string | null,
-    memoryInstruction?: string | null,
-): string {
-    return [
-        config.useSystemPrompt ? getResponseLanguageInstruction(responseLanguage) : null,
-        config.systemPrompt && config.useSystemPrompt ? config.systemPrompt : null,
-        additions?.trim() ? additions.trim() : null,
-        memoryInstruction?.trim() ? memoryInstruction.trim() : null,
-        includePythonToolPrompt ? pythonInterpreterToolPrompt : null,
-    ].filter(Boolean).join("\n\n");
-}
-
-export async function buildConversationSnapshot(
-    msg: Message,
-    textOverride: string,
-    downloads: AiDownloadedFile[],
-    config: RuntimeConfigSnapshot,
-    runtimeTarget: AiRuntimeTarget,
-    responseLanguage: UserAiResponseLanguage,
-    includePythonToolPrompt: boolean,
-): Promise<ConversationSnapshot> {
-    const storedMsg = await MessageStore.get(msg.chat.id, msg.message_id);
-    const messageParts = await collectReplyChainText({triggerMsg: storedMsg ?? msg, downloads});
-
-    if (messageParts.length && textOverride.trim()) {
-        const latest = messageParts[0];
-        if (!latest.bot) latest.content = textOverride.trim();
-    }
-
-    const turns = messageParts
-        .reverse()
-        .map(part => ({
-            bot: part.bot,
-            name: part.name,
-            langCode: part.langCode,
-            userName: part.userName,
-            content: part.content,
-            deletedByBotAt: part.deletedByBotAt,
-            attachments: buildConversationAttachments(part),
-            documentNames: part.documentNames,
-        }));
-
-    const imageCount = turns.reduce((sum, turn) => {
-        if (turn.bot) return sum;
-        return sum + turn.attachments.filter(attachment => attachment.kind === "image").length;
-    }, 0);
-    const memoryInstruction = await buildUserMemoryPrompt(msg.from?.id);
-
-    return {
-        turns,
-        imageCount,
-        systemInstruction: buildSystemInstruction(config, responseLanguage, includePythonToolPrompt, runtimeTarget.systemPromptAdditions, memoryInstruction),
-    };
-}
-
-export function serializeConversationSnapshot(
-    snapshot: ConversationSnapshot,
-    provider: AiProvider,
-    includeNames: boolean,
-): { chatMessages: Array<OpenAIChatMessage | MistralChatMessage | OllamaChatMessage>; imageCount: number } {
-    switch (provider) {
-        case AiProvider.OPENAI: {
-            const messages = snapshot.turns.map(turn => buildOpenAiMessage(turn, provider, includeNames));
-            if (snapshot.systemInstruction) {
-                messages.unshift({role: "system", content: snapshot.systemInstruction, type: "message"});
-            }
-
-            return {chatMessages: messages, imageCount: snapshot.imageCount};
-        }
-        case AiProvider.MISTRAL: {
-            const messages = snapshot.turns.map(turn => buildMistralMessage(turn, provider, includeNames));
-            if (snapshot.systemInstruction) {
-                messages.unshift({role: "system", content: snapshot.systemInstruction});
-            }
-
-            return {chatMessages: messages, imageCount: snapshot.imageCount};
-        }
-        case AiProvider.OLLAMA: {
-            const messages = snapshot.turns.map(turn => buildOllamaMessage(turn, provider, includeNames));
-            if (snapshot.systemInstruction) {
-                messages.unshift({role: "system", content: snapshot.systemInstruction});
-            }
-
-            return {chatMessages: messages, imageCount: snapshot.imageCount};
-        }
-    }
-
-    return {chatMessages: [], imageCount: snapshot.imageCount};
-}

src/ai/document-rag-pipeline.ts

@@ -1,102 +0,0 @@
-import {AiProvider} from "../model/ai-provider";
-import {AiDownloadedFile} from "./telegram-attachments";
-import {TelegramStreamMessage} from "./telegram-stream-message";
-import {deleteMistralLibrary, RuntimeConfigSnapshot, MistralDocumentReference, prepareMistralDocuments} from "./unified-ai-runner.shared";
-import {MistralChatMessage} from "./mistral-chat-message";
-import {OllamaChatMessage} from "./ollama-chat-message";
-import {prepareOllamaDocumentRag} from "./ollama-rag";
-import type {OllamaRagArtifactDetails} from "./ollama-rag";
-import {OpenAIChatMessage} from "./openai-chat-message";
-import {createOpenAiClient, createOllamaClient} from "./ai-runtime-target";
-import {prepareOpenAiDocumentRag} from "./unified-ai-runner.openai";
-
-export type PreparedDocumentRag =
-    | {
-        provider: AiProvider.OPENAI;
-        vectorStoreIds: string[];
-        uploadedFileIds: string[];
-        cleanup: () => Promise<void>;
-    }
-    | {
-        provider: AiProvider.MISTRAL;
-        documents: MistralDocumentReference[];
-        libraryId?: string;
-        cleanup: () => Promise<void>;
-    }
-    | {
-        provider: AiProvider.OLLAMA;
-        prepared: boolean;
-        artifact?: OllamaRagArtifactDetails;
-        cleanup: () => Promise<void>;
-    };
-
-export async function prepareDocumentRag(
-    provider: AiProvider,
-    downloads: AiDownloadedFile[],
-    messages: Array<OpenAIChatMessage | MistralChatMessage | OllamaChatMessage>,
-    streamMessage: TelegramStreamMessage,
-    config: RuntimeConfigSnapshot,
-    signal: AbortSignal,
-    userQuery: string,
-): Promise<PreparedDocumentRag | undefined> {
-    const documents = downloads.filter(download => download.kind === "document");
-    if (!documents.length) return undefined;
-
-    if (provider === AiProvider.OPENAI && config.openAiBackend === "compatible") {
-        return undefined;
-    }
-
-    switch (provider) {
-        case AiProvider.OPENAI: {
-            const openAi = createOpenAiClient(config.openAiChatTarget);
-            const prepared = await prepareOpenAiDocumentRag(openAi, documents);
-            if (!prepared) {
-                throw new Error("OpenAI document RAG preparation returned no context.");
-            }
-            return {
-                provider,
-                vectorStoreIds: prepared.vectorStoreIds,
-                uploadedFileIds: prepared.uploadedFileIds,
-                cleanup: prepared.cleanup,
-            };
-        }
-        case AiProvider.MISTRAL: {
-            const prepared = await prepareMistralDocuments(documents, messages as MistralChatMessage[], streamMessage, config.mistralChatTarget, signal);
-            return {
-                provider,
-                documents: prepared.documents,
-                libraryId: prepared.libraryId,
-                cleanup: async () => {
-                    await deleteMistralLibrary(prepared.libraryId, config.mistralChatTarget);
-                },
-            };
-        }
-        case AiProvider.OLLAMA: {
-            const prepared = await prepareOllamaDocumentRag({
-                downloads,
-                messages: messages as OllamaChatMessage[],
-                userQuery,
-                message: streamMessage,
-                config: {
-                    embeddingModel: config.ollamaDocumentsTarget.model,
-                    embeddingClient: createOllamaClient(config.ollamaDocumentsTarget),
-                    chunkSize: config.ollamaRagChunkSize,
-                    chunkOverlap: config.ollamaRagChunkOverlap,
-                    topK: config.ollamaRagTopK,
-                    maxContextChars: config.ollamaRagMaxContextChars,
-                    minScore: config.ollamaRagMinScore,
-                    maxArchiveFiles: config.ollamaRagMaxArchiveFiles,
-                    maxArchiveBytes: config.ollamaRagMaxArchiveBytes,
-                    maxArchiveDepth: config.ollamaRagMaxArchiveDepth,
-                },
-            });
-
-            return {
-                provider,
-                prepared: prepared.prepared,
-                artifact: prepared.artifact,
-                cleanup: async () => undefined,
-            };
-        }
-    }
-}

src/ai/final-response-artifact-store.ts

@@ -1,58 +0,0 @@
-import {AiProvider} from "../model/ai-provider";
-import type {StoredAttachment} from "../model/stored-attachment";
-import {persistInternalJsonArtifactAttachment} from "./internal-artifact-store";
-
-export async function persistFinalTextArtifactAttachment(params: {
-    provider: AiProvider;
-    model: string;
-    text: string;
-    chatId: number;
-    messageId: number;
-}): Promise<StoredAttachment | undefined> {
-    const text = params.text.trim();
-    if (!text) return Promise.resolve(undefined);
-
-    return await persistInternalJsonArtifactAttachment({
-        artifactKind: "final_text",
-        fileNamePrefix: "final-text",
-        chatId: params.chatId,
-        messageId: params.messageId,
-        payload: {
-            provider: params.provider,
-            model: params.model,
-            text,
-        },
-        metadata: {
-            provider: params.provider,
-            model: params.model,
-            textChars: text.length,
-        },
-    });
-}
-
-export async function persistErrorArtifactAttachment(params: {
-    provider: AiProvider;
-    model: string;
-    message: string;
-    recoverable: boolean;
-    chatId: number;
-    messageId: number;
-}): Promise<StoredAttachment> {
-    return await persistInternalJsonArtifactAttachment({
-        artifactKind: "error",
-        fileNamePrefix: "error",
-        chatId: params.chatId,
-        messageId: params.messageId,
-        payload: {
-            provider: params.provider,
-            model: params.model,
-            message: params.message,
-            recoverable: params.recoverable,
-        },
-        metadata: {
-            provider: params.provider,
-            model: params.model,
-            recoverable: params.recoverable,
-        },
-    });
-}

src/ai/gemini-chat-message.ts

@@ -0,0 +1,84 @@
+export type GeminiUserInputStep = {
+    type: "user_input";
+    content?: Array<GeminiContent>;
+}
+
+export type GeminiModelOutputStep = {
+    type: "model_output";
+    content?: Array<GeminiContent>;
+}
+
+export type GeminiFunctionCallStep = {
+    id: string;
+    arguments: {
+        [key: string]: unknown;
+    };
+    name: string;
+    type: "function_call";
+    signature?: string;
+}
+
+export type GeminiFunctionResultStep = {
+    call_id: string;
+    result: unknown | Array<GeminiTextContent | GeminiImageContent> | string;
+    type: "function_result";
+    is_error?: boolean;
+    name?: string;
+    signature?: string;
+}
+
+export type GeminiStep =
+    | GeminiUserInputStep
+    | GeminiModelOutputStep
+    | GeminiFunctionCallStep
+    | GeminiFunctionResultStep;
+
+export type GeminiTextContent = {
+    text: string;
+}
+
+export type GeminiInlineContent = {
+    inlineData: {
+        data: string;
+        mimeType: string;
+    };
+}
+
+export type GeminiImageContent = GeminiInlineContent;
+export type GeminiAudioContent = GeminiInlineContent;
+export type GeminiDocumentContent = GeminiInlineContent;
+export type GeminiVideoContent = GeminiInlineContent;
+
+export type GeminiFunctionCallContent = {
+    functionCall: {
+        id?: string;
+        name?: string;
+        args?: Record<string, unknown>;
+    };
+}
+
+export type GeminiFunctionResponseContent = {
+    functionResponse: {
+        id?: string;
+        name?: string;
+        response: Record<string, unknown>;
+    };
+}
+
+export type GeminiContent =
+    | GeminiTextContent
+    | GeminiInlineContent
+    | GeminiFunctionCallContent
+    | GeminiFunctionResponseContent;
+
+export type GeminiTurn = {
+    content?: Array<GeminiContent> | GeminiContent;
+    role?: string;
+}
+
+export type GeminiInput = string | Array<GeminiStep> | Array<GeminiContent> | GeminiContent;
+
+export type GeminiMessage = {
+    role: "user" | "model";
+    parts: GeminiContent[];
+};

src/ai/internal-artifact-store.ts

@@ -1,102 +0,0 @@
-import fs from "node:fs";
-import path from "node:path";
-import {createHash} from "node:crypto";
-import {Environment} from "../common/environment";
-import {ArtifactStore} from "../common/artifact-store";
-import type {StoredAttachment} from "../model/stored-attachment";
-import {PIPELINE_ATTACHMENT_LIMIT_BYTES, type PipelineArtifactKind} from "./user-request-pipeline";
-
-export type InternalArtifactAttachmentInput = {
-    artifactKind: PipelineArtifactKind;
-    fileNamePrefix: string;
-    chatId: number;
-    messageId: number;
-    requestId?: string;
-    payload: Record<string, unknown>;
-    metadata?: Record<string, unknown>;
-};
-
-const INTERNAL_ARTIFACT_RETENTION_MS = 14 * 24 * 60 * 60 * 1000;
-
-function sha256(buffer: Buffer): string {
-    return createHash("sha256").update(buffer).digest("hex");
-}
-
-function safeFileNamePart(value: string): string {
-    return value.replace(/[\\/:*?"<>|\u0000-\u001F]/g, "_").slice(0, 80) || "artifact";
-}
-
-export async function persistInternalJsonArtifactAttachment(input: InternalArtifactAttachmentInput): Promise<StoredAttachment> {
-    const createdAt = new Date().toISOString();
-    const buffer = Buffer.from(JSON.stringify({
-        artifactKind: input.artifactKind,
-        createdAt,
-        ...input.payload,
-    }, null, 2), "utf8");
-
-    if (buffer.length > PIPELINE_ATTACHMENT_LIMIT_BYTES) {
-        throw new Error(`Internal ${input.artifactKind} artifact is larger than ${PIPELINE_ATTACHMENT_LIMIT_BYTES} bytes.`);
-    }
-
-    const dir = path.join(Environment.DATA_PATH, "cache", "internal-artifacts", input.artifactKind);
-    fs.mkdirSync(dir, {recursive: true});
-
-    const digest = sha256(buffer);
-    const fileName = `${safeFileNamePart(input.fileNamePrefix)}-${input.chatId}-${input.messageId}-${Date.now()}.json`;
-    const cachePath = path.join(dir, fileName);
-    fs.writeFileSync(cachePath, buffer);
-
-    const attachment: StoredAttachment = {
-        kind: "document",
-        fileId: cachePath,
-        fileUniqueId: digest,
-        fileName,
-        mimeType: "application/json",
-        cachePath,
-        sizeBytes: buffer.length,
-        sha256: digest,
-        scope: "internal_artifact",
-        artifactKind: input.artifactKind,
-        metadata: input.metadata,
-    };
-
-    await ArtifactStore.put({
-        id: "",
-        requestId: input.requestId ?? `message:${input.chatId}:${input.messageId}:${input.artifactKind}`,
-        messageChatId: input.chatId,
-        messageId: input.messageId,
-        kind: input.artifactKind,
-        stage: input.artifactKind,
-        attachmentId: cachePath,
-        payload: {
-            artifactKind: input.artifactKind,
-            createdAt,
-            ...input.payload,
-        },
-        createdAt,
-        attachment,
-    });
-
-    return attachment;
-}
-
-export function cleanupInternalArtifactCache(now = Date.now()): void {
-    const root = path.join(Environment.DATA_PATH, "cache", "internal-artifacts");
-    if (!fs.existsSync(root)) return;
-
-    const cutoff = now - INTERNAL_ARTIFACT_RETENTION_MS;
-    for (const artifactKind of fs.readdirSync(root, {withFileTypes: true})) {
-        if (!artifactKind.isDirectory()) continue;
-
-        const dir = path.join(root, artifactKind.name);
-        for (const entry of fs.readdirSync(dir, {withFileTypes: true})) {
-            if (!entry.isFile()) continue;
-
-            const filePath = path.join(dir, entry.name);
-            const stat = fs.statSync(filePath);
-            if (stat.mtimeMs < cutoff) {
-                fs.rmSync(filePath, {force: true});
-            }
-        }
-    }
-}

src/ai/mcp/mcp-client.ts

@@ -1,421 +0,0 @@
-import {spawn, type ChildProcessWithoutNullStreams} from "node:child_process";
-import type {BoundaryValue} from "../../common/boundary-types.js";
-import {toolsLogger} from "../tools/tool-logger.js";
-import type {McpServerConfig} from "./mcp-config.js";
-
-const logger = toolsLogger.child("mcp");
-const MCP_PROTOCOL_VERSION = "2025-06-18";
-const DEFAULT_REQUEST_TIMEOUT_MS = 30_000;
-
-export type McpToolDefinition = {
-    name: string;
-    description?: string;
-    inputSchema?: BoundaryValue;
-};
-
-type JsonRpcRequest = {
-    jsonrpc: "2.0";
-    id: number;
-    method: string;
-    params?: BoundaryValue;
-};
-
-type JsonRpcNotification = {
-    jsonrpc: "2.0";
-    method: string;
-    params?: BoundaryValue;
-};
-
-type JsonRpcResponse = {
-    jsonrpc?: "2.0";
-    id?: BoundaryValue;
-    result?: BoundaryValue;
-    error?: {
-        code?: number;
-        message?: string;
-        data?: BoundaryValue;
-    };
-};
-
-interface JsonRpcTransport {
-    request(method: string, params?: BoundaryValue): Promise<BoundaryValue>;
-    notify(method: string, params?: BoundaryValue): Promise<void>;
-    close(): Promise<void>;
-}
-
-function isRecord(value: BoundaryValue): value is Record<string, BoundaryValue> {
-    return value !== null && typeof value === "object" && !Array.isArray(value);
-}
-
-function toJsonRpcResponse(value: BoundaryValue): JsonRpcResponse | undefined {
-    if (!isRecord(value)) return undefined;
-    if (value.jsonrpc !== undefined && value.jsonrpc !== "2.0") return undefined;
-    return value as JsonRpcResponse;
-}
-
-function extractJsonRpcResult(response: BoundaryValue, expectedId?: number): BoundaryValue {
-    const parsed = toJsonRpcResponse(response);
-    if (!parsed) {
-        throw new Error("Invalid JSON-RPC response from MCP server.");
-    }
-
-    if (parsed.error) {
-        throw new Error(parsed.error.message || "MCP server returned an error.");
-    }
-
-    if (expectedId !== undefined && parsed.id !== undefined && parsed.id !== expectedId) {
-        throw new Error(`Unexpected JSON-RPC response id from MCP server. Expected ${expectedId}, got ${String(parsed.id)}.`);
-    }
-
-    return parsed.result ?? {};
-}
-
-function parseSsePayload(text: string): BoundaryValue[] {
-    const events: string[] = [];
-    let current: string[] = [];
-
-    for (const rawLine of text.split(/\r?\n/)) {
-        const line = rawLine.trimEnd();
-
-        if (!line) {
-            if (current.length) {
-                events.push(current.join("\n"));
-                current = [];
-            }
-            continue;
-        }
-
-        if (line.startsWith("data:")) {
-            current.push(line.slice(5).replace(/^ /, ""));
-        }
-    }
-
-    if (current.length) {
-        events.push(current.join("\n"));
-    }
-
-    return events.map(event => {
-        try {
-            return JSON.parse(event) as BoundaryValue;
-        } catch {
-            return undefined;
-        }
-    }).filter((event): event is BoundaryValue => event !== undefined);
-}
-
-function timeoutPromise<T>(promise: Promise<T>, timeoutMs: number, label: string): Promise<T> {
-    if (!Number.isFinite(timeoutMs) || timeoutMs <= 0) return promise;
-
-    let timeoutId: NodeJS.Timeout | undefined;
-    const timeout = new Promise<T>((_, reject) => {
-        timeoutId = setTimeout(() => {
-            reject(new Error(`${label} timed out after ${timeoutMs}ms`));
-        }, timeoutMs);
-    });
-
-    return Promise.race([promise, timeout]).finally(() => {
-        if (timeoutId) clearTimeout(timeoutId);
-    });
-}
-
-class StdioJsonRpcTransport implements JsonRpcTransport {
-    private readonly process: ChildProcessWithoutNullStreams;
-    private readonly pending = new Map<number, {resolve: (value: BoundaryValue) => void; reject: (error: Error) => void;}>();
-    private buffer = "";
-    private nextId = 1;
-
-    constructor(private readonly config: McpServerConfig) {
-        if (!config.command) {
-            throw new Error(`MCP stdio server '${config.name}' is missing command.`);
-        }
-
-        this.process = spawn(config.command, config.args ?? [], {
-            cwd: config.cwd,
-            env: {
-                ...process.env,
-                ...config.env,
-            },
-            stdio: ["pipe", "pipe", "pipe"],
-            windowsHide: true,
-        });
-
-        this.process.stdout.on("data", chunk => this.handleStdout(chunk));
-        this.process.stderr.on("data", chunk => {
-            const text = chunk.toString("utf8").trim();
-            if (text) logger.debug("stdio.stderr", {server: config.name, text});
-        });
-        this.process.on("error", error => this.failAll(error));
-        this.process.on("exit", code => this.failAll(new Error(`MCP stdio server '${config.name}' exited with code ${code ?? "unknown"}.`)));
-    }
-
-    private handleStdout(chunk: Buffer): void {
-        this.buffer += chunk.toString("utf8");
-
-        let newlineIndex = this.buffer.indexOf("\n");
-        while (newlineIndex !== -1) {
-            const line = this.buffer.slice(0, newlineIndex).trim();
-            this.buffer = this.buffer.slice(newlineIndex + 1);
-            newlineIndex = this.buffer.indexOf("\n");
-
-            if (!line) continue;
-
-            try {
-                const message = JSON.parse(line) as JsonRpcResponse | JsonRpcNotification;
-                if ("id" in message && message.id !== undefined) {
-                    const pending = this.pending.get(Number(message.id));
-                    if (pending) {
-                        this.pending.delete(Number(message.id));
-                        if ("error" in message && message.error) {
-                            pending.reject(new Error(message.error.message || "MCP stdio request failed."));
-                        } else {
-                            pending.resolve((message as JsonRpcResponse).result ?? {});
-                        }
-                    }
-                    continue;
-                }
-
-                if ("method" in message) {
-                    logger.debug("stdio.notification", {server: this.config.name, method: message.method});
-                }
-            } catch (error) {
-                logger.warn("stdio.parse_failed", {
-                    server: this.config.name,
-                    line: line.slice(0, 500),
-                    error: error instanceof Error ? error.message : String(error),
-                });
-            }
-        }
-    }
-
-    private failAll(error: Error): void {
-        for (const pending of this.pending.values()) {
-            pending.reject(error);
-        }
-        this.pending.clear();
-    }
-
-    async request(method: string, params?: BoundaryValue): Promise<BoundaryValue> {
-        if (this.process.exitCode !== null) {
-            throw new Error(`MCP stdio server '${this.config.name}' is not running.`);
-        }
-
-        const id = this.nextId++;
-        const request: JsonRpcRequest = {
-            jsonrpc: "2.0",
-            id,
-            method,
-            params,
-        };
-
-        const result = new Promise<BoundaryValue>((resolve, reject) => {
-            this.pending.set(id, {resolve, reject});
-        });
-
-        this.process.stdin.write(`${JSON.stringify(request)}\n`);
-        return timeoutPromise(result, this.config.timeoutMs ?? DEFAULT_REQUEST_TIMEOUT_MS, `${this.config.name}.${method}`);
-    }
-
-    async notify(method: string, params?: BoundaryValue): Promise<void> {
-        if (this.process.exitCode !== null) {
-            throw new Error(`MCP stdio server '${this.config.name}' is not running.`);
-        }
-
-        const notification: JsonRpcNotification = {
-            jsonrpc: "2.0",
-            method,
-            params,
-        };
-
-        this.process.stdin.write(`${JSON.stringify(notification)}\n`);
-    }
-
-    async close(): Promise<void> {
-        this.failAll(new Error(`MCP stdio server '${this.config.name}' closed.`));
-        if (!this.process.killed) {
-            this.process.kill();
-        }
-    }
-}
-
-class HttpJsonRpcTransport implements JsonRpcTransport {
-    private nextId = 1;
-    private sessionId?: string;
-
-    constructor(private readonly config: McpServerConfig) {
-        if (!config.url) {
-            throw new Error(`MCP HTTP server '${config.name}' is missing url.`);
-        }
-    }
-
-    private async post(body: BoundaryValue): Promise<Response> {
-        const controller = new AbortController();
-        const timeoutMs = this.config.timeoutMs ?? DEFAULT_REQUEST_TIMEOUT_MS;
-        const timeoutId = setTimeout(() => controller.abort(), timeoutMs);
-
-        try {
-            return await fetch(this.config.url!, {
-                method: "POST",
-                headers: {
-                    "Content-Type": "application/json",
-                    "Accept": "application/json, text/event-stream",
-                    ...(this.sessionId ? {"Mcp-Session-Id": this.sessionId} : {}),
-                    ...(this.config.headers ?? {}),
-                },
-                body: JSON.stringify(body),
-                signal: controller.signal,
-            }).finally(() => clearTimeout(timeoutId));
-        } catch (error) {
-            clearTimeout(timeoutId);
-            throw error;
-        }
-    }
-
-    async request(method: string, params?: BoundaryValue): Promise<BoundaryValue> {
-        const id = this.nextId++;
-        const request: JsonRpcRequest = {
-            jsonrpc: "2.0",
-            id,
-            method,
-            params,
-        };
-
-        const response = await this.post(request);
-        const sessionId = response.headers.get("Mcp-Session-Id");
-        if (sessionId) {
-            this.sessionId = sessionId;
-        }
-
-        if (!response.ok) {
-            const errorText = await response.text().catch(() => "");
-            throw new Error(`MCP HTTP server '${this.config.name}' returned ${response.status}: ${errorText || response.statusText}`);
-        }
-
-        const contentType = response.headers.get("content-type")?.toLowerCase() ?? "";
-        let payload: BoundaryValue;
-
-        if (contentType.includes("text/event-stream")) {
-            const text = await response.text();
-            const messages = parseSsePayload(text);
-            const responseMessage = messages.map(toJsonRpcResponse).find(message => message?.id === id && (message.result !== undefined || message.error));
-            payload = extractJsonRpcResult(responseMessage ?? messages[0] ?? {}, id);
-        } else {
-            payload = extractJsonRpcResult(await response.json() as BoundaryValue, id);
-        }
-
-        return payload;
-    }
-
-    async notify(method: string, params?: BoundaryValue): Promise<void> {
-        const response = await this.post({
-            jsonrpc: "2.0",
-            method,
-            params,
-        });
-
-        const sessionId = response.headers.get("Mcp-Session-Id");
-        if (sessionId) {
-            this.sessionId = sessionId;
-        }
-
-        if (!response.ok && response.status !== 202) {
-            const errorText = await response.text().catch(() => "");
-            throw new Error(`MCP HTTP notification failed for '${this.config.name}' with ${response.status}: ${errorText || response.statusText}`);
-        }
-    }
-
-    async close(): Promise<void> {
-        return;
-    }
-}
-
-function createTransport(config: McpServerConfig): JsonRpcTransport {
-    return config.transport === "stdio"
-        ? new StdioJsonRpcTransport(config)
-        : new HttpJsonRpcTransport(config);
-}
-
-function normalizeToolResultContent(content: BoundaryValue): string {
-    if (content === undefined || content === null) return "";
-    if (typeof content === "string") return content;
-    if (typeof content === "number" || typeof content === "boolean") return String(content);
-    if (Array.isArray(content)) return content.map(item => normalizeToolResultContent(item)).filter(Boolean).join("\n");
-    if (!isRecord(content)) return JSON.stringify(content);
-
-    if (content.type === "text" && typeof content.text === "string") return content.text;
-    if (content.type === "image") {
-        return `[image ${typeof content.mimeType === "string" ? content.mimeType : "unknown"}]`;
-    }
-    if (content.type === "resource" && isRecord(content.resource)) {
-        if (typeof content.resource.text === "string") return content.resource.text;
-        return JSON.stringify(content.resource);
-    }
-
-    return JSON.stringify(content);
-}
-
-export class McpClient {
-    private readonly transport: JsonRpcTransport;
-    private initialized = false;
-
-    constructor(readonly config: McpServerConfig) {
-        this.transport = createTransport(config);
-    }
-
-    async initialize(): Promise<void> {
-        if (this.initialized) return;
-
-        await this.transport.request("initialize", {
-            protocolVersion: MCP_PROTOCOL_VERSION,
-            clientInfo: {
-                name: "tg-chat-bot",
-                version: "1.0.0",
-            },
-            capabilities: {},
-        });
-
-        await this.transport.notify("notifications/initialized");
-        this.initialized = true;
-    }
-
-    async listTools(): Promise<McpToolDefinition[]> {
-        await this.initialize();
-        const result = await this.transport.request("tools/list");
-
-        if (!isRecord(result)) return [];
-
-        const tools = Array.isArray(result.tools) ? result.tools : [];
-        return tools.flatMap(tool => {
-            if (!isRecord(tool) || typeof tool.name !== "string") return [];
-            return [{
-                name: tool.name,
-                description: typeof tool.description === "string" ? tool.description : undefined,
-                inputSchema: tool.inputSchema,
-            }];
-        });
-    }
-
-    async callTool(name: string, args?: BoundaryValue): Promise<string> {
-        await this.initialize();
-        const result = await this.transport.request("tools/call", {
-            name,
-            arguments: args ?? {},
-        });
-
-        if (!isRecord(result)) {
-            return normalizeToolResultContent(result);
-        }
-
-        const content = Array.isArray(result.content) ? result.content : [];
-        const text = content.map(item => normalizeToolResultContent(item)).filter(Boolean).join("\n");
-
-        if (result.isError) {
-            return text ? `[MCP error] ${text}` : "[MCP error]";
-        }
-
-        return text || JSON.stringify(result);
-    }
-
-    async close(): Promise<void> {
-        await this.transport.close();
-    }
-}

src/ai/mcp/mcp-config.ts

@@ -1,106 +0,0 @@
-import type {BoundaryValue} from "../../common/boundary-types.js";
-
-export type McpTransport = "stdio" | "http";
-
-export type McpServerConfig = {
-    name: string;
-    transport: McpTransport;
-    command?: string;
-    args?: string[];
-    cwd?: string;
-    env?: Record<string, string>;
-    url?: string;
-    headers?: Record<string, string>;
-    timeoutMs?: number;
-};
-
-function isRecord(value: BoundaryValue): value is Record<string, BoundaryValue> {
-    return value !== null && typeof value === "object" && !Array.isArray(value);
-}
-
-function asString(value: BoundaryValue): string | undefined {
-    return typeof value === "string" && value.trim().length > 0 ? value.trim() : undefined;
-}
-
-function toStringRecord(value: BoundaryValue): Record<string, string> | undefined {
-    if (!isRecord(value)) return undefined;
-
-    const result: Record<string, string> = {};
-    for (const [key, entry] of Object.entries(value)) {
-        if (typeof entry === "string" || typeof entry === "number" || typeof entry === "boolean") {
-            result[key] = String(entry);
-        }
-    }
-
-    return Object.keys(result).length ? result : undefined;
-}
-
-function toStringArray(value: BoundaryValue): string[] | undefined {
-    if (!Array.isArray(value)) return undefined;
-    const items = value.filter((item): item is string => typeof item === "string" && item.trim().length > 0)
-        .map(item => item.trim());
-    return items.length ? items : undefined;
-}
-
-function toPositiveInt(value: BoundaryValue): number | undefined {
-    const n = typeof value === "number"
-        ? value
-        : typeof value === "string"
-            ? Number(value)
-            : NaN;
-
-    if (!Number.isFinite(n) || n <= 0) return undefined;
-    return Math.floor(n);
-}
-
-function normalizeServerConfig(value: BoundaryValue, fallbackName?: string): McpServerConfig | undefined {
-    if (!isRecord(value)) return undefined;
-
-    const name = asString(value.name) ?? fallbackName;
-    const transportRaw = asString(value.transport);
-    const transport = transportRaw === "http" || transportRaw === "stdio" ? transportRaw : undefined;
-
-    if (!name || !transport) return undefined;
-
-    return {
-        name,
-        transport,
-        command: asString(value.command),
-        args: toStringArray(value.args),
-        cwd: asString(value.cwd),
-        env: toStringRecord(value.env),
-        url: asString(value.url),
-        headers: toStringRecord(value.headers),
-        timeoutMs: toPositiveInt(value.timeoutMs),
-    };
-}
-
-export function parseMcpServerConfigs(raw: string | undefined): McpServerConfig[] {
-    if (!raw?.trim()) return [];
-
-    let parsed: BoundaryValue;
-    try {
-        parsed = JSON.parse(raw) as BoundaryValue;
-    } catch (error) {
-        throw new Error(`Invalid MCP_SERVERS JSON: ${error instanceof Error ? error.message : String(error)}`);
-    }
-
-    if (Array.isArray(parsed)) {
-        return parsed.flatMap((item, index) => normalizeServerConfig(item, `server-${index + 1}`) ? [normalizeServerConfig(item, `server-${index + 1}`)!] : []);
-    }
-
-    if (!isRecord(parsed)) {
-        return [];
-    }
-
-    if (Array.isArray(parsed.servers)) {
-        return parsed.servers.flatMap((item, index) => normalizeServerConfig(item, `server-${index + 1}`) ? [normalizeServerConfig(item, `server-${index + 1}`)!] : []);
-    }
-
-    if (isRecord(parsed.mcpServers)) {
-        return Object.entries(parsed.mcpServers).flatMap(([name, item]) => normalizeServerConfig(item, name) ? [normalizeServerConfig(item, name)!] : []);
-    }
-
-    const single = normalizeServerConfig(parsed);
-    return single ? [single] : [];
-}

src/ai/mcp/mcp-json-schema.ts

@@ -1,123 +0,0 @@
-import type {AiJsonValue, AiToolParameters} from "../tool-types.js";
-import type {BoundaryValue} from "../../common/boundary-types.js";
-
-type JsonSchemaRecord = Record<string, BoundaryValue>;
-
-function isRecord(value: BoundaryValue): value is JsonSchemaRecord {
-    return value !== null && typeof value === "object" && !Array.isArray(value);
-}
-
-function toAiJsonValue(value: BoundaryValue): AiJsonValue | undefined {
-    if (value === undefined) return undefined;
-    if (value === null) return null;
-    if (typeof value === "string" || typeof value === "number" || typeof value === "boolean") return value;
-
-    if (Array.isArray(value)) {
-        return value.map(item => toAiJsonValue(item) ?? null);
-    }
-
-    if (!isRecord(value)) return undefined;
-
-    const result: Record<string, AiJsonValue> = {};
-    for (const [key, entry] of Object.entries(value)) {
-        const normalized = toAiJsonValue(entry);
-        if (normalized !== undefined) {
-            result[key] = normalized;
-        }
-    }
-
-    return result;
-}
-
-function normalizeType(value: BoundaryValue): AiToolParameters["type"] | undefined {
-    const candidates = Array.isArray(value)
-        ? value.filter((item): item is string => typeof item === "string")
-        : typeof value === "string"
-            ? [value]
-            : [];
-
-    const prioritized = candidates.find(item => item !== "null") ?? candidates[0];
-    if (!prioritized) return undefined;
-
-    switch (prioritized) {
-        case "object":
-        case "string":
-        case "number":
-        case "integer":
-        case "boolean":
-        case "array":
-            return prioritized;
-        default:
-            return undefined;
-    }
-}
-
-export function convertJsonSchemaToToolParameters(schema: BoundaryValue): AiToolParameters | undefined {
-    if (!isRecord(schema)) return undefined;
-
-    const declaredType = normalizeType(schema.type);
-    const inferredType = declaredType
-        ?? (schema.properties !== undefined || schema.additionalProperties !== undefined ? "object" : undefined)
-        ?? (schema.items !== undefined ? "array" : undefined)
-        ?? "object";
-
-    const result: AiToolParameters = {
-        type: inferredType,
-    };
-
-    const description = typeof schema.description === "string" && schema.description.trim().length > 0
-        ? schema.description.trim()
-        : undefined;
-    if (description) result.description = description;
-
-    const defaultValue = toAiJsonValue(schema.default);
-    if (defaultValue !== undefined) result.default = defaultValue;
-
-    if (Array.isArray(schema.enum)) {
-        const enumValues = schema.enum
-            .filter((item): item is string => typeof item === "string" && item.length > 0);
-        if (enumValues.length) result.enum = enumValues;
-    }
-
-    if (typeof schema.minItems === "number") result.minItems = schema.minItems;
-    if (typeof schema.maxItems === "number") result.maxItems = schema.maxItems;
-    if (typeof schema.minimum === "number") result.minimum = schema.minimum;
-    if (typeof schema.maximum === "number") result.maximum = schema.maximum;
-
-    if (Array.isArray(schema.required)) {
-        const required = schema.required.filter((item): item is string => typeof item === "string" && item.trim().length > 0);
-        if (required.length) result.required = required;
-    }
-
-    if (inferredType === "object" || schema.properties !== undefined || schema.additionalProperties !== undefined) {
-        if (isRecord(schema.properties)) {
-            const properties: Record<string, AiToolParameters> = {};
-            for (const [key, value] of Object.entries(schema.properties)) {
-                const converted = convertJsonSchemaToToolParameters(value);
-                if (converted) properties[key] = converted;
-            }
-            if (Object.keys(properties).length) result.properties = properties;
-        }
-
-        if (schema.additionalProperties !== undefined) {
-            result.additionalProperties = typeof schema.additionalProperties === "boolean"
-                ? schema.additionalProperties
-                : convertJsonSchemaToToolParameters(schema.additionalProperties);
-        }
-    }
-
-    if (inferredType === "array" || schema.items !== undefined) {
-        if (Array.isArray(schema.items)) {
-            const firstItem = schema.items[0];
-            if (firstItem !== undefined) {
-                const converted = convertJsonSchemaToToolParameters(firstItem);
-                if (converted) result.items = converted;
-            }
-        } else {
-            const converted = convertJsonSchemaToToolParameters(schema.items);
-            if (converted) result.items = converted;
-        }
-    }
-
-    return result;
-}

src/ai/mcp/mcp-registry.ts

@@ -1,165 +0,0 @@
-import {Environment} from "../../common/environment.js";
-import type {AiTool} from "../tool-types.js";
-import type {ToolHandler} from "../tools/types.js";
-import {normalizeToolArguments} from "../tools/utils.js";
-import {toolsLogger} from "../tools/tool-logger.js";
-import {convertJsonSchemaToToolParameters} from "./mcp-json-schema.js";
-import {McpClient, type McpToolDefinition} from "./mcp-client.js";
-import {parseMcpServerConfigs, type McpServerConfig} from "./mcp-config.js";
-
-const logger = toolsLogger.child("mcp-registry");
-
-type McpToolBinding = {
-    server: McpServerConfig;
-    client: McpClient;
-    remoteToolName: string;
-    localToolName: string;
-    tool: AiTool;
-};
-
-type McpInitSummary = {
-    servers: number;
-    loadedServers: number;
-    tools: number;
-    failedServers: string[];
-};
-
-const toolBindings = new Map<string, McpToolBinding>();
-const clients = new Map<string, McpClient>();
-let initPromise: Promise<McpInitSummary> | undefined;
-
-function sanitizeSegment(value: string): string {
-    return value
-        .trim()
-        .replace(/[^a-zA-Z0-9_]+/g, "_")
-        .replace(/_+/g, "_")
-        .replace(/^_+|_+$/g, "") || "tool";
-}
-
-function buildLocalToolName(serverName: string, toolName: string): string {
-    return `mcp__${sanitizeSegment(serverName)}__${sanitizeSegment(toolName)}`;
-}
-
-function buildTool(serverName: string, tool: McpToolDefinition): AiTool {
-    const localName = buildLocalToolName(serverName, tool.name);
-    const description = tool.description?.trim()
-        ? `[MCP ${serverName}] ${tool.description.trim()}`
-        : `[MCP ${serverName}] ${tool.name}`;
-
-    return {
-        type: "function",
-        function: {
-            name: localName,
-            description,
-            parameters: convertJsonSchemaToToolParameters(tool.inputSchema),
-        },
-    };
-}
-
-async function loadServer(config: McpServerConfig): Promise<{loaded: boolean; tools: number}> {
-    const client = new McpClient(config);
-    clients.set(config.name, client);
-
-    try {
-        const remoteTools = await client.listTools();
-        let loaded = 0;
-
-        for (const remoteTool of remoteTools) {
-            const localName = buildLocalToolName(config.name, remoteTool.name);
-            if (toolBindings.has(localName)) {
-                logger.warn("tool.duplicate", {
-                    server: config.name,
-                    tool: remoteTool.name,
-                    localName,
-                });
-                continue;
-            }
-
-            const binding: McpToolBinding = {
-                server: config,
-                client,
-                remoteToolName: remoteTool.name,
-                localToolName: localName,
-                tool: buildTool(config.name, remoteTool),
-            };
-
-            toolBindings.set(localName, binding);
-            loaded += 1;
-        }
-
-        logger.info("server.loaded", {
-            server: config.name,
-            transport: config.transport,
-            tools: loaded,
-        });
-        return {loaded: true, tools: loaded};
-    } catch (error) {
-        logger.error("server.failed", {
-            server: config.name,
-            transport: config.transport,
-            error: error instanceof Error ? error.message : String(error),
-        });
-        await client.close().catch(() => undefined);
-        clients.delete(config.name);
-        return {loaded: false, tools: 0};
-    }
-}
-
-export async function initializeMcpTools(): Promise<McpInitSummary> {
-    if (initPromise) return initPromise;
-
-    initPromise = (async () => {
-        toolBindings.clear();
-        await Promise.all([...clients.values()].map(client => client.close().catch(() => undefined)));
-        clients.clear();
-
-        const configs = parseMcpServerConfigs(Environment.MCP_SERVERS);
-        const results = await Promise.all(configs.map(config => loadServer(config)));
-
-        return {
-            servers: configs.length,
-            loadedServers: results.filter(result => result.loaded).length,
-            tools: [...results].reduce((sum, result) => sum + result.tools, 0),
-            failedServers: configs.filter((_, index) => !results[index]?.loaded).map(config => config.name),
-        };
-    })();
-
-    try {
-        const summary = await initPromise;
-        logger.info("init.done", summary);
-        return summary;
-    } catch (error) {
-        initPromise = undefined;
-        logger.error("init.failed", {error: error instanceof Error ? error.message : String(error)});
-        throw error;
-    }
-}
-
-export function getMcpTools(): AiTool[] {
-    return [...toolBindings.values()].map(binding => binding.tool);
-}
-
-export function getMcpToolHandlers(): Record<string, ToolHandler> {
-    const handlers: Record<string, ToolHandler> = {};
-
-    for (const binding of toolBindings.values()) {
-        handlers[binding.localToolName] = async args => {
-            const normalized = normalizeToolArguments(args, undefined);
-            return binding.client.callTool(binding.remoteToolName, normalized);
-        };
-    }
-
-    return handlers;
-}
-
-export function getMcpToolPrompts(_toolNames: string[]): string[] {
-    return [];
-}
-
-export async function shutdownMcpTools(): Promise<void> {
-    initPromise = undefined;
-    toolBindings.clear();
-
-    await Promise.all([...clients.values()].map(client => client.close().catch(() => undefined)));
-    clients.clear();
-}

src/ai/mistral-chat-message.ts

@@ -67,7 +67,7 @@ export type MistralContentChunk =
 
 export type MistralFunctionCall = {
     name: string;
-    arguments: AiJsonObject | string;
+    arguments: Record<string, unknown> | string;
 };
 
 export type MistralToolCall = {
@@ -109,5 +109,4 @@ export type MistralChatMessage =
     | MistralAssistantMessage
     | MistralSystemMessage
     | MistralToolMessage
-    | MistralUserMessage
-import {AiJsonObject} from "./tool-types";
+    | MistralUserMessage

src/ai/model-call-stage.ts

@@ -1,5 +0,0 @@
-export async function runSingleModelRequest<T>(params: {
-    execute: () => Promise<T>;
-}): Promise<T> {
-    return await params.execute();
-}

src/ai/ollama-rag.ts

@@ -476,40 +476,6 @@ type ExtractedRagDocument = {
     text: string;
 };
 
-export type OllamaRagArtifactDetails = {
-    query: string;
-    extractedDocuments: Array<{
-        documentIndex: number;
-        fileName: string;
-        textChars: number;
-    }>;
-    selectedChunks: Array<{
-        sourceId: string;
-        documentIndex: number;
-        documentName: string;
-        chunkIndex: number;
-        chunkCount: number;
-        textChars: number;
-        score?: number;
-    }>;
-    skippedDocuments: Array<{
-        documentIndex: number;
-        fileName: string;
-        reason: string;
-    }>;
-    providerState: {
-        embeddingModel: string;
-        topK: number;
-        chunkSize: number;
-        chunkOverlap: number;
-        maxContextChars: number;
-        minScore: number;
-        maxArchiveFiles: number;
-        maxArchiveBytes: number;
-        maxArchiveDepth: number;
-    };
-};
-
 type ArchiveSkippedDocument = {
     fileName: string;
     reason: string;
@@ -621,7 +587,7 @@ function reserveArchiveFile(
     return true;
 }
 
-function pushArchiveSkip(state: ArchiveExtractionState, fileName: string, reason: Error | string | object | null | undefined): void {
+function pushArchiveSkip(state: ArchiveExtractionState, fileName: string, reason: unknown): void {
     state.skipped.push({
         fileName,
         reason: reason instanceof Error ? reason.message : String(reason),
@@ -641,7 +607,7 @@ function extractArchiveChildDocuments(
     try {
         return extractRagDocumentsFromFile(child, config, state, depth + 1);
     } catch (e) {
-        pushArchiveSkip(state, child.fileName, e instanceof Error ? e : String(e));
+        pushArchiveSkip(state, child.fileName, e);
         return [];
     }
 }
@@ -675,7 +641,7 @@ function extractZipArchiveDocuments(
             const buffer = readZipEntry(doc.buffer, entry);
             documents.push(...extractArchiveChildDocuments(doc, normalizedName, buffer, config, state, depth));
         } catch (e) {
-            pushArchiveSkip(state, displayName, e instanceof Error ? e : String(e));
+            pushArchiveSkip(state, displayName, e);
         }
     }
 
@@ -1269,48 +1235,6 @@ function formatRagContext(chunks: DocumentChunk[], totalChunks: number, document
     ].filter(line => line.length > 0).join("\n");
 }
 
-function buildOllamaRagArtifactDetails(
-    query: string,
-    documents: SourceDocument[],
-    selected: DocumentChunk[],
-    skippedDocuments: SkippedDocument[],
-    config: OllamaDocumentRagConfig,
-): OllamaRagArtifactDetails {
-    return {
-        query,
-        extractedDocuments: documents.map(document => ({
-            documentIndex: document.documentIndex,
-            fileName: document.fileName,
-            textChars: document.text.length,
-        })),
-        selectedChunks: selected.map(chunk => ({
-            sourceId: chunk.sourceId,
-            documentIndex: chunk.documentIndex,
-            documentName: chunk.documentName,
-            chunkIndex: chunk.chunkIndex,
-            chunkCount: chunk.chunkCount,
-            textChars: chunk.text.length,
-            score: chunk.score,
-        })),
-        skippedDocuments: skippedDocuments.map(document => ({
-            documentIndex: document.documentIndex,
-            fileName: document.fileName,
-            reason: document.reason,
-        })),
-        providerState: {
-            embeddingModel: config.embeddingModel,
-            topK: config.topK,
-            chunkSize: config.chunkSize,
-            chunkOverlap: config.chunkOverlap,
-            maxContextChars: config.maxContextChars,
-            minScore: config.minScore,
-            maxArchiveFiles: config.maxArchiveFiles,
-            maxArchiveBytes: config.maxArchiveBytes,
-            maxArchiveDepth: config.maxArchiveDepth,
-        },
-    };
-}
-
 function injectOllamaRagContext(messages: OllamaChatMessage[], context: string): void {
     const systemIndex = messages.findIndex(message => message.role === "system");
 
@@ -1334,7 +1258,7 @@ export async function buildOllamaDocumentRagContext(params: {
     userQuery: string;
     config: OllamaDocumentRagConfig;
     onStatus?: (status: string) => Promise<void> | void;
-}): Promise<{context: string; artifact: OllamaRagArtifactDetails} | null> {
+}): Promise<string | null> {
     const docs = params.downloads.filter(download => download.kind === "document");
     if (!docs.length) return null;
 
@@ -1409,10 +1333,7 @@ export async function buildOllamaDocumentRagContext(params: {
         throw new Error(Environment.localRagNoSuitableFragmentsText);
     }
 
-    return {
-        context: formatRagContext(selected, chunks.length, documents, skippedDocuments),
-        artifact: buildOllamaRagArtifactDetails(buildRetrievalQuery(params.userQuery, params.messages), documents, selected, skippedDocuments, params.config),
-    };
+    return formatRagContext(selected, chunks.length, documents, skippedDocuments);
 }
 
 export async function prepareOllamaDocumentRag(params: {
@@ -1421,7 +1342,7 @@ export async function prepareOllamaDocumentRag(params: {
     userQuery: string;
     message: TelegramStreamMessage;
     config: OllamaDocumentRagConfig;
-}): Promise<{prepared: boolean; artifact?: OllamaRagArtifactDetails}> {
+}): Promise<boolean> {
     const context = await buildOllamaDocumentRagContext({
         downloads: params.downloads,
         messages: params.messages,
@@ -1433,7 +1354,7 @@ export async function prepareOllamaDocumentRag(params: {
         },
     });
 
-    if (!context) return {prepared: false};
-    injectOllamaRagContext(params.messages, context.context);
-    return {prepared: true, artifact: context.artifact};
+    if (!context) return false;
+    injectOllamaRagContext(params.messages, context);
+    return true;
 }

src/ai/openai-chat-completions.ts

@@ -1,66 +0,0 @@
-import {isRecord} from "./unified-ai-runner.shared.js";
-import type {OpenAIChatMessage, OpenAICompatibleChatMessage} from "./openai-chat-message.js";
-import type {ToolCallData} from "./unified-ai-runner.shared.js";
-
-export function responseContentToText(content: unknown): string {
-    if (typeof content === "string") return content;
-    if (!Array.isArray(content)) return "";
-
-    return content
-        .map(part => isRecord(part) && typeof part.text === "string" ? part.text : "")
-        .join("");
-}
-
-export function openAiResponseMessagesToChatCompletions(messages: OpenAIChatMessage[]): OpenAICompatibleChatMessage[] {
-    return messages.map((message): OpenAICompatibleChatMessage => {
-        if (message.role === "system") {
-            return {role: "system", content: responseContentToText(message.content)};
-        }
-
-        if (message.role === "assistant") {
-            const text = responseContentToText(message.content);
-            return text.length
-                ? {role: "assistant", content: text}
-                : {role: "assistant", content: null};
-        }
-
-        const content = Array.isArray(message.content)
-            ? (() => {
-                const parts = message.content.map((part): {type: "text"; text: string} | {type: "image_url"; image_url: {url: string}} => {
-                    if (isRecord(part) && part.type === "input_image") {
-                        return {
-                            type: "image_url",
-                            image_url: {url: String(part.image_url ?? "")},
-                        };
-                    }
-
-                    return {
-                        type: "text",
-                        text: isRecord(part) && typeof part.text === "string" ? part.text : "",
-                    };
-                });
-
-                return parts.every(part => part.type === "text")
-                    ? parts.map(part => part.text).join("")
-                    : parts;
-            })()
-            : message.content;
-
-        return {role: "user", content};
-    });
-}
-
-export function buildAssistantToolMessage(calls: ToolCallData[], text: string): OpenAICompatibleChatMessage {
-    return {
-        role: "assistant",
-        content: text,
-        tool_calls: calls.map(call => ({
-            id: call.id,
-            type: "function",
-            function: {
-                name: call.name,
-                arguments: call.argumentsText,
-            },
-        })),
-    };
-}

src/ai/openai-chat-message.ts

@@ -1,22 +1,7 @@
-import type {
-    ResponseInputMessageContentList,
-    ResponseOutputMessage,
-} from "openai/resources/responses/responses";
-import type {ChatCompletionMessageParam} from "openai/resources/chat/completions";
+import type {ResponseInputMessageContentList} from "openai/resources/responses/responses";
 
-type OpenAIInputChatMessage = {
+export type OpenAIChatMessage = {
     type: "message";
-    role: "system" | "user";
+    role: "system" | "user" | "assistant";
     content: string | ResponseInputMessageContentList;
 };
-
-type OpenAIOutputChatMessage = {
-    type: "message";
-    role: "assistant";
-    content: ResponseOutputMessage["content"];
-    phase?: ResponseOutputMessage["phase"];
-} & Pick<ResponseOutputMessage, "id" | "status">;
-
-export type OpenAIChatMessage = OpenAIInputChatMessage | OpenAIOutputChatMessage;
-
-export type OpenAICompatibleChatMessage = ChatCompletionMessageParam;

src/ai/openai-upload-files.ts

@@ -1,74 +0,0 @@
-import {Message} from "typescript-telegram-bot-api";
-import fs from "node:fs";
-import path from "node:path";
-import {bot} from "../index.js";
-import {Environment} from "../common/environment.js";
-import {logError} from "../util/utils.js";
-import {errorMessage} from "./unified-ai-runner.shared.js";
-import {SendFileAttachmentResult, SendFileAttachmentResultSchema} from "./tools/files.js";
-
-export async function tryToUploadFiles(
-    msg: Message,
-    toolResults: string[]
-): Promise<
-    | { found: false }
-    | { found: true, uploaded: true }
-    | { found: boolean, uploaded: false, error: string, toolIndex: number }
-> {
-    let sendFileAttachment: {
-        result: SendFileAttachmentResult & { success: true },
-        toolIndex: number
-    } | null = null;
-
-    let found = false;
-
-    try {
-        for (const [index, toolResult] of toolResults.entries()) {
-            const raw = JSON.parse(toolResult);
-            const res = SendFileAttachmentResultSchema.safeParse(raw);
-
-            if (res.success) {
-                found = true;
-
-                if (res.data.success) {
-                    sendFileAttachment = {result: res.data, toolIndex: index};
-                }
-            }
-        }
-
-        if (!found) {
-            return {found: false};
-        }
-
-        const attachmentRoot = Environment.FILE_TOOLS_ROOT_DIR;
-        const attachmentPath = attachmentRoot
-            ? path.join(
-                attachmentRoot,
-                String(msg.from?.id),
-                sendFileAttachment?.result?.attachment?.relativePath ?? "",
-            )
-            : "";
-
-        if (!fs.existsSync(attachmentPath)) {
-            throw new Error(`Attachment file does not exist: ${attachmentPath}`);
-        }
-
-        await bot.sendDocument({
-            chat_id: msg.chat.id,
-            reply_parameters: {
-                message_id: msg.message_id,
-            },
-            document: fs.createReadStream(attachmentPath),
-        });
-
-        return {found: true, uploaded: true};
-    } catch (e) {
-        logError(e instanceof Error ? e : String(e));
-        return {
-            found: found,
-            uploaded: false,
-            error: errorMessage(e instanceof Error ? e : String(e)),
-            toolIndex: sendFileAttachment?.toolIndex ?? -1
-        };
-    }
-}

src/ai/provider-adapter-contract.ts

@@ -1,198 +0,0 @@
-import type {ToolCallData} from "./unified-ai-runner.shared.js";
-import type {ResponseStreamEvent} from "openai/resources/responses/responses";
-
-function isRecord(value: unknown): value is Record<string, unknown> {
-    return !!value && typeof value === "object" && !Array.isArray(value);
-}
-
-function normalizeToolCallId(value: unknown, fallback: string): string {
-    return typeof value === "string" && value.trim().length > 0 ? value : fallback;
-}
-
-function normalizeToolArguments(value: unknown): string {
-    if (typeof value === "string") return value;
-    return JSON.stringify(value ?? {});
-}
-
-function normalizeToolArgumentsChunk(value: unknown): string {
-    if (typeof value === "string") return value;
-    if (value === undefined || value === null) return "";
-    return JSON.stringify(value);
-}
-
-export function extractOpenAiToolCalls(response: unknown): ToolCallData[] {
-    const output = isRecord(response) && Array.isArray(response.output) ? response.output : [];
-
-    return output
-        .filter(item => isRecord(item) && item.type === "function_call" && (typeof item.call_id === "string" || typeof item.name === "string"))
-        .map((item, index) => ({
-            id: normalizeToolCallId(item.call_id, `openai_${index}`),
-            name: typeof item.name === "string" ? item.name : "",
-            argumentsText: normalizeToolArguments(item.arguments),
-        }))
-        .filter(call => call.name.length > 0);
-}
-
-export function extractOpenAiTextDelta(input: unknown): string {
-    const event = input as ResponseStreamEvent | undefined;
-    return event?.type === "response.output_text.delta" ? event.delta ?? "" : "";
-}
-
-export function extractOpenAiChatTextDelta(input: unknown): string {
-    const event = isRecord(input) ? input : undefined;
-    const choice = event && Array.isArray(event.choices) && isRecord(event.choices[0]) ? event.choices[0] : undefined;
-    const delta = isRecord(choice?.delta) ? choice.delta : undefined;
-    const content = delta && typeof delta.content === "string" ? delta.content : "";
-    return content;
-}
-
-export function normalizeStreamingTextDelta(existingText: string, deltaText: string): string {
-    if (!deltaText) return "";
-    if (!existingText) return deltaText;
-
-    if (deltaText.startsWith(existingText)) {
-        return deltaText.slice(existingText.length);
-    }
-
-    return deltaText;
-}
-
-export function extractOpenAiChatToolCalls(response: unknown): ToolCallData[] {
-    const record = isRecord(response) ? response : undefined;
-    const choice = record && Array.isArray(record.choices) && isRecord(record.choices[0]) ? record.choices[0] : undefined;
-    const message = isRecord(choice?.message) ? choice.message : undefined;
-    const toolCalls = message && Array.isArray(message.tool_calls) ? message.tool_calls : [];
-
-    return toolCalls
-        .filter((item, index) => isRecord(item) && ((typeof item.id === "string") || typeof item.index === "number" || index >= 0))
-        .map((item, index) => {
-            const call = isRecord(item) ? item : {};
-            const fn = isRecord(call.function) ? call.function : undefined;
-            const name = typeof fn?.name === "string" ? fn.name : typeof call.name === "string" ? call.name : "";
-            return {
-                id: normalizeToolCallId(call.id, `openai_chat_${typeof call.index === "number" ? call.index : index}`),
-                name,
-                argumentsText: normalizeToolArguments(fn?.arguments ?? call.arguments),
-            };
-        })
-        .filter(call => call.name.length > 0);
-}
-
-export function extractOpenAiChatStreamingToolCalls(input: unknown): ToolCallData[] {
-    const event = isRecord(input) ? input : undefined;
-    const choice = event && Array.isArray(event.choices) && isRecord(event.choices[0]) ? event.choices[0] : undefined;
-    const delta = isRecord(choice?.delta) ? choice.delta : undefined;
-    const toolCalls = Array.isArray(delta?.tool_calls) ? delta.tool_calls : [];
-
-    return toolCalls
-        .map((item, index) => {
-            const call = isRecord(item) ? item : {};
-            const fn = isRecord(call.function) ? call.function : undefined;
-            const name = typeof fn?.name === "string" ? fn.name : typeof call.name === "string" ? call.name : "";
-            return {
-                id: normalizeToolCallId(call.id, `openai_chat_${typeof call.index === "number" ? call.index : index}`),
-                name,
-                argumentsText: normalizeToolArgumentsChunk(fn?.arguments ?? call.arguments),
-            };
-        })
-        .filter(call => call.id.length > 0);
-}
-
-export function mergeToolCallChunks(existing: ToolCallData[], chunks: ToolCallData[]): ToolCallData[] {
-    const merged = new Map<string, ToolCallData>(existing.map(call => [call.id, {...call}]));
-
-    for (const chunk of chunks) {
-        const current = merged.get(chunk.id);
-        if (!current) {
-            merged.set(chunk.id, {...chunk});
-            continue;
-        }
-
-        merged.set(chunk.id, {
-            id: current.id,
-            name: current.name || chunk.name,
-            argumentsText: current.argumentsText + (chunk.argumentsText ?? ""),
-        });
-    }
-
-    return [...merged.values()];
-}
-
-export function extractOpenAiStreamingToolCalls(input: unknown): ToolCallData[] {
-    const event = input as ResponseStreamEvent | undefined;
-    if (event?.type === "response.output_item.added" && isRecord(event.item) && event.item.type === "function_call") {
-        return extractOpenAiToolCalls({
-            output: [{
-                type: "function_call",
-                call_id: event.item.call_id ?? event.item.id,
-                name: event.item.name,
-                arguments: event.item.arguments,
-            }],
-        });
-    }
-
-    return [];
-}
-
-export function extractMistralToolCalls(calls: unknown): ToolCallData[] {
-    const normalized = Array.isArray(calls)
-        ? calls
-        : isRecord(calls) && (Array.isArray(calls.toolCalls) || Array.isArray(calls.tool_calls))
-            ? (calls.toolCalls ?? calls.tool_calls)
-            : [];
-
-    if (!Array.isArray(normalized)) return [];
-
-    return normalized
-        .map((item, index) => {
-            const call = isRecord(item) ? item : {};
-            const fn = isRecord(call.function) ? call.function : undefined;
-            const name = typeof fn?.name === "string" ? fn.name : typeof call.name === "string" ? call.name : "";
-            return {
-                id: normalizeToolCallId(call.id, `mistral_${index}`),
-                name,
-                argumentsText: normalizeToolArguments(fn?.arguments ?? call.arguments),
-            };
-        })
-        .filter(call => call.name.length > 0);
-}
-
-export function extractMistralTextDelta(input: unknown): string {
-    const delta = isRecord(input) ? input : {};
-    const content = delta.content;
-    if (typeof content === "string") return content;
-    if (Array.isArray(content)) {
-        return content
-            .map(part => isRecord(part) && typeof part.text === "string" ? part.text : "")
-            .join("");
-    }
-    return "";
-}
-
-export function extractOllamaToolCalls(calls: unknown): ToolCallData[] {
-    const normalized = Array.isArray(calls)
-        ? calls
-        : isRecord(calls) && Array.isArray(calls.tool_calls)
-            ? calls.tool_calls
-            : [];
-
-    if (!Array.isArray(normalized)) return [];
-
-    return normalized
-        .map((item, index) => {
-            const call = isRecord(item) ? item : {};
-            const fn = isRecord(call.function) ? call.function : undefined;
-            const name = typeof fn?.name === "string" ? fn.name : typeof call.name === "string" ? call.name : "";
-            return {
-                id: normalizeToolCallId(call.id, `ollama_${index}`),
-                name,
-                argumentsText: normalizeToolArguments(fn?.arguments ?? call.arguments),
-            };
-        })
-        .filter(call => call.name.length > 0);
-}
-
-export function extractOllamaTextDelta(input: unknown): string {
-    const chunk = isRecord(input) ? input.message : undefined;
-    return isRecord(chunk) && typeof chunk.content === "string" ? chunk.content : "";
-}

src/ai/provider-adapters.ts

@@ -1,196 +0,0 @@
-import {AiProvider} from "../model/ai-provider.js";
-import type {BoundaryValue} from "../common/boundary-types.js";
-import type {RuntimeConfigSnapshot, ToolCallData} from "./unified-ai-runner.shared.js";
-import {getMistralTools, getOllamaTools, getOpenAIResponsesTools, getOpenAICodeInterpreterTool} from "./tool-mappers.js";
-import type {MistralChatMessage as MistralMessageType} from "./mistral-chat-message.js";
-import type {OpenAIChatMessage as OpenAiMessageType} from "./openai-chat-message.js";
-import type {Message as OllamaMessage} from "ollama";
-import {
-    extractMistralTextDelta,
-    extractMistralToolCalls,
-    extractOllamaTextDelta,
-    extractOllamaToolCalls,
-    extractOpenAiTextDelta,
-    extractOpenAiStreamingToolCalls,
-    extractOpenAiToolCalls,
-} from "./provider-adapter-contract.js";
-
-export type ProviderRankToolOptions = {
-    forCreator?: boolean;
-    vectorStoreIds?: string[];
-};
-
-export interface AiProviderAdapter {
-    readonly provider: AiProvider;
-    mapMessages(messages: readonly unknown[]): unknown[];
-    rankTools(config: RuntimeConfigSnapshot, options?: ProviderRankToolOptions): readonly BoundaryValue[];
-    callModel<T>(request: unknown, execute: () => Promise<T>): Promise<T>;
-    extractTextDelta(input: unknown): string;
-    extractToolCalls(input: unknown): ToolCallData[];
-    extractStreamingToolCalls(input: unknown): ToolCallData[];
-    appendToolResults(messages: unknown[], calls: ToolCallData[], results: string[]): void;
-    finalize(): Promise<void>;
-}
-
-function appendOllamaToolResults(messages: unknown[], calls: ToolCallData[], results: string[]): void {
-    for (const [index, call] of calls.entries()) {
-        messages.push({
-            role: "tool",
-            content: results[index] ?? "",
-            tool_name: call.name,
-        });
-    }
-}
-
-class OpenAiProviderAdapter implements AiProviderAdapter {
-    readonly provider = AiProvider.OPENAI;
-
-    mapMessages(messages: readonly unknown[]): unknown[] {
-        return messages as OpenAiMessageType[];
-    }
-
-    rankTools(config: RuntimeConfigSnapshot, options?: ProviderRankToolOptions): readonly BoundaryValue[] {
-        const tools: BoundaryValue[] = [
-            ...getOpenAIResponsesTools(options?.forCreator) as BoundaryValue[],
-            getOpenAICodeInterpreterTool() as BoundaryValue,
-            {
-                type: "image_generation",
-                model: config.openAiImageTarget.model,
-                size: "auto",
-                moderation: "low",
-                output_format: "png",
-                partial_images: 3,
-            },
-            {type: "web_search"},
-        ];
-
-        if (options?.vectorStoreIds?.length) {
-            tools.unshift({
-                type: "file_search",
-                vector_store_ids: options.vectorStoreIds,
-            });
-        }
-
-        return tools;
-    }
-
-    async callModel<T>(_request: unknown, execute: () => Promise<T>): Promise<T> {
-        return execute();
-    }
-
-    extractTextDelta(input: unknown): string {
-        return extractOpenAiTextDelta(input);
-    }
-
-    extractToolCalls(input: unknown): ToolCallData[] {
-        return extractOpenAiToolCalls(input);
-    }
-
-    extractStreamingToolCalls(input: unknown): ToolCallData[] {
-        return extractOpenAiStreamingToolCalls(input);
-    }
-
-    appendToolResults(messages: unknown[], calls: ToolCallData[], results: string[]): void {
-        for (const [index, call] of calls.entries()) {
-            messages.push({
-                type: "function_call_output",
-                call_id: call.id,
-                output: results[index] ?? "",
-            });
-        }
-    }
-
-    async finalize(): Promise<void> {
-        return;
-    }
-}
-
-class MistralProviderAdapter implements AiProviderAdapter {
-    readonly provider = AiProvider.MISTRAL;
-
-    mapMessages(messages: readonly unknown[]): unknown[] {
-        return messages as MistralMessageType[];
-    }
-
-    rankTools(_config: RuntimeConfigSnapshot, options?: ProviderRankToolOptions): readonly BoundaryValue[] {
-        return getMistralTools(options?.forCreator) as BoundaryValue[];
-    }
-
-    async callModel<T>(_request: unknown, execute: () => Promise<T>): Promise<T> {
-        return execute();
-    }
-
-    extractTextDelta(input: unknown): string {
-        return extractMistralTextDelta(input);
-    }
-
-    extractToolCalls(input: unknown): ToolCallData[] {
-        return extractMistralToolCalls(input);
-    }
-
-    extractStreamingToolCalls(input: unknown): ToolCallData[] {
-        return this.extractToolCalls(input);
-    }
-
-    appendToolResults(messages: unknown[], calls: ToolCallData[], results: string[]): void {
-        for (const [index, call] of calls.entries()) {
-            messages.push({
-                role: "tool",
-                name: call.name,
-                toolCallId: call.id,
-                content: results[index] ?? "",
-            });
-        }
-    }
-
-    async finalize(): Promise<void> {
-        return;
-    }
-}
-
-class OllamaProviderAdapter implements AiProviderAdapter {
-    readonly provider = AiProvider.OLLAMA;
-
-    mapMessages(messages: readonly unknown[]): unknown[] {
-        return messages as OllamaMessage[];
-    }
-
-    rankTools(_config: RuntimeConfigSnapshot, options?: ProviderRankToolOptions): readonly BoundaryValue[] {
-        return getOllamaTools(options?.forCreator) as BoundaryValue[];
-    }
-
-    async callModel<T>(_request: unknown, execute: () => Promise<T>): Promise<T> {
-        return execute();
-    }
-
-    extractTextDelta(input: unknown): string {
-        return extractOllamaTextDelta(input);
-    }
-
-    extractToolCalls(input: unknown): ToolCallData[] {
-        return extractOllamaToolCalls(input);
-    }
-
-    extractStreamingToolCalls(input: unknown): ToolCallData[] {
-        return this.extractToolCalls(input);
-    }
-
-    appendToolResults(messages: unknown[], calls: ToolCallData[], results: string[]): void {
-        appendOllamaToolResults(messages, calls, results);
-    }
-
-    async finalize(): Promise<void> {
-        return;
-    }
-}
-
-export function getProviderAdapter(provider: AiProvider): AiProviderAdapter {
-    switch (provider) {
-        case AiProvider.OPENAI:
-            return new OpenAiProviderAdapter();
-        case AiProvider.MISTRAL:
-            return new MistralProviderAdapter();
-        case AiProvider.OLLAMA:
-            return new OllamaProviderAdapter();
-    }
-}

src/ai/provider-aliases.ts

@@ -1,18 +0,0 @@
-import {AiProvider} from "../model/ai-provider";
-
-const PROVIDER_ALIASES = new Map<string, AiProvider>([
-    ["openai", AiProvider.OPENAI],
-    ["chatgpt", AiProvider.OPENAI],
-    ["gpt", AiProvider.OPENAI],
-    ["mistral", AiProvider.MISTRAL],
-    ["ollama", AiProvider.OLLAMA],
-]);
-
-export function parseProviderToken(token: string | undefined): AiProvider | undefined {
-    if (!token) return undefined;
-    return PROVIDER_ALIASES.get(token.toLowerCase().replace(/:$/, ""));
-}
-
-export function providerDisplayName(provider: AiProvider): string {
-    return provider.charAt(0) + provider.slice(1).toLowerCase();
-}

src/ai/provider-model-runtime.ts

@@ -7,9 +7,12 @@ import {isOllamaSpeechToTextModel} from "./speech-to-text-models";
 import {
     AiCapabilityName,
     AiRuntimeTarget,
+    createGeminiOpenAiClient,
+    createGoogleGenAiClient,
     createMistralClient,
     createOllamaClient,
     createOpenAiClient,
+    getGeminiApiMode,
     resolveAiRuntimeTarget,
     sameRuntimeEndpoint,
 } from "./ai-runtime-target";
@@ -32,6 +35,8 @@ export function getRuntimeModel(provider: AiProvider): string {
     switch (provider) {
         case AiProvider.OLLAMA:
             return Environment.OLLAMA_CHAT_MODEL;
+        case AiProvider.GEMINI:
+            return Environment.GEMINI_MODEL;
         case AiProvider.MISTRAL:
             return Environment.MISTRAL_MODEL;
         case AiProvider.OPENAI:
@@ -44,6 +49,9 @@ export function setRuntimeModel(provider: AiProvider, model: string): void {
         case AiProvider.OLLAMA:
             Environment.OLLAMA_CHAT_MODEL = model;
             break;
+        case AiProvider.GEMINI:
+            Environment.GEMINI_MODEL = model;
+            break;
         case AiProvider.MISTRAL:
             Environment.MISTRAL_MODEL = model;
             break;
@@ -103,6 +111,12 @@ function isOpenAiReasoningModel(model: string): boolean {
     return /^o\d/.test(name) || name.startsWith("gpt-5");
 }
 
+// TODO: OpenAI image input rollout
+// 1. Keep OpenAI chat payload building `input_image` parts from `MessagePart.imageParts`.
+// 2. Replace name-only vision detection with a dedicated OpenAI vision-capability helper.
+// 3. Use allowlist/denylist heuristics for `vision` and `ocr`, with a probe/cache fallback later if needed.
+// 4. Gate `rejectUnsupportedAttachments()` on the resolved vision capability, not on `OPENAI_IMAGE_MODEL`.
+// 5. Add tests for supported/unsupported model names and the resulting `input_image` payload shape.
 function isOpenAiVisionModel(model: string): boolean {
     const name = lowerModelName(model);
     if (!isOpenAiTextModel(model)) return false;
@@ -111,6 +125,16 @@ function isOpenAiVisionModel(model: string): boolean {
     return true;
 }
 
+function isGeminiNonChatModel(model: string): boolean {
+    const name = lowerModelName(model);
+    return name.includes("lyria") || name.includes("-tts") || name.includes("image-preview") || name.endsWith("-image");
+}
+
+function geminiSupportsAudioInput(model: string): boolean {
+    const name = lowerModelName(model);
+    return name.startsWith("gemini-") && !isGeminiNonChatModel(model);
+}
+
 export async function getModelCapabilities(
     provider: AiProvider,
     model: string,
@@ -143,6 +167,26 @@ export async function getModelCapabilities(
                     speechToText: capability(audioSupported, target, runtimeTarget),
                 });
             }
+            case AiProvider.GEMINI: {
+                const chatLike = lowerModelName(model).startsWith("gemini-") && !isGeminiNonChatModel(model);
+                const reasoningModel = lowerModelName(model).includes("2.5") || lowerModelName(model).includes("thinking");
+                const imageTarget = resolveAiRuntimeTarget(provider, "vision");
+                const speechTarget = resolveAiRuntimeTarget(provider, "speechToText");
+                const ttsTarget = resolveAiRuntimeTarget(provider, "textToSpeech");
+
+                return buildCapabilities({
+                    chat: capability(true, target, runtimeTarget),
+                    vision: capability(!!imageTarget.apiKey && !!imageTarget.model, imageTarget, runtimeTarget),
+                    ocr: capability(!!imageTarget.apiKey && !!imageTarget.model, imageTarget, runtimeTarget),
+                    thinking: capability(reasoningModel, target, runtimeTarget),
+                    extendedThinking: capability(reasoningModel, target, runtimeTarget),
+                    tools: capability(chatLike, target, runtimeTarget),
+                    audio: capability(geminiSupportsAudioInput(model), target, runtimeTarget),
+                    speechToText: capability(!!speechTarget.apiKey && geminiSupportsAudioInput(speechTarget.model), speechTarget, runtimeTarget),
+                    outputImages: capability(!!imageTarget.apiKey && !!imageTarget.model, imageTarget, runtimeTarget),
+                    textToSpeech: capability(!!ttsTarget.apiKey && !!ttsTarget.model, ttsTarget, runtimeTarget),
+                });
+            }
             case AiProvider.MISTRAL: {
                 const mistral = createMistralClient(target);
                 const info = await mistral.models.retrieve({modelId: model});
@@ -176,7 +220,6 @@ export async function getModelCapabilities(
                     thinking: capability(reasoningModel, target, runtimeTarget),
                     extendedThinking: capability(reasoningModel, target, runtimeTarget),
                     tools: capability(textModel, target, runtimeTarget),
-                    documents: capability(textModel, target, runtimeTarget),
                     outputImages: capability(!!imageTarget.model, imageTarget, runtimeTarget),
                     speechToText: capability(!!speechTarget.model, speechTarget, runtimeTarget),
                     textToSpeech: capability(!!ttsTarget.apiKey && !!ttsTarget.model, ttsTarget, runtimeTarget),
@@ -185,7 +228,7 @@ export async function getModelCapabilities(
         }
 
     } catch (e) {
-        logError(e instanceof Error ? e : String(e));
+        logError(e);
         return undefined;
     }
 }
@@ -196,14 +239,9 @@ export async function getRuntimeCapabilities(
     target?: AiRuntimeTarget
 ): Promise<AiModelCapabilities> {
     const runtimeTarget = target ?? resolveAiRuntimeTarget(provider, "chat", model ?? getRuntimeModel(provider));
-    const targetPurpose = target?.purpose && target.purpose !== "memoryCompress" ? target.purpose : "chat";
-    const result = await getModelCapabilities(provider, runtimeTarget.model, targetPurpose) ?? buildCapabilities({});
+    const result = await getModelCapabilities(provider, runtimeTarget.model, target?.purpose ?? "chat") ?? buildCapabilities({});
 
     for (const capabilityName of CAPABILITY_NAMES) {
-        if (provider === AiProvider.OPENAI && (capabilityName === "vision" || capabilityName === "ocr")) {
-            continue;
-        }
-
         const target = resolveAiRuntimeTarget(provider, capabilityName);
         if (target.model === runtimeTarget.model && sameRuntimeEndpoint(target, runtimeTarget)) continue;
 
@@ -278,12 +316,29 @@ type ModelListResponse = {
 export async function listProviderModels(provider: AiProvider): Promise<string[]> {
     const target = resolveAiRuntimeTarget(provider, "chat", getRuntimeModel(provider));
 
-        switch (provider) {
-            case AiProvider.OLLAMA: {
-                const ollama = createOllamaClient(target);
-                const result = await ollama.list() as ModelListResponse;
-                return (result.models ?? []).map(m => m.model || m.name).filter((name): name is string => !!name);
+    switch (provider) {
+        case AiProvider.OLLAMA: {
+            const ollama = createOllamaClient(target);
+            const result = await ollama.list() as ModelListResponse;
+            return (result.models ?? []).map(m => m.model || m.name).filter((name): name is string => !!name);
+        }
+        case AiProvider.GEMINI: {
+            const models: string[] = [];
+            if (getGeminiApiMode(target) === "openai") {
+                const geminiAi = createGeminiOpenAiClient(target);
+                const iterable = await geminiAi.models.list() as AsyncIterable<NamedModel>;
+                for await (const model of iterable) models.push(model.name || model.id || String(model));
+                return models;
             }
+
+            const geminiAi = createGoogleGenAiClient(target);
+            const iterable = await geminiAi.models.list() as AsyncIterable<NamedModel>;
+            for await (const model of iterable) {
+                const name = model.name || model.id || String(model);
+                models.push(String(name).replace(/^models\//, ""));
+            }
+            return models;
+        }
         case AiProvider.MISTRAL: {
             const mistralAi = createMistralClient(target);
             const result = await mistralAi.models.list() as ModelListResponse | NamedModel[];

src/ai/provider-request-queue.ts

@@ -1,7 +1,6 @@
 import {Environment} from "../common/environment";
 import {AiProvider} from "../model/ai-provider";
 import {appLogger} from "../logging/logger";
-import type {BoundaryValue} from "../common/boundary-types";
 
 const logger = appLogger.child("ai-provider-queue");
 
@@ -14,16 +13,16 @@ export type AiRequestQueueTarget = {
 type QueueEntry = {
     target: AiRequestQueueTarget;
     queueKey: string;
-    run: () => Promise<BoundaryValue>;
-    resolve: (value: BoundaryValue) => void;
-    reject: (reason?: Error | string | BoundaryValue | null | undefined) => void;
+    run: () => Promise<unknown>;
+    resolve: (value: unknown) => void;
+    reject: (reason?: unknown) => void;
     onPositionChange: (requestsBefore: number) => Promise<void> | void;
     signal?: AbortSignal;
     abortHandler?: () => void;
     started: boolean;
 };
 
-type EnqueueOptions<T extends BoundaryValue> = {
+type EnqueueOptions<T> = {
     signal?: AbortSignal;
     onPositionChange: (requestsBefore: number) => Promise<void> | void;
     run: () => Promise<T>;
@@ -33,7 +32,7 @@ class AiProviderRequestQueue {
     private readonly waiting = new Map<string, QueueEntry[]>();
     private readonly active = new Map<string, number>();
 
-    enqueue<T extends BoundaryValue>(target: AiRequestQueueTarget, options: EnqueueOptions<T>): Promise<T> {
+    enqueue<T>(target: AiRequestQueueTarget, options: EnqueueOptions<T>): Promise<T> {
         if (options.signal?.aborted) {
             logger.debug("enqueue.rejected.aborted", {provider: target.provider, model: target.model, baseUrl: target.baseUrl});
             return Promise.reject(new Error("Aborted"));
@@ -161,9 +160,8 @@ class AiProviderRequestQueue {
             entry.resolve(await entry.run());
             logger.debug("entry.done", {provider: entry.target.provider, model: entry.target.model, baseUrl: entry.target.baseUrl});
         } catch (e) {
-            const error = e instanceof Error ? e : String(e);
-            logger.error("entry.failed", {provider: entry.target.provider, model: entry.target.model, baseUrl: entry.target.baseUrl, error});
-            entry.reject(error);
+            logger.error("entry.failed", {provider: entry.target.provider, model: entry.target.model, baseUrl: entry.target.baseUrl, error: e});
+            entry.reject(e);
         } finally {
             this.setActiveCount(entry.queueKey, this.activeCount(entry.queueKey) - 1);
             this.schedule(entry.target);
@@ -180,10 +178,10 @@ class AiProviderRequestQueue {
         })).then(results => {
             for (const result of results) {
                 if (result.status === "rejected") {
-                    logger.error("position_update.failed", {provider: target.provider, model: target.model, reason: result.reason instanceof Error ? result.reason : String(result.reason)});
+                    logger.error("position_update.failed", {provider: target.provider, model: target.model, reason: result.reason});
                 }
             }
-        }).catch(error => logger.error("position_updates.failed", {provider: target.provider, model: target.model, error: error instanceof Error ? error : String(error)}));
+        }).catch(error => logger.error("position_updates.failed", {provider: target.provider, model: target.model, error}));
     }
 
     private deleteQueueIfIdle(queueKey: string, queue: QueueEntry[]): void {

src/ai/rag-artifact-payload.ts

@@ -1,77 +0,0 @@
-import type {AiProvider} from "../model/ai-provider";
-
-export type RagArtifactSource = {
-    fileId: string;
-    fileName: string;
-    mimeType?: string;
-    sizeBytes?: number;
-    sha256?: string;
-    uploadedFileId?: string;
-    documentId?: string;
-};
-
-export type RagArtifactPayload = {
-    artifactKind: "rag";
-    provider: AiProvider;
-    createdAt: string;
-    sources: RagArtifactSource[];
-    providerState:
-        | {
-            provider: AiProvider.OPENAI;
-            vectorStoreIds: string[];
-            uploadedFileIds: string[];
-        }
-        | {
-            provider: AiProvider.MISTRAL;
-            libraryId?: string;
-            documentCount: number;
-        }
-        | {
-            provider: AiProvider.OLLAMA;
-            prepared: boolean;
-            embeddingModel?: string;
-            topK?: number;
-            chunkSize?: number;
-            chunkOverlap?: number;
-            maxContextChars?: number;
-            extractedDocuments: Array<{
-                documentIndex: number;
-                fileName: string;
-                textChars: number;
-            }>;
-            selectedChunks: Array<{
-                sourceId: string;
-                documentIndex: number;
-                documentName: string;
-                chunkIndex: number;
-                chunkCount: number;
-                textChars: number;
-                score?: number;
-            }>;
-            skippedDocuments: Array<{
-                documentIndex: number;
-                fileName: string;
-                reason: string;
-            }>;
-            query: string;
-            minScore: number;
-            maxArchiveFiles: number;
-            maxArchiveBytes: number;
-            maxArchiveDepth: number;
-        };
-};
-
-export function buildRagArtifactPayload(params: {
-    provider: AiProvider;
-    createdAt?: string;
-    sources: RagArtifactSource[];
-    providerState: RagArtifactPayload["providerState"];
-}): RagArtifactPayload {
-    return {
-        artifactKind: "rag",
-        provider: params.provider,
-        createdAt: params.createdAt ?? new Date().toISOString(),
-        sources: params.sources,
-        providerState: params.providerState,
-    };
-}

src/ai/rag-artifact-store.ts

@@ -1,100 +0,0 @@
-import type {StoredAttachment} from "../model/stored-attachment";
-import {AiProvider} from "../model/ai-provider";
-import type {AiDownloadedFile} from "./telegram-attachments";
-import type {PreparedDocumentRag} from "./document-rag-pipeline";
-import type {OllamaRagArtifactDetails} from "./ollama-rag";
-import {persistInternalJsonArtifactAttachment} from "./internal-artifact-store";
-import {buildRagArtifactPayload, type RagArtifactPayload} from "./rag-artifact-payload";
-
-function providerState(prepared: PreparedDocumentRag, details?: NonNullable<Parameters<typeof persistRagArtifactAttachment>[0]["details"]>): RagArtifactPayload["providerState"] {
-    switch (prepared.provider) {
-        case AiProvider.OPENAI:
-            return {
-                provider: AiProvider.OPENAI,
-                vectorStoreIds: prepared.vectorStoreIds,
-                uploadedFileIds: prepared.uploadedFileIds,
-            };
-        case AiProvider.MISTRAL:
-            return {
-                provider: AiProvider.MISTRAL,
-                libraryId: prepared.libraryId,
-                documentCount: prepared.documents.length,
-            };
-        case AiProvider.OLLAMA:
-            return {
-                provider: AiProvider.OLLAMA,
-                prepared: prepared.prepared,
-                embeddingModel: details?.embeddingModel,
-                topK: details?.topK,
-                chunkSize: details?.chunkSize,
-                chunkOverlap: details?.chunkOverlap,
-                maxContextChars: details?.maxContextChars,
-                extractedDocuments: details?.artifact?.extractedDocuments ?? [],
-                selectedChunks: details?.artifact?.selectedChunks ?? [],
-                skippedDocuments: details?.artifact?.skippedDocuments ?? [],
-                query: details?.artifact?.query ?? "",
-                minScore: details?.artifact?.providerState?.minScore ?? 0,
-                maxArchiveFiles: details?.artifact?.providerState?.maxArchiveFiles ?? 0,
-                maxArchiveBytes: details?.artifact?.providerState?.maxArchiveBytes ?? 0,
-                maxArchiveDepth: details?.artifact?.providerState?.maxArchiveDepth ?? 0,
-            };
-    }
-}
-
-export async function persistRagArtifactAttachment(params: {
-    provider: AiProvider;
-    prepared: PreparedDocumentRag | undefined;
-    downloads: AiDownloadedFile[];
-    chatId: number;
-    messageId: number;
-    details?: {
-        uploadedFileIds?: string[];
-        sourceDocuments?: Array<{
-            fileId: string;
-            fileName: string;
-            mimeType?: string;
-            sizeBytes?: number;
-            sha256?: string;
-            uploadedFileId?: string;
-            documentId?: string;
-        }>;
-        embeddingModel?: string;
-        topK?: number;
-        chunkSize?: number;
-        chunkOverlap?: number;
-        maxContextChars?: number;
-        artifact?: OllamaRagArtifactDetails;
-    };
-}): Promise<StoredAttachment | undefined> {
-    if (!params.prepared) return Promise.resolve(undefined);
-
-    const sources = params.downloads
-        .filter(download => download.kind === "document")
-        .map((download, index) => ({
-            fileId: download.fileId,
-            fileName: download.fileName,
-            mimeType: download.mimeType,
-            sizeBytes: download.sizeBytes ?? download.buffer.length,
-            sha256: download.sha256,
-            uploadedFileId: params.details?.uploadedFileIds?.[index],
-        }));
-
-    if (!sources.length) return Promise.resolve(undefined);
-
-    const payload = buildRagArtifactPayload({
-        provider: params.provider,
-        sources,
-        providerState: providerState(params.prepared, params.details),
-    });
-    return await persistInternalJsonArtifactAttachment({
-        artifactKind: "rag",
-        fileNamePrefix: "rag",
-        chatId: params.chatId,
-        messageId: params.messageId,
-        payload,
-        metadata: {
-            sourceFileNames: sources.map(source => source.fileName),
-            ...payload.providerState,
-        },
-    });
-}

src/ai/rag-retention-planner.ts

@@ -1,75 +0,0 @@
-import type {RagArtifactPayload} from "./rag-artifact-payload";
-
-export type ArtifactLike = {
-    id: string;
-    createdAt: string;
-    payload: string;
-};
-
-export type RagCleanupTarget = {
-    artifactId: string;
-    createdAt: string;
-    provider: RagArtifactPayload["providerState"]["provider"];
-    vectorStoreIds?: string[];
-    uploadedFileIds?: string[];
-    libraryId?: string;
-};
-
-export type RagCleanupPlan = {
-    cutoffAt: string;
-    targets: RagCleanupTarget[];
-};
-
-function parseRagArtifactPayload(payload: string): RagArtifactPayload | null {
-    try {
-        const parsed = JSON.parse(payload) as Partial<RagArtifactPayload>;
-        if (!parsed || parsed.artifactKind !== "rag" || !parsed.providerState) return null;
-        return parsed as RagArtifactPayload;
-    } catch {
-        return null;
-    }
-}
-
-export function buildStaleRagCleanupPlan(
-    artifacts: ArtifactLike[],
-    retentionDays = 14,
-    now = new Date(),
-): RagCleanupPlan {
-    const cutoffAt = new Date(now.getTime() - retentionDays * 24 * 60 * 60 * 1000).toISOString();
-    const targets: RagCleanupTarget[] = [];
-
-    for (const artifact of artifacts) {
-        if (artifact.createdAt > cutoffAt) continue;
-
-        const payload = parseRagArtifactPayload(artifact.payload);
-        if (!payload || payload.artifactKind !== "rag") continue;
-
-        switch (payload.providerState.provider) {
-            case "OPENAI":
-                if (payload.providerState.vectorStoreIds.length || payload.providerState.uploadedFileIds.length) {
-                    targets.push({
-                        artifactId: artifact.id,
-                        createdAt: artifact.createdAt,
-                        provider: payload.providerState.provider,
-                        vectorStoreIds: [...payload.providerState.vectorStoreIds],
-                        uploadedFileIds: [...payload.providerState.uploadedFileIds],
-                    });
-                }
-                break;
-            case "MISTRAL":
-                if (payload.providerState.libraryId) {
-                    targets.push({
-                        artifactId: artifact.id,
-                        createdAt: artifact.createdAt,
-                        provider: payload.providerState.provider,
-                        libraryId: payload.providerState.libraryId,
-                    });
-                }
-                break;
-            case "OLLAMA":
-                break;
-        }
-    }
-
-    return {cutoffAt, targets};
-}

src/ai/rag-retention.ts

@@ -1,117 +0,0 @@
-import {appLogger} from "../logging/logger.js";
-import {DatabaseManager} from "../db/database-manager.js";
-import {AiProvider} from "../model/ai-provider.js";
-import {createOpenAiClient, resolveAiRuntimeTarget} from "./ai-runtime-target.js";
-import {deleteMistralLibrary} from "./unified-ai-runner.shared.js";
-import {buildStaleRagCleanupPlan} from "./rag-retention-planner.js";
-
-const logger = appLogger.child("rag-retention");
-
-function unique(values: string[]): string[] {
-    return [...new Set(values.filter(Boolean))];
-}
-
-async function cleanupOpenAiRag(vectorStoreIds: string[], uploadedFileIds: string[]): Promise<void> {
-    const target = resolveAiRuntimeTarget(AiProvider.OPENAI, "documents");
-    const client = createOpenAiClient(target);
-
-    for (const vectorStoreId of unique(vectorStoreIds)) {
-        const startedAt = Date.now();
-        logger.info("openai.vector_store.cleanup.start", {vectorStoreId});
-        try {
-            await client.vectorStores.delete(vectorStoreId);
-            logger.success("openai.vector_store.cleanup.done", {vectorStoreId, duration: `${Date.now() - startedAt}ms`});
-        } catch (error) {
-            logger.warn("openai.vector_store.cleanup.failed", {
-                vectorStoreId,
-                duration: `${Date.now() - startedAt}ms`,
-                error: error instanceof Error ? error : String(error),
-            });
-        }
-    }
-
-    for (const fileId of unique(uploadedFileIds)) {
-        const startedAt = Date.now();
-        logger.info("openai.file.cleanup.start", {fileId});
-        try {
-            await client.files.delete(fileId);
-            logger.success("openai.file.cleanup.done", {fileId, duration: `${Date.now() - startedAt}ms`});
-        } catch (error) {
-            logger.warn("openai.file.cleanup.failed", {
-                fileId,
-                duration: `${Date.now() - startedAt}ms`,
-                error: error instanceof Error ? error : String(error),
-            });
-        }
-    }
-}
-
-async function cleanupMistralRag(libraryId: string): Promise<void> {
-    const target = resolveAiRuntimeTarget(AiProvider.MISTRAL, "documents");
-    const startedAt = Date.now();
-    logger.info("mistral.library.cleanup.start", {libraryId});
-    try {
-        await deleteMistralLibrary(libraryId, target);
-        logger.success("mistral.library.cleanup.done", {libraryId, duration: `${Date.now() - startedAt}ms`});
-    } catch (error) {
-        logger.warn("mistral.library.cleanup.failed", {
-            libraryId,
-            duration: `${Date.now() - startedAt}ms`,
-            error: error instanceof Error ? error : String(error),
-        });
-    }
-}
-
-export async function cleanupStaleRagProviderState(retentionDays = 14): Promise<{
-    scannedArtifacts: number;
-    cleanupTargets: number;
-    openaiTargets: number;
-    mistralTargets: number;
-}> {
-    const startedAt = Date.now();
-    const artifacts = await DatabaseManager.getAllArtifacts().catch(() => []);
-    const plan = buildStaleRagCleanupPlan(artifacts, retentionDays);
-
-    logger.info("cleanup.start", {
-        retentionDays,
-        scannedArtifacts: artifacts.length,
-        cleanupTargets: plan.targets.length,
-        cutoffAt: plan.cutoffAt,
-    });
-
-    let openaiTargets = 0;
-    let mistralTargets = 0;
-
-    for (const target of plan.targets) {
-        switch (target.provider) {
-            case "OPENAI":
-                openaiTargets += 1;
-                await cleanupOpenAiRag(target.vectorStoreIds ?? [], target.uploadedFileIds ?? []);
-                break;
-            case "MISTRAL":
-                mistralTargets += 1;
-                if (target.libraryId) {
-                    await cleanupMistralRag(target.libraryId);
-                }
-                break;
-            case "OLLAMA":
-                break;
-        }
-    }
-
-    logger.success("cleanup.done", {
-        retentionDays,
-        scannedArtifacts: artifacts.length,
-        cleanupTargets: plan.targets.length,
-        openaiTargets,
-        mistralTargets,
-        duration: `${Date.now() - startedAt}ms`,
-    });
-
-    return {
-        scannedArtifacts: artifacts.length,
-        cleanupTargets: plan.targets.length,
-        openaiTargets,
-        mistralTargets,
-    };
-}

src/ai/reply-chain-downloads.ts

@@ -1,39 +0,0 @@
-import type {AiDownloadedFile} from "./telegram-attachments.js";
-
-function downloadKey(download: AiDownloadedFile): string {
-    return [
-        download.kind,
-        download.fileId,
-        download.sha256 ?? "",
-        download.fileName,
-    ].join(":");
-}
-
-export function mergeReplyChainDownloads(
-    currentDownloads: readonly AiDownloadedFile[],
-    replyChainDownloads: readonly AiDownloadedFile[],
-): AiDownloadedFile[] {
-    const result: AiDownloadedFile[] = [];
-    const seen = new Set<string>();
-
-    for (const download of [...currentDownloads, ...replyChainDownloads]) {
-        const key = downloadKey(download);
-        if (seen.has(key)) continue;
-        seen.add(key);
-        result.push(download);
-    }
-
-    return result;
-}
-
-export function shouldPreferCurrentDownloads(text: string, currentDownloads: readonly AiDownloadedFile[]): boolean {
-    if (!currentDownloads.length) return false;
-
-    const normalized = text.trim().toLowerCase();
-    if (!normalized) return false;
-
-    return normalized.includes("this file")
-        || normalized.includes("this document")
-        || normalized.includes("этот файл")
-        || normalized.includes("этот документ");
-}

src/ai/response-model-output.ts

@@ -1,19 +0,0 @@
-import type {TelegramOutputAttachmentRecord, TelegramToolExecutionRecord} from "./telegram-stream-message.js";
-
-export type NormalizedModelOutput = {
-    text: string;
-    toolExecutions: TelegramToolExecutionRecord[];
-    outputAttachments: TelegramOutputAttachmentRecord[];
-};
-
-export function summarizeModelOutput(params: {
-    text: string;
-    toolExecutions: readonly TelegramToolExecutionRecord[];
-    outputAttachments: readonly TelegramOutputAttachmentRecord[];
-}): NormalizedModelOutput {
-    return {
-        text: params.text.trim(),
-        toolExecutions: [...params.toolExecutions],
-        outputAttachments: [...params.outputAttachments],
-    };
-}

src/ai/speech-to-text.ts

@@ -2,13 +2,19 @@ import fs, {openAsBlob} from "node:fs";
 import {AiProvider} from "../model/ai-provider";
 import {
     getAvailableAiProviderChoices,
+    getProviderChoiceLabel,
     normalizeAiProviderChoice,
     resolveEffectiveAiProviderForUser,
 } from "../common/user-ai-settings";
-import {providerDisplayName} from "./provider-aliases";
 import {AiDownloadedFile} from "./telegram-attachments";
 import {isOllamaSpeechToTextModel} from "./speech-to-text-models";
-import {createMistralClient, createOllamaClient, createOpenAiClient, resolveAiRuntimeTarget} from "./ai-runtime-target";
+import {
+    createGoogleGenAiClient,
+    createMistralClient,
+    createOllamaClient,
+    createOpenAiClient,
+    resolveAiRuntimeTarget
+} from "./ai-runtime-target";
 import {Environment} from "../common/environment";
 
 export type TranscribedSpeech = {
@@ -33,6 +39,10 @@ export type SpeechToTextResolveOptions = {
     allowFallback?: boolean;
 };
 
+function providerName(provider: AiProvider): string {
+    return getProviderChoiceLabel(provider);
+}
+
 export function isTranscribableAudioDownload(download: AiDownloadedFile): boolean {
     if (download.kind === "audio") return true;
     return download.kind === "video-note" && (download.mimeType?.startsWith("audio/") || download.path.toLowerCase().endsWith(".wav"));
@@ -43,6 +53,9 @@ export function isSpeechToTextConfigured(provider: AiProvider): boolean {
         case AiProvider.OPENAI:
             const openAiTarget = resolveAiRuntimeTarget(provider, "speechToText");
             return !!openAiTarget.apiKey && !!openAiTarget.model;
+        case AiProvider.GEMINI:
+            const geminiTarget = resolveAiRuntimeTarget(provider, "speechToText");
+            return !!geminiTarget.apiKey && !!geminiTarget.model;
         case AiProvider.MISTRAL:
             const mistralTarget = resolveAiRuntimeTarget(provider, "speechToText");
             return !!mistralTarget.apiKey && !!mistralTarget.model;
@@ -65,7 +78,7 @@ export async function resolveSpeechToTextProviderForUser(
 
     if (preferredProvider) {
         if (!allowedProviders.includes(preferredProvider)) {
-            throw new Error(Environment.getProviderNotAvailableForAccessText(providerDisplayName(preferredProvider)));
+            throw new Error(Environment.getProviderNotAvailableForAccessText(providerName(preferredProvider)));
         }
 
         if (isSpeechToTextConfigured(preferredProvider)) {
@@ -73,7 +86,7 @@ export async function resolveSpeechToTextProviderForUser(
         }
 
         if (!allowFallback) {
-            throw new Error(Environment.getProviderSpeechToTextUnsupportedText(providerDisplayName(preferredProvider)));
+            throw new Error(Environment.getProviderSpeechToTextUnsupportedText(providerName(preferredProvider)));
         }
     }
 
@@ -99,6 +112,8 @@ export async function transcribeSpeech(request: SpeechToTextRequest): Promise<Tr
     switch (request.provider) {
         case AiProvider.OPENAI:
             return transcribeOpenAiSpeech(request.audio, request.signal);
+        case AiProvider.GEMINI:
+            return transcribeGeminiSpeech(request.audio, request.signal);
         case AiProvider.MISTRAL:
             return transcribeMistralSpeech(request.audio, request.signal);
         case AiProvider.OLLAMA:
@@ -162,6 +177,37 @@ async function transcribeMistralSpeech(audio: AiDownloadedFile, signal?: AbortSi
     };
 }
 
+async function transcribeGeminiSpeech(audio: AiDownloadedFile, signal?: AbortSignal): Promise<TranscribedSpeech> {
+    const target = resolveAiRuntimeTarget(AiProvider.GEMINI, "speechToText");
+    const geminiAi = createGoogleGenAiClient(target);
+    const response = await geminiAi.models.generateContent({
+        model: target.model,
+        contents: [{
+            role: "user",
+            parts: [
+                {text: "Transcribe the attached audio verbatim. Reply only with the transcription text. Do not answer the speaker."},
+                {
+                    inlineData: {
+                        data: audio.buffer.toString("base64"),
+                        mimeType: audio.mimeType || "audio/wav",
+                    }
+                }
+            ]
+        }],
+        config: {
+            temperature: 0,
+            abortSignal: signal,
+        },
+    }) as unknown as GeminiSpeechResponse;
+
+    return {
+        provider: AiProvider.GEMINI,
+        model: target.model,
+        text: collectGeminiText(response),
+        fileName: audio.fileName,
+    };
+}
+
 async function transcribeOllamaSpeech(audio: AiDownloadedFile, signal?: AbortSignal): Promise<TranscribedSpeech> {
     if (signal?.aborted) throw new Error("Aborted");
 
@@ -193,3 +239,20 @@ async function transcribeOllamaSpeech(audio: AiDownloadedFile, signal?: AbortSig
         fileName: audio.fileName,
     };
 }
+
+type GeminiSpeechResponse = {
+    text?: string;
+    candidates?: Array<{content?: {parts?: Array<{text?: string}>}}> ;
+};
+
+function collectGeminiText(response: GeminiSpeechResponse): string {
+    if (typeof response.text === "string") return response.text;
+
+    const candidateText = (response.candidates ?? [])
+        .flatMap(candidate => candidate.content?.parts ?? [])
+        .map(part => part.text ?? "")
+        .join("");
+    if (candidateText.trim()) return candidateText;
+
+    return "";
+}

src/ai/telegram-attachments.ts

@@ -9,8 +9,6 @@ import {performFFmpeg} from "../util/ffmpeg";
 import ffmpeg from "fluent-ffmpeg";
 import {AsyncSemaphore, KeyedAsyncLock} from "../util/async-lock";
 import {appLogger} from "../logging/logger";
-import {createHash} from "node:crypto";
-import {PIPELINE_ATTACHMENT_LIMIT_BYTES} from "./user-request-pipeline/types";
 
 export type AiDownloadedFile = {
     kind: StoredAttachmentKind;
@@ -19,33 +17,6 @@ export type AiDownloadedFile = {
     mimeType?: string;
     buffer: Buffer;
     path: string;
-    sizeBytes?: number;
-    sha256?: string;
-};
-
-export type RejectedTelegramAttachment = {
-    kind: StoredAttachmentKind;
-    fileId: string;
-    fileUniqueId?: string;
-    fileName: string;
-    mimeType?: string;
-    sizeBytes: number;
-    limitBytes: number;
-    reason: "too_large";
-};
-
-export type TelegramAttachmentDescriptor = {
-    kind: StoredAttachmentKind;
-    fileId: string;
-    fileUniqueId?: string;
-    fileName: string;
-    mimeType?: string;
-    sizeBytes?: number;
-};
-
-export type MessageAttachmentCacheResult = {
-    attachments: StoredAttachment[];
-    rejected: RejectedTelegramAttachment[];
 };
 
 const cachePathLocks = new KeyedAsyncLock();
@@ -120,113 +91,7 @@ function cachePathFor(kind: StoredAttachmentKind, fileUniqueId: string | undefin
     return path.join(cacheDirFor(kind), `${base}${ext || ""}`);
 }
 
-function fileSha256(location: string): string | undefined {
-    if (!fs.existsSync(location)) return undefined;
-    return createHash("sha256").update(fs.readFileSync(location)).digest("hex");
-}
-
-function rejectIfTooLarge(
-    rejected: RejectedTelegramAttachment[],
-    kind: StoredAttachmentKind,
-    fileId: string,
-    fileName: string,
-    mimeType?: string,
-    sizeBytes?: number,
-    fileUniqueId?: string,
-): boolean {
-    if (!sizeBytes || sizeBytes <= PIPELINE_ATTACHMENT_LIMIT_BYTES) {
-        return false;
-    }
-
-    rejected.push({
-        kind,
-        fileId,
-        fileUniqueId,
-        fileName,
-        mimeType,
-        sizeBytes,
-        limitBytes: PIPELINE_ATTACHMENT_LIMIT_BYTES,
-        reason: "too_large",
-    });
-    logger.warn("message.cache.rejected.too_large", {kind, fileId, fileName, mimeType, sizeBytes});
-    return true;
-}
-
-export function collectTelegramAttachmentDescriptors(msg: Message): TelegramAttachmentDescriptor[] {
-    const attachments: TelegramAttachmentDescriptor[] = [];
-
-    if (msg.photo?.length) {
-        const size = msg.photo[msg.photo.length - 1]!;
-        attachments.push({
-            kind: "image",
-            fileId: size.file_id,
-            fileUniqueId: size.file_unique_id,
-            fileName: `${size.file_unique_id || size.file_id}.jpg`,
-            mimeType: "image/jpeg",
-            sizeBytes: size.file_size,
-        });
-    }
-
-    if (msg.document) {
-        const doc = msg.document;
-        attachments.push({
-            kind: doc.mime_type?.startsWith("image/")
-                ? "image"
-                : doc.mime_type?.startsWith("audio/")
-                    ? "audio"
-                    : "document",
-            fileId: doc.file_id,
-            fileUniqueId: doc.file_unique_id,
-            fileName: doc.file_name || `${doc.file_unique_id || doc.file_id}`,
-            mimeType: doc.mime_type,
-            sizeBytes: doc.file_size,
-        });
-    }
-
-    if (msg.voice) {
-        attachments.push({
-            kind: "audio",
-            fileId: msg.voice.file_id,
-            fileUniqueId: msg.voice.file_unique_id,
-            fileName: `${msg.voice.file_unique_id || msg.voice.file_id}.ogg`,
-            mimeType: msg.voice.mime_type || "audio/ogg",
-            sizeBytes: msg.voice.file_size,
-        });
-    }
-
-    if (msg.audio) {
-        attachments.push({
-            kind: "audio",
-            fileId: msg.audio.file_id,
-            fileUniqueId: msg.audio.file_unique_id,
-            fileName: msg.audio.file_name || `${msg.audio.file_unique_id || msg.audio.file_id}.mp3`,
-            mimeType: msg.audio.mime_type,
-            sizeBytes: msg.audio.file_size,
-        });
-    }
-
-    if (msg.video_note) {
-        attachments.push({
-            kind: "video-note",
-            fileId: msg.video_note.file_id,
-            fileUniqueId: msg.video_note.file_unique_id,
-            fileName: `${msg.video_note.file_unique_id || msg.video_note.file_id}.mp4`,
-            mimeType: "video/mp4",
-            sizeBytes: msg.video_note.file_size,
-        });
-    }
-
-    return attachments;
-}
-
-async function downloadToCache(
-    kind: StoredAttachmentKind,
-    fileId: string,
-    fileName: string,
-    mimeType?: string,
-    fileUniqueId?: string,
-    sizeBytes?: number,
-): Promise<StoredAttachment | null> {
+async function downloadToCache(kind: StoredAttachmentKind, fileId: string, fileName: string, mimeType?: string, fileUniqueId?: string): Promise<StoredAttachment | null> {
     const startedAt = Date.now();
     logger.debug("download.start", {kind, fileId, fileName, mimeType});
     const file = await bot.getFile({file_id: fileId});
@@ -252,17 +117,7 @@ async function downloadToCache(
         logger.debug("download.saved", {kind, location, bytes: buffer.length, duration: logger.duration(startedAt)});
     });
 
-    const resolvedSizeBytes = sizeBytes ?? (fs.existsSync(location) ? fs.statSync(location).size : undefined);
-    return {
-        kind,
-        fileId,
-        fileUniqueId,
-        fileName: finalFileName,
-        mimeType,
-        cachePath: location,
-        sizeBytes: resolvedSizeBytes,
-        sha256: fileSha256(location),
-    };
+    return {kind, fileId, fileUniqueId, fileName: finalFileName, mimeType, cachePath: location};
 }
 
 async function convertAudioToWav(input: string, output: string, noVideo = false): Promise<void> {
@@ -298,28 +153,23 @@ async function convertAudioToWav(input: string, output: string, noVideo = false)
                 if (fs.existsSync(tempOutput)) {
                     fs.rmSync(tempOutput, {force: true});
                 }
-                logger.error("audio.convert.failed", {input, output, error: e instanceof Error ? e : String(e)});
+                logger.error("audio.convert.failed", {input, output, error: e});
                 throw e;
             }
         });
     });
 }
 
-export async function cacheMessageAttachmentsWithRejections(msg: Message): Promise<MessageAttachmentCacheResult> {
+export async function cacheMessageAttachments(msg: Message): Promise<StoredAttachment[]> {
     const startedAt = Date.now();
     const result: StoredAttachment[] = [];
-    const rejected: RejectedTelegramAttachment[] = [];
     logger.debug("message.cache.start", {chatId: msg.chat?.id, messageId: msg.message_id});
 
     try {
         if (msg.photo?.length) {
             const size = msg.photo[msg.photo.length - 1]!;
-            const fileName = `${size.file_unique_id || size.file_id}.jpg`;
-            const mimeType = "image/jpeg";
-            if (!rejectIfTooLarge(rejected, "image", size.file_id, fileName, mimeType, size.file_size, size.file_unique_id)) {
-                const file = await downloadToCache("image", size.file_id, fileName, mimeType, size.file_unique_id, size.file_size);
-                if (file) result.push(file);
-            }
+            const file = await downloadToCache("image", size.file_id, `${size.file_unique_id || size.file_id}.jpg`, "image/jpeg", size.file_unique_id);
+            if (file) result.push(file);
         }
 
         if (msg.document) {
@@ -329,19 +179,12 @@ export async function cacheMessageAttachmentsWithRejections(msg: Message): Promi
                 : doc.mime_type?.startsWith("audio/")
                     ? "audio"
                     : "document";
-            const fileName = doc.file_name || `${doc.file_unique_id || doc.file_id}`;
-            if (!rejectIfTooLarge(rejected, kind, doc.file_id, fileName, doc.mime_type, doc.file_size, doc.file_unique_id)) {
-                const file = await downloadToCache(kind, doc.file_id, fileName, doc.mime_type, doc.file_unique_id, doc.file_size);
-                if (file) result.push(file);
-            }
+            const file = await downloadToCache(kind, doc.file_id, doc.file_name || `${doc.file_unique_id || doc.file_id}`, doc.mime_type, doc.file_unique_id);
+            if (file) result.push(file);
         }
 
         if (msg.voice) {
-            const fileName = `${msg.voice.file_unique_id || msg.voice.file_id}.ogg`;
-            const mimeType = msg.voice.mime_type || "audio/ogg";
-            const file = rejectIfTooLarge(rejected, "audio", msg.voice.file_id, fileName, mimeType, msg.voice.file_size, msg.voice.file_unique_id)
-                ? null
-                : await downloadToCache("audio", msg.voice.file_id, fileName, mimeType, msg.voice.file_unique_id, msg.voice.file_size);
+            const file = await downloadToCache("audio", msg.voice.file_id, `${msg.voice.file_unique_id || msg.voice.file_id}.ogg`, msg.voice.mime_type || "audio/ogg", msg.voice.file_unique_id);
             if (file) {
                 const output = cachePathFor("audio", msg.voice.file_unique_id, msg.voice.file_id, `${msg.voice.file_unique_id || msg.voice.file_id}.wav`);
                 try {
@@ -349,10 +192,8 @@ export async function cacheMessageAttachmentsWithRejections(msg: Message): Promi
                     file.cachePath = output;
                     file.fileName = file?.fileName?.replace(".ogg", ".wav");
                     file.mimeType = "audio/wav";
-                    file.sizeBytes = fs.existsSync(output) ? fs.statSync(output).size : file.sizeBytes;
-                    file.sha256 = fileSha256(output);
                 } catch (e) {
-                    logError(e instanceof Error ? e : String(e));
+                    logError(e);
                 }
             }
 
@@ -360,19 +201,12 @@ export async function cacheMessageAttachmentsWithRejections(msg: Message): Promi
         }
 
         if (msg.audio) {
-            const fileName = msg.audio.file_name || `${msg.audio.file_unique_id || msg.audio.file_id}.mp3`;
-            if (!rejectIfTooLarge(rejected, "audio", msg.audio.file_id, fileName, msg.audio.mime_type, msg.audio.file_size, msg.audio.file_unique_id)) {
-                const file = await downloadToCache("audio", msg.audio.file_id, fileName, msg.audio.mime_type, msg.audio.file_unique_id, msg.audio.file_size);
-                if (file) result.push(file);
-            }
+            const file = await downloadToCache("audio", msg.audio.file_id, msg.audio.file_name || `${msg.audio.file_unique_id || msg.audio.file_id}.mp3`, msg.audio.mime_type, msg.audio.file_unique_id);
+            if (file) result.push(file);
         }
 
         if (msg.video_note) {
-            const fileName = `${msg.video_note.file_unique_id || msg.video_note.file_id}.mp4`;
-            const mimeType = "video/mp4";
-            const file = rejectIfTooLarge(rejected, "video-note", msg.video_note.file_id, fileName, mimeType, msg.video_note.file_size, msg.video_note.file_unique_id)
-                ? null
-                : await downloadToCache("video-note", msg.video_note.file_id, fileName, mimeType, msg.video_note.file_unique_id, msg.video_note.file_size);
+            const file = await downloadToCache("video-note", msg.video_note.file_id, `${msg.video_note.file_unique_id || msg.video_note.file_id}.mp4`, "video/mp4", msg.video_note.file_unique_id);
             if (file) {
                 const output = cachePathFor("audio", msg.video_note.file_unique_id, msg.video_note.file_id, `${msg.video_note.file_unique_id || msg.video_note.file_id}.wav`);
                 try {
@@ -380,61 +214,33 @@ export async function cacheMessageAttachmentsWithRejections(msg: Message): Promi
                     file.cachePath = output;
                     file.fileName = file?.fileName?.replace(".mp4", ".wav");
                     file.mimeType = "audio/wav";
-                    file.sizeBytes = fs.existsSync(output) ? fs.statSync(output).size : file.sizeBytes;
-                    file.sha256 = fileSha256(output);
                 } catch (e) {
-                    logError(e instanceof Error ? e : String(e));
+                    logError(e);
                 }
             }
 
             if (file) result.push(file);
         }
     } catch (e) {
-        logError(e instanceof Error ? e : String(e));
+        logError(e);
     }
 
-    logger.debug("message.cache.done", {
-        chatId: msg.chat?.id,
-        messageId: msg.message_id,
-        attachments: result.length,
-        rejected: rejected.length,
-        duration: logger.duration(startedAt),
-    });
-    return {attachments: result, rejected};
-}
-
-export async function cacheMessageAttachments(msg: Message): Promise<StoredAttachment[]> {
-    const {attachments} = await cacheMessageAttachmentsWithRejections(msg);
-    return attachments;
+    logger.debug("message.cache.done", {chatId: msg.chat?.id, messageId: msg.message_id, attachments: result.length, duration: logger.duration(startedAt)});
+    return result;
 }
 
 export function attachmentsToDownloadedFiles(attachments: StoredAttachment[]): AiDownloadedFile[] {
     logger.trace("downloaded_files.build", {attachments: attachments.length});
     return attachments
         .filter(attachment => fs.existsSync(attachment.cachePath))
-        .flatMap(attachment => {
-            const sizeBytes = attachment.sizeBytes ?? fs.statSync(attachment.cachePath).size;
-            if (sizeBytes > PIPELINE_ATTACHMENT_LIMIT_BYTES) {
-                logger.warn("downloaded_files.skipped.too_large", {
-                    kind: attachment.kind,
-                    fileName: attachment.fileName,
-                    sizeBytes,
-                    limitBytes: PIPELINE_ATTACHMENT_LIMIT_BYTES,
-                });
-                return [];
-            }
-
-            return [{
-                kind: attachment.kind,
-                fileId: attachment.fileId,
-                fileName: attachment.fileName,
-                mimeType: attachment.mimeType,
-                buffer: fs.readFileSync(attachment.cachePath),
-                path: attachment.cachePath,
-                sizeBytes,
-                sha256: attachment.sha256,
-            }];
-        });
+        .map(attachment => ({
+            kind: attachment.kind,
+            fileId: attachment.fileId,
+            fileName: attachment.fileName,
+            mimeType: attachment.mimeType,
+            buffer: fs.readFileSync(attachment.cachePath),
+            path: attachment.cachePath,
+        }));
 }
 
 export function cleanupDownloads(files: AiDownloadedFile[]): void {

src/ai/telegram-stream-message.ts

@@ -5,22 +5,17 @@ import {Environment} from "../common/environment";
 import {MessageStore} from "../common/message-store";
 import {createQueuedFunction} from "../util/async-lock";
 import {enqueueTelegramApiCall} from "../util/telegram-api-queue";
-import {appLogger} from "../logging/logger";
 import fs from "node:fs";
-import path from "node:path";
 import {StoredAttachment, StoredAttachmentKind} from "../model/stored-attachment";
 import {StoredMessage} from "../model/stored-message";
 import {prepareTelegramMarkdownV2} from "../util/markdown-v2-renderer";
 import {AiProvider} from "../model/ai-provider";
-import {AI_IMAGE_OUTPUT_MODE_DOCUMENT, UserAiImageOutputMode} from "../common/user-ai-settings";
-import {PIPELINE_ATTACHMENT_LIMIT_BYTES} from "./user-request-pipeline";
-import {recordToolCall} from "../common/ai-observability.js";
 
 const TELEGRAM_LIMIT = 4096;
 const TELEGRAM_CAPTION_LIMIT = 1024;
+const TELEGRAM_FILE_LIMIT_BYTES = 50 * 1024 * 1024;
 const TELEGRAM_PHOTO_LIMIT_BYTES = 10 * 1024 * 1024;
 const EDIT_INTERVAL_MS = 4500;
-const logger = appLogger.child("telegram-stream-message");
 
 export type TelegramArtifactFile = {
     kind: "image" | "file";
@@ -30,23 +25,6 @@ export type TelegramArtifactFile = {
     sizeBytes: number;
 };
 
-export type TelegramToolExecutionRecord = {
-    toolName: string;
-    callId: string;
-    argumentsText: string;
-    resultChars: number;
-    startedAt: string;
-    finishedAt: string;
-};
-
-export type TelegramOutputAttachmentRecord = {
-    artifactKind: "generated_file" | "tts_audio";
-    fileName: string;
-    mimeType?: string;
-    sizeBytes?: number;
-    messageId?: number;
-};
-
 export class TelegramStreamMessage {
     private waitMessage: Message | null = null;
     private timer: NodeJS.Timeout | null = null;
@@ -56,11 +34,8 @@ export class TelegramStreamMessage {
     private mediaMode = false;
     private cancelled = false;
     private cancelledProvider = "";
-    private readonly sendImagesAsDocuments: boolean;
     private readonly startedAt = Date.now();
     private readonly enqueueEdit = createQueuedFunction();
-    private readonly toolExecutions: TelegramToolExecutionRecord[] = [];
-    private readonly outputAttachments: TelegramOutputAttachmentRecord[] = [];
 
     constructor(
         private readonly sourceMessage: Message,
@@ -70,9 +45,7 @@ export class TelegramStreamMessage {
         private readonly targetMessage?: Message,
         private readonly cancelProvider?: AiProvider,
         private readonly isGuest?: boolean,
-        imageOutputMode: UserAiImageOutputMode = "photo",
     ) {
-        this.sendImagesAsDocuments = imageOutputMode === AI_IMAGE_OUTPUT_MODE_DOCUMENT;
     }
 
     keyboard(): InlineKeyboardMarkup {
@@ -101,8 +74,18 @@ export class TelegramStreamMessage {
         };
     }
 
-    private isMessageNotModified(message: string): boolean {
-        return message.includes("message is not modified");
+    private isMessageNotModified(error: unknown): boolean {
+        const textToLookUp = "message is not modified";
+
+        if (error && error instanceof Error) {
+            return String(error.message).includes(textToLookUp);
+        }
+
+        if (error && error instanceof String) {
+            return error.includes(textToLookUp);
+        }
+
+        return false;
     }
 
     private async updateKeyboard(replyMarkup: InlineKeyboardMarkup): Promise<void> {
@@ -122,8 +105,7 @@ export class TelegramStreamMessage {
                 }
             );
         } catch (e) {
-            const message = e instanceof Error ? e.message : String(e);
-            if (!this.isMessageNotModified(message)) logError(e instanceof Error ? e : message);
+            if (!this.isMessageNotModified(e)) logError(e);
         }
     }
 
@@ -184,8 +166,7 @@ export class TelegramStreamMessage {
                 this.startFlushTimer();
                 return this.waitMessage;
             } catch (e) {
-                const message = e instanceof Error ? e.message : String(e);
-                if (this.isMessageNotModified(message)) {
+                if (this.isMessageNotModified(e)) {
                     this.lastSent = rawText;
                     await this.updateKeyboard(this.keyboard());
                     await this.store();
@@ -193,7 +174,7 @@ export class TelegramStreamMessage {
                     return this.waitMessage;
                 }
 
-                logError(e instanceof Error ? e : message);
+                logError(e);
                 this.waitMessage = null;
                 this.mediaMode = false;
             }
@@ -239,44 +220,6 @@ export class TelegramStreamMessage {
         return this.text;
     }
 
-    recordToolExecution(record: TelegramToolExecutionRecord): void {
-        this.toolExecutions.push(record);
-        recordToolCall();
-        logger.debug("tool.execution.recorded", {
-            requestId: this.cancelRequestId,
-            toolName: record.toolName,
-            callId: record.callId,
-            resultChars: record.resultChars,
-        });
-    }
-
-    getToolExecutions(): TelegramToolExecutionRecord[] {
-        return [...this.toolExecutions];
-    }
-
-    recordOutputAttachment(record: TelegramOutputAttachmentRecord): void {
-        this.outputAttachments.push(record);
-        logger.debug("output_attachment.recorded", {
-            requestId: this.cancelRequestId,
-            artifactKind: record.artifactKind,
-            fileName: record.fileName,
-            sizeBytes: record.sizeBytes,
-            messageId: record.messageId,
-        });
-    }
-
-    getOutputAttachments(): TelegramOutputAttachmentRecord[] {
-        return [...this.outputAttachments];
-    }
-
-    sourceChatId(): number {
-        return this.sourceMessage.chat.id;
-    }
-
-    sourceMessageId(): number {
-        return this.sourceMessage.message_id;
-    }
-
     async flush(replyMarkup: InlineKeyboardMarkup | null = this.keyboard(), end?: boolean): Promise<void> {
         return this.enqueueEdit(() => this.flushUnsafe(replyMarkup, end));
     }
@@ -349,14 +292,13 @@ export class TelegramStreamMessage {
             }
             if (shouldRemoveKeyboard) await this.removeKeyboard();
             this.lastSent = next;
-        } catch (e) {
-            const message = e instanceof Error ? e.message : String(e);
-            if (shouldRemoveKeyboard && this.isMessageNotModified(message)) {
+        } catch (e: unknown) {
+            if (shouldRemoveKeyboard && this.isMessageNotModified(e)) {
                 await this.removeKeyboard();
                 this.lastSent = next;
                 return;
             }
-            if (!this.isMessageNotModified(message)) logError(e instanceof Error ? e : message);
+            if (!this.isMessageNotModified(e)) logError(e);
         }
     }
 
@@ -371,68 +313,51 @@ export class TelegramStreamMessage {
         await this.store();
     }
 
-    async showImage(image: Buffer, attachment?: StoredAttachment): Promise<void> {
-        return this.enqueueEdit(() => this.showImageUnsafe(image, attachment));
+    async showImage(image: Buffer): Promise<void> {
+        return this.enqueueEdit(() => this.showImageUnsafe(image));
     }
 
     async sendArtifact(file: TelegramArtifactFile): Promise<Message | null> {
         return this.enqueueEdit(() => this.sendArtifactUnsafe(file));
     }
 
-    private async showImageUnsafe(image: Buffer, attachment?: StoredAttachment): Promise<void> {
+    private async showImageUnsafe(image: Buffer): Promise<void> {
         if (this.cancelled) return;
         const next = this.visibleCaption();
-        const useDocument = this.sendImagesAsDocuments;
 
         if (!this.waitMessage) {
             if (this.stream) return;
 
-            const upload = useDocument ? this.createImageUpload(image, attachment) : null;
-            try {
-                this.waitMessage = useDocument
-                    ? await this.sendImageAsDocument(upload!, next)
-                    : await enqueueTelegramApiCall(
-                        () => bot.sendPhoto({
-                            chat_id: this.sourceMessage.chat.id,
-                            photo: image,
-                            caption: prepareTelegramMarkdownV2(next, {mode: "final"}),
-                            parse_mode: "MarkdownV2",
-                            reply_parameters: {message_id: this.sourceMessage.message_id},
-                        }),
-                        {
-                            method: "sendPhoto",
-                            chatId: this.sourceMessage.chat.id,
-                            chatType: this.sourceMessage.chat.type,
-                        }
-                    );
-            } finally {
-                if (upload) this.destroyUpload(upload);
-            }
+            this.waitMessage = await enqueueTelegramApiCall(
+                () => bot.sendPhoto({
+                    chat_id: this.sourceMessage.chat.id,
+                    photo: image,
+                    caption: prepareTelegramMarkdownV2(next, {mode: "final"}),
+                    parse_mode: "MarkdownV2",
+                    reply_parameters: {message_id: this.sourceMessage.message_id},
+                }),
+                {
+                    method: "sendPhoto",
+                    chatId: this.sourceMessage.chat.id,
+                    chatType: this.sourceMessage.chat.type,
+                }
+            );
             this.mediaMode = true;
             this.lastSent = next;
-            await this.storeMediaMessage(this.waitMessage, attachment);
             return;
         }
 
-        const upload = useDocument ? this.createImageUpload(image, attachment) : null;
         try {
             const result = await enqueueTelegramApiCall(
                 () => bot.editMessageMedia({
                     chat_id: this.waitMessage!.chat.id,
                     message_id: this.waitMessage!.message_id,
-                    media: useDocument
-                        ? {
-                            type: "document",
-                            media: upload!,
-                            caption: prepareTelegramMarkdownV2(next, {mode: "final"}),
-                            parse_mode: "MarkdownV2",
-                        }
-                        : {
-                            type: "photo",
-                            media: image,
-                            caption: prepareTelegramMarkdownV2(next, {mode: "final"}),
-                            parse_mode: "MarkdownV2",
-                        },
+                    media: {
+                        type: "photo",
+                        media: image,
+                        caption: prepareTelegramMarkdownV2(next, {mode: "final"}),
+                        parse_mode: "MarkdownV2",
+                    },
                     reply_markup: this.keyboard(),
                 }),
                 {
@@ -444,50 +369,19 @@ export class TelegramStreamMessage {
             if (result && result !== true) this.waitMessage = result;
             this.mediaMode = true;
             this.lastSent = next;
-            await this.storeMediaMessage(this.waitMessage, attachment);
-        } catch (e) {
+        } catch (e: unknown) {
             const message = e instanceof Error ? e.message : String(e);
-            if (useDocument) {
-                try {
-                    this.waitMessage = await this.sendImageAsDocument(upload!, next);
-                    this.mediaMode = true;
-                    this.lastSent = next;
-                    await this.storeMediaMessage(this.waitMessage, attachment);
-                    return;
-                } catch (fallbackError) {
-                    logError(fallbackError instanceof Error ? fallbackError : String(fallbackError));
-                }
-            }
-
-            if (!message.includes("message is not modified")) logError(e instanceof Error ? e : message);
-        } finally {
-            if (upload) this.destroyUpload(upload);
+            if (!message.includes("message is not modified")) logError(e);
         }
     }
 
-    private async storeMediaMessage(sent: Message | null, attachment?: StoredAttachment): Promise<void> {
-        if (!sent || !attachment) return;
-
-        const stored: StoredMessage = {
-            chatId: sent.chat.id,
-            id: sent.message_id,
-            replyToMessageId: sent.reply_to_message?.message_id ?? this.sourceMessage.message_id,
-            fromId: sent.from?.id ?? 0,
-            text: sent.caption ?? this.visibleText(),
-            date: sent.date ?? Math.floor(Date.now() / 1000),
-            attachments: [attachment],
-        };
-
-        await MessageStore.put(stored);
-    }
-
     private async sendArtifactUnsafe(file: TelegramArtifactFile): Promise<Message | null> {
         if (this.cancelled) return null;
 
-        if (file.sizeBytes > PIPELINE_ATTACHMENT_LIMIT_BYTES) {
+        if (file.sizeBytes > TELEGRAM_FILE_LIMIT_BYTES) {
             throw new Error(Environment.getTelegramFileTooLargeText(
                 file.fileName,
-                PIPELINE_ATTACHMENT_LIMIT_BYTES / 1024 / 1024,
+                TELEGRAM_FILE_LIMIT_BYTES / 1024 / 1024,
             ));
         }
 
@@ -530,7 +424,7 @@ export class TelegramStreamMessage {
                     }
                 );
             } catch (e) {
-                logError(e instanceof Error ? e : String(e));
+                logError(e);
                 sent = await this.sendArtifactAsDocument(file, caption);
             }
         } else {
@@ -538,37 +432,15 @@ export class TelegramStreamMessage {
         }
 
         await this.storeArtifactMessage(sent, file);
-        this.recordOutputAttachment({
-            artifactKind: "generated_file",
-            fileName: file.fileName,
-            mimeType: file.mimeType,
-            sizeBytes: file.sizeBytes,
-            messageId: sent.message_id,
-        });
         return sent;
     }
 
     private isPhotoArtifact(file: TelegramArtifactFile): boolean {
-        if (this.sendImagesAsDocuments) return false;
         return file.kind === "image"
             && file.sizeBytes <= TELEGRAM_PHOTO_LIMIT_BYTES
             && ["image/jpeg", "image/png", "image/webp"].includes((file.mimeType || "").toLowerCase());
     }
 
-    private createImageUpload(image: Buffer, attachment?: StoredAttachment): FileOptions {
-        if (attachment?.cachePath && fs.existsSync(attachment.cachePath)) {
-            return new FileOptions(fs.createReadStream(attachment.cachePath), {
-                filename: attachment.fileName || path.basename(attachment.cachePath),
-                contentType: attachment.mimeType || "application/octet-stream",
-            });
-        }
-
-        return new FileOptions(image, {
-            filename: attachment?.fileName ?? `image_${Date.now()}.png`,
-            contentType: attachment?.mimeType || "image/png",
-        });
-    }
-
     private createArtifactUpload(file: TelegramArtifactFile): FileOptions {
         return new FileOptions(fs.createReadStream(file.path), {
             filename: file.fileName,
@@ -582,23 +454,6 @@ export class TelegramStreamMessage {
         }
     }
 
-    private async sendImageAsDocument(upload: FileOptions, caption: string): Promise<Message> {
-        return enqueueTelegramApiCall(
-            () => bot.sendDocument({
-                chat_id: this.sourceMessage.chat.id,
-                document: upload,
-                caption: prepareTelegramMarkdownV2(caption, {mode: "final"}),
-                parse_mode: "MarkdownV2",
-                reply_parameters: {message_id: this.sourceMessage.message_id},
-            }),
-            {
-                method: "sendDocument",
-                chatId: this.sourceMessage.chat.id,
-                chatType: this.sourceMessage.chat.type,
-            }
-        );
-    }
-
     private async sendArtifactAsDocument(file: TelegramArtifactFile, caption: string): Promise<Message> {
         return enqueueTelegramApiCall(
             async () => {
@@ -632,9 +487,6 @@ export class TelegramStreamMessage {
             fileName: file.fileName,
             mimeType: file.mimeType,
             cachePath: file.path,
-            sizeBytes: file.sizeBytes,
-            scope: "bot_output",
-            artifactKind: "generated_file",
         };
 
         const stored: StoredMessage = {
@@ -650,44 +502,6 @@ export class TelegramStreamMessage {
         await MessageStore.put(stored);
     }
 
-    async storeInternalAttachment(attachment: StoredAttachment): Promise<void> {
-        if (!this.waitMessage) return;
-
-        const stored = await MessageStore.get(this.waitMessage.chat.id, this.waitMessage.message_id);
-        await MessageStore.put({
-            chatId: this.waitMessage.chat.id,
-            id: this.waitMessage.message_id,
-            replyToMessageId: this.waitMessage.reply_to_message?.message_id ?? this.sourceMessage.message_id,
-            fromId: this.waitMessage.from?.id ?? 0,
-            text: this.visibleText(),
-            date: this.waitMessage.date ?? Math.floor(Date.now() / 1000),
-            attachments: [
-                ...(stored?.attachments ?? []),
-                attachment,
-            ],
-            pipelineAudit: stored?.pipelineAudit,
-        });
-    }
-
-    async storePipelineAudit(events: StoredMessage["pipelineAudit"]): Promise<void> {
-        if (!this.waitMessage || !events?.length) return;
-
-        const stored = await MessageStore.get(this.waitMessage.chat.id, this.waitMessage.message_id);
-        await MessageStore.put({
-            chatId: this.waitMessage.chat.id,
-            id: this.waitMessage.message_id,
-            replyToMessageId: this.waitMessage.reply_to_message?.message_id ?? this.sourceMessage.message_id,
-            fromId: this.waitMessage.from?.id ?? 0,
-            text: this.visibleText(),
-            date: this.waitMessage.date ?? Math.floor(Date.now() / 1000),
-            attachments: stored?.attachments,
-            pipelineAudit: [
-                ...(stored?.pipelineAudit ?? []),
-                ...events,
-            ],
-        });
-    }
-
     async finish(removeKeyboard = true): Promise<void> {
         if (this.timer) clearInterval(this.timer);
         this.timer = null;
@@ -709,7 +523,7 @@ export class TelegramStreamMessage {
         await this.store();
     }
 
-    async fail(error: Error | string | object | null | undefined): Promise<void> {
+    async fail(error: unknown): Promise<void> {
         if (this.timer) clearInterval(this.timer);
         this.timer = null;
         this.status = "";
@@ -722,7 +536,7 @@ export class TelegramStreamMessage {
         try {
             await MessageStore.put({...this.waitMessage, text: this.visibleText()} as Message);
         } catch (e) {
-            logError(e instanceof Error ? e : String(e));
+            logError(e);
         }
     }
 }

src/ai/text-to-speech.ts

@@ -7,20 +7,20 @@ import {Environment} from "../common/environment";
 import {bot} from "../index";
 import {
     getAvailableAiProviderChoices,
+    getProviderChoiceLabel,
     normalizeAiProviderChoice,
     resolveEffectiveAiProviderForUser,
 } from "../common/user-ai-settings";
-import {providerDisplayName} from "./provider-aliases";
 import {enqueueTelegramApiCall} from "../util/telegram-api-queue";
 import {MessageStore} from "../common/message-store";
 import {StoredAttachment} from "../model/stored-attachment";
 import {StoredMessage} from "../model/stored-message";
 import {logError} from "../util/utils";
 import {SpeechRequest} from "@mistralai/mistralai/models/components";
-import {createMistralClient, createOpenAiClient, resolveAiRuntimeTarget} from "./ai-runtime-target";
-import {PIPELINE_ATTACHMENT_LIMIT_BYTES} from "./user-request-pipeline";
+import {createGoogleGenAiClient, createMistralClient, createOpenAiClient, resolveAiRuntimeTarget} from "./ai-runtime-target";
 
 const MAX_TTS_TEXT_CHARS = 4096;
+const TELEGRAM_FILE_LIMIT_BYTES = 50 * 1024 * 1024;
 
 export type TextToSpeechFormat = "mp3" | "wav" | "flac" | "opus" | "aac" | "pcm";
 
@@ -54,6 +54,10 @@ function ttsCacheDir(): string {
     return path.join(Environment.DATA_PATH, "cache", "audio");
 }
 
+function providerName(provider: AiProvider): string {
+    return getProviderChoiceLabel(provider);
+}
+
 function assertText(text: string): string {
     const normalized = text.trim();
     if (!normalized) {
@@ -72,6 +76,9 @@ export function isTextToSpeechConfigured(provider: AiProvider): boolean {
         case AiProvider.OPENAI:
             const openAiTarget = resolveAiRuntimeTarget(provider, "textToSpeech");
             return !!openAiTarget.apiKey && !!openAiTarget.model;
+        case AiProvider.GEMINI:
+            const geminiTarget = resolveAiRuntimeTarget(provider, "textToSpeech");
+            return !!geminiTarget.apiKey && !!geminiTarget.model;
         case AiProvider.MISTRAL:
             const mistralTarget = resolveAiRuntimeTarget(provider, "textToSpeech");
             return !!mistralTarget.apiKey && !!mistralTarget.model;
@@ -91,11 +98,11 @@ export async function resolveTextToSpeechProviderForUser(
 
     if (explicitProvider) {
         if (!allowedProviders.includes(explicitProvider)) {
-            throw new Error(Environment.getProviderNotAvailableForAccessText(providerDisplayName(explicitProvider)));
+            throw new Error(Environment.getProviderNotAvailableForAccessText(providerName(explicitProvider)));
         }
 
         if (!isTextToSpeechConfigured(explicitProvider)) {
-            throw new Error(Environment.getProviderTextToSpeechUnsupportedText(providerDisplayName(explicitProvider)));
+            throw new Error(Environment.getProviderTextToSpeechUnsupportedText(providerName(explicitProvider)));
         }
 
         return {provider: explicitProvider, fallback: false};
@@ -120,6 +127,8 @@ export async function synthesizeSpeech(request: TextToSpeechRequest): Promise<Sy
     switch (request.provider) {
         case AiProvider.OPENAI:
             return synthesizeOpenAiSpeech(text, request.voice);
+        case AiProvider.GEMINI:
+            return synthesizeGeminiSpeech(text, request.voice);
         case AiProvider.MISTRAL:
             return synthesizeMistralSpeech(text, request.voice);
         case AiProvider.OLLAMA:
@@ -162,7 +171,7 @@ async function synthesizeMistralSpeech(text: string, voice?: string): Promise<Sy
     if (target.model) request.model = target.model;
     if (voice || Environment.MISTRAL_TTS_VOICE_ID) request.voiceId = voice || Environment.MISTRAL_TTS_VOICE_ID;
 
-    const response = await mistralAi.audio.speech.complete(request) as {audioData?: string; audio_data?: string};
+    const response = await mistralAi.audio.speech.complete(request) as unknown as {audioData?: string; audio_data?: string};
     const audioData = response?.audioData ?? response?.audio_data;
     if (typeof audioData !== "string" || !audioData.trim()) {
         throw new Error(Environment.mistralTtsNoAudioDataText);
@@ -180,6 +189,130 @@ async function synthesizeMistralSpeech(text: string, voice?: string): Promise<Sy
     });
 }
 
+async function synthesizeGeminiSpeech(text: string, voice?: string): Promise<SynthesizedSpeech> {
+    const target = resolveAiRuntimeTarget(AiProvider.GEMINI, "textToSpeech");
+    const geminiAi = createGoogleGenAiClient(target);
+    const response = await geminiAi.models.generateContent({
+        model: target.model,
+        contents: text,
+        config: {
+            responseModalities: ["AUDIO"],
+            speechConfig: {
+                voiceConfig: {
+                    prebuiltVoiceConfig: {
+                        voiceName: voice || Environment.GEMINI_TTS_VOICE,
+                    },
+                },
+            },
+        },
+    });
+
+    const audioPart = findGeminiAudioPart(response);
+    if (!audioPart) {
+        throw new Error(Environment.geminiTextToSpeechUnsupportedText);
+    }
+
+    const decoded = decodeGeminiAudio(audioPart.data, audioPart.mimeType);
+
+    return writeSpeechFile({
+        provider: AiProvider.GEMINI,
+        model: target.model,
+        voice: voice || Environment.GEMINI_TTS_VOICE,
+        buffer: decoded.buffer,
+        format: decoded.format,
+        mimeType: decoded.mimeType,
+    });
+}
+
+function findGeminiAudioPart(value: unknown): { data: string; mimeType?: string } | null {
+    if (!value || typeof value !== "object") return null;
+    const record = value as Record<string, unknown>;
+
+    const inlineData = record.inlineData ?? record.inline_data;
+    if (inlineData && typeof inlineData === "object") {
+        const inlineRecord = inlineData as Record<string, unknown>;
+        const data = inlineRecord.data;
+        const mimeType = inlineRecord.mimeType ?? inlineRecord.mime_type;
+
+        if (typeof data === "string" && (!mimeType || String(mimeType).startsWith("audio/"))) {
+            return {data, mimeType: typeof mimeType === "string" ? mimeType : undefined};
+        }
+    }
+
+    for (const child of Object.values(record)) {
+        if (Array.isArray(child)) {
+            for (const item of child) {
+                const found = findGeminiAudioPart(item);
+                if (found) return found;
+            }
+        } else if (child && typeof child === "object") {
+            const found = findGeminiAudioPart(child);
+            if (found) return found;
+        }
+    }
+
+    return null;
+}
+
+function decodeGeminiAudio(data: string, mimeType = "audio/wav"): {
+    buffer: Buffer;
+    format: TextToSpeechFormat;
+    mimeType: string;
+} {
+    const normalizedMime = mimeType.toLowerCase();
+    const raw = Buffer.from(data, "base64");
+
+    if (normalizedMime.includes("mpeg") || normalizedMime.includes("mp3")) {
+        return {buffer: raw, format: "mp3", mimeType: "audio/mpeg"};
+    }
+
+    if (normalizedMime.includes("wav") || raw.subarray(0, 4).toString("ascii") === "RIFF") {
+        return {buffer: raw, format: "wav", mimeType: "audio/wav"};
+    }
+
+    if (normalizedMime.includes("flac")) {
+        return {buffer: raw, format: "flac", mimeType: "audio/flac"};
+    }
+
+    if (normalizedMime.includes("opus")) {
+        return {buffer: raw, format: "opus", mimeType: "audio/opus"};
+    }
+
+    if (normalizedMime.includes("aac")) {
+        return {buffer: raw, format: "aac", mimeType: "audio/aac"};
+    }
+
+    const sampleRate = Number(/rate=(\d+)/i.exec(mimeType)?.[1]) || 24_000;
+    return {
+        buffer: wrapPcm16InWav(raw, sampleRate, 1),
+        format: "wav",
+        mimeType: "audio/wav",
+    };
+}
+
+function wrapPcm16InWav(pcm: Buffer, sampleRate: number, channels: number): Buffer {
+    const bitsPerSample = 16;
+    const byteRate = sampleRate * channels * bitsPerSample / 8;
+    const blockAlign = channels * bitsPerSample / 8;
+    const header = Buffer.alloc(44);
+
+    header.write("RIFF", 0);
+    header.writeUInt32LE(36 + pcm.length, 4);
+    header.write("WAVE", 8);
+    header.write("fmt ", 12);
+    header.writeUInt32LE(16, 16);
+    header.writeUInt16LE(1, 20);
+    header.writeUInt16LE(channels, 22);
+    header.writeUInt32LE(sampleRate, 24);
+    header.writeUInt32LE(byteRate, 28);
+    header.writeUInt16LE(blockAlign, 32);
+    header.writeUInt16LE(bitsPerSample, 34);
+    header.write("data", 36);
+    header.writeUInt32LE(pcm.length, 40);
+
+    return Buffer.concat([header, pcm]);
+}
+
 function writeSpeechFile(params: SpeechFileParams): SynthesizedSpeech {
     fs.mkdirSync(ttsCacheDir(), {recursive: true});
 
@@ -213,11 +346,11 @@ function destroyUpload(upload: FileOptions): void {
 }
 
 export async function sendSynthesizedSpeech(sourceMessage: Message, speech: SynthesizedSpeech): Promise<Message> {
-    if (speech.sizeBytes > PIPELINE_ATTACHMENT_LIMIT_BYTES) {
+    if (speech.sizeBytes > TELEGRAM_FILE_LIMIT_BYTES) {
         throw new Error(Environment.speechFileTooLargeText);
     }
 
-    const caption = Environment.getTextToSpeechCaption(providerDisplayName(speech.provider), speech.model, speech.voice);
+    const caption = Environment.getTextToSpeechCaption(providerName(speech.provider), speech.model, speech.voice);
 
     await enqueueTelegramApiCall(
         () => bot.sendChatAction({
@@ -246,10 +379,10 @@ export async function sendSynthesizedSpeech(sourceMessage: Message, speech: Synt
                 },
                 {method: "sendVoice", chatId: sourceMessage.chat.id, chatType: sourceMessage.chat.type}
             );
-    } catch (e) {
-        logError(e instanceof Error ? e : String(e));
-        sent = await sendSpeechDocument(sourceMessage, speech, caption);
-    }
+        } catch (e) {
+            logError(e);
+            sent = await sendSpeechDocument(sourceMessage, speech, caption);
+        }
     } else {
         sent = await sendSpeechDocument(sourceMessage, speech, caption);
     }
@@ -258,16 +391,6 @@ export async function sendSynthesizedSpeech(sourceMessage: Message, speech: Synt
     return sent;
 }
 
-export function speechToOutputAttachmentRecord(speech: SynthesizedSpeech, messageId?: number) {
-    return {
-        artifactKind: "tts_audio" as const,
-        fileName: speech.fileName,
-        mimeType: speech.mimeType,
-        sizeBytes: speech.sizeBytes,
-        messageId,
-    };
-}
-
 async function sendSpeechDocument(sourceMessage: Message, speech: SynthesizedSpeech, caption: string): Promise<Message> {
     return enqueueTelegramApiCall(
         async () => {
@@ -296,15 +419,6 @@ async function storeSpeechMessage(sent: Message, sourceMessage: Message, speech:
         fileName: speech.fileName,
         mimeType: speech.mimeType,
         cachePath: speech.path,
-        sizeBytes: speech.sizeBytes,
-        scope: "bot_output",
-        artifactKind: "tts_audio",
-        metadata: {
-            provider: speech.provider,
-            model: speech.model,
-            voice: speech.voice,
-            format: speech.format,
-        },
     };
 
     const stored: StoredMessage = {

src/ai/tool-batch-runner.ts

@@ -1,28 +0,0 @@
-import type {AiProviderAdapter} from "./provider-adapters.js";
-import {executeToolBatch, type ToolCallData, type ToolExecutionMemory} from "./unified-ai-runner.shared.js";
-import type {TelegramStreamMessage} from "./telegram-stream-message.js";
-import type {ToolRuntimeContext} from "./tools/runtime.js";
-
-export async function executeToolBatchWithAdapter(params: {
-    userId: number | undefined | null;
-    toolCalls: ToolCallData[];
-    streamMessage: TelegramStreamMessage;
-    toolContext: ToolRuntimeContext;
-    toolMemory: ToolExecutionMemory;
-    adapter: AiProviderAdapter;
-    appendTargets?: unknown[][];
-}): Promise<string[]> {
-    const results = await executeToolBatch(
-        params.userId,
-        params.toolCalls,
-        params.streamMessage,
-        params.toolContext,
-        params.toolMemory,
-    );
-
-    for (const target of params.appendTargets ?? []) {
-        params.adapter.appendToolResults(target, params.toolCalls, results);
-    }
-
-    return results;
-}

src/ai/tool-loop-artifact-store.ts

@@ -1,39 +0,0 @@
-import type {StoredAttachment} from "../model/stored-attachment";
-import type {TelegramOutputAttachmentRecord, TelegramToolExecutionRecord} from "./telegram-stream-message.js";
-import {persistInternalJsonArtifactAttachment} from "./internal-artifact-store";
-
-export async function persistToolLoopSummaryArtifactAttachment(params: {
-    chatId: number;
-    messageId: number;
-    text: string;
-    executions: readonly TelegramToolExecutionRecord[];
-    outputAttachments: readonly TelegramOutputAttachmentRecord[];
-}): Promise<StoredAttachment | undefined> {
-    if (!params.executions.length) return undefined;
-
-    return await persistInternalJsonArtifactAttachment({
-        artifactKind: "tool_result",
-        fileNamePrefix: "tool-loop-summary",
-        chatId: params.chatId,
-        messageId: params.messageId,
-        payload: {
-            stage: "tool_loop",
-            text: params.text.trim(),
-            executions: params.executions.map(execution => ({
-                toolName: execution.toolName,
-                callId: execution.callId,
-                argumentsText: execution.argumentsText,
-                resultChars: execution.resultChars,
-                startedAt: execution.startedAt,
-                finishedAt: execution.finishedAt,
-            })),
-            outputAttachments: params.outputAttachments,
-        },
-        metadata: {
-            stage: "tool_loop",
-            toolExecutions: params.executions.length,
-            outputAttachments: params.outputAttachments.length,
-            textChars: params.text.trim().length,
-        },
-    });
-}

src/ai/tool-loop-control.ts

@@ -1,38 +0,0 @@
-import type {ToolCallData} from "./unified-ai-runner.shared.js";
-
-export type ToolLoopStopReason = "no_tool_calls" | "max_rounds_reached";
-
-export type ToolLoopContinuation = {
-    continue: boolean;
-    reason?: ToolLoopStopReason;
-    remainingRounds: number;
-};
-
-export function decideToolLoopContinuation(params: {
-    round: number;
-    maxRounds: number;
-    toolCalls: readonly ToolCallData[];
-}): ToolLoopContinuation {
-    const remainingRounds = Math.max(params.maxRounds - params.round - 1, 0);
-
-    if (!params.toolCalls.length) {
-        return {
-            continue: false,
-            reason: "no_tool_calls",
-            remainingRounds,
-        };
-    }
-
-    if (remainingRounds === 0) {
-        return {
-            continue: false,
-            reason: "max_rounds_reached",
-            remainingRounds,
-        };
-    }
-
-    return {
-        continue: true,
-        remainingRounds,
-    };
-}

src/ai/tool-loop-runner.ts

@@ -1,22 +0,0 @@
-export type ToolLoopRoundOutcome = {
-    shouldContinue: boolean;
-    maxRoundsReached?: boolean;
-};
-
-export async function runToolLoopRounds(params: {
-    maxRounds: number;
-    onRound: (round: number) => Promise<ToolLoopRoundOutcome>;
-    onMaxRoundsReached?: (round: number) => Promise<void> | void;
-}): Promise<void> {
-    for (let round = 0; round < params.maxRounds; round++) {
-        const outcome = await params.onRound(round);
-        if (!outcome.shouldContinue) {
-            if (outcome.maxRoundsReached) {
-                await params.onMaxRoundsReached?.(round);
-            }
-            return;
-        }
-    }
-
-    await params.onMaxRoundsReached?.(params.maxRounds - 1);
-}

src/ai/tool-loop-summary.ts

@@ -1,56 +0,0 @@
-import type {PipelineArtifact} from "./user-request-pipeline/types.js";
-import type {TelegramOutputAttachmentRecord, TelegramToolExecutionRecord} from "./telegram-stream-message.js";
-import {summarizeModelOutput} from "./response-model-output.js";
-
-export type ToolLoopSummary = {
-    status: "succeeded" | "skipped";
-    fallbackAction?: "continue_without_stage";
-    details: {
-        modelOutput: ReturnType<typeof summarizeModelOutput>;
-        count: number;
-        tools: Array<{
-            toolName: string;
-            callId: string;
-            resultChars: number;
-        }>;
-    };
-    artifacts?: PipelineArtifact[];
-};
-
-export function summarizeToolLoop(params: {
-    text: string;
-    executions: readonly TelegramToolExecutionRecord[];
-    outputAttachments: readonly TelegramOutputAttachmentRecord[];
-}): ToolLoopSummary {
-    const count = params.executions.length;
-    const tools = params.executions.map(execution => ({
-        toolName: execution.toolName,
-        callId: execution.callId,
-        resultChars: execution.resultChars,
-    }));
-
-    return {
-        status: count ? "succeeded" : "skipped",
-        fallbackAction: count ? undefined : "continue_without_stage",
-        details: {
-            modelOutput: summarizeModelOutput({
-                text: params.text,
-                toolExecutions: params.executions,
-                outputAttachments: params.outputAttachments,
-            }),
-            count,
-            tools,
-        },
-        artifacts: count ? [{
-            kind: "tool_result",
-            stage: "tool_loop",
-            createdAt: new Date().toISOString(),
-            toolName: "summary",
-            callId: "tool_loop_summary",
-            resultText: JSON.stringify({
-                count,
-                tools,
-            }),
-        }] : undefined,
-    };
-}

src/ai/tool-mappers.ts

@@ -1,11 +1,10 @@
 import {AiTool} from "./tool-types";
-import {AiProvider} from "../model/ai-provider.js";
-import {getTools} from "./tools/registry.js";
-import {WEB_SEARCH_TOOL_NAME} from "./tools/web-search.js";
-import {PYTHON_INTERPRETER_TOOL_NAME} from "./tools/python-interpretator.js";
-import {toolSchemaNames} from "./tool-schema-utils.js";
+import {AiProvider} from "../model/ai-provider";
+import {getTools} from "./tools/registry";
+import {WEB_SEARCH_TOOL_NAME} from "./tools/web-search";
+import {PYTHON_INTERPRETER_TOOL_NAME} from "./tools/python-interpretator";
 
-export type AiProviderName = "ollama" | "openai" | "mistral";
+export type AiProviderName = "ollama" | "openai" | "gemini" | "mistral";
 
 export function getOllamaTools(forCreator?: boolean): AiTool[] {
     return getTools(forCreator);
@@ -14,10 +13,10 @@ export function getOllamaTools(forCreator?: boolean): AiTool[] {
 const openAiForbiddenTools = [
     WEB_SEARCH_TOOL_NAME,
     PYTHON_INTERPRETER_TOOL_NAME
-];
+]
 
 function allowedOpenAiTool(tool: AiTool): boolean {
-    return !openAiForbiddenTools.includes(tool.function.name);
+    return !openAiForbiddenTools.includes(tool.function.name)
 }
 
 export function getOpenAITools(forCreator?: boolean): AiTool[] {
@@ -27,16 +26,11 @@ export function getOpenAITools(forCreator?: boolean): AiTool[] {
     }));
 }
 
-export function getOpenAICompatibleTools(forCreator?: boolean): AiTool[] {
-    // The compatible chat.completions backend only accepts plain function tools.
-    return getOpenAITools(forCreator);
-}
-
 export type OpenAiResponseTool = {
     type: "function";
     name: string;
     description?: string;
-    parameters?: object;
+    parameters?: unknown;
     strict: false;
 };
 
@@ -50,7 +44,7 @@ export type OpenAiCodeInterpreterTool = {
 };
 
 export function getOpenAIResponsesTools(forCreator?: boolean): OpenAiResponseTool[] {
-    return getOpenAITools(forCreator).map(tool => ({
+    return getTools(forCreator).filter(allowedOpenAiTool).map(tool => ({
         type: "function",
         name: tool.function.name,
         description: tool.function.description,
@@ -75,30 +69,33 @@ export function getMistralTools(forCreator?: boolean): AiTool[] {
     }));
 }
 
+export type GeminiTool = {
+    functionDeclarations: Array<{
+        name: string;
+        description?: string;
+        parametersJsonSchema?: unknown;
+    }>;
+}
+
+export function getGeminiTools(forCreator?: boolean): GeminiTool[] {
+    const functionDeclarations = getTools(forCreator).map(tool => ({
+        name: tool.function.name,
+        description: tool.function.description,
+        parametersJsonSchema: tool.function.parameters,
+    }));
+
+    return functionDeclarations.length ? [{functionDeclarations}] : [];
+}
+
 export function getProviderTools(provider: AiProvider, forCreator?: boolean): AiTool[] {
     switch (provider) {
         case AiProvider.OLLAMA:
             return getOllamaTools(forCreator);
+        case AiProvider.GEMINI:
+            return getTools(forCreator);
         case AiProvider.MISTRAL:
             return getMistralTools(forCreator);
         case AiProvider.OPENAI:
             return getOpenAITools(forCreator);
     }
 }
-
-export function ensureToolsSelected<T>(availableTools: readonly T[], selectedTools: readonly T[], toolNames: readonly string[]): T[] {
-    const selected = [...selectedTools];
-    const selectedNames = new Set(selected.flatMap(tool => toolSchemaNames(tool as never)));
-
-    for (const toolName of toolNames) {
-        if (selectedNames.has(toolName)) continue;
-
-        const extraTool = availableTools.find(tool => toolSchemaNames(tool as never).includes(toolName));
-        if (extraTool) {
-            selected.unshift(extraTool);
-            selectedNames.add(toolName);
-        }
-    }
-
-    return selected;
-}

src/ai/tool-rank-stage.ts

@@ -1,146 +0,0 @@
-import {AiProvider} from "../model/ai-provider.js";
-import type {BoundaryValue} from "../common/boundary-types.js";
-import type {TelegramStreamMessage} from "./telegram-stream-message.js";
-import type {RuntimeConfigSnapshot} from "./unified-ai-runner.shared.js";
-import {allToolSchemaNames, toolSchemaNames} from "./tool-schema-utils.js";
-import type {ToolRanker} from "./unified-ai-runner.tool-ranker.js";
-import type {PipelineAuditEvent} from "./user-request-pipeline/types.js";
-
-function latestUserText(messages: readonly { role?: string; content?: unknown }[]): string {
-    for (let i = messages.length - 1; i >= 0; i--) {
-        const message = messages[i];
-        if (message?.role !== "user") continue;
-        if (typeof message.content === "string") return message.content;
-        if (Array.isArray(message.content)) {
-            return message.content
-                .map(part => typeof part === "object" && part !== null && "text" in part && typeof (part as { text?: unknown }).text === "string"
-                    ? (part as { text: string }).text
-                    : "")
-                .filter(Boolean)
-                .join("\n");
-        }
-    }
-
-    return "";
-}
-
-export async function runToolRankStage(params: {
-    provider: AiProvider;
-    model: string;
-    round: number;
-    config: RuntimeConfigSnapshot;
-    availableTools: readonly BoundaryValue[];
-    messages: readonly { role?: string; content?: unknown }[];
-    streamMessage: TelegramStreamMessage;
-    signal: AbortSignal;
-    toolRanker?: ToolRanker;
-    storeAudit?: (params: {
-        streamMessage: TelegramStreamMessage;
-        provider: AiProvider;
-        model: string;
-        round: number;
-        startedAt: number;
-        startedAtIso: string;
-        availableTools: string[];
-        selectedTools?: string[];
-        usedRanker?: boolean;
-        error?: unknown;
-    }) => Promise<void>;
-}): Promise<{
-    filteredTools: BoundaryValue[];
-    selectedToolNames: string[];
-    usedRanker: boolean;
-}> {
-    const toolRanker = params.toolRanker ?? new (await import("./unified-ai-runner.tool-ranker.js")).ToolRanker(params.config);
-    const startedAt = Date.now();
-    const startedAtIso = new Date().toISOString();
-    const filterSelectedTools = (selectedToolNames: readonly string[]): BoundaryValue[] => {
-        const selected = new Set(selectedToolNames);
-        return params.availableTools.filter(tool => toolSchemaNames(tool).some(name => selected.has(name)));
-    };
-    const storeAudit = params.storeAudit ?? (async (auditParams: {
-        streamMessage: TelegramStreamMessage;
-        provider: AiProvider;
-        model: string;
-        round: number;
-        startedAt: number;
-        startedAtIso: string;
-        availableTools: string[];
-        selectedTools?: string[];
-        usedRanker?: boolean;
-        error?: unknown;
-    }) => {
-        const event: PipelineAuditEvent = {
-            stage: "tool_rank",
-            status: auditParams.error ? "failed" : "succeeded",
-            startedAt: auditParams.startedAtIso,
-            finishedAt: new Date().toISOString(),
-            durationMs: Date.now() - auditParams.startedAt,
-            provider: auditParams.provider,
-            model: auditParams.model,
-            details: {
-                round: auditParams.round,
-                availableTools: auditParams.availableTools,
-                selectedTools: auditParams.selectedTools ?? [],
-                usedRanker: auditParams.usedRanker ?? false,
-                toolRankDecision: {
-                    provider: auditParams.provider,
-                    round: auditParams.round,
-                    availableTools: auditParams.availableTools,
-                    selectedTools: auditParams.selectedTools ?? [],
-                    usedRanker: auditParams.usedRanker ?? false,
-                },
-            },
-            error: auditParams.error instanceof Error ? auditParams.error.message : auditParams.error ? String(auditParams.error) : undefined,
-        };
-
-        await auditParams.streamMessage.storePipelineAudit([event]);
-    });
-
-    params.streamMessage.setStatus("🧩 Выбираю подходящие инструменты...");
-    await params.streamMessage.flush();
-
-    try {
-        const selection = await toolRanker.selectTools({
-            provider: params.provider,
-            userQuery: latestUserText(params.messages),
-            availableTools: params.availableTools,
-            round: params.round,
-            signal: params.signal,
-        });
-
-        params.streamMessage.clearStatus();
-        await params.streamMessage.flush();
-        await storeAudit({
-            streamMessage: params.streamMessage,
-            provider: params.provider,
-            model: params.model,
-            round: params.round,
-            startedAt,
-            startedAtIso,
-            availableTools: allToolSchemaNames(params.availableTools),
-            selectedTools: selection.toolNames,
-            usedRanker: selection.usedRanker,
-        });
-
-        return {
-            filteredTools: filterSelectedTools(selection.toolNames),
-            selectedToolNames: selection.toolNames,
-            usedRanker: selection.usedRanker,
-        };
-    } catch (error) {
-        params.streamMessage.clearStatus();
-        await params.streamMessage.flush();
-        await storeAudit({
-            streamMessage: params.streamMessage,
-            provider: params.provider,
-            model: params.model,
-            round: params.round,
-            startedAt,
-            startedAtIso,
-            availableTools: allToolSchemaNames(params.availableTools),
-            error,
-        });
-        throw error;
-    }
-}

src/ai/tool-ranker-fallback.ts

@@ -1,56 +0,0 @@
-import {ToolRankerFallbackPolicy} from "../common/policies.js";
-import {decidePipelineFallback, type PipelineFallbackDecision} from "./user-request-pipeline/fallback-executor.js";
-
-export type ToolRankerFallbackSelection = {
-    toolNames: string[];
-    usedRanker: boolean;
-};
-
-export type ToolRankerFallbackDecision = PipelineFallbackDecision & ToolRankerFallbackSelection;
-
-function fallbackActionForPolicy(policy: ToolRankerFallbackPolicy) {
-    return policy === ToolRankerFallbackPolicy.MAIN_MODEL
-        ? "use_alternate_target"
-        : "continue_without_stage";
-}
-
-export function decideToolRankerFallback(params: {
-    fallbackPolicy: ToolRankerFallbackPolicy;
-    availableToolNames: readonly string[];
-    reason: "unavailable" | "failed";
-}): ToolRankerFallbackDecision {
-    const action = fallbackActionForPolicy(params.fallbackPolicy);
-    const decision = decidePipelineFallback({
-        stage: "tool_rank",
-        reason: params.reason,
-        policies: [{
-            stage: "tool_rank",
-            onUnavailable: action,
-            onFailed: action,
-        }],
-    });
-
-    return {
-        ...decision,
-        toolNames: params.fallbackPolicy === ToolRankerFallbackPolicy.NO_TOOLS
-            ? []
-            : [...params.availableToolNames],
-        usedRanker: false,
-    };
-}
-
-export function resolveToolRankerFallbackSelection(params: {
-    fallbackPolicy: ToolRankerFallbackPolicy;
-    availableToolNames: readonly string[];
-}): ToolRankerFallbackSelection {
-    const decision = decideToolRankerFallback({
-        fallbackPolicy: params.fallbackPolicy,
-        availableToolNames: params.availableToolNames,
-        reason: "failed",
-    });
-
-    return {
-        toolNames: decision.toolNames,
-        usedRanker: decision.usedRanker,
-    };
-}

src/ai/tool-ranker-metadata.ts

@@ -1,669 +0,0 @@
-import type {BoundaryValue} from "../common/boundary-types";
-
-export type ToolRankerExample = {
-    user: string;
-    toolNames: string[];
-    note?: string;
-};
-
-export type ToolRankerToolInfo = {
-    name: string;
-    description: string;
-    rankerHint: string;
-    examples?: ToolRankerExample[];
-};
-
-const tool = (
-    name: string,
-    description: string,
-    rankerHint: string,
-    examples: ToolRankerExample[] = [],
-): ToolRankerToolInfo => ({
-    name,
-    description,
-    rankerHint,
-    examples: examples.length ? examples : undefined,
-});
-
-const example = (user: string, toolNames: string[], note?: string): ToolRankerExample => ({
-    user,
-    toolNames,
-    note,
-});
-
-export const TOOL_RANKER_TOOL_INFOS = {
-    no_tool: tool(
-        "no_tool",
-        "No tool action is needed.",
-        "Use for normal answers, explanations, advice, planning, code writing without execution, rewriting, translation, and general conversation.",
-        [
-            example("объясни docker volumes", ["no_tool"]),
-            example("напиши промпт для Claude", ["no_tool"]),
-            example("как лучше спроектировать эту архитектуру?", ["no_tool"]),
-        ],
-    ),
-    get_datetime: tool(
-        "get_datetime",
-        "Get the current date, time, or timezone-aware moment.",
-        "Use for current date/time, today/tomorrow/yesterday, timezone-aware time, and calculations based on the current moment.",
-        [
-            example("какое сегодня число?", ["get_datetime"]),
-            example("который час?", ["get_datetime"]),
-            example("что будет через 10 дней?", ["get_datetime"]),
-        ],
-    ),
-    get_financial_market_data: tool(
-        "get_financial_market_data",
-        "Get current market, price, currency, or ticker data.",
-        "Use for current/recent stocks, crypto, fiat exchange rates, commodities, indices, futures, and market prices.",
-        [
-            example("сколько сейчас BTC?", ["get_financial_market_data"]),
-            example("курс USD/RUB", ["get_financial_market_data"]),
-            example("цена золота сейчас", ["get_financial_market_data"]),
-        ],
-    ),
-    get_weather: tool(
-        "get_weather",
-        "Get current weather or forecast data.",
-        "Use for weather, rain, snow, wind, temperature, forecast, and weather-dependent planning.",
-        [
-            example("погода завтра", ["get_weather"]),
-            example("будет дождь сегодня?", ["get_weather"]),
-            example("можно сегодня на велике?", ["get_weather"]),
-        ],
-    ),
-    read_file: tool(
-        "read_file",
-        "Read a known local file path.",
-        "Use when the user asks to read, open, inspect, or summarize a known local file path.",
-        [
-            example("прочитай src/index.ts", ["read_file"]),
-            example("посмотри package.json", ["read_file"]),
-            example("открой этот файл", ["read_file"]),
-        ],
-    ),
-    list_directory: tool(
-        "list_directory",
-        "List files or folders in a local path.",
-        "Use when the user asks to list files/folders, inspect a directory, show project structure, or see what exists in a path.",
-        [
-            example("покажи структуру проекта", ["list_directory"]),
-            example("что лежит в src?", ["list_directory"]),
-            example("выведи список файлов", ["list_directory"]),
-        ],
-    ),
-    search_files: tool(
-        "search_files",
-        "Search local files by name, content, symbol, or keyword.",
-        "Use when the exact file path is unknown and the user wants to find files, usages, TODOs, symbols, classes, functions, or error messages.",
-        [
-            example("найди где используется sendMessage", ["search_files"]),
-            example("найди все TODO", ["search_files"]),
-            example("где определён BotService?", ["search_files"]),
-        ],
-    ),
-    read_user_info: tool(
-        "read_user_info",
-        "Read persistent user memory from user.md.",
-        "Use before editing or when the user asks what you remember about them.",
-        [
-            example("что ты помнишь обо мне?", ["read_user_info"]),
-            example("покажи мою память", ["read_user_info"]),
-        ],
-    ),
-    read_system_info: tool(
-        "read_system_info",
-        "Read persistent assistant memory from system.md.",
-        "Use before editing or when the user asks what instructions you remember about yourself.",
-        [
-            example("что ты помнишь о себе?", ["read_system_info"]),
-            example("покажи память о тебе", ["read_system_info"]),
-        ],
-    ),
-    add_user_info: tool(
-        "add_user_info",
-        "Append a durable fact about the user to persistent memory.",
-        "Use when the user asks to remember a new fact, preference, identity detail, or profile information about themselves.",
-        [
-            example("запомни, что меня зовут Иван", ["add_user_info"]),
-            example("запомни, что я люблю чай", ["add_user_info"]),
-            example("remember that I like short answers", ["add_user_info"]),
-        ],
-    ),
-    add_system_info: tool(
-        "add_system_info",
-        "Append a durable instruction about the assistant to persistent memory.",
-        "Use when the user asks to remember a new assistant identity, style, or behavior instruction.",
-        [
-            example("тебя зовут Евлампий", ["add_system_info"]),
-            example("ты ИИ помощник", ["add_system_info"]),
-            example("remember you are a concise assistant", ["add_system_info"]),
-        ],
-    ),
-    remove_user_info: tool(
-        "remove_user_info",
-        "Remove a specific user fact from persistent memory.",
-        "Use when the user asks to forget, delete, or remove a specific fact about themselves.",
-        [
-            example("забудь, что я люблю кофе", ["remove_user_info"]),
-            example("удали из памяти, что я живу в Москве", ["remove_user_info"]),
-            example("forget that I work at ACME", ["remove_user_info"]),
-        ],
-    ),
-    remove_system_info: tool(
-        "remove_system_info",
-        "Remove a specific assistant instruction from persistent memory.",
-        "Use when the user asks to forget or remove a specific instruction about the assistant.",
-        [
-            example("забудь, что тебя зовут Евлампий", ["remove_system_info"]),
-            example("убери правило отвечать коротко", ["remove_system_info"]),
-            example("forget that you are a concise assistant", ["remove_system_info"]),
-        ],
-    ),
-    replace_user_info: tool(
-        "replace_user_info",
-        "Replace the full user memory with a new compact version.",
-        "Use when the user wants to overwrite all remembered user info, for example when they say to forget everything and keep only the new fact.",
-        [
-            example("забудь всё обо мне и запиши только это: меня зовут Иван", ["replace_user_info"]),
-            example("замени всю память обо мне на: люблю чай и короткие ответы", ["replace_user_info"]),
-        ],
-    ),
-    replace_system_info: tool(
-        "replace_system_info",
-        "Replace the full assistant memory with a new compact version.",
-        "Use when the user wants to overwrite all remembered assistant info or instructions.",
-        [
-            example("забудь всё о себе и запиши только это: тебя зовут Евлампий", ["replace_system_info"]),
-            example("замени инструкцию о себе на: ты краткий ИИ помощник", ["replace_system_info"]),
-        ],
-    ),
-    delete_user_info: tool(
-        "delete_user_info",
-        "Delete user.md entirely.",
-        "Use when the user explicitly asks to delete all remembered user info, not just a fragment.",
-        [
-            example("удали всю память обо мне", ["delete_user_info"]),
-            example("forget all user memory", ["delete_user_info"]),
-        ],
-    ),
-    delete_system_info: tool(
-        "delete_system_info",
-        "Delete system.md entirely.",
-        "Use when the user explicitly asks to delete all remembered assistant info, not just a fragment.",
-        [
-            example("удали всю память о себе", ["delete_system_info"]),
-            example("forget all assistant memory", ["delete_system_info"]),
-        ],
-    ),
-    create_file: tool(
-        "create_file",
-        "Create a new small file.",
-        "Use when the user asks to create a new file with specific content.",
-        [
-            example("создай README.md", ["create_file"]),
-            example("создай .env.example", ["create_file"]),
-            example("сделай docker-compose.yml", ["create_file"]),
-        ],
-    ),
-    update_file: tool(
-        "update_file",
-        "Replace an existing file completely.",
-        "Use only for full file replacement or overwrite.",
-        [
-            example("полностью перезапиши config.json", ["update_file"]),
-            example("замени файл этой версией", ["update_file"]),
-            example("overwrite this file", ["update_file"]),
-        ],
-    ),
-    edit_file_patch: tool(
-        "edit_file_patch",
-        "Apply a targeted patch to an existing file.",
-        "Use for targeted edits, patches, diffs, refactors, and changes that should preserve most of the file.",
-        [
-            example("исправь этот баг патчем", ["edit_file_patch"]),
-            example("добавь эту опцию в существующий конфиг", ["edit_file_patch"]),
-            example("измени только эту функцию", ["edit_file_patch"]),
-        ],
-    ),
-    create_directory: tool(
-        "create_directory",
-        "Create directories or folder trees.",
-        "Use when the user asks to create folders or directory structures.",
-        [
-            example("создай папку src/services", ["create_directory"]),
-            example("создай структуру директорий", ["create_directory"]),
-        ],
-    ),
-    copy_path: tool(
-        "copy_path",
-        "Copy a file or folder path.",
-        "Use when the user asks to copy or duplicate a file or folder.",
-        [
-            example("скопируй config.example.json в config.json", ["copy_path"]),
-            example("дублируй эту папку", ["copy_path"]),
-        ],
-    ),
-    rename_path: tool(
-        "rename_path",
-        "Rename or move a file or folder.",
-        "Use when the user asks to rename or move a file or folder.",
-        [
-            example("переименуй файл", ["rename_path"]),
-            example("перемести notes.md в archive", ["rename_path"]),
-        ],
-    ),
-    delete_path: tool(
-        "delete_path",
-        "Delete a file or folder.",
-        "Use only when the user clearly asks to delete or remove something.",
-        [
-            example("удали папку dist", ["delete_path"]),
-            example("remove node_modules", ["delete_path"]),
-            example("delete this file", ["delete_path"]),
-        ],
-    ),
-    send_file_as_attachment: tool(
-        "send_file_as_attachment",
-        "Send a local file as an attachment.",
-        "Use when the user wants to receive, export, send, attach, or download a local file as an attachment.",
-        [
-            example("пришли мне этот файл", ["send_file_as_attachment"]),
-            example("отправь заметку файлом", ["send_file_as_attachment"]),
-            example("export this as attachment", ["send_file_as_attachment"]),
-        ],
-    ),
-    begin_file_write: tool(
-        "begin_file_write",
-        "Start a large chunked file write.",
-        "Use with write_file_chunk and finish_file_write for large file creation or writing.",
-        [
-            example("создай большой markdown отчёт", ["begin_file_write", "write_file_chunk", "finish_file_write"]),
-            example("запиши большой файл чанками", ["begin_file_write", "write_file_chunk", "finish_file_write"]),
-        ],
-    ),
-    write_file_chunk: tool(
-        "write_file_chunk",
-        "Append a chunk to an active large file write.",
-        "Use together with begin_file_write and finish_file_write for chunked file writing.",
-    ),
-    finish_file_write: tool(
-        "finish_file_write",
-        "Complete an active large file write.",
-        "Use together with begin_file_write and write_file_chunk to finish chunked file writing.",
-    ),
-    cancel_file_write: tool(
-        "cancel_file_write",
-        "Cancel an active large file write.",
-        "Use when the user asks to cancel an active file write operation.",
-        [
-            example("отмени запись файла", ["cancel_file_write"]),
-            example("cancel file write", ["cancel_file_write"]),
-        ],
-    ),
-    shell_execute: tool(
-        "shell_execute",
-        "Run shell commands in the workspace environment.",
-        "Use for terminal commands, tests, builds, docker, git, npm, pnpm, bun, gradle, diagnostics, logs, install commands, or system inspection.",
-        [
-            example("запусти npm test", ["shell_execute"]),
-            example("собери проект", ["shell_execute"]),
-            example("проверь docker logs", ["shell_execute"]),
-        ],
-    ),
-    python_interpreter: tool(
-        "python_interpreter",
-        "Execute Python code.",
-        "Use when the user explicitly asks to run Python code, execute Python, calculate with Python, or test a Python script.",
-        [
-            example("выполни этот python код", ["python_interpreter"]),
-            example("посчитай это питоном", ["python_interpreter"]),
-            example("напиши и запусти python скрипт", ["python_interpreter"]),
-        ],
-    ),
-    code_interpreter: tool(
-        "code_interpreter",
-        "Run sandboxed code and data analysis.",
-        "Use for sandbox computation, data/file analysis, CSV processing, archive processing, charts, tables, and generated reports.",
-        [
-            example("проанализируй CSV", ["code_interpreter"]),
-            example("построй график", ["code_interpreter"]),
-            example("обработай архив", ["code_interpreter"]),
-        ],
-    ),
-    image_generation: tool(
-        "image_generation",
-        "Generate or edit an image.",
-        "Use when the user asks to generate, create, edit, transform, restyle, enhance, remove, add, replace, recolor, upscale, or alter an image.",
-        [
-            example("сделай его лысым", ["image_generation"]),
-            example("убери фон", ["image_generation"]),
-            example("сделай в стиле аниме", ["image_generation"]),
-        ],
-    ),
-    web_search: tool(
-        "web_search",
-        "Search the public web for current, recent, or external information.",
-        "Use only for current/recent/public online information, search, verification, links, documentation, comparisons, or external data.",
-        [
-            example("найди актуальную документацию OpenAI API", ["web_search"]),
-            example("проверь, вышел ли Kotlin 2.3", ["web_search"]),
-            example("какие сейчас цены на VPS?", ["web_search"]),
-        ],
-    ),
-    file_search: tool(
-        "file_search",
-        "Search uploaded documents or indexed vector-store files.",
-        "Use for uploaded documents, vector stores, PDFs/docs already indexed or attached to the assistant context.",
-        [
-            example("найди в моих документах про MCP", ["file_search"]),
-            example("что в загруженном PDF написано про оплату?", ["file_search"]),
-            example("поищи в базе знаний", ["file_search"]),
-        ],
-    ),
-} as const satisfies Record<string, ToolRankerToolInfo>;
-
-export type ToolRankerToolName = keyof typeof TOOL_RANKER_TOOL_INFOS;
-
-function isString(value: BoundaryValue): value is string {
-    return typeof value === "string";
-}
-
-function normalizeToolNames(names: readonly string[]): string[] {
-    const unique: string[] = [];
-
-    for (const name of names) {
-        if (!name || unique.includes(name)) {
-            continue;
-        }
-
-        unique.push(name);
-    }
-
-    return unique;
-}
-
-function extractJsonCandidate(raw: string): string {
-    const trimmed = raw.trim();
-    if (!trimmed) {
-        return "";
-    }
-
-    const fenced = trimmed.match(/^```(?:json)?\s*([\s\S]*?)\s*```$/i);
-    if (fenced?.[1]) {
-        return fenced[1].trim();
-    }
-
-    const firstObjectStart = trimmed.indexOf("{");
-    const lastObjectEnd = trimmed.lastIndexOf("}");
-    if (firstObjectStart !== -1 && lastObjectEnd !== -1 && lastObjectEnd > firstObjectStart) {
-        return trimmed.slice(firstObjectStart, lastObjectEnd + 1).trim();
-    }
-
-    const firstArrayStart = trimmed.indexOf("[");
-    const lastArrayEnd = trimmed.lastIndexOf("]");
-    if (firstArrayStart !== -1 && lastArrayEnd !== -1 && lastArrayEnd > firstArrayStart) {
-        return trimmed.slice(firstArrayStart, lastArrayEnd + 1).trim();
-    }
-
-    return trimmed;
-}
-
-function parseSelectionValue(value: BoundaryValue): string[] {
-    if (typeof value === "string") {
-        return [value];
-    }
-
-    if (Array.isArray(value)) {
-        return value.filter(isString);
-    }
-
-    if (value !== null && typeof value === "object") {
-        const rawToolNames = (value as Record<string, BoundaryValue>).toolNames;
-        return parseSelectionValue(rawToolNames as BoundaryValue);
-    }
-
-    return [];
-}
-
-function asOptionalString(value: BoundaryValue): string | undefined {
-    return typeof value === "string" && value.trim().length > 0 ? value.trim() : undefined;
-}
-
-function isRecord(value: BoundaryValue): value is Record<string, BoundaryValue> {
-    return value !== null && typeof value === "object" && !Array.isArray(value);
-}
-
-function toolNamesFromTool(tool: BoundaryValue): string[] {
-    if (!isRecord(tool)) {
-        return [];
-    }
-
-    const functionValue = isRecord(tool.function) ? tool.function : undefined;
-    const directName = functionValue?.name ?? tool.name ?? (typeof tool.type === "string" && tool.type !== "function" ? tool.type : undefined);
-    const name = asOptionalString(directName);
-
-    return name ? [name] : [];
-}
-
-function fallbackToolInfoFromTool(toolValue: BoundaryValue, name: string): ToolRankerToolInfo | undefined {
-    if (!isRecord(toolValue)) return undefined;
-
-    const fn = isRecord(toolValue.function) ? toolValue.function : undefined;
-    const description = asOptionalString(fn?.description ?? toolValue.description)
-        ?? `Tool ${name}.`;
-
-    return tool(
-        name,
-        description,
-        "Use when the tool description matches the user's request.",
-    );
-}
-
-export function getToolRankerToolInfo(name: string): ToolRankerToolInfo | undefined {
-    return TOOL_RANKER_TOOL_INFOS[name as ToolRankerToolName];
-}
-
-export function getToolRankerToolInfos(names: readonly string[]): ToolRankerToolInfo[] {
-    return normalizeToolNames(names)
-        .map(name => getToolRankerToolInfo(name))
-        .filter((tool): tool is ToolRankerToolInfo => !!tool);
-}
-
-export function getToolRankerAvailableToolInfos(availableTools: readonly BoundaryValue[]): ToolRankerToolInfo[] {
-    const infos = new Map<string, ToolRankerToolInfo>();
-
-    infos.set("no_tool", TOOL_RANKER_TOOL_INFOS.no_tool);
-
-    for (const tool of availableTools) {
-        for (const name of toolNamesFromTool(tool)) {
-            if (infos.has(name)) continue;
-
-            const known = getToolRankerToolInfo(name);
-            const fallback = fallbackToolInfoFromTool(tool, name);
-            if (known) {
-                infos.set(name, known);
-            } else if (fallback) {
-                infos.set(name, fallback);
-            }
-        }
-    }
-
-    return [...infos.values()];
-}
-
-function renderToolLine(tool: ToolRankerToolInfo, compact: boolean): string {
-    if (compact) {
-        return `- ${tool.name}: ${tool.rankerHint}`;
-    }
-
-    return `- ${tool.name}: ${tool.description}\n  ${tool.rankerHint}`;
-}
-
-function renderExamples(tool: ToolRankerToolInfo, maxExamplesPerTool: number): string[] {
-    if (!tool.examples?.length || maxExamplesPerTool <= 0) {
-        return [];
-    }
-
-    return tool.examples.slice(0, maxExamplesPerTool).flatMap(example => {
-        const lines = [
-            `User: ${JSON.stringify(example.user)}`,
-        ];
-
-        if (example.note?.trim()) {
-            lines.push(`Note: ${example.note.trim()}`);
-        }
-
-        lines.push(JSON.stringify({toolNames: example.toolNames}));
-        return lines;
-    });
-}
-
-function buildPriorityLines(tools: readonly ToolRankerToolInfo[]): string[] {
-    const names = new Set(tools.map(tool => tool.name));
-    const lines: string[] = [];
-
-    const pushIfAvailable = (name: string, line: string): void => {
-        if (names.has(name)) {
-            lines.push(`- ${line}`);
-        }
-    };
-
-    pushIfAvailable("get_datetime", "current date/time -> get_datetime");
-    pushIfAvailable("get_financial_market_data", "market prices, currency, crypto, stocks -> get_financial_market_data");
-    pushIfAvailable("get_weather", "weather or forecast -> get_weather");
-    pushIfAvailable("image_generation", "image creation or editing -> image_generation");
-    pushIfAvailable("file_search", "uploaded/vector documents -> file_search");
-    pushIfAvailable("read_file", "known local file path -> read_file");
-    pushIfAvailable("list_directory", "project structure or directory listing -> list_directory");
-    pushIfAvailable("search_files", "local file/content search or unknown file path -> search_files");
-    pushIfAvailable("read_user_info", "inspect remembered user info -> read_user_info");
-    pushIfAvailable("read_system_info", "inspect remembered assistant info -> read_system_info");
-    pushIfAvailable("add_user_info", "remember a new user fact -> add_user_info");
-    pushIfAvailable("add_system_info", "remember a new assistant instruction -> add_system_info");
-    pushIfAvailable("remove_user_info", "forget a user fact -> remove_user_info");
-    pushIfAvailable("remove_system_info", "forget an assistant instruction -> remove_system_info");
-    pushIfAvailable("replace_user_info", "overwrite all user memory -> replace_user_info");
-    pushIfAvailable("replace_system_info", "overwrite all assistant memory -> replace_system_info");
-    pushIfAvailable("delete_user_info", "delete all user memory -> delete_user_info");
-    pushIfAvailable("delete_system_info", "delete all assistant memory -> delete_system_info");
-    pushIfAvailable("edit_file_patch", "targeted existing file edit -> edit_file_patch");
-    pushIfAvailable("update_file", "full existing file replacement -> update_file");
-    pushIfAvailable("create_file", "small new file -> create_file");
-    pushIfAvailable("begin_file_write", "large file writing -> begin_file_write + write_file_chunk + finish_file_write");
-    pushIfAvailable("delete_path", "delete/remove only when the user clearly asks -> delete_path");
-    pushIfAvailable("shell_execute", "terminal commands, builds, tests, git, docker -> shell_execute");
-    pushIfAvailable("python_interpreter", "explicit Python execution -> python_interpreter");
-    pushIfAvailable("code_interpreter", "sandbox computation or data analysis -> code_interpreter");
-
-    return lines;
-}
-
-function buildRulesSection(availableToolNames: readonly string[]): string[] {
-    const names = new Set(availableToolNames);
-    const rules: string[] = [
-        "You are a tool router, not an answering model.",
-        "Your only job is to select the minimal set of tools needed for the user's latest request.",
-        "Return ONLY valid JSON: {\"toolNames\":[\"tool1\",\"tool2\"]}",
-        "No explanations.",
-        "No markdown.",
-        "No arguments.",
-        "Use only tool names from Available tools.",
-        "If no tool is needed, return {\"toolNames\":[\"no_tool\"]}.",
-        "Pick the smallest correct tool set.",
-        "Prefer specialized tools over generic tools.",
-        "Use multiple tools only when the request likely needs a combination of capabilities.",
-        "Be extra careful with destructive tools.",
-    ];
-
-    if (names.has("web_search")) {
-        rules.push("Do not use web_search just because you are unsure.");
-    }
-
-    if (names.has("delete_path")) {
-        rules.push("delete_path only when the user clearly asks to delete or remove something.");
-    }
-
-    if (names.has("update_file")) {
-        rules.push("update_file only for full file replacement.");
-    }
-
-    if (names.has("edit_file_patch")) {
-        rules.push("edit_file_patch for targeted file edits.");
-    }
-
-    return rules;
-}
-
-export function buildToolRankerSystemPrompt(params: {
-    availableTools: ToolRankerToolInfo[];
-    includeExamples?: boolean;
-    maxExamplesPerTool?: number;
-    compact?: boolean;
-}): string {
-    const includeExamples = params.includeExamples ?? false;
-    const maxExamplesPerTool = Math.max(0, params.maxExamplesPerTool ?? 1);
-    const compact = params.compact ?? true;
-    const availableTools = params.availableTools;
-    const availableToolNames = availableTools.map(tool => tool.name);
-
-    const sections: string[] = [
-        ...buildRulesSection(availableToolNames),
-        "",
-        "Available tools:",
-        ...availableTools.map(tool => renderToolLine(tool, compact)),
-    ];
-
-    const priorityLines = buildPriorityLines(availableTools);
-    if (priorityLines.length) {
-        sections.push("", "Priority:", ...priorityLines);
-    }
-
-    if (includeExamples) {
-        const exampleLines = availableTools.flatMap(tool => renderExamples(tool, maxExamplesPerTool));
-        if (exampleLines.length) {
-            sections.push("", "Examples:", ...exampleLines);
-        }
-    }
-
-    sections.push("", "Return ONLY JSON.");
-    return sections.join("\n");
-}
-
-export function sanitizeToolRankerResult(params: {
-    raw: string;
-    availableToolNames: readonly string[];
-}): string[] {
-    const raw = params.raw.trim();
-    if (!raw) {
-        return ["no_tool"];
-    }
-
-    const candidate = extractJsonCandidate(raw);
-    let parsed: BoundaryValue;
-
-    try {
-        parsed = JSON.parse(candidate) as BoundaryValue;
-    } catch {
-        return ["no_tool"];
-    }
-
-    const availableToolNames = new Set(params.availableToolNames.filter(Boolean));
-    const selected: string[] = [];
-
-    for (const name of normalizeToolNames(parseSelectionValue(parsed))) {
-        if (name === "no_tool") {
-            selected.push(name);
-            continue;
-        }
-
-        if (availableToolNames.has(name)) {
-            selected.push(name);
-        }
-    }
-
-    const deduped = normalizeToolNames(selected);
-    const withoutNoTool = deduped.filter(name => name !== "no_tool");
-
-    return withoutNoTool.length > 0 ? withoutNoTool : ["no_tool"];
-}

src/ai/tool-ranker-pipeline.ts

@@ -1,116 +0,0 @@
-import type {BoundaryValue} from "../common/boundary-types.js";
-import type {AiRuntimeTarget} from "./ai-runtime-target.js";
-import {AiProvider} from "../model/ai-provider.js";
-import {RuntimeConfigSnapshot, toolSchemaNames} from "./unified-ai-runner.shared.js";
-import {
-    buildToolRankerSystemPrompt,
-    getToolRankerAvailableToolInfos,
-    type ToolRankerToolInfo,
-} from "./tool-ranker-metadata.js";
-
-export type ToolRankerMessage = {
-    role?: string;
-    content?: BoundaryValue;
-};
-
-export type ToolRankerSelection = {
-    toolNames: string[];
-    usedRanker: boolean;
-};
-
-export type ToolRankerContext = {
-    provider: AiProvider;
-    round: number;
-    userQuery: string;
-    availableTools: readonly BoundaryValue[];
-    targetModel: string;
-    rankerPrompt?: string | null;
-    promptAdditions?: string | null;
-};
-
-export type ToolRankerPromptPlan = {
-    availableToolNames: string[];
-    availableToolInfos: ToolRankerToolInfo[];
-    prompt: string;
-};
-
-export function latestUserTextFromMessages(messages: readonly ToolRankerMessage[]): string {
-    for (let i = messages.length - 1; i >= 0; i--) {
-        const message = messages[i];
-        if (message?.role !== "user") continue;
-        if (typeof message.content === "string") return message.content;
-
-        if (Array.isArray(message.content)) {
-            return message.content
-                .map(part => {
-                    if (typeof part === "object" && part !== null && "text" in part && typeof part.text === "string") {
-                        return part.text;
-                    }
-                    return "";
-                })
-                .filter(Boolean)
-                .join("\n");
-        }
-    }
-
-    return "";
-}
-
-export function buildToolRankerPrompt(context: ToolRankerContext): ToolRankerPromptPlan {
-    const availableToolInfos = getToolRankerAvailableToolInfos(context.availableTools);
-    const availableToolNames = availableToolInfos.map(tool => tool.name);
-    const prompt = buildToolRankerSystemPrompt({
-        availableTools: availableToolInfos,
-        includeExamples: true,
-        maxExamplesPerTool: 1,
-        compact: true,
-    });
-
-    return {
-        availableToolNames,
-        availableToolInfos,
-        prompt: [
-            context.rankerPrompt?.trim() || null,
-            context.promptAdditions?.trim() || null,
-            prompt,
-        ].filter((line): line is string => Boolean(line?.trim?.() ?? line)).join("\n\n"),
-    };
-}
-
-export function filterRankedTools<T extends BoundaryValue>(availableTools: readonly T[], toolNames: readonly string[]): T[] {
-    const selected = new Set(toolNames);
-    return availableTools.filter(tool => toolSchemaNames(tool).some(name => selected.has(name)));
-}
-
-export function buildRankerContext(config: RuntimeConfigSnapshot, provider: AiProvider, target: AiRuntimeTarget, round: number, userQuery: string, availableTools: readonly BoundaryValue[]): ToolRankerContext {
-    return {
-        provider,
-        round,
-        userQuery,
-        availableTools,
-        targetModel: target.model,
-        rankerPrompt: config.rankerToolPrompt,
-        promptAdditions: target.systemPromptAdditions ?? null,
-    };
-}
-
-export function buildRankerTarget(config: RuntimeConfigSnapshot, provider: AiProvider): AiRuntimeTarget | undefined {
-    const target = provider === AiProvider.OLLAMA
-        ? config.ollamaToolRankerTarget
-        : provider === AiProvider.MISTRAL
-            ? config.mistralToolRankerTarget
-            : provider === AiProvider.OPENAI
-                ? config.openAiToolRankerTarget
-                : undefined;
-
-    if (!target?.model) return undefined;
-
-    return {
-        provider: target.provider,
-        purpose: target.purpose,
-        model: target.model,
-        baseUrl: target.baseUrl,
-        apiKey: target.apiKey,
-        systemPromptAdditions: target.systemPromptAdditions ?? null,
-    };
-}

src/ai/tool-result-artifact-store.ts

@@ -1,28 +0,0 @@
-import type {StoredAttachment} from "../model/stored-attachment";
-import type {ToolCallData} from "./unified-ai-runner.shared";
-import {persistInternalJsonArtifactAttachment} from "./internal-artifact-store";
-
-export async function persistToolResultArtifactAttachment(params: {
-    toolCall: ToolCallData;
-    resultText: string;
-    chatId: number;
-    messageId: number;
-}): Promise<StoredAttachment> {
-    return await persistInternalJsonArtifactAttachment({
-        artifactKind: "tool_result",
-        fileNamePrefix: `tool-${params.toolCall.name}`,
-        chatId: params.chatId,
-        messageId: params.messageId,
-        payload: {
-            toolName: params.toolCall.name,
-            callId: params.toolCall.id,
-            argumentsText: params.toolCall.argumentsText,
-            resultText: params.resultText,
-        },
-        metadata: {
-            toolName: params.toolCall.name,
-            callId: params.toolCall.id,
-            resultChars: params.resultText.length,
-        },
-    });
-}

src/ai/tool-schema-utils.ts

@@ -1,33 +0,0 @@
-import type {BoundaryValue} from "../common/boundary-types.js";
-
-function isRecord(value: BoundaryValue): value is Record<string, BoundaryValue> {
-    return value !== null && typeof value === "object" && !Array.isArray(value);
-}
-
-function asOptionalString(value: BoundaryValue): string | undefined {
-    return typeof value === "string" && value.trim().length > 0 ? value.trim() : undefined;
-}
-
-export function toolSchemaName(tool: BoundaryValue): string | undefined {
-    if (!isRecord(tool)) return undefined;
-    const fn = isRecord(tool.function) ? tool.function : undefined;
-    const directName = fn?.name ?? tool.name ?? (typeof tool.type === "string" && tool.type !== "function" ? tool.type : undefined);
-    return asOptionalString(directName);
-}
-
-export function toolSchemaNames(tool: BoundaryValue): string[] {
-    if (!isRecord(tool)) return [];
-
-    if (Array.isArray(tool.functionDeclarations)) {
-        return tool.functionDeclarations
-            .map(declaration => isRecord(declaration) ? asOptionalString(declaration.name) : undefined)
-            .filter((name): name is string => !!name);
-    }
-
-    const name = toolSchemaName(tool);
-    return name ? [name] : [];
-}
-
-export function allToolSchemaNames(tools: readonly BoundaryValue[]): string[] {
-    return [...new Set(tools.flatMap(toolSchemaNames))];
-}

src/ai/tool-types.ts

@@ -1,23 +1,12 @@
 
-export type AiJsonPrimitive = string | number | boolean | null;
-export interface AiJsonObject {
-    readonly [key: string]: AiJsonValue;
-}
-export type AiJsonValue = AiJsonPrimitive | undefined | readonly AiJsonValue[] | AiJsonObject;
-export interface AiToolParameters {
-    type: "object" | "string" | "number" | "integer" | "boolean" | "array";
-    properties?: Record<string, AiToolParameters>;
-    required?: readonly string[];
-    items?: AiToolParameters;
-    enum?: readonly string[];
-    description?: string;
-    minItems?: number;
-    maxItems?: number;
-    minimum?: number;
-    maximum?: number;
-    default?: AiJsonValue;
-    additionalProperties?: boolean | AiToolParameters;
-}
+
+
+export type AiToolParameters = {
+    type: "object";
+    properties?: Record<string, unknown>;
+    required?: string[];
+    [key: string]: unknown;
+};
 
 export type AiTool = {
     type: "function";
@@ -32,7 +21,9 @@ export type AiTool = {
 export type AiToolCall = {
     function: {
         name: string;
-        arguments: AiJsonObject;
+        arguments: {
+            [key: string]: unknown;
+        };
     };
 };
 

src/ai/tools/create-note.ts

@@ -1,11 +1,10 @@
-import {AiTool} from "../tool-types.js";
+import {AiTool} from "../tool-types";
 import path from "node:path";
 import {readFile, writeFile} from "node:fs/promises";
-import {NOTES_HEADER, notesDir, notesRootFile} from "../../index.js";
-import {asNonEmptyString} from "./utils.js";
+import {NOTES_HEADER, notesDir, notesRootFile} from "../../index";
+import {asNonEmptyString} from "./utils";
 import fs from "node:fs";
-import {toolsLogger} from "./tool-logger.js";
-import {AiJsonObject} from "../tool-types.js";
+import {toolsLogger} from "./tool-logger";
 
 const logger = toolsLogger.child("create-note");
 
@@ -40,7 +39,7 @@ export const createNoteTool = {
 } satisfies AiTool;
 
 export async function createNote(
-    args?: AiJsonObject
+    args?: Record<string, unknown>
 ): Promise<CreateNoteResult> {
     const startedAt = Date.now();
     logger.debug("start", {args});
@@ -84,8 +83,8 @@ export async function createNote(
         logger.debug("done", {fileName, filePath: newFilePath, duration: logger.duration(startedAt)});
         return {success: true, filePath: newFilePath};
     } catch (error) {
-        logger.error("failed", {duration: logger.duration(startedAt), error: error instanceof Error ? error : String(error)});
+        logger.error("failed", {duration: logger.duration(startedAt), error});
         const errorMessage = error instanceof Error ? error.message : String(error);
         return {success: false, error: `Failed to process files: ${errorMessage}`};
     }
-}
+}

src/ai/tools/datetime.ts

@@ -1,6 +1,5 @@
 import {AiTool} from "../tool-types";
-import {asNonEmptyString} from "./utils.js";
-import {AiJsonObject} from "../tool-types";
+import {asNonEmptyString} from "./utils";
 
 export const getCurrentDateTimeTool = {
     type: "function",
@@ -45,7 +44,7 @@ function getSystemTimeZone(): string {
     return Intl.DateTimeFormat().resolvedOptions().timeZone;
 }
 
-export function getCurrentDateTime(args?: AiJsonObject) {
+export function getCurrentDateTime(args?: Record<string, unknown>) {
     const now = new Date();
 
     const systemTimeZone = getSystemTimeZone();

src/ai/tools/files.ts

@@ -3,8 +3,8 @@ import fs from "node:fs";
 import path from "node:path";
 import {z} from "zod";
 
-import {Environment} from "../../common/environment.js";
-import {AiJsonObject, AiJsonValue, AiTool} from "../tool-types.js";
+import {Environment} from "../../common/environment";
+import {AiTool} from "../tool-types";
 import {
     MAX_COPY_ENTRIES,
     MAX_COPY_TOTAL_BYTES,
@@ -23,8 +23,8 @@ import {
     MAX_PATCH_SEARCH_BYTES,
     MAX_STREAM_WRITE_IDLE_MS,
     MAX_STREAM_WRITE_SESSIONS,
-} from "./limits.js";
-import {asBoolean, asNonEmptyString, asPositiveInt, asString} from "./utils.js";
+} from "./limits";
+import {asBoolean, asNonEmptyString, asPositiveInt, asString} from "./utils";
 
 // =============================================================================
 // Public types and schemas
@@ -613,7 +613,7 @@ export const fileToolsToolPrompt = [
     "- Do not use ../ paths.",
     "- Do not use absolute paths.",
     "- Do not try to access symlinks.",
-    "- Use search_files to find files by name, path or text content before reading or editing unfamiliar files.",
+    "- Use search_files to find files by name, path or text content before reading or editing unknown files.",
     "- Use read_file for reading files.",
     "- Use list_directory for reading directories.",
     "- Use create_file for creating small or medium files in one call.",
@@ -637,7 +637,7 @@ export const fileToolsToolPrompt = [
 // Exported tool implementations
 // =============================================================================
 
-export async function readFile(args?: AiJsonObject) {
+export async function readFile(args?: Record<string, unknown>) {
     const {absolutePath, relativePath, rootDir} = resolveSafeToolPath(
         args?.path,
         ".",
@@ -678,7 +678,7 @@ export async function readFile(args?: AiJsonObject) {
     };
 }
 
-export async function listDirectory(args?: AiJsonObject) {
+export async function listDirectory(args?: Record<string, unknown>) {
     const {absolutePath, relativePath, rootDir} = resolveSafeToolPath(
         args?.path,
         ".",
@@ -727,7 +727,7 @@ export async function listDirectory(args?: AiJsonObject) {
     };
 }
 
-export async function searchFiles(args?: AiJsonObject) {
+export async function searchFiles(args?: Record<string, unknown>) {
     const start = resolveSafeToolPath(args?.path, ".", args?.userId);
 
     await assertNoSymlinkInPath(start.absolutePath, start.rootDir);
@@ -894,7 +894,7 @@ export async function searchFiles(args?: AiJsonObject) {
     };
 }
 
-export async function createFile(args?: AiJsonObject) {
+export async function createFile(args?: Record<string, unknown>) {
     const {absolutePath, relativePath, rootDir} = resolveSafeToolPath(
         args?.path,
         ".",
@@ -953,7 +953,7 @@ export async function createFile(args?: AiJsonObject) {
     };
 }
 
-export async function updateFile(args?: AiJsonObject) {
+export async function updateFile(args?: Record<string, unknown>) {
     const {absolutePath, relativePath, rootDir} = resolveSafeToolPath(
         args?.path,
         ".",
@@ -1036,7 +1036,7 @@ export async function updateFile(args?: AiJsonObject) {
     };
 }
 
-export async function editFilePatch(args?: AiJsonObject) {
+export async function editFilePatch(args?: Record<string, unknown>) {
     const {absolutePath, relativePath, rootDir} = resolveSafeToolPath(
         args?.path,
         ".",
@@ -1146,7 +1146,7 @@ export async function editFilePatch(args?: AiJsonObject) {
     };
 }
 
-export async function createDirectory(args?: AiJsonObject) {
+export async function createDirectory(args?: Record<string, unknown>) {
     const {absolutePath, relativePath, rootDir} = resolveSafeToolPath(
         args?.path,
         ".",
@@ -1168,7 +1168,7 @@ export async function createDirectory(args?: AiJsonObject) {
     };
 }
 
-export async function copyPath(args?: AiJsonObject) {
+export async function copyPath(args?: Record<string, unknown>) {
     const source = resolveSafeToolPath(args?.sourcePath, undefined, args?.userId);
     const target = resolveSafeToolPath(args?.targetPath, undefined, args?.userId);
 
@@ -1237,7 +1237,7 @@ export async function copyPath(args?: AiJsonObject) {
     };
 }
 
-export async function renamePath(args?: AiJsonObject) {
+export async function renamePath(args?: Record<string, unknown>) {
     const source = resolveSafeToolPath(args?.sourcePath, undefined, args?.userId);
     const target = resolveSafeToolPath(args?.targetPath, undefined, args?.userId);
 
@@ -1307,7 +1307,7 @@ export async function renamePath(args?: AiJsonObject) {
     };
 }
 
-export async function deletePath(args?: AiJsonObject) {
+export async function deletePath(args?: Record<string, unknown>) {
     const {absolutePath, relativePath, rootDir} = resolveSafeToolPath(
         args?.path,
         ".",
@@ -1350,7 +1350,7 @@ export async function deletePath(args?: AiJsonObject) {
 }
 
 export async function sendFileAsAttachment(
-    args?: AiJsonObject,
+    args?: Record<string, unknown>,
 ): Promise<SendFileAttachmentResult> {
     try {
         const target = resolveSafeToolPath(args?.path, undefined, args?.userId);
@@ -1419,7 +1419,7 @@ export async function sendFileAsAttachment(
     }
 }
 
-export async function beginFileWrite(args?: AiJsonObject) {
+export async function beginFileWrite(args?: Record<string, unknown>) {
     await cleanupExpiredFileWriteSessions();
 
     if (fileWriteSessions.size >= MAX_STREAM_WRITE_SESSIONS) {
@@ -1510,7 +1510,7 @@ export async function beginFileWrite(args?: AiJsonObject) {
     };
 }
 
-export async function writeFileChunk(args?: AiJsonObject) {
+export async function writeFileChunk(args?: Record<string, unknown>) {
     await cleanupExpiredFileWriteSessions();
 
     const session = getFileWriteSession(args?.sessionId);
@@ -1575,7 +1575,7 @@ export async function writeFileChunk(args?: AiJsonObject) {
     };
 }
 
-export async function finishFileWrite(args?: AiJsonObject) {
+export async function finishFileWrite(args?: Record<string, unknown>) {
     await cleanupExpiredFileWriteSessions();
 
     const session = getFileWriteSession(args?.sessionId);
@@ -1634,7 +1634,7 @@ export async function finishFileWrite(args?: AiJsonObject) {
     };
 }
 
-export async function cancelFileWrite(args?: AiJsonObject) {
+export async function cancelFileWrite(args?: Record<string, unknown>) {
     const session = getFileWriteSession(args?.sessionId);
 
     fileWriteSessions.delete(session.sessionId);
@@ -1657,7 +1657,7 @@ export async function cancelFileWrite(args?: AiJsonObject) {
 // Path and filesystem helpers
 // =============================================================================
 
-function parseTelegramUserId(input: AiJsonValue | null | undefined): number | null {
+function parseTelegramUserId(input: unknown): number | null {
     if (input === null || input === undefined) {
         return null;
     }
@@ -1673,7 +1673,7 @@ function parseTelegramUserId(input: AiJsonValue | null | undefined): number | nu
     return input;
 }
 
-function requireFileToolsRootDir(userIdInput?: AiJsonValue | null | undefined): string {
+function requireFileToolsRootDir(userIdInput?: unknown): string {
     const baseRootDir = Environment.FILE_TOOLS_ROOT_DIR as string;
     const userId = parseTelegramUserId(userIdInput);
 
@@ -1695,9 +1695,9 @@ async function ensureFileToolsRootExists(rootDir: string): Promise<void> {
 }
 
 function resolveSafeToolPath(
-    inputPath: AiJsonValue | null | undefined,
+    inputPath: unknown,
     fallback = ".",
-    userIdInput?: AiJsonValue | null | undefined,
+    userIdInput?: unknown,
 ): {
     absolutePath: string;
     relativePath: string;
@@ -1788,8 +1788,11 @@ async function assertNoSymlinkInPath(
             if (stat.isSymbolicLink()) {
                 throw new Error("Symlinks are not allowed in file tool paths.");
             }
-        } catch (error) {
-            if (error instanceof Error && "code" in error && (error as {code?: string}).code === "ENOENT" && options?.allowMissingTail) {
+        } catch (error: unknown) {
+            if (
+                (error as NodeJS.ErrnoException).code === "ENOENT" &&
+                options?.allowMissingTail
+            ) {
                 return;
             }
 
@@ -1802,8 +1805,8 @@ async function pathExists(absolutePath: string): Promise<boolean> {
     try {
         await fs.promises.lstat(absolutePath);
         return true;
-    } catch (error) {
-        if (error instanceof Error && "code" in error && (error as {code?: string}).code === "ENOENT") {
+    } catch (error: unknown) {
+        if ((error as NodeJS.ErrnoException).code === "ENOENT") {
             return false;
         }
 
@@ -1985,7 +1988,7 @@ function isPatchOperationType(value: string): value is PatchOperationType {
     return (PATCH_OPERATION_TYPES as readonly string[]).includes(value);
 }
 
-function parsePatchOperations(input: AiJsonValue | null | undefined): ParsedPatchOperation[] {
+function parsePatchOperations(input: unknown): ParsedPatchOperation[] {
     if (!Array.isArray(input)) {
         throw new Error("operations must be an array.");
     }
@@ -2009,7 +2012,7 @@ function parsePatchOperations(input: AiJsonValue | null | undefined): ParsedPatc
             throw new Error(`Operation #${index} must be an object.`);
         }
 
-        const operation = rawOperation as AiJsonObject;
+        const operation = rawOperation as Record<string, unknown>;
         const rawType = asNonEmptyString(operation.type)?.toLowerCase();
 
         if (!rawType || !isPatchOperationType(rawType)) {
@@ -2192,7 +2195,7 @@ function normalizeForSearch(value: string, caseSensitive: boolean): string {
     return caseSensitive ? value : value.toLowerCase();
 }
 
-function parseSearchExtensions(input: AiJsonValue | null | undefined): string[] | null {
+function parseSearchExtensions(input: unknown): string[] | null {
     if (input === undefined || input === null) {
         return null;
     }
@@ -2382,7 +2385,7 @@ function guessMimeType(fileName: string): string {
 // Chunked write helpers
 // =============================================================================
 
-function parsePositiveInteger(value: AiJsonValue | null | undefined, fieldName: string): number {
+function parsePositiveInteger(value: unknown, fieldName: string): number {
     const numberValue =
         typeof value === "number"
             ? value
@@ -2397,7 +2400,7 @@ function parsePositiveInteger(value: AiJsonValue | null | undefined, fieldName:
     return numberValue;
 }
 
-function getFileWriteSession(sessionIdInput: AiJsonValue | null | undefined): FileWriteSession {
+function getFileWriteSession(sessionIdInput: unknown): FileWriteSession {
     const sessionId = asNonEmptyString(sessionIdInput);
 
     if (!sessionId) {

src/ai/tools/market-rates.ts

@@ -1,7 +1,6 @@
-import {AiTool} from "../tool-types.js";
+import {AiTool} from "../tool-types";
 import axios from "axios";
-import {toolsLogger} from "./tool-logger.js";
-import {AiJsonObject} from "../tool-types.js";
+import {toolsLogger} from "./tool-logger";
 
 const logger = toolsLogger.child("market-rates");
 
@@ -64,15 +63,15 @@ export const getFinancialMarketDataToolPrompt = [
     "- When the user asks for all rates, group fiat currencies separately from crypto and gold.",
 ].join("\n");
 
-export async function getMarketRates(): Promise<AiJsonObject | undefined> {
+export async function getMarketRates(): Promise<unknown | undefined> {
     const startedAt = Date.now();
     try {
         logger.info("start");
         const response = await axios.get("https://apid.r00t.top/api/v2/currency/rates");
         logger.debug("done", {duration: logger.duration(startedAt), status: response.status});
         return response.data;
-    } catch (error) {
-        logger.error("failed", {duration: logger.duration(startedAt), error: error instanceof Error ? error : String(error)});
+    } catch (e: unknown) {
+        logger.error("failed", {duration: logger.duration(startedAt), error: e});
         return undefined;
     }
-}
+}

src/ai/tools/notes.ts

@@ -1,11 +1,10 @@
-import {AiTool} from "../tool-types.js";
+import {AiTool} from "../tool-types";
 import path from "node:path";
 import {readdir, readFile, stat, unlink, writeFile} from "node:fs/promises";
-import {notesDir, notesRootFile} from "../../index.js";
-import {asNonEmptyString} from "./utils.js";
-import {toolsLogger} from "./tool-logger.js";
+import {notesDir, notesRootFile} from "../../index";
+import {asNonEmptyString} from "./utils";
+import {toolsLogger} from "./tool-logger";
 import {z} from "zod";
-import {AiJsonObject} from "../tool-types.js";
 
 const logger = toolsLogger.child("notes");
 
@@ -100,14 +99,14 @@ export async function listNotes(): Promise<ListNotesResult> {
         logger.debug("list.done", {notes: notes.length, duration: logger.duration(startedAt)});
         return {success: true, notes};
     } catch (error) {
-        logger.error("list.failed", {duration: logger.duration(startedAt), error: error instanceof Error ? error : String(error)});
+        logger.error("list.failed", {duration: logger.duration(startedAt), error});
         const errorMessage = error instanceof Error ? error.message : String(error);
         return {success: false, error: `Failed to list notes: ${errorMessage}`};
     }
 }
 
 export async function getNoteContent(
-    args?: AiJsonObject,
+    args?: Record<string, unknown>,
 ): Promise<GetNoteContentResult> {
     const startedAt = Date.now();
     logger.debug("get_content.start", {args});
@@ -146,7 +145,7 @@ export async function getNoteContent(
             content,
         };
     } catch (error) {
-        logger.error("list.failed", {duration: logger.duration(startedAt), error: error instanceof Error ? error : String(error)});
+        logger.error("list.failed", {duration: logger.duration(startedAt), error});
         const errorMessage = error instanceof Error ? error.message : String(error);
         return {success: false, error: `Failed to read note: ${errorMessage}`};
     }
@@ -237,7 +236,7 @@ export const deleteNoteTool = {
 } satisfies AiTool;
 
 export async function updateNoteContent(
-    args?: AiJsonObject,
+    args?: Record<string, unknown>,
 ): Promise<UpdateNoteContentResult> {
     const startedAt = Date.now();
     logger.debug("update_content.start", {args});
@@ -273,14 +272,14 @@ export async function updateNoteContent(
 
         return {success: true, filePath: noteFilePath};
     } catch (error) {
-        logger.error("list.failed", {duration: logger.duration(startedAt), error: error instanceof Error ? error : String(error)});
+        logger.error("list.failed", {duration: logger.duration(startedAt), error});
         const errorMessage = error instanceof Error ? error.message : String(error);
         return {success: false, error: `Failed to update note: ${errorMessage}`};
     }
 }
 
 export async function deleteNote(
-    args?: AiJsonObject,
+    args?: Record<string, unknown>,
 ): Promise<DeleteNoteResult> {
     const startedAt = Date.now();
     logger.debug("delete.start", {args});
@@ -306,7 +305,7 @@ export async function deleteNote(
 
         return {success: true, filePath: noteFilePath};
     } catch (error) {
-        logger.error("list.failed", {duration: logger.duration(startedAt), error: error instanceof Error ? error : String(error)});
+        logger.error("list.failed", {duration: logger.duration(startedAt), error});
         const errorMessage = error instanceof Error ? error.message : String(error);
         return {success: false, error: `Failed to delete note: ${errorMessage}`};
     }
@@ -397,7 +396,7 @@ export const sendNoteAsFileTool = {
 } satisfies AiTool;
 
 export async function sendNoteAsFile(
-    args?: AiJsonObject,
+    args?: Record<string, unknown>,
 ): Promise<GetNoteFileResult> {
     logger.debug("start", {args});
 
@@ -446,4 +445,4 @@ export async function sendNoteAsFile(
         const errorMessage = error instanceof Error ? error.message : String(error);
         return {success: false, error: `Failed to prepare note file: ${errorMessage}`};
     }
-}
+}

src/ai/tools/python-interpretator.ts

@@ -2,11 +2,10 @@ import {spawn} from "node:child_process";
 import {copyFile, lstat, mkdir, readdir, rm, writeFile} from "node:fs/promises";
 import os from "node:os";
 import path from "node:path";
-import {AiTool} from "../tool-types.js";
-import {Environment} from "../../common/environment.js";
-import {toolsLogger} from "./tool-logger.js";
+import {AiTool} from "../tool-types";
+import {Environment} from "../../common/environment";
+import {toolsLogger} from "./tool-logger";
 import {randomUUID} from "node:crypto";
-import {AiJsonObject} from "../tool-types.js";
 
 const logger = toolsLogger.child("python-interpreter");
 
@@ -192,7 +191,7 @@ export const pythonInterpreterTool = {
 } satisfies AiTool;
 
 export async function runPythonInterpreter(
-    rawArgs: string | AiJsonObject | undefined,
+    rawArgs: unknown,
     options: PythonInterpreterOptions = {},
 ): Promise<PythonToolResult> {
     let args: PythonInterpreterArgs;
@@ -203,7 +202,7 @@ export async function runPythonInterpreter(
         return {
             ok: false,
             phase: "internal",
-            error: errorToString(error instanceof Error ? error : String(error)),
+            error: errorToString(error),
         };
     }
 
@@ -433,11 +432,11 @@ async function executePythonCode(
             skippedArtifacts,
         };
     } catch (error) {
-        logger.error("execute.failed", {duration: logger.duration(startedAt), error: error instanceof Error ? error : String(error)});
+        logger.error("execute.failed", {duration: logger.duration(startedAt), error});
         return {
             ok: false,
             phase: "internal",
-            error: errorToString(error instanceof Error ? error : String(error)),
+            error: errorToString(error),
         };
     } finally {
         await rm(tempDir, {
@@ -661,7 +660,7 @@ function mimeTypeFromPath(filePath: string): string | undefined {
 }
 
 function parsePythonInterpreterArgs(
-    rawArgs: string | AiJsonObject | undefined,
+    rawArgs: unknown,
     options: PythonInterpreterOptions,
 ): PythonInterpreterArgs {
     let args = rawArgs;
@@ -674,11 +673,11 @@ function parsePythonInterpreterArgs(
         }
     }
 
-    if (!args || typeof args !== "object" || Array.isArray(args)) {
+    if (!args || typeof args !== "object") {
         throw new Error("Tool arguments must be an object.");
     }
 
-    const record = args as AiJsonObject;
+    const record = args as Record<string, unknown>;
     const code = record.code;
 
     if (typeof code !== "string" || !code.trim()) {
@@ -813,7 +812,7 @@ function buildSafeEnv(tempDir?: string): NodeJS.ProcessEnv {
     };
 }
 
-function errorToString(error: Error | string | object | null | undefined): string {
+function errorToString(error: unknown): string {
     if (error instanceof Error) {
         return error.stack || error.message;
     }

src/ai/tools/registry.ts

@@ -1,17 +1,17 @@
-import {Environment} from "../../common/environment.js";
-import {AiTool} from "../tool-types.js";
-import {WEB_SEARCH_TOOL_NAME, webSearch, webSearchTool, webSearchToolPrompt} from "./web-search.js";
-import {getCurrentDateTime, getCurrentDateTimeTool} from "./datetime.js";
-import {shellExecute, shellExecuteTool} from "./shell.js";
-import {ToolHandler} from "./types.js";
-import {getWeather, getWeatherTool} from "./weather.js";
+import {Environment} from "../../common/environment";
+import {AiTool} from "../tool-types";
+import {WEB_SEARCH_TOOL_NAME, webSearch, webSearchTool, webSearchToolPrompt} from "./web-search";
+import {getCurrentDateTime, getCurrentDateTimeTool} from "./datetime";
+import {shellExecute, shellExecuteTool} from "./shell";
+import {ToolHandler} from "./types";
+import {getWeather, getWeatherTool} from "./weather";
 import {
     GET_FINANCIAL_MARKET_DATA_TOOL_NAME,
     getFinancialMarketData,
     getFinancialMarketDataToolPrompt,
     getMarketRates
-} from "./market-rates.js";
-import {pythonInterpreterTool, runPythonInterpreter} from "./python-interpretator.js";
+} from "./market-rates";
+import {pythonInterpreterTool, runPythonInterpreter} from "./python-interpretator";
 import {
     beginFileWrite,
     beginFileWriteTool,
@@ -44,15 +44,12 @@ import {
     updateFileTool,
     writeFileChunk,
     writeFileChunkTool
-} from "./files.js";
-import {executeMemoryTool, memoryToolPrompt, memoryTools, type MemoryToolName} from "./user-memory.js";
-import {getMcpToolHandlers, getMcpToolPrompts, getMcpTools} from "../mcp/mcp-registry.js";
+} from "./files";
 
 export const defaultTools: AiTool[] = [
     getCurrentDateTimeTool,
     getFinancialMarketData,
-    ...memoryTools,
-];
+]
 
 export const fileTools = [
     readFileTool,
@@ -75,67 +72,44 @@ export const fileTools = [
     deletePathTool,
 ] satisfies AiTool[];
 
-function parseToolNameSet(raw: string | undefined): Set<string> | undefined {
-    if (!raw?.trim()) return undefined;
-
-    const names = raw
-        .split(",")
-        .map(item => item.trim().toLowerCase())
-        .filter(Boolean);
-
-    return names.length ? new Set(names) : undefined;
-}
-
-function isLocalToolEnabled(toolName: string): boolean {
-    if (Environment.DISABLE_LOCAL_TOOLS) return false;
-
-    const allowlist = parseToolNameSet(Environment.LOCAL_TOOL_ALLOWLIST);
-    if (allowlist && !allowlist.has(toolName.toLowerCase())) return false;
-
-    const denylist = parseToolNameSet(Environment.LOCAL_TOOL_DENYLIST);
-    if (denylist && denylist.has(toolName.toLowerCase())) return false;
-
-    return true;
-}
-
-function filterEnabledTools(tools: AiTool[]): AiTool[] {
-    return tools.filter(tool => isLocalToolEnabled(tool.function.name));
-}
+// export const notesFileTools: AiTool[] = [
+//     createNoteTool,
+//     listNotesTool,
+//     getNoteContentTool,
+//     updateNoteContentTool,
+//     deleteNoteTool,
+//     sendNoteAsFileTool,
+//     searchNotesTool
+// ]
 
 export const getTools = (forCreator?: boolean) => {
-    const tools: AiTool[] = [];
-
-    if (Environment.DISABLE_LOCAL_TOOLS) {
-        tools.push(...getMcpTools());
-        return tools;
-    }
-
-    tools.push(...filterEnabledTools(defaultTools));
+    const tools: AiTool[] = [
+        ...defaultTools,
+        // ...notesFileTools
+    ];
 
     if (Environment.BRAVE_SEARCH_API_KEY) {
-        tools.push(...filterEnabledTools([webSearchTool]));
+        tools.push(webSearchTool);
     }
 
     if (Environment.OPEN_WEATHER_MAP_API_KEY) {
-        tools.push(...filterEnabledTools([getWeatherTool]));
+        tools.push(getWeatherTool);
     }
 
     if (Environment.FILE_TOOLS_ROOT_DIR && Environment.ENABLE_FS_TOOLS) {
-        tools.push(...filterEnabledTools(fileTools));
+        tools.push(...fileTools);
     }
 
     if (forCreator) {
         if (Environment.ENABLE_PYTHON_INTERPRETER) {
-            tools.push(...filterEnabledTools([pythonInterpreterTool]));
+            tools.push(pythonInterpreterTool);
         }
 
         if (Environment.ENABLE_UNSAFE_EVAL) {
-            tools.push(...filterEnabledTools([shellExecuteTool]));
+            tools.push(shellExecuteTool);
         }
     }
 
-    tools.push(...getMcpTools());
-
     return tools;
 };
 
@@ -161,83 +135,44 @@ export const fileToolHandlers = {
 };
 
 export const getToolHandlers = () => {
-    const handlers: Record<string, ToolHandler> = {
-        ...getMcpToolHandlers(),
+    let handlers: Record<string, ToolHandler> = {
+        get_datetime: getCurrentDateTime,
+        get_financial_market_data: getMarketRates,
+
+        // create_note: createNote,
+        // list_notes: listNotes,
+        // get_note_content: getNoteContent,
+        // update_note_content: updateNoteContent,
+        // delete_note: deleteNote,
+        // send_note_as_file: sendNoteAsFile,
+        // search_notes: searchNotes,
+
+        ...fileToolHandlers,
+
+
+        python_interpreter: runPythonInterpreter,
+
+        shell_execute: shellExecute,
+
+        web_search: webSearch,
+
+        get_weather: getWeather,
+
     };
 
-    if (Environment.DISABLE_LOCAL_TOOLS) {
-        return handlers;
-    }
-
-    if (isLocalToolEnabled("get_datetime")) handlers.get_datetime = getCurrentDateTime;
-    if (isLocalToolEnabled("get_financial_market_data")) handlers.get_financial_market_data = getMarketRates;
-    for (const tool of memoryTools) {
-        if (!isLocalToolEnabled(tool.function.name)) continue;
-        handlers[tool.function.name] = async (args, context) => {
-            const userId = typeof args?.userId === "number" ? args.userId : undefined;
-            if (!userId) {
-                return {success: false, error: "Missing userId"};
-            }
-
-            return executeMemoryTool(tool.function.name as MemoryToolName, {
-                userId,
-                content: typeof args?.content === "string" ? args.content : undefined,
-            }, context);
-        };
-    }
-
-    if (isLocalToolEnabled("read_file")) handlers.read_file = readFile;
-    if (isLocalToolEnabled("list_directory")) handlers.list_directory = listDirectory;
-    if (isLocalToolEnabled("search_files")) handlers.search_files = searchFiles;
-    if (isLocalToolEnabled("create_file")) handlers.create_file = createFile;
-    if (isLocalToolEnabled("begin_file_write")) handlers.begin_file_write = beginFileWrite;
-    if (isLocalToolEnabled("write_file_chunk")) handlers.write_file_chunk = writeFileChunk;
-    if (isLocalToolEnabled("finish_file_write")) handlers.finish_file_write = finishFileWrite;
-    if (isLocalToolEnabled("cancel_file_write")) handlers.cancel_file_write = cancelFileWrite;
-    if (isLocalToolEnabled("send_file_as_attachment")) handlers.send_file_as_attachment = sendFileAsAttachment;
-    if (isLocalToolEnabled("create_directory")) handlers.create_directory = createDirectory;
-    if (isLocalToolEnabled("copy_path")) handlers.copy_path = copyPath;
-    if (isLocalToolEnabled("update_file")) handlers.update_file = updateFile;
-    if (isLocalToolEnabled("edit_file_patch")) handlers.edit_file_patch = editFilePatch;
-    if (isLocalToolEnabled("rename_path")) handlers.rename_path = renamePath;
-    if (isLocalToolEnabled("delete_path")) handlers.delete_path = deletePath;
-
-    if (isLocalToolEnabled("python_interpreter")) handlers.python_interpreter = (args, _context) => runPythonInterpreter(args);
-    if (isLocalToolEnabled("shell_execute")) handlers.shell_execute = shellExecute;
-    if (isLocalToolEnabled("web_search")) handlers.web_search = webSearch;
-    if (isLocalToolEnabled("get_weather")) handlers.get_weather = getWeather;
-
     return handlers;
 };
 
 export function getToolPrompts(toolNames: string[]): string[] {
-    if (Environment.DISABLE_LOCAL_TOOLS) {
-        return getMcpToolPrompts(toolNames);
-    }
-
     const prompts: string[] = [];
-    const memoryToolNames = new Set(memoryTools.map(tool => tool.function.name));
-    let memoryPromptAdded = false;
 
     for (const toolName of toolNames) {
-        if (!isLocalToolEnabled(toolName)) {
-            continue;
-        }
-
         if (!prompts.includes(fileToolsToolPrompt) &&
             fileTools.map(t => t.function.name).includes(toolName)) {
             prompts.push(fileToolsToolPrompt);
             continue;
         }
 
-        if (memoryToolNames.has(toolName)) {
-            if (!memoryPromptAdded) {
-                prompts.push(memoryToolPrompt);
-                memoryPromptAdded = true;
-            }
-            continue;
-        }
-
         switch (toolName) {
             case GET_FINANCIAL_MARKET_DATA_TOOL_NAME:
                 prompts.push(getFinancialMarketDataToolPrompt);
@@ -250,6 +185,5 @@ export function getToolPrompts(toolNames: string[]): string[] {
         }
     }
 
-    prompts.push(...getMcpToolPrompts(toolNames));
     return prompts;
-}
+}

src/ai/tools/runtime.ts

@@ -1,21 +1,15 @@
-import {getToolHandlers} from "./registry.js";
-import {normalizeToolArguments} from "./utils.js";
-import {PYTHON_INTERPRETER_TOOL_NAME, PythonInterpreterInputFile, runPythonInterpreter} from "./python-interpretator.js";
-import {toolsLogger} from "./tool-logger.js";
-import {AiJsonObject, AiJsonValue} from "../tool-types.js";
-import type {MemoryRuntimeContext} from "./user-memory.js";
-import type {AiRuntimeTarget} from "../ai-runtime-target.js";
-import type {AiProvider} from "../../model/ai-provider.js";
+import {getToolHandlers} from "./registry";
+import {normalizeToolArguments} from "./utils";
+import {PYTHON_INTERPRETER_TOOL_NAME, PythonInterpreterInputFile, runPythonInterpreter} from "./python-interpretator";
+import {toolsLogger} from "./tool-logger";
 
 const logger = toolsLogger.child("runtime");
 
 export type ToolRuntimeContext = {
     pythonInputFiles?: PythonInterpreterInputFile[];
-    provider?: AiProvider;
-    runtimeTarget?: AiRuntimeTarget;
-} & MemoryRuntimeContext;
+};
 
-function stringifyToolResult(result: AiJsonValue): string {
+function stringifyToolResult(result: unknown): string {
     if (typeof result === "string") return result;
     return JSON.stringify(result, null, 2);
 }
@@ -23,7 +17,7 @@ function stringifyToolResult(result: AiJsonValue): string {
 export async function executeToolCall(
     userId: number | undefined | null,
     name: string,
-    args?: string | AiJsonObject,
+    args?: unknown,
     context: ToolRuntimeContext = {},
 ): Promise<string> {
     const startedAt = Date.now();
@@ -53,12 +47,12 @@ export async function executeToolCall(
         }
 
         const arguments1 = normalizeToolArguments(args, userId);
-        const result = await handler(arguments1, context);
+        const result = await handler(arguments1);
         const s = stringifyToolResult(result);
         logger.debug("execute.done", {name, chars: s.length, duration: logger.duration(startedAt)});
         return s;
     } catch (error) {
-        logger.error("execute.failed", {name, duration: logger.duration(startedAt), error: error instanceof Error ? error : String(error)});
+        logger.error("execute.failed", {name, duration: logger.duration(startedAt), error});
         return stringifyToolResult({
             error: error instanceof Error ? error.message : String(error),
         });

src/ai/tools/search-notes.ts

@@ -1,10 +1,9 @@
-import {AiTool} from "../tool-types.js";
+import {AiTool} from "../tool-types";
 import path from "node:path";
 import {readdir, readFile} from "node:fs/promises";
-import {notesDir, notesRootFile} from "../../index.js";
-import {asNonEmptyString} from "./utils.js";
-import {toolsLogger} from "./tool-logger.js";
-import {AiJsonObject, AiJsonValue} from "../tool-types.js";
+import {notesDir, notesRootFile} from "../../index";
+import {asNonEmptyString} from "./utils";
+import {toolsLogger} from "./tool-logger";
 
 const logger = toolsLogger.child("search-notes");
 
@@ -53,7 +52,7 @@ export const searchNotesTool = {
 } satisfies AiTool;
 
 export async function searchNotes(
-    args?: AiJsonObject,
+    args?: Record<string, unknown>,
 ): Promise<SearchNotesResult> {
     const startedAt = Date.now();
     logger.debug("start", {args});
@@ -140,7 +139,7 @@ export async function searchNotes(
     }
 }
 
-function parseSearchLimit(value: AiJsonValue | undefined): number {
+function parseSearchLimit(value: unknown): number {
     const parsed =
         typeof value === "number"
             ? value
@@ -392,4 +391,4 @@ function buildContentSnippet(query: string, content: string): string | undefined
     const suffix = end < content.length ? "..." : "";
 
     return `${prefix}${content.slice(start, end).replace(/\s+/g, " ").trim()}${suffix}`;
-}
+}

src/ai/tools/shell.ts

@@ -1,7 +1,6 @@
 import {AiTool} from "../tool-types";
-import {runCommand} from "../../util/utils.js";
-import {asNonEmptyString} from "./utils.js";
-import {AiJsonObject} from "../tool-types";
+import {runCommand} from "../../util/utils";
+import {asNonEmptyString} from "./utils";
 
 export const shellExecuteTool = {
     type: "function",
@@ -33,7 +32,7 @@ export const shellExecuteToolPrompt = [
     "- The server shell may be Linux/macOS shell, Windows CMD, or Windows PowerShell.",
     "- Do not assume Bash/Linux commands are available.",
     "- Do not assume Windows commands are available.",
-    "- If the current OS/shell is unclear, first run a safe environment inspection command.",
+    "- If the current OS/shell is unknown, first run a safe environment inspection command.",
     "- Safe OS inspection examples:",
     "  - Node.js: `node -p \"process.platform\"`",
     "  - Node.js: `node -p \"process.cwd()\"`",
@@ -100,7 +99,7 @@ export const shellExecuteToolPrompt = [
     "",
 ].join("\n");
 
-export async function shellExecute(args?: AiJsonObject): Promise<string | undefined | null> {
+export async function shellExecute(args?: Record<string, unknown>): Promise<string | undefined | null> {
     const cmd = asNonEmptyString(args?.cmd);
     if (!cmd) return undefined;
 

src/ai/tools/tool-logger.ts

@@ -1,3 +1,3 @@
-import {appLogger} from "../../logging/logger.js";
+import {appLogger} from "../../logging/logger";
 
 export const toolsLogger = appLogger.child("ai-tools");

src/ai/tools/types.ts

@@ -1,4 +1 @@
-import {AiJsonObject, AiJsonValue} from "../tool-types";
-import type {ToolRuntimeContext} from "./runtime.js";
-
-export type ToolHandler = (args?: AiJsonObject, context?: ToolRuntimeContext) => Promise<AiJsonValue | string | null | undefined> | AiJsonValue | string | null | undefined;
+export type ToolHandler = (args?: Record<string, unknown>) => Promise<unknown> | unknown;

src/ai/tools/user-memory.ts

@@ -1,582 +0,0 @@
-import path from "node:path";
-import {readFile, rename, writeFile, mkdir, rm} from "node:fs/promises";
-import {AiProvider} from "../../model/ai-provider.js";
-import {Environment} from "../../common/environment.js";
-import {createMistralClient, createOllamaClient, createOpenAiClient, resolveOptionalAiRuntimeTarget, type AiRuntimeTarget} from "../ai-runtime-target.js";
-import {AiTool} from "../tool-types.js";
-import {toolsLogger} from "./tool-logger.js";
-import {asNonEmptyString} from "./utils.js";
-
-const logger = toolsLogger.child("user-memory");
-
-function memoryDir(): string {
-    return path.join(Environment.DATA_PATH, "memory");
-}
-
-export const USER_MEMORY_MAX_CHARS = 1000;
-
-export type MemoryScope = "user" | "system";
-export type MemoryAction = "add" | "replace" | "remove";
-
-export type MemoryRuntimeContext = {
-    provider?: AiProvider;
-    runtimeTarget?: AiRuntimeTarget;
-};
-
-export type MemoryOperationResult =
-    | {success: true; scope: MemoryScope; filePath: string; content: string; chars: number; compressed: boolean}
-    | {success: false; scope: MemoryScope; error: string};
-
-type CompressionRunResult = {
-    content: string;
-};
-
-export type MemoryCompressionRunner = (params: {
-    target: AiRuntimeTarget;
-    scope: MemoryScope;
-    currentText: string;
-    limit: number;
-}) => Promise<string>;
-
-function extractMistralText(content: unknown): string {
-    if (typeof content === "string") return content;
-    if (!Array.isArray(content)) return "";
-
-    return content
-        .map(part => {
-            if (typeof part === "string") return part;
-            if (part && typeof part === "object" && "text" in part && typeof (part as {text?: unknown}).text === "string") {
-                return (part as {text: string}).text;
-            }
-            return "";
-        })
-        .join("");
-}
-
-export type MemoryToolName =
-    | "read_user_info"
-    | "read_system_info"
-    | "add_user_info"
-    | "add_system_info"
-    | "remove_user_info"
-    | "remove_system_info"
-    | "replace_user_info"
-    | "replace_system_info"
-    | "delete_user_info"
-    | "delete_system_info";
-
-export const MEMORY_TOOL_NAMES: MemoryToolName[] = [
-    "read_user_info",
-    "read_system_info",
-    "add_user_info",
-    "add_system_info",
-    "remove_user_info",
-    "remove_system_info",
-    "replace_user_info",
-    "replace_system_info",
-    "delete_user_info",
-    "delete_system_info",
-];
-
-type MemoryToolSpec = {
-    name: MemoryToolName;
-    scope: MemoryScope;
-    kind: "read" | "write" | "delete";
-    action?: MemoryAction;
-    description: string;
-    prompt: string;
-};
-
-const MEMORY_TOOL_SPECS: MemoryToolSpec[] = [
-    {
-        name: "read_user_info",
-        scope: "user",
-        kind: "read",
-        description: "Read persistent user memory from user.md.",
-        prompt: `Use when you need to inspect remembered user facts before editing or answering.`,
-    },
-    {
-        name: "read_system_info",
-        scope: "system",
-        kind: "read",
-        description: "Read persistent assistant memory from system.md.",
-        prompt: `Use when you need to inspect remembered assistant instructions before editing or answering.`,
-    },
-    {
-        name: "add_user_info",
-        scope: "user",
-        kind: "write",
-        action: "add",
-        description: "Append a durable fact about the user to user.md.",
-        prompt: `Use for new user facts, preferences, identity details, and profile information. Keep the result at or below ${USER_MEMORY_MAX_CHARS} characters.`,
-    },
-    {
-        name: "add_system_info",
-        scope: "system",
-        kind: "write",
-        action: "add",
-        description: "Append a durable instruction about the assistant to system.md.",
-        prompt: `Use for new assistant identity, style, or behavior instructions. Keep the result at or below ${USER_MEMORY_MAX_CHARS} characters.`,
-    },
-    {
-        name: "remove_user_info",
-        scope: "user",
-        kind: "write",
-        action: "remove",
-        description: "Remove a specific user fact or fragment from user.md.",
-        prompt: `Use when the user asks to forget something about themselves. Keep the result at or below ${USER_MEMORY_MAX_CHARS} characters.`,
-    },
-    {
-        name: "remove_system_info",
-        scope: "system",
-        kind: "write",
-        action: "remove",
-        description: "Remove a specific assistant instruction or fragment from system.md.",
-        prompt: `Use when the user asks to forget something about the assistant. Keep the result at or below ${USER_MEMORY_MAX_CHARS} characters.`,
-    },
-    {
-        name: "replace_user_info",
-        scope: "user",
-        kind: "write",
-        action: "replace",
-        description: "Replace user.md completely with a new compact version.",
-        prompt: `Use when the user wants to overwrite all remembered user info, such as "forget everything about me and remember only this". Keep the result at or below ${USER_MEMORY_MAX_CHARS} characters.`,
-    },
-    {
-        name: "replace_system_info",
-        scope: "system",
-        kind: "write",
-        action: "replace",
-        description: "Replace system.md completely with a new compact version.",
-        prompt: `Use when the user wants to overwrite all remembered assistant info or instructions. Keep the result at or below ${USER_MEMORY_MAX_CHARS} characters.`,
-    },
-    {
-        name: "delete_user_info",
-        scope: "user",
-        kind: "delete",
-        description: "Delete the user memory file user.md.",
-        prompt: `Use when the user asks to delete all remembered user info and remove the memory file entirely.`,
-    },
-    {
-        name: "delete_system_info",
-        scope: "system",
-        kind: "delete",
-        description: "Delete the assistant memory file system.md.",
-        prompt: `Use when the user asks to delete all remembered assistant info and remove the memory file entirely.`,
-    },
-];
-
-export const memoryToolPrompt = [
-    "Use the memory tools to manage persistent per-user memory.",
-    "- `read_*` shows the current file content before editing.",
-    "- `user.md` stores durable facts about the user.",
-    "- `system.md` stores durable facts/instructions about the assistant itself.",
-    "- `add_*` appends a new fact or instruction.",
-    "- `remove_*` removes a specific fact or fragment.",
-    "- `replace_*` rewrites the whole file when the user wants to overwrite memory.",
-    "- `delete_*` removes the file entirely.",
-    `- Keep each file at or below ${USER_MEMORY_MAX_CHARS} characters.`,
-].join("\n");
-
-function createMemoryTool(spec: MemoryToolSpec): AiTool {
-    return {
-        type: "function",
-        function: {
-            name: spec.name,
-            description: spec.description,
-            parameters: {
-                type: "object",
-                properties: spec.kind === "read" || spec.kind === "delete" ? {} : {
-                    content: {
-                        type: "string",
-                        description: spec.action === "remove"
-                            ? "Exact text or fragment to remove from memory."
-                            : "Text to append or replace in memory.",
-                    },
-                },
-                required: spec.kind === "read" || spec.kind === "delete" ? [] : ["content"],
-            },
-        },
-    } satisfies AiTool;
-}
-
-export const memoryTools = MEMORY_TOOL_SPECS.map(createMemoryTool);
-
-function normalizeUserId(userId: number): number | null {
-    return Number.isSafeInteger(userId) && userId > 0 ? userId : null;
-}
-
-function normalizeMemoryText(value: string): string {
-    return value.replaceAll("\r\n", "\n");
-}
-
-function getMemoryUserDir(userId: number): string {
-    return path.join(memoryDir(), String(userId));
-}
-
-export function getMemoryFilePath(userId: number, scope: MemoryScope): string {
-    return path.join(getMemoryUserDir(userId), `${scope}.md`);
-}
-
-async function ensureMemoryDir(userId: number): Promise<string> {
-    const dir = getMemoryUserDir(userId);
-    await mkdir(dir, {recursive: true});
-    return dir;
-}
-
-async function readMemoryFile(userId: number, scope: MemoryScope): Promise<string> {
-    const filePath = getMemoryFilePath(userId, scope);
-    try {
-        return normalizeMemoryText(await readFile(filePath, "utf-8"));
-    } catch (error) {
-        if (error instanceof Error && "code" in error && (error as NodeJS.ErrnoException).code === "ENOENT") {
-            return "";
-        }
-
-        throw error;
-    }
-}
-
-async function writeMemoryFile(userId: number, scope: MemoryScope, content: string): Promise<string> {
-    const normalized = normalizeMemoryText(content);
-    const filePath = getMemoryFilePath(userId, scope);
-    await ensureMemoryDir(userId);
-
-    const tempPath = `${filePath}.tmp-${process.pid}-${Date.now()}`;
-    await writeFile(tempPath, normalized, "utf-8");
-    await rename(tempPath, filePath);
-    return filePath;
-}
-
-function trimToLimit(content: string, limit = USER_MEMORY_MAX_CHARS): string {
-    if (content.length <= limit) return content;
-    return content.slice(0, limit).trimEnd();
-}
-
-function stripCodeFences(content: string): string {
-    const trimmed = content.trim();
-    const fenced = trimmed.match(/^```(?:markdown|md)?\s*([\s\S]*?)\s*```$/i);
-    if (fenced?.[1]) return fenced[1].trim();
-    return trimmed;
-}
-
-function sameTarget(left: AiRuntimeTarget | undefined, right: AiRuntimeTarget | undefined): boolean {
-    if (!left || !right) return false;
-    return left.provider === right.provider
-        && left.model === right.model
-        && (left.baseUrl ?? "") === (right.baseUrl ?? "")
-        && (left.apiKey ?? "") === (right.apiKey ?? "");
-}
-
-async function compressWithTarget(params: {
-    target: AiRuntimeTarget;
-    scope: MemoryScope;
-    currentText: string;
-    limit: number;
-}): Promise<CompressionRunResult> {
-    const {target, scope, currentText, limit} = params;
-
-    const systemPrompt = [
-        "You compress persistent memory for a chat bot.",
-        "Return only the rewritten Markdown text.",
-        "Preserve important facts, preferences, identities, instructions, and durable context.",
-        "Remove noise, duplication, stale details, and low-value filler.",
-        `Keep the result at or below ${limit} characters.`,
-        "Do not add explanations, bullet labels, or code fences.",
-    ].join("\n");
-
-    const userPrompt = [
-        `Memory scope: ${scope}`,
-        `Character limit: ${limit}`,
-        "Current memory:",
-        currentText.trim() || "(empty)",
-        "",
-        "Rewrite it as compact Markdown only.",
-    ].join("\n");
-
-    logger.info("compress.start", {provider: target.provider, model: target.model, scope, chars: currentText.length});
-
-    switch (target.provider) {
-        case AiProvider.OPENAI: {
-            const client = createOpenAiClient(target);
-            const response = await client.chat.completions.create({
-                model: target.model,
-                temperature: 0,
-                messages: [
-                    {role: "system", content: systemPrompt},
-                    {role: "user", content: userPrompt},
-                ],
-            });
-            const text = response.choices[0]?.message?.content ?? "";
-            return {content: stripCodeFences(text)};
-        }
-        case AiProvider.MISTRAL: {
-            const client = createMistralClient(target);
-            const response = await client.chat.complete({
-                model: target.model,
-                temperature: 0,
-                messages: [
-                    {role: "system", content: systemPrompt},
-                    {role: "user", content: userPrompt},
-                ],
-            } as Parameters<typeof client.chat.complete>[0]);
-            const text = extractMistralText(response.choices?.[0]?.message?.content);
-            return {content: stripCodeFences(text)};
-        }
-        case AiProvider.OLLAMA: {
-            const client = createOllamaClient(target);
-            const response = await client.chat({
-                model: target.model,
-                stream: false,
-                options: {temperature: 0},
-                messages: [
-                    {role: "system", content: systemPrompt},
-                    {role: "user", content: userPrompt},
-                ],
-            });
-            const text = typeof response.message?.content === "string" ? response.message.content : "";
-            return {content: stripCodeFences(text)};
-        }
-    }
-}
-
-export async function compressMemoryWithFallback(params: {
-    provider?: AiProvider;
-    currentTarget?: AiRuntimeTarget;
-    scope: MemoryScope;
-    currentText: string;
-    limit?: number;
-}, runner: MemoryCompressionRunner = async (input) => (await compressWithTarget(input)).content): Promise<{content: string; compressed: boolean; usedTarget?: AiRuntimeTarget}> {
-    const limit = params.limit ?? USER_MEMORY_MAX_CHARS;
-    const trimmed = normalizeMemoryText(params.currentText);
-    if (trimmed.length <= limit) {
-        return {content: trimmed, compressed: false};
-    }
-
-    const explicitTarget = params.provider ? resolveOptionalAiRuntimeTarget(params.provider, "memoryCompress") : undefined;
-    const targets = [explicitTarget, params.currentTarget].filter((target, index, list): target is AiRuntimeTarget => !!target && list.findIndex(item => sameTarget(item, target)) === index);
-
-    for (const target of targets) {
-        try {
-            const content = trimToLimit(await runner({target, scope: params.scope, currentText: trimmed, limit}), limit);
-            if (content.length <= limit) {
-                return {content, compressed: true, usedTarget: target};
-            }
-        } catch (error) {
-            logger.warn("compress.failed", {
-                provider: params.provider,
-                scope: params.scope,
-                target: target.model,
-                error: error instanceof Error ? error.message : String(error),
-            });
-        }
-    }
-
-    return {content: trimToLimit(trimmed, limit), compressed: true};
-}
-
-async function compressMemoryIfNeeded(params: {
-    userId: number;
-    scope: MemoryScope;
-    content: string;
-    context?: MemoryRuntimeContext;
-    limit?: number;
-}): Promise<{content: string; compressed: boolean}> {
-    const {scope, context, limit = USER_MEMORY_MAX_CHARS} = params;
-    const result = await compressMemoryWithFallback({
-        provider: context?.provider,
-        currentTarget: context?.runtimeTarget,
-        scope,
-        currentText: params.content,
-        limit,
-    });
-
-    if (!result.compressed) {
-        return result;
-    }
-
-    if (result.content.length > limit) {
-        return {content: trimToLimit(result.content, limit), compressed: true};
-    }
-
-    return {content: result.content, compressed: true};
-}
-
-async function finalizeMemoryWrite(params: {
-    userId: number;
-    scope: MemoryScope;
-    content: string;
-    context?: MemoryRuntimeContext;
-}): Promise<{filePath: string; content: string; compressed: boolean}> {
-    const {userId, scope, context} = params;
-    const compressed = await compressMemoryIfNeeded({userId, scope, content: params.content, context});
-    const filePath = await writeMemoryFile(userId, scope, compressed.content);
-    return {filePath, content: compressed.content, compressed: compressed.compressed};
-}
-
-function findMemoryToolSpec(toolName: string): MemoryToolSpec | undefined {
-    return MEMORY_TOOL_SPECS.find(spec => spec.name === toolName);
-}
-
-function isMemoryWriteTool(spec: MemoryToolSpec): spec is MemoryToolSpec & {kind: "write"; action: MemoryAction} {
-    return spec.kind === "write";
-}
-
-export async function buildUserMemoryPrompt(userId: number | undefined | null): Promise<string | undefined> {
-    const normalizedUserId = typeof userId === "number" ? normalizeUserId(userId) : null;
-    if (!normalizedUserId) return undefined;
-
-    const [userMemoryResult, systemMemoryResult] = await Promise.all([
-        readUserMemory(normalizedUserId, "user"),
-        readUserMemory(normalizedUserId, "system"),
-    ]);
-
-    const userMemory = userMemoryResult.success ? userMemoryResult.content : "";
-    const systemMemory = systemMemoryResult.success ? systemMemoryResult.content : "";
-
-    const blocks: string[] = [];
-    if (systemMemory.trim()) {
-        blocks.push([
-            "## Assistant memory (system.md)",
-            "This is information about the assistant and its behavior.",
-            systemMemory.trim(),
-        ].join("\n"));
-    }
-    if (userMemory.trim()) {
-        blocks.push([
-            "## User memory (user.md)",
-            "This is information about the user.",
-            userMemory.trim(),
-        ].join("\n"));
-    }
-
-    return blocks.length ? blocks.join("\n\n") : undefined;
-}
-
-export async function readUserMemory(userId: number, scope: MemoryScope): Promise<MemoryOperationResult> {
-    const normalizedUserId = normalizeUserId(userId);
-    if (!normalizedUserId) {
-        return {success: false, scope, error: "Invalid userId"};
-    }
-
-    try {
-        const content = await readMemoryFile(normalizedUserId, scope);
-        return {
-            success: true,
-            scope,
-            filePath: getMemoryFilePath(normalizedUserId, scope),
-            content,
-            chars: content.length,
-            compressed: false,
-        };
-    } catch (error) {
-        return {success: false, scope, error: error instanceof Error ? error.message : String(error)};
-    }
-}
-
-export async function updateUserMemory(args: {
-    userId: number;
-    scope: MemoryScope;
-    action: MemoryAction;
-    content?: string;
-    context?: MemoryRuntimeContext;
-}): Promise<MemoryOperationResult> {
-    const normalizedUserId = normalizeUserId(args.userId);
-    if (!normalizedUserId) {
-        return {success: false, scope: args.scope, error: "Invalid userId"};
-    }
-
-    try {
-        const current = await readMemoryFile(normalizedUserId, args.scope);
-        let next = current;
-
-        switch (args.action) {
-            case "add": {
-                const content = normalizeMemoryText(asNonEmptyString(args.content) ?? "");
-                if (!content.trim()) {
-                    return {success: false, scope: args.scope, error: "No content provided"};
-                }
-                next = [current.trimEnd(), content.trim()].filter(Boolean).join(current.trim() ? "\n\n" : "");
-                break;
-            }
-            case "replace": {
-                const content = normalizeMemoryText(asNonEmptyString(args.content) ?? "");
-                next = content;
-                break;
-            }
-            case "remove": {
-                const needle = normalizeMemoryText(asNonEmptyString(args.content) ?? "");
-                if (!needle.trim()) {
-                    return {success: false, scope: args.scope, error: "No text to remove provided"};
-                }
-                if (!current.includes(needle)) {
-                    return {success: false, scope: args.scope, error: "Text not found in memory"};
-                }
-                next = current.split(needle).join("").trim();
-                break;
-            }
-        }
-
-        const finalized = await finalizeMemoryWrite({userId: normalizedUserId, scope: args.scope, content: next, context: args.context});
-        logger.debug("write.done", {
-            userId: normalizedUserId,
-            scope: args.scope,
-            chars: finalized.content.length,
-            compressed: finalized.compressed,
-            filePath: finalized.filePath,
-        });
-
-        return {
-            success: true,
-            scope: args.scope,
-            filePath: finalized.filePath,
-            content: finalized.content,
-            chars: finalized.content.length,
-            compressed: finalized.compressed,
-        };
-    } catch (error) {
-        return {success: false, scope: args.scope, error: error instanceof Error ? error.message : String(error)};
-    }
-}
-
-export async function executeMemoryTool(toolName: MemoryToolName, args: {userId: number; content?: string}, context?: MemoryRuntimeContext): Promise<MemoryOperationResult> {
-    const spec = findMemoryToolSpec(toolName);
-    if (!spec) {
-        return {success: false, scope: "user", error: `Unknown memory tool: ${toolName}`};
-    }
-
-    if (spec.kind === "read") {
-        return readUserMemory(args.userId, spec.scope);
-    }
-
-    if (spec.kind === "delete") {
-        return deleteUserMemory(args.userId, spec.scope);
-    }
-
-    if (!isMemoryWriteTool(spec)) {
-        return {success: false, scope: spec.scope, error: `Unsupported memory tool: ${toolName}`};
-    }
-
-    return updateUserMemory({
-        userId: args.userId,
-        scope: spec.scope,
-        action: spec.action,
-        content: args.content,
-        context,
-    });
-}
-
-export async function deleteUserMemory(userId: number, scope: MemoryScope): Promise<MemoryOperationResult> {
-    const normalizedUserId = normalizeUserId(userId);
-    if (!normalizedUserId) {
-        return {success: false, scope, error: "Invalid userId"};
-    }
-
-    const filePath = getMemoryFilePath(normalizedUserId, scope);
-    try {
-        await rm(filePath, {force: true});
-        return {success: true, scope, filePath, content: "", chars: 0, compressed: false};
-    } catch (error) {
-        return {success: false, scope, error: error instanceof Error ? error.message : String(error)};
-    }
-}

src/ai/tools/utils.ts

@@ -1,25 +1,23 @@
 import {Ollama} from "ollama";
-import {toolsLogger} from "./tool-logger.js";
-import {AiJsonObject, AiJsonValue} from "../tool-types";
-import type {BoundaryValue} from "../../common/boundary-types";
+import {toolsLogger} from "./tool-logger";
 
 const logger = toolsLogger.child("utils");
 
-export function asNonEmptyString(value: BoundaryValue): string | undefined {
+export function asNonEmptyString(value: unknown): string | undefined {
     return typeof value === "string" && value.trim().length > 0
         ? value.trim()
         : undefined;
 }
 
-export function normalizeToolArguments(args: string | AiJsonObject | undefined, userId?: number | null): AiJsonObject {
+export function normalizeToolArguments(args: unknown, userId?: number | null): Record<string, unknown> {
     if (!args) return {};
 
     if (typeof args === "string") {
         try {
-            const parsed = JSON.parse(args) as AiJsonValue;
+            const parsed = JSON.parse(args);
 
             if (parsed && typeof parsed === "object" && !Array.isArray(parsed)) {
-                return parsed as AiJsonObject;
+                return parsed as Record<string, unknown>;
             }
         } catch {
             return {
@@ -33,15 +31,15 @@ export function normalizeToolArguments(args: string | AiJsonObject | undefined,
     if (typeof args === "object" && !Array.isArray(args)) {
         const userIdObject = userId ? {"userId": userId} : {};
         return {
-            ...args,
-            ...userIdObject,
-        } as AiJsonObject;
+            ...args as Record<string, unknown>,
+            ...userIdObject as Record<string, unknown>
+        }
     }
 
     return {};
 }
 
-export function asBoolean(value: BoundaryValue, defaultValue = false): boolean {
+export function asBoolean(value: unknown, defaultValue = false): boolean {
     if (typeof value === "boolean") return value;
 
     if (typeof value === "string") {
@@ -54,11 +52,11 @@ export function asBoolean(value: BoundaryValue, defaultValue = false): boolean {
     return defaultValue;
 }
 
-export function asString(value: BoundaryValue, defaultValue = ""): string {
+export function asString(value: unknown, defaultValue = ""): string {
     return typeof value === "string" ? value : defaultValue;
 }
 
-export function asPositiveInt(value: BoundaryValue, defaultValue: number, maxValue: number): number {
+export function asPositiveInt(value: unknown, defaultValue: number, maxValue: number): number {
     const n = typeof value === "number"
         ? value
         : typeof value === "string"
@@ -89,7 +87,7 @@ export async function unloadAllOllamaModels(ollama: Ollama, exceptFor?: string[]
         await Promise.all(unloadPromises);
         logger.info("ollama.unload_all.done", {count: modelsToUnload.length, exceptFor});
     } catch (error) {
-        logger.error("ollama.unload_all.failed", {exceptFor, error: error instanceof Error ? error : String(error)});
+        logger.error("ollama.unload_all.failed", {exceptFor, error});
     }
 }
 
@@ -106,8 +104,8 @@ export async function loadOllamaModel(model: string, ollama: Ollama, contextLeng
         });
         logger.info("ollama.load.done", {model, contextLength});
         return true;
-    } catch (error) {
-        logger.error("ollama.load.failed", {model, contextLength, error: error instanceof Error ? error : String(error)});
+    } catch (e: unknown) {
+        logger.error("ollama.load.failed", {model, contextLength, error: e});
         return false;
     }
-}
+}

src/ai/tools/weather.ts

@@ -1,11 +1,11 @@
 import axios from "axios";
-import {toolsLogger} from "./tool-logger.js";
+import {toolsLogger} from "./tool-logger";
 
 const logger = toolsLogger.child("weather");
-import {Environment} from "../../common/environment.js";
-import {logError} from "../../util/utils.js";
-import {AiJsonObject, AiTool} from "../tool-types.js";
-import {asNonEmptyString} from "./utils.js";
+import {Environment} from "../../common/environment";
+import {logError} from "../../util/utils";
+import {AiTool} from "../tool-types";
+import {asNonEmptyString} from "./utils";
 
 export const getWeatherTool = {
     type: "function",
@@ -45,7 +45,7 @@ export const weatherToolPrompt = [
     "If the city is missing or unclear, ask the user to specify it.",
 ].join("\n");
 
-export async function getWeather(args?: AiJsonObject): Promise<AiJsonObject | null> {
+export async function getWeather(args?: Record<string, unknown>): Promise<Record<string, unknown> | null> {
     const startedAt = Date.now();
     logger.info("start", {args});
     try {
@@ -141,9 +141,9 @@ export async function getWeather(args?: AiJsonObject): Promise<AiJsonObject | nu
                 windSpeed: wind.speed,
             },
         };
-    } catch (error) {
-        logger.error("failed", {duration: logger.duration(startedAt), error: error instanceof Error ? error : String(error)});
-        logError(error instanceof Error ? error : String(error));
+    } catch (e: unknown) {
+        logger.error("failed", {duration: logger.duration(startedAt), error: e});
+        logError(e);
         return null;
     } finally {
         logger.debug("done", {duration: logger.duration(startedAt)});

src/ai/tools/web-search.ts

@@ -1,11 +1,11 @@
 import axios from "axios";
-import {toolsLogger} from "./tool-logger.js";
+import {toolsLogger} from "./tool-logger";
 
 const logger = toolsLogger.child("brave-search");
-import {Environment} from "../../common/environment.js";
-import {logError} from "../../util/utils.js";
-import {AiJsonObject, AiJsonValue, AiTool} from "../tool-types.js";
-import {asBoolean, asNonEmptyString} from "./utils.js";
+import {Environment} from "../../common/environment";
+import {logError} from "../../util/utils";
+import {AiTool} from "../tool-types";
+import {asBoolean, asNonEmptyString} from "./utils";
 
 type BraveSearchProfile = {
     name?: string;
@@ -83,11 +83,11 @@ type BraveSearchApiResponse = {
         results?: BraveSearchResult[];
     };
 
-    faq?: AiJsonValue;
-    infobox?: AiJsonValue;
-    locations?: AiJsonValue;
-    mixed?: AiJsonValue;
-    summarizer?: AiJsonValue;
+    faq?: unknown;
+    infobox?: unknown;
+    locations?: unknown;
+    mixed?: unknown;
+    summarizer?: unknown;
 };
 
 export const WEB_SEARCH_TOOL_NAME = "web_search";
@@ -197,7 +197,7 @@ export const webSearchToolPrompt = [
 ].join("\n");
 
 function asIntegerInRange(
-    value: AiJsonValue | undefined,
+    value: unknown,
     fallback: number,
     min: number,
     max: number,
@@ -216,7 +216,7 @@ function asIntegerInRange(
 }
 
 function asEnum<T extends string>(
-    value: AiJsonValue | undefined,
+    value: unknown,
     allowed: readonly T[],
     fallback: T,
 ): T {
@@ -229,7 +229,7 @@ function asEnum<T extends string>(
         : fallback;
 }
 
-function cleanSearchText(value: AiJsonValue | undefined): string | null {
+function cleanSearchText(value: unknown): string | null {
     if (typeof value !== "string") return null;
 
     return value
@@ -243,7 +243,7 @@ function cleanSearchText(value: AiJsonValue | undefined): string | null {
         .trim() || null;
 }
 
-function normalizeBraveResultFilter(value: AiJsonValue | undefined): string {
+function normalizeBraveResultFilter(value: unknown): string {
     const allowed = new Set([
         "discussions",
         "faq",
@@ -268,7 +268,7 @@ function normalizeBraveResultFilter(value: AiJsonValue | undefined): string {
     return parts.length ? [...new Set(parts)].join(",") : "web";
 }
 
-export async function webSearch(args?: AiJsonObject) {
+export async function webSearch(args?: Record<string, unknown>) {
     const startedAt = Date.now();
     logger.info("start", {args});
 
@@ -362,16 +362,17 @@ export async function webSearch(args?: AiJsonObject) {
 
             note: "Use returned URLs as sources. Do not invent facts that are not present in the snippets/results.",
         };
-    } catch (error) {
-        logError(error instanceof Error ? error : String(error));
+    } catch (e: unknown) {
+        logError(e);
 
-        const status = axios.isAxiosError(error) ? error.response?.status : undefined;
-        const data = axios.isAxiosError(error) ? error.response?.data : undefined;
+        const axiosLike = e as {response?: {status?: unknown; data?: unknown}};
+        const status = axiosLike.response?.status;
+        const data = axiosLike.response?.data;
 
         return {
             ok: false,
             status: typeof status === "number" ? status : null,
-            error: error instanceof Error ? error.message : String(error),
+            error: e instanceof Error ? e.message : String(e),
             response: data ?? null,
         };
     } finally {

src/ai/transcript-artifact-store.ts

@@ -1,42 +0,0 @@
-import {AiProvider} from "../model/ai-provider";
-import type {StoredAttachment} from "../model/stored-attachment";
-import type {AiDownloadedFile} from "./telegram-attachments";
-import {persistInternalJsonArtifactAttachment} from "./internal-artifact-store";
-
-export async function persistTranscriptArtifactAttachment(params: {
-    provider: AiProvider;
-    transcript: string;
-    downloads: AiDownloadedFile[];
-    chatId: number;
-    messageId: number;
-}): Promise<StoredAttachment | undefined> {
-    const text = params.transcript.trim();
-    if (!text) return Promise.resolve(undefined);
-
-    const sources = params.downloads
-        .filter(download => download.kind === "audio" || download.kind === "video-note")
-        .map(download => ({
-            fileId: download.fileId,
-            fileName: download.fileName,
-            mimeType: download.mimeType,
-            sizeBytes: download.sizeBytes ?? download.buffer.length,
-            sha256: download.sha256,
-        }));
-
-    return await persistInternalJsonArtifactAttachment({
-        artifactKind: "transcript",
-        fileNamePrefix: "transcript",
-        chatId: params.chatId,
-        messageId: params.messageId,
-        payload: {
-            provider: params.provider,
-            transcript: text,
-            sources,
-        },
-        metadata: {
-            provider: params.provider,
-            sourceFileNames: sources.map(source => source.fileName),
-            transcriptChars: text.length,
-        },
-    });
-}

src/ai/unified-ai-request-pipeline.ts

@@ -1,373 +0,0 @@
-import {AiProvider} from "../model/ai-provider";
-import {AI_VOICE_MODE_TRANSCRIPT, DEFAULT_AI_RESPONSE_LANGUAGE} from "../common/user-ai-settings";
-import {Environment} from "../common/environment";
-import {UserRequestPipeline, type UserRequestPipelineState, type UserRequestPipelineStage} from "./user-request-pipeline";
-import {PipelineFallbackNotifier} from "./user-request-pipeline/fallback-notifier";
-import {buildToolRankFallbackTargetDetails} from "./user-request-pipeline/fallback-target-details";
-import {mergeReplyChainDownloads, shouldPreferCurrentDownloads} from "./reply-chain-downloads";
-import {attachmentsToDownloadedFiles, type AiDownloadedFile} from "./telegram-attachments";
-import type {TelegramStreamMessage} from "./telegram-stream-message";
-import type {ChatMessage} from "./chat-messages-types";
-import type {OpenAIChatMessage} from "./openai-chat-message";
-import type {MistralChatMessage} from "./mistral-chat-message";
-import type {PreparedDocumentRag} from "./document-rag-pipeline";
-import {prepareDocumentRag} from "./document-rag-pipeline";
-import {persistRagArtifactAttachment} from "./rag-artifact-store";
-import {persistTranscriptArtifactAttachment} from "./transcript-artifact-store";
-import type {ToolRuntimeContext} from "./tools/runtime";
-import {recordPipelineFallback, recordRagRun} from "../common/ai-observability.js";
-import {
-    appendTranscriptToChatMessages,
-    collectTextMessages,
-    initialStatus,
-    providerName,
-    RuntimeConfigSnapshot,
-    stripAudioFromRunnerMessages,
-    toolRuntimeContextFromDownloads,
-    transcribeAudioIfNeeded,
-    collectStoredReplyChainAttachments,
-    UnifiedRunOptions,
-} from "./unified-ai-runner.shared";
-import {aiLog} from "../logging/ai-logger";
-import {isTranscribableAudioDownload} from "./speech-to-text";
-
-export type PreparedUnifiedAiRequest = {
-    chatMessages: Array<OpenAIChatMessage | MistralChatMessage | ChatMessage>;
-    imageCount: number;
-    firstRoundStatus: string;
-    toolContext: ToolRuntimeContext;
-    preparedDocumentRag?: PreparedDocumentRag;
-    finishAfterTranscript: boolean;
-    cleanup: () => Promise<void>;
-};
-
-type MutablePreparedContext = {
-    chatMessages: Array<OpenAIChatMessage | MistralChatMessage | ChatMessage>;
-    imageCount: number;
-    firstRoundStatus: string;
-    toolContext: ToolRuntimeContext;
-    transcript: string;
-    preparedDocumentRag?: PreparedDocumentRag;
-    finishAfterTranscript: boolean;
-};
-
-function nowIso(): string {
-    return new Date().toISOString();
-}
-
-function runtimeTargetFor(options: UnifiedRunOptions, config: RuntimeConfigSnapshot) {
-    return options.provider === AiProvider.OLLAMA
-        ? config.ollamaChatTarget
-        : options.provider === AiProvider.MISTRAL
-            ? config.mistralChatTarget
-            : config.openAiChatTarget;
-}
-
-function createAiRequestPipelineState(options: UnifiedRunOptions): UserRequestPipelineState {
-    return {
-        requestId: options.requestId ?? `ai:${options.msg.chat.id}:${options.msg.message_id}:${Date.now()}`,
-        chatId: options.msg.chat.id,
-        messageId: options.msg.message_id,
-        replyToMessageId: options.msg.reply_to_message?.message_id,
-        fromId: options.msg.from?.id ?? 0,
-        receivedAt: nowIso(),
-        text: options.text,
-        settings: {
-            provider: options.provider,
-            responseLanguage: options.responseLanguage ?? DEFAULT_AI_RESPONSE_LANGUAGE,
-            contextSize: options.contextSize,
-            voiceMode: options.voiceMode ?? "execute",
-            imageOutputMode: "photo",
-        },
-        inputAttachments: [],
-        outputAttachments: [],
-        artifacts: [],
-        toolRankDecisions: [],
-        audit: [],
-    };
-}
-
-export async function prepareUnifiedAiRequestPipeline(params: {
-    options: UnifiedRunOptions;
-    config: RuntimeConfigSnapshot;
-    downloads: AiDownloadedFile[];
-    streamMessage: TelegramStreamMessage;
-    controller: AbortController;
-}): Promise<PreparedUnifiedAiRequest> {
-    const {options, config, downloads, streamMessage, controller} = params;
-    const replyChainDownloads = shouldPreferCurrentDownloads(options.text, downloads)
-        ? downloads
-        : mergeReplyChainDownloads(
-            downloads,
-            attachmentsToDownloadedFiles(await collectStoredReplyChainAttachments(options.msg)),
-        );
-    const prepared: MutablePreparedContext = {
-        chatMessages: [],
-        imageCount: 0,
-        firstRoundStatus: Environment.waitThinkText,
-        toolContext: {},
-        transcript: "",
-        finishAfterTranscript: false,
-    };
-
-    const stages: UserRequestPipelineStage[] = [
-        {
-            name: "audit_start",
-            async run() {
-                return {
-                    stage: "audit_start",
-                    status: "succeeded",
-                    details: {
-                        phase: "ai_request_prepare",
-                        provider: options.provider,
-                        downloads: replyChainDownloads.map(download => ({
-                            kind: download.kind,
-                            fileName: download.fileName,
-                            mimeType: download.mimeType,
-                            sizeBytes: download.sizeBytes ?? download.buffer.length,
-                        })),
-                    },
-                };
-            },
-        },
-        {
-            name: "collect_conversation_context",
-            async run() {
-                const collected = await collectTextMessages(
-                    options.msg,
-                    options.text,
-                    options.provider,
-                    replyChainDownloads,
-                    config,
-                    runtimeTargetFor(options, config),
-                    options.responseLanguage ?? DEFAULT_AI_RESPONSE_LANGUAGE,
-                );
-                prepared.chatMessages = collected.chatMessages as typeof prepared.chatMessages;
-                prepared.imageCount = collected.imageCount;
-                prepared.firstRoundStatus = initialStatus(replyChainDownloads, prepared.imageCount);
-                prepared.toolContext = toolRuntimeContextFromDownloads(replyChainDownloads);
-
-                return {
-                    stage: "collect_conversation_context",
-                    status: "succeeded",
-                };
-            },
-        },
-        {
-            name: "prepare_text_context",
-            async run() {
-                streamMessage.setStatus(prepared.firstRoundStatus);
-                await streamMessage.flush();
-
-                return {
-                    stage: "prepare_text_context",
-                    status: "succeeded",
-                };
-            },
-        },
-        {
-            name: "resolve_runtime",
-            async run() {
-                return {
-                    stage: "resolve_runtime",
-                    status: "succeeded",
-                };
-            },
-        },
-        {
-            name: "speech_to_text",
-            async run() {
-                prepared.transcript = await transcribeAudioIfNeeded(
-                    options.provider,
-                    options.msg.from?.id,
-                    replyChainDownloads,
-                    streamMessage,
-                    controller.signal,
-                ).catch(error => {
-                    if (replyChainDownloads.some(isTranscribableAudioDownload)) throw error;
-                    return "";
-                });
-
-                const transcript = prepared.transcript.trim();
-                if (!transcript) {
-                    return {
-                        stage: "speech_to_text",
-                        status: "skipped",
-                    };
-                }
-
-                const transcriptArtifact = await persistTranscriptArtifactAttachment({
-                    provider: options.provider,
-                    transcript,
-                    downloads: replyChainDownloads,
-                    chatId: options.msg.chat.id,
-                    messageId: options.msg.message_id,
-                });
-                if (transcriptArtifact) {
-                    await streamMessage.storeInternalAttachment(transcriptArtifact);
-                }
-
-                if (options.voiceMode === AI_VOICE_MODE_TRANSCRIPT) {
-                    prepared.finishAfterTranscript = true;
-                    streamMessage.replaceText(`[Расшифровка]\n${transcript}`);
-                    await streamMessage.finish();
-                    return {
-                        stage: "speech_to_text",
-                        status: "succeeded",
-                        fallbackAction: "continue_without_stage",
-                    };
-                }
-
-                appendTranscriptToChatMessages(prepared.chatMessages, transcript);
-                stripAudioFromRunnerMessages(prepared.chatMessages);
-                aiLog("debug", "request.transcript.appended", {
-                    provider: providerName(options.provider),
-                    transcriptChars: transcript.length,
-                    chatMessages: prepared.chatMessages.length,
-                });
-
-                return {
-                    stage: "speech_to_text",
-                    status: "succeeded",
-                };
-            },
-        },
-        {
-            name: "document_rag",
-            async run() {
-                if (prepared.finishAfterTranscript) {
-                    return {
-                        stage: "document_rag",
-                        status: "skipped",
-                    };
-                }
-
-                prepared.preparedDocumentRag = await prepareDocumentRag(
-                    options.provider,
-                    replyChainDownloads,
-                    prepared.chatMessages,
-                    streamMessage,
-                    config,
-                    controller.signal,
-                    options.text,
-                );
-
-                const ragArtifact = await persistRagArtifactAttachment({
-                    provider: options.provider,
-                    prepared: prepared.preparedDocumentRag,
-                    downloads: replyChainDownloads,
-                    chatId: options.msg.chat.id,
-                    messageId: options.msg.message_id,
-                    details: prepared.preparedDocumentRag?.provider === AiProvider.OPENAI
-                        ? {uploadedFileIds: prepared.preparedDocumentRag.uploadedFileIds}
-                        : prepared.preparedDocumentRag?.provider === AiProvider.OLLAMA
-                            ? {
-                                embeddingModel: config.ollamaDocumentsTarget.model,
-                                topK: config.ollamaRagTopK,
-                                chunkSize: config.ollamaRagChunkSize,
-                                chunkOverlap: config.ollamaRagChunkOverlap,
-                                maxContextChars: config.ollamaRagMaxContextChars,
-                                artifact: prepared.preparedDocumentRag.artifact,
-                            }
-                            : undefined,
-                });
-                if (ragArtifact) {
-                    await streamMessage.storeInternalAttachment(ragArtifact);
-                }
-
-                if (prepared.preparedDocumentRag) {
-                    recordRagRun();
-                }
-
-                return {
-                    stage: "document_rag",
-                    status: prepared.preparedDocumentRag ? "succeeded" : "skipped",
-                };
-            },
-        },
-        {
-            name: "audit_finish",
-            async run() {
-                return {
-                    stage: "audit_finish",
-                    status: "succeeded",
-                    details: {
-                        phase: "ai_request_prepare",
-                        chatMessages: prepared.chatMessages.length,
-                        imageCount: prepared.imageCount,
-                        hasTranscript: !!prepared.transcript.trim(),
-                        hasDocumentRag: !!prepared.preparedDocumentRag,
-                        finishAfterTranscript: prepared.finishAfterTranscript,
-                    },
-                };
-            },
-        },
-    ];
-
-    const state = createAiRequestPipelineState(options);
-    const fallbackNotifier = new PipelineFallbackNotifier(options.msg, options.responseLanguage);
-    const pipeline = new UserRequestPipeline({
-        stages,
-        stageNames: [
-            "audit_start",
-            "collect_conversation_context",
-            "prepare_text_context",
-            "resolve_runtime",
-            "speech_to_text",
-            "document_rag",
-            "audit_finish",
-        ],
-        onFallback: async decision => {
-            recordPipelineFallback(decision.action);
-            if (decision.action === "use_alternate_target") {
-                aiLog("warn", "request.fallback.use_alternate_target", {
-                    provider: options.provider,
-                    stage: decision.stage,
-                    reason: decision.reason,
-                    requestId: state.requestId,
-                    ...buildToolRankFallbackTargetDetails(options.provider, config),
-                });
-            }
-
-            if (decision.action === "fail_request") {
-                aiLog("error", "request.fallback.fail_request", {
-                    provider: options.provider,
-                    stage: decision.stage,
-                    reason: decision.reason,
-                    requestId: state.requestId,
-                });
-            }
-
-            const notification = await fallbackNotifier.notify(state.requestId, decision);
-            state.audit.push({
-                stage: decision.stage,
-                status: "fallback",
-                startedAt: nowIso(),
-                finishedAt: nowIso(),
-                details: {
-                    fallbackAction: decision.action,
-                    fallbackNotification: notification.text,
-                    fallbackNotified: notification.notified,
-                    reason: decision.reason,
-                    ...(decision.action === "use_alternate_target"
-                        ? buildToolRankFallbackTargetDetails(options.provider, config)
-                        : {}),
-                },
-            });
-        },
-    });
-    await pipeline.run(state, controller.signal);
-    await streamMessage.storePipelineAudit(state.audit);
-
-    return {
-        chatMessages: prepared.chatMessages,
-        imageCount: prepared.imageCount,
-        firstRoundStatus: prepared.firstRoundStatus,
-        toolContext: prepared.toolContext,
-        preparedDocumentRag: prepared.preparedDocumentRag,
-        finishAfterTranscript: prepared.finishAfterTranscript,
-        cleanup: async () => {
-            await prepared.preparedDocumentRag?.cleanup();
-        },
-    };
-}

src/ai/unified-ai-response-pipeline.ts

@@ -1,486 +0,0 @@
-import {AiProvider} from "../model/ai-provider";
-import {Environment} from "../common/environment";
-import {ifTrue, logError} from "../util/utils";
-import {UserRequestPipeline, type UserRequestPipelineState, type UserRequestPipelineStage} from "./user-request-pipeline";
-import {getProviderAdapter} from "./provider-adapters";
-import type {AiDownloadedFile} from "./telegram-attachments";
-import type {TelegramStreamMessage} from "./telegram-stream-message";
-import type {PreparedUnifiedAiRequest} from "./unified-ai-request-pipeline";
-import type {OpenAIChatMessage} from "./openai-chat-message";
-import type {MistralChatMessage} from "./mistral-chat-message";
-import type {ChatMessage} from "./chat-messages-types";
-import {
-    allToolSchemaNames,
-    providerName,
-    RuntimeConfigSnapshot,
-    snapshotModel,
-    TELEGRAM_LIMIT,
-    UnifiedRunOptions,
-} from "./unified-ai-runner.shared";
-import {runToolRankStage} from "./tool-rank-stage";
-import {runOpenAi} from "./unified-ai-runner.openai";
-import {runOpenAiCompatible} from "./unified-ai-runner.openai-compatible";
-import {runOllama} from "./unified-ai-runner.ollama";
-import {runMistral} from "./unified-ai-runner.mistral";
-import {summarizeModelOutput} from "./response-model-output";
-import {summarizeToolLoop} from "./tool-loop-summary";
-import {persistToolLoopSummaryArtifactAttachment} from "./tool-loop-artifact-store";
-import {PipelineFallbackNotifier} from "./user-request-pipeline/fallback-notifier";
-import {buildToolRankFallbackTargetDetails} from "./user-request-pipeline/fallback-target-details";
-import {
-    resolveTextToSpeechProviderForUser,
-    sendSynthesizedSpeech,
-    speechToOutputAttachmentRecord,
-    synthesizeSpeech
-} from "./text-to-speech";
-import {persistFinalTextArtifactAttachment} from "./final-response-artifact-store";
-import {aiLog} from "../logging/ai-logger";
-import {recordPipelineFallback, recordTtsRun} from "../common/ai-observability.js";
-
-function nowIso(): string {
-    return new Date().toISOString();
-}
-
-function createResponsePipelineState(options: UnifiedRunOptions): UserRequestPipelineState {
-    return {
-        requestId: options.requestId ?? `ai-response:${options.msg.chat.id}:${options.msg.message_id}:${Date.now()}`,
-        chatId: options.msg.chat.id,
-        messageId: options.msg.message_id,
-        replyToMessageId: options.msg.reply_to_message?.message_id,
-        fromId: options.msg.from?.id ?? 0,
-        receivedAt: nowIso(),
-        text: options.text,
-        settings: {
-            provider: options.provider,
-            responseLanguage: options.responseLanguage ?? "default",
-            contextSize: options.contextSize,
-            voiceMode: options.voiceMode ?? "execute",
-            imageOutputMode: "photo",
-        },
-        inputAttachments: [],
-        outputAttachments: [],
-        artifacts: [],
-        toolRankDecisions: [],
-        audit: [],
-    };
-}
-
-async function runProviderModelCall(params: {
-    options: UnifiedRunOptions;
-    config: RuntimeConfigSnapshot;
-    downloads: AiDownloadedFile[];
-    prepared: PreparedUnifiedAiRequest;
-    streamMessage: TelegramStreamMessage;
-    signal: AbortSignal;
-}): Promise<void> {
-    const {options, config, downloads, prepared, streamMessage, signal} = params;
-    const preparedDocumentRag = prepared.preparedDocumentRag;
-    const documents = preparedDocumentRag?.provider === AiProvider.MISTRAL ? preparedDocumentRag.documents : [];
-
-    aiLog("info", "request.provider.dispatch", {provider: providerName(options.provider)});
-
-    switch (options.provider) {
-        case AiProvider.OPENAI:
-            if (config.openAiBackend === "compatible") {
-                await runOpenAiCompatible(
-                    options.msg,
-                    prepared.chatMessages as OpenAIChatMessage[],
-                    streamMessage,
-                    signal,
-                    options.stream ?? true,
-                    options.msg,
-                    config,
-                    prepared.toolContext,
-                    downloads,
-                );
-                return;
-            }
-
-            await runOpenAi(
-                options.msg,
-                prepared.chatMessages as OpenAIChatMessage[],
-                streamMessage,
-                signal,
-                options.stream ?? true,
-                options.msg,
-                config,
-                prepared.toolContext,
-                downloads,
-                preparedDocumentRag?.provider === AiProvider.OPENAI ? preparedDocumentRag : undefined,
-            );
-            return;
-        case AiProvider.OLLAMA:
-            if (config.ollamaChatTarget.model?.includes("gpt-oss") && options.think) {
-                options.think = "high";
-            }
-
-            await runOllama(
-                options.msg,
-                prepared.chatMessages as ChatMessage[],
-                streamMessage,
-                signal,
-                ifTrue(options.stream),
-                options.think ?? false,
-                prepared.firstRoundStatus,
-                config,
-                prepared.toolContext,
-                options.contextSize,
-            );
-            return;
-        case AiProvider.MISTRAL:
-            await runMistral(
-                options.msg,
-                prepared.chatMessages as MistralChatMessage[],
-                documents,
-                streamMessage,
-                signal,
-                options.stream ?? true,
-                prepared.firstRoundStatus,
-                config,
-                prepared.toolContext,
-            );
-    }
-}
-
-async function synthesizeResponseIfRequested(params: {
-    options: UnifiedRunOptions;
-    config: RuntimeConfigSnapshot;
-    streamMessage: TelegramStreamMessage;
-}): Promise<"succeeded" | "skipped" | "failed"> {
-    const {options, config, streamMessage} = params;
-
-    if (!options.synthesizeSpeechResponse) return "skipped";
-    const text = streamMessage.getText().trim();
-    if (!text) return "skipped";
-
-    try {
-        if (!options.msg.from?.id) {
-            throw new Error(Environment.couldNotIdentifyUserForSpeechToTextText);
-        }
-
-        const resolved = await resolveTextToSpeechProviderForUser(options.msg.from.id, options.provider)
-            .catch(() => resolveTextToSpeechProviderForUser(options.msg.from!.id));
-        const speech = await synthesizeSpeech({provider: resolved.provider, text});
-        const sent = await sendSynthesizedSpeech(options.msg, speech);
-        streamMessage.recordOutputAttachment(speechToOutputAttachmentRecord(speech, sent.message_id));
-        return "succeeded";
-    } catch (error) {
-        aiLog("error", "text_to_speech.failed", {
-            provider: providerName(options.provider),
-            model: snapshotModel(options.provider, config),
-            error: error instanceof Error ? error.message : String(error),
-        });
-        return "failed";
-    }
-}
-
-export async function runUnifiedAiResponsePipeline(params: {
-    options: UnifiedRunOptions;
-    config: RuntimeConfigSnapshot;
-    downloads: AiDownloadedFile[];
-    prepared: PreparedUnifiedAiRequest;
-    streamMessage: TelegramStreamMessage;
-    controller: AbortController;
-}): Promise<void> {
-    const {options, config, downloads, prepared, streamMessage, controller} = params;
-    const state = createResponsePipelineState(options);
-    const fallbackNotifier = new PipelineFallbackNotifier(options.msg, options.responseLanguage);
-    const adapter = getProviderAdapter(options.provider);
-    let selectedToolNames: string[] = [];
-    let filteredTools: unknown[] = [];
-
-    const stages: UserRequestPipelineStage[] = [
-        {
-            name: "audit_start",
-            async run() {
-                return {
-                    stage: "audit_start",
-                    status: "succeeded",
-                    details: {
-                        phase: "ai_response",
-                        provider: options.provider,
-                        model: snapshotModel(options.provider, config),
-                        chatMessages: prepared.chatMessages.length,
-                        hasDocumentRag: !!prepared.preparedDocumentRag,
-                    },
-                };
-            },
-        },
-        {
-            name: "tool_rank",
-            async run() {
-                const availableTools = adapter.rankTools(config, {
-                    forCreator: options.msg.from?.id === Environment.CREATOR_ID,
-                    vectorStoreIds: prepared.preparedDocumentRag?.provider === AiProvider.OPENAI
-                        ? prepared.preparedDocumentRag.vectorStoreIds
-                        : [],
-                });
-
-                const rankResult = await runToolRankStage({
-                    provider: options.provider,
-                    model: snapshotModel(options.provider, config),
-                    round: state.toolRankDecisions.length,
-                    config,
-                    availableTools,
-                    messages: prepared.chatMessages,
-                    streamMessage,
-                    signal: controller.signal,
-                });
-
-                selectedToolNames = rankResult.selectedToolNames;
-                filteredTools = rankResult.filteredTools;
-                state.toolRankDecisions.push({
-                    provider: options.provider,
-                    round: state.toolRankDecisions.length,
-                    availableTools: allToolSchemaNames(availableTools),
-                    selectedTools: selectedToolNames,
-                    usedRanker: rankResult.usedRanker,
-                });
-
-                return {
-                    stage: "tool_rank",
-                    status: "succeeded",
-                    details: {
-                        selectedTools: selectedToolNames,
-                        usedRanker: rankResult.usedRanker,
-                        availableTools: allToolSchemaNames(availableTools),
-                        toolRankDecision: state.toolRankDecisions.at(-1),
-                    },
-                };
-            },
-        },
-        {
-            name: "filter_tools",
-            async run() {
-                return {
-                    stage: "filter_tools",
-                    status: "succeeded",
-                    details: {
-                        selectedTools: selectedToolNames,
-                        filteredToolCount: filteredTools.length,
-                    },
-                };
-            },
-        },
-        {
-            name: "model_call",
-            async run() {
-                await runProviderModelCall({
-                    options,
-                    config,
-                    downloads,
-                    prepared,
-                    streamMessage,
-                    signal: controller.signal,
-                });
-
-                return {
-                    stage: "model_call",
-                    status: "succeeded",
-                    details: {
-                        modelOutput: summarizeModelOutput({
-                            text: streamMessage.getText(),
-                            toolExecutions: streamMessage.getToolExecutions(),
-                            outputAttachments: streamMessage.getOutputAttachments(),
-                        }),
-                    },
-                };
-            },
-        },
-        {
-            name: "tool_loop",
-            async run() {
-                const executions = streamMessage.getToolExecutions();
-                const outputAttachments = streamMessage.getOutputAttachments();
-                const summary = summarizeToolLoop({
-                    text: streamMessage.getText(),
-                    executions,
-                    outputAttachments,
-                });
-                const persisted = await persistToolLoopSummaryArtifactAttachment({
-                    chatId: options.msg.chat.id,
-                    messageId: options.msg.message_id,
-                    text: streamMessage.getText(),
-                    executions,
-                    outputAttachments,
-                });
-
-                if (persisted) {
-                    await streamMessage.storeInternalAttachment(persisted);
-                }
-
-                return {
-                    stage: "tool_loop",
-                    ...summary,
-                    details: {
-                        ...summary.details,
-                        persistedSummaryArtifact: !!persisted,
-                    },
-                };
-            },
-        },
-        {
-            name: "output_size_gate",
-            async run() {
-                const originalChars = streamMessage.getText().length;
-                if (originalChars > TELEGRAM_LIMIT) {
-                    streamMessage.replaceText(streamMessage.getText().slice(0, TELEGRAM_LIMIT - 3) + "...");
-                }
-
-                return {
-                    stage: "output_size_gate",
-                    status: originalChars > TELEGRAM_LIMIT ? "fallback" : "succeeded",
-                    fallbackAction: originalChars > TELEGRAM_LIMIT ? "notify_user" : undefined,
-                };
-            },
-        },
-        {
-            name: "send_response",
-            async run() {
-                await streamMessage.finish();
-                return {
-                    stage: "send_response",
-                    status: "succeeded",
-                };
-            },
-        },
-        {
-            name: "persist_output_artifacts",
-            async run() {
-                const outputAttachments = streamMessage.getOutputAttachments();
-                const artifact = await persistFinalTextArtifactAttachment({
-                    provider: options.provider,
-                    model: snapshotModel(options.provider, config),
-                    text: streamMessage.getText(),
-                    chatId: options.msg.chat.id,
-                    messageId: options.msg.message_id,
-                });
-
-                if (artifact) {
-                    await streamMessage.storeInternalAttachment(artifact);
-                }
-
-                return {
-                    stage: "persist_output_artifacts",
-                    status: artifact || outputAttachments.length ? "succeeded" : "skipped",
-                    details: {
-                        finalTextPersisted: !!artifact,
-                        outputAttachments,
-                    },
-                };
-            },
-        },
-        {
-            name: "text_to_speech",
-            async run() {
-                const status = await synthesizeResponseIfRequested({options, config, streamMessage});
-                recordTtsRun(status);
-                return {
-                    stage: "text_to_speech",
-                    status,
-                    fallbackAction: status === "failed" ? "continue_without_stage" : undefined,
-                };
-            },
-        },
-        {
-            name: "audit_finish",
-            async run() {
-                return {
-                    stage: "audit_finish",
-                    status: "succeeded",
-                    details: {
-                        phase: "ai_response",
-                        textChars: streamMessage.getText().length,
-                        toolExecutions: streamMessage.getToolExecutions().length,
-                        outputAttachments: streamMessage.getOutputAttachments().length,
-                    },
-                };
-            },
-        },
-    ];
-
-    const responsePipeline = new UserRequestPipeline({
-        stages,
-        stageNames: [
-            "audit_start",
-            "tool_rank",
-            "filter_tools",
-            "model_call",
-            "tool_loop",
-            "output_size_gate",
-            "send_response",
-            "text_to_speech",
-            "persist_output_artifacts",
-            "audit_finish",
-        ],
-        onFallback: async decision => {
-            recordPipelineFallback(decision.action);
-            if (decision.action === "use_alternate_target") {
-                aiLog("warn", "response.fallback.use_alternate_target", {
-                    provider: options.provider,
-                    stage: decision.stage,
-                    reason: decision.reason,
-                    requestId: state.requestId,
-                    ...buildToolRankFallbackTargetDetails(options.provider, config),
-                });
-            }
-
-            if (decision.action === "fail_request") {
-                aiLog("error", "response.fallback.fail_request", {
-                    provider: options.provider,
-                    stage: decision.stage,
-                    reason: decision.reason,
-                    requestId: state.requestId,
-                });
-            }
-
-            const notification = await fallbackNotifier.notify(state.requestId, decision);
-            state.audit.push({
-                stage: decision.stage,
-                status: "fallback",
-                startedAt: new Date().toISOString(),
-                finishedAt: new Date().toISOString(),
-                details: {
-                    fallbackAction: decision.action,
-                    fallbackNotification: notification.text,
-                    fallbackNotified: notification.notified,
-                    reason: decision.reason,
-                    ...(decision.action === "use_alternate_target"
-                        ? buildToolRankFallbackTargetDetails(options.provider, config)
-                        : {}),
-                },
-            });
-        },
-    });
-
-    try {
-        await responsePipeline.run(state, controller.signal);
-        await streamMessage.storePipelineAudit(state.audit);
-    } catch (error) {
-        await streamMessage.storePipelineAudit(state.audit).catch(logError);
-        throw error;
-    } finally {
-        const cleanupState = createResponsePipelineState(options);
-        const cleanupPipeline = new UserRequestPipeline({
-            stages: [{
-                name: "cleanup",
-                async run() {
-                    await prepared.cleanup();
-                    return {
-                        stage: "cleanup",
-                        status: "succeeded",
-                    };
-                },
-            }],
-            stageNames: ["cleanup"],
-        });
-
-        try {
-            await cleanupPipeline.run(cleanupState, controller.signal);
-            await streamMessage.storePipelineAudit(cleanupState.audit);
-        } catch (error) {
-            await streamMessage.storePipelineAudit(cleanupState.audit).catch(logError);
-            logError(error instanceof Error ? error : String(error));
-        }
-    }
-}

src/ai/unified-ai-runner.gemini.ts

@@ -0,0 +1,178 @@
+// Gemini provider runner extracted from unified-ai-runner.ts.
+import {getGeminiTools} from "./tool-mappers";
+import {TelegramStreamMessage} from "./telegram-stream-message";
+import {ToolRuntimeContext} from "./tools/runtime";
+import {GeminiMessage} from "./gemini-chat-message";
+import {createGoogleGenAiClient} from "./ai-runtime-target";
+import {aiLog, aiLogDuration, aiLogProviderTarget, aiLogToolCall} from "../logging/ai-logger";
+
+import {
+    AsyncIterableStream,
+    executeToolBatch,
+    GeminiFunctionCallLike,
+    GeminiGenerationRequest,
+    GeminiResponseLike,
+    MAX_TOOL_ROUNDS,
+    roundStatus,
+    RuntimeConfigSnapshot,
+    safeJsonParseObject,
+    ToolCallData,
+    ToolExecutionMemory
+} from "./unified-ai-runner.shared";
+import {Message} from "typescript-telegram-bot-api";
+
+function collectGeminiResponseText(response: GeminiResponseLike & { text?: string }): string {
+    if (typeof response.text === "string") return response.text;
+
+    return (response.candidates ?? [])
+        .flatMap(candidate => candidate.content?.parts ?? [])
+        .map(part => part.text ?? "")
+        .join("");
+}
+
+function collectGeminiFunctionCalls(response: GeminiResponseLike): ToolCallData[] {
+    const calls = response.functionCalls
+        ?? (response.candidates ?? []).flatMap(candidate => {
+            return (candidate.content?.parts ?? [])
+                .map(part => part.functionCall)
+                .filter((call): call is GeminiFunctionCallLike => !!call);
+        });
+
+    return (calls ?? []).map((call, index) => ({
+        id: call.id ?? `gemini_${index}_${call.name ?? "call"}`,
+        name: call.name ?? "",
+        argumentsText: JSON.stringify(call.args ?? {}),
+    })).filter((call: ToolCallData) => call.name);
+}
+
+function mergeGeminiFunctionCalls(existing: ToolCallData[], next: ToolCallData[]): ToolCallData[] {
+    const merged = [...existing];
+    for (const call of next) {
+        const index = merged.findIndex(item => item.id === call.id);
+        if (index === -1) {
+            merged.push(call);
+        } else {
+            merged[index] = call;
+        }
+    }
+    return merged;
+}
+
+function appendGeminiToolRound(messages: GeminiMessage[], calls: ToolCallData[], results: string[]): void {
+    messages.push({
+        role: "model",
+        parts: calls.map(call => ({
+            functionCall: {
+                id: call.id,
+                name: call.name,
+                args: safeJsonParseObject(call.argumentsText),
+            },
+        })),
+    });
+
+    messages.push({
+        role: "user",
+        parts: calls.map((call, index) => ({
+            functionResponse: {
+                id: call.id,
+                name: call.name,
+                response: {result: results[index] ?? ""},
+            },
+        })),
+    });
+}
+
+export async function runGemini(
+    msg: Message,
+    messages: GeminiMessage[],
+    streamMessage: TelegramStreamMessage,
+    signal: AbortSignal,
+    stream: boolean,
+    firstRoundStatus: string,
+    config: RuntimeConfigSnapshot,
+    toolContext: ToolRuntimeContext,
+): Promise<void> {
+    const runnerStartedAt = Date.now();
+    const geminiAi = createGoogleGenAiClient(config.geminiChatTarget);
+
+    aiLog("info", "gemini.run.start", {
+        stream,
+        target: aiLogProviderTarget(config.geminiChatTarget),
+        inputMessages: messages.length,
+        hasToolInputFiles: !!toolContext.pythonInputFiles?.length,
+    });
+
+    // TODO: 13.05.2026, Danil Nikolaev: find a better way?
+    const imageCount = messages.reduce((sum, m) => {
+        return sum + (m.parts.filter(p => "inlineData" in p && "mimeType" in p.inlineData && p.inlineData.mimeType.startsWith("image")).length)
+    }, 0);
+
+    const target = imageCount ? config.geminiImageTarget : config.geminiChatTarget;
+    const model = target.model;
+
+    const toolMemory: ToolExecutionMemory = new Map();
+
+    for (let round = 0; round < MAX_TOOL_ROUNDS; round++) {
+        const roundStartedAt = Date.now();
+        aiLog("debug", "gemini.round.start", {round, messages: messages.length, stream});
+        if (signal.aborted) throw new Error("Aborted");
+
+        streamMessage.setStatus(roundStatus(round, firstRoundStatus) ?? "");
+        await streamMessage.flush();
+
+        const request: GeminiGenerationRequest = {
+            model: model,
+            contents: messages,
+            config: {
+                tools: getGeminiTools(),
+                temperature: messages.length <= 2 ? 0 : 0.6,
+                abortSignal: signal,
+            },
+        };
+
+        if (!stream) {
+            const response = await geminiAi.models.generateContent(request) as unknown as GeminiResponseLike & {
+                text?: string
+            };
+            const text = collectGeminiResponseText(response);
+            streamMessage.append(text);
+            const calls = collectGeminiFunctionCalls(response);
+            aiLog(calls.length ? "info" : "success", calls.length ? "gemini.tool_calls" : "gemini.run.done", {
+                round,
+                duration: calls.length ? aiLogDuration(roundStartedAt) : aiLogDuration(runnerStartedAt),
+                textChars: text.length,
+                calls: calls.map(aiLogToolCall),
+            });
+            if (!calls.length) return;
+
+            appendGeminiToolRound(messages, calls, await executeToolBatch(msg.from?.id, calls, streamMessage, toolContext, toolMemory));
+            continue;
+        }
+
+        const response = await geminiAi.models.generateContentStream(request) as unknown as AsyncIterableStream<GeminiResponseLike & {
+            text?: string
+        }>;
+        aiLog("debug", "gemini.stream.open", {round});
+        let calls: ToolCallData[] = [];
+        const roundTextStart = streamMessage.getText().length;
+        for await (const chunk of response) {
+            if (signal.aborted) throw new Error("Aborted");
+            streamMessage.append(collectGeminiResponseText(chunk));
+            calls = mergeGeminiFunctionCalls(calls, collectGeminiFunctionCalls(chunk));
+        }
+
+        aiLog(calls.length ? "info" : "success", calls.length ? "gemini.tool_calls" : "gemini.run.done", {
+            round,
+            duration: calls.length ? aiLogDuration(roundStartedAt) : aiLogDuration(runnerStartedAt),
+            textChars: streamMessage.getText().slice(roundTextStart).length,
+            calls: calls.map(aiLogToolCall),
+        });
+        if (!calls.length) return;
+        appendGeminiToolRound(messages, calls, await executeToolBatch(msg.from?.id, calls, streamMessage, toolContext, toolMemory));
+    }
+}
+
+
+export class GeminiProviderRunner {
+    static run = runGemini;
+}

src/ai/unified-ai-runner.mistral.ts

@@ -1,28 +1,25 @@
 import {Environment} from "../common/environment";
+import {getMistralTools} from "./tool-mappers";
 import {TelegramStreamMessage} from "./telegram-stream-message";
 import {ToolRuntimeContext} from "./tools/runtime";
 import {MistralChatMessage} from "./mistral-chat-message";
 import {createMistralClient} from "./ai-runtime-target";
 import {aiLog, aiLogDuration, aiLogProviderTarget, aiLogToolCall} from "../logging/ai-logger";
-import {AiProvider} from "../model/ai-provider";
-import {getProviderAdapter} from "./provider-adapters";
-import {runToolRankStage} from "./tool-rank-stage";
-import {ensureToolsSelected} from "./tool-mappers.js";
-import {MEMORY_TOOL_NAMES} from "./tools/user-memory.js";
 
 import {
+    contentFromMistralDelta,
+    executeToolBatch,
     MAX_TOOL_ROUNDS,
+    MistralDeltaLike,
     MistralDocumentReference,
+    mistralToolCalls,
+    normalizeMistralToolCalls,
     roundStatus,
     RuntimeConfigSnapshot,
     StreamingToolCallAccumulator,
     ToolCallData,
     ToolExecutionMemory
 } from "./unified-ai-runner.shared";
-import {executeToolBatchWithAdapter} from "./tool-batch-runner";
-import {decideToolLoopContinuation} from "./tool-loop-control";
-import {runToolLoopRounds} from "./tool-loop-runner";
-import {runSingleModelRequest} from "./model-call-stage";
 import {Message} from "typescript-telegram-bot-api";
 
 export async function runMistral(
@@ -38,9 +35,6 @@ export async function runMistral(
 ): Promise<void> {
     const runnerStartedAt = Date.now();
     const mistralAi = createMistralClient(config.mistralChatTarget);
-    const adapter = getProviderAdapter(AiProvider.MISTRAL);
-    const availableTools = adapter.rankTools(config, {forCreator: msg.from?.id === Environment.CREATOR_ID});
-    const requestMessages = adapter.mapMessages([...messages]) as unknown as MistralChatMessage[];
     aiLog("info", "mistral.run.start", {
         stream,
         target: aiLogProviderTarget(config.mistralChatTarget),
@@ -50,169 +44,103 @@ export async function runMistral(
     });
 
     const toolMemory: ToolExecutionMemory = new Map();
-    try {
-        await runToolLoopRounds({
-            maxRounds: MAX_TOOL_ROUNDS,
-            onRound: async (round) => {
-            const roundStartedAt = Date.now();
-            aiLog("debug", "mistral.round.start", {round, messages: messages.length, stream});
-            if (signal.aborted) throw new Error("Aborted");
 
-            const rankResult = await runToolRankStage({
-                provider: AiProvider.MISTRAL,
-                model: config.mistralChatTarget.model,
-                round,
-                config,
-                availableTools,
-                messages,
-                streamMessage,
-                signal,
-            });
-            const filteredTools = ensureToolsSelected(availableTools, rankResult.filteredTools, MEMORY_TOOL_NAMES);
-            const requestTools = filteredTools.length ? filteredTools : undefined;
+    for (let round = 0; round < MAX_TOOL_ROUNDS; round++) {
+        const roundStartedAt = Date.now();
+        aiLog("debug", "mistral.round.start", {round, messages: messages.length, stream});
+        if (signal.aborted) throw new Error("Aborted");
 
-            streamMessage.setStatus(roundStatus(round, firstRoundStatus) ?? "");
-            await streamMessage.flush();
-
-            if (!stream) {
-                const request = {
-                    model: config.mistralChatTarget.model,
-                    messages: requestMessages,
-                    tools: requestTools,
-                    documents: documents
-                } as Parameters<typeof mistralAi.chat.complete>[0];
-                const response = await runSingleModelRequest({
-                    execute: () => adapter.callModel(request, () => mistralAi.chat.complete(request, {signal})),
-                });
-                const message = response.choices?.[0]?.message;
-                const text = typeof message?.content === "string" ? message.content : JSON.stringify(message?.content ?? "");
-                streamMessage.append(text);
-                const calls = adapter.extractToolCalls(message);
-                aiLog(calls.length ? "info" : "success", calls.length ? "mistral.tool_calls" : "mistral.run.done", {
-                    round,
-                    duration: calls.length ? aiLogDuration(roundStartedAt) : aiLogDuration(runnerStartedAt),
-                    textChars: text.length,
-                    calls: calls.map(aiLogToolCall),
-                });
-                if (!calls.length) return {shouldContinue: false};
-                messages.push({
-                    role: "assistant",
-                    content: text,
-                    toolCalls: calls.map(call => ({
-                        id: call.id,
-                        function: {name: call.name, arguments: call.argumentsText},
-                    })),
-                });
-                requestMessages.push({
-                    role: "assistant",
-                    content: text,
-                    toolCalls: calls.map(call => ({
-                        id: call.id,
-                        function: {name: call.name, arguments: call.argumentsText},
-                    })),
-                });
-                await executeToolBatchWithAdapter({
-                    userId: msg.from?.id,
-                    toolCalls: calls,
-                    streamMessage,
-                    toolContext: {
-                        ...toolContext,
-                        provider: AiProvider.MISTRAL,
-                        runtimeTarget: config.mistralChatTarget,
-                    },
-                    toolMemory,
-                    adapter,
-                    appendTargets: [messages, requestMessages],
-                });
-                const continuation = decideToolLoopContinuation({
-                    round,
-                    maxRounds: MAX_TOOL_ROUNDS,
-                    toolCalls: calls,
-                });
-                if (!continuation.continue && continuation.reason === "max_rounds_reached") {
-                    aiLog("warn", "mistral.tool_loop.max_rounds_reached", {
-                        round,
-                        maxRounds: MAX_TOOL_ROUNDS,
-                    });
-                }
-                return {shouldContinue: true};
-            }
+        streamMessage.setStatus(roundStatus(round, firstRoundStatus) ?? "");
+        await streamMessage.flush();
 
+        if (!stream) {
             const request = {
                 model: config.mistralChatTarget.model,
-                messages: requestMessages,
-                tools: requestTools,
+                messages,
+                tools: getMistralTools(msg.from?.id === Environment.CREATOR_ID),
                 documents: documents
-            } as Parameters<typeof mistralAi.chat.stream>[0];
-            const streamResponse = await runSingleModelRequest({
-                execute: () => adapter.callModel(request, () => mistralAi.chat.stream(request, {signal})),
-            });
-            aiLog("debug", "mistral.stream.open", {round});
-            let calls: ToolCallData[] = [];
-            const roundTextStart = streamMessage.getText().length;
-            const toolCallAccumulator = new StreamingToolCallAccumulator("mistral_stream", round);
-
-            for await (const event of streamResponse) {
-                if (signal.aborted) throw new Error("Aborted");
-
-                const choice = event.data?.choices?.[0];
-                const delta = choice?.delta;
-                const mistralDelta = delta;
-                streamMessage.append(adapter.extractTextDelta(mistralDelta));
-
-                const rawDeltaCalls = adapter.extractStreamingToolCalls(mistralDelta);
-                if (rawDeltaCalls.length) {
-                    calls = toolCallAccumulator.add(rawDeltaCalls);
-                    streamMessage.setStatus(Environment.getUseToolText(calls));
-                    await streamMessage.flush();
-                }
-            }
+            } as unknown as Parameters<typeof mistralAi.chat.complete>[0];
+            const response = await mistralAi.chat.complete(request, {signal});
+            const message = response.choices?.[0]?.message;
+            const text = typeof message?.content === "string" ? message.content : JSON.stringify(message?.content ?? "");
+            streamMessage.append(text);
+            const calls = normalizeMistralToolCalls(mistralToolCalls(message));
             aiLog(calls.length ? "info" : "success", calls.length ? "mistral.tool_calls" : "mistral.run.done", {
                 round,
                 duration: calls.length ? aiLogDuration(roundStartedAt) : aiLogDuration(runnerStartedAt),
-                textChars: streamMessage.getText().slice(roundTextStart).length,
+                textChars: text.length,
                 calls: calls.map(aiLogToolCall),
             });
-            if (!calls.length) return {shouldContinue: false};
-            const roundText = streamMessage.getText().slice(roundTextStart);
+            if (!calls.length) return;
             messages.push({
                 role: "assistant",
-                content: roundText,
-                toolCalls: calls.map(c => ({id: c.id, function: {name: c.name, arguments: c.argumentsText}}))
+                content: text,
+                toolCalls: calls.map(call => ({
+                    id: call.id,
+                    function: {name: call.name, arguments: call.argumentsText},
+                })),
             });
-            requestMessages.push({
-                role: "assistant",
-                content: roundText,
-                toolCalls: calls.map(c => ({id: c.id, function: {name: c.name, arguments: c.argumentsText}}))
-            });
-            await executeToolBatchWithAdapter({
-                userId: msg.from?.id,
-                toolCalls: calls,
-                streamMessage,
-                toolContext: {
-                    ...toolContext,
-                    provider: AiProvider.MISTRAL,
-                    runtimeTarget: config.mistralChatTarget,
-                },
-                toolMemory,
-                adapter,
-                appendTargets: [messages, requestMessages],
-            });
-            const continuation = decideToolLoopContinuation({
-                round,
-                maxRounds: MAX_TOOL_ROUNDS,
-                toolCalls: calls,
-            });
-                if (!continuation.continue && continuation.reason === "max_rounds_reached") {
-                    aiLog("warn", "mistral.tool_loop.max_rounds_reached", {
-                        round,
-                        maxRounds: MAX_TOOL_ROUNDS,
-                    });
-                }
-                return {shouldContinue: true};
-        },
+            const toolResults = await executeToolBatch(msg.from?.id, calls, streamMessage, toolContext, toolMemory);
+            for (const [index, call] of calls.entries()) {
+                messages.push({
+                    role: "tool",
+                    name: call.name,
+                    toolCallId: call.id,
+                    content: toolResults[index] ?? "",
+                });
+            }
+            continue;
+        }
+
+        const request = {
+            model: config.mistralChatTarget.model,
+            messages,
+            tools: getMistralTools(msg.from?.id === Environment.CREATOR_ID),
+            documents: documents
+        } as unknown as Parameters<typeof mistralAi.chat.stream>[0];
+        const streamResponse = await mistralAi.chat.stream(request, {signal});
+        aiLog("debug", "mistral.stream.open", {round});
+        let calls: ToolCallData[] = [];
+        const roundTextStart = streamMessage.getText().length;
+        const toolCallAccumulator = new StreamingToolCallAccumulator("mistral_stream", round);
+
+        for await (const event of streamResponse) {
+            if (signal.aborted) throw new Error("Aborted");
+
+            const choice = event.data?.choices?.[0];
+            const delta = choice?.delta;
+            const mistralDelta = delta as MistralDeltaLike;
+
+            streamMessage.append(contentFromMistralDelta(mistralDelta));
+
+            const rawDeltaCalls = mistralToolCalls(mistralDelta);
+            if (rawDeltaCalls.length) {
+                calls = toolCallAccumulator.add(rawDeltaCalls);
+                streamMessage.setStatus(Environment.getUseToolText(calls));
+                await streamMessage.flush();
+            }
+        }
+        aiLog(calls.length ? "info" : "success", calls.length ? "mistral.tool_calls" : "mistral.run.done", {
+            round,
+            duration: calls.length ? aiLogDuration(roundStartedAt) : aiLogDuration(runnerStartedAt),
+            textChars: streamMessage.getText().slice(roundTextStart).length,
+            calls: calls.map(aiLogToolCall),
         });
-    } finally {
-        await adapter.finalize().catch(() => undefined);
+        if (!calls.length) return;
+        const roundText = streamMessage.getText().slice(roundTextStart);
+        messages.push({
+            role: "assistant",
+            content: roundText,
+            toolCalls: calls.map(c => ({id: c.id, function: {name: c.name, arguments: c.argumentsText}}))
+        });
+        const toolResults = await executeToolBatch(msg.from?.id, calls, streamMessage, toolContext, toolMemory);
+        for (const [index, call] of calls.entries()) {
+            messages.push({
+                role: "tool",
+                name: call.name,
+                toolCallId: call.id,
+                content: toolResults[index] ?? "",
+            });
+        }
     }
-}
+}

src/ai/unified-ai-runner.ollama.ts

@@ -2,9 +2,9 @@
 import * as fs from "node:fs";
 import path from "node:path";
 import {Environment} from "../common/environment";
-import type {BoundaryValue} from "../common/boundary-types";
 import {bot, notesDir} from "../index";
 import {clamp, logError} from "../util/utils";
+import {getOllamaTools} from "./tool-mappers";
 import {TelegramStreamMessage} from "./telegram-stream-message";
 import {ChatMessage} from "./chat-messages-types";
 import {ChatRequest, Tool} from "ollama";
@@ -13,20 +13,20 @@ import {enqueueTelegramApiCall} from "../util/telegram-api-queue";
 import {loadOllamaModel, unloadAllOllamaModels} from "./tools/utils";
 import {createOllamaClient} from "./ai-runtime-target";
 import {aiLog, aiLogDuration, aiLogMessageIdentity, aiLogProviderTarget, aiLogToolCall} from "../logging/ai-logger";
-import {getProviderAdapter} from "./provider-adapters";
-import {runToolRankStage} from "./tool-rank-stage";
-import {ensureToolsSelected} from "./tool-mappers.js";
-import {MEMORY_TOOL_NAMES} from "./tools/user-memory.js";
 
 import {
     allToolSchemaNames,
+    appendOllamaToolResults,
     dedupeToolCalls,
     DEFAULT_OLLAMA_CONTEXT_SIZE,
+    executeToolBatch,
     isOllamaModelActive,
     isRecord,
     MAX_OLLAMA_CONTEXT_SIZE,
     MAX_TOOL_ROUNDS,
     MIN_OLLAMA_CONTEXT_SIZE,
+    normalizeOllamaToolCalls,
+    OllamaToolCallLike,
     roundStatus,
     RuntimeConfigSnapshot,
     safeJsonParseObject,
@@ -34,10 +34,7 @@ import {
     ToolCallData,
     ToolExecutionMemory
 } from "./unified-ai-runner.shared";
-import {executeToolBatchWithAdapter} from "./tool-batch-runner";
-import {decideToolLoopContinuation} from "./tool-loop-control";
-import {runToolLoopRounds} from "./tool-loop-runner";
-import {runSingleModelRequest} from "./model-call-stage";
+import {latestUserTextFromOllamaMessages, OllamaToolRanker} from "./unified-ai-runner.tool-ranker";
 import {getToolPrompts} from "./tools/registry";
 import {GetNoteFileResult, GetNoteFileResultSchema} from "./tools/notes";
 import {getModelCapabilities} from "./provider-model-runtime";
@@ -78,8 +75,9 @@ export async function runOllama(
 
     const ollama = createOllamaClient(target);
     const modelInfo = await ollama.show({model});
-    const modelInfoMap: Record<string, BoundaryValue> = isRecord(modelInfo.model_info) ? modelInfo.model_info : {};
+    const modelInfoMap = isRecord(modelInfo.model_info) ? modelInfo.model_info : {};
     const contextKey = Object.keys(modelInfoMap).find(k => k.endsWith(".context_length"));
+    // @ts-ignore
     const rawMaxContextLength = contextKey ? modelInfoMap[contextKey] : undefined;
     const parsedMaxContextLength =
         typeof rawMaxContextLength === "number"
@@ -115,7 +113,7 @@ export async function runOllama(
             await unloadAllOllamaModels(ollama, modelsToLoad);
         }
     } catch (e) {
-        logError(e instanceof Error ? e : String(e));
+        logError(e);
     }
 
     if (!(await isOllamaModelActive(ollama, target))) {
@@ -157,12 +155,9 @@ export async function runOllama(
     }
 
     const toolMemory: ToolExecutionMemory = new Map();
-    const adapter = getProviderAdapter(AiProvider.OLLAMA);
 
     try {
-        await runToolLoopRounds({
-            maxRounds: MAX_TOOL_ROUNDS,
-            onRound: async (round) => {
+        for (let round = 0; round < MAX_TOOL_ROUNDS; round++) {
             const roundStartedAt = Date.now();
             aiLog("debug", "ollama.round.start", {
                 round,
@@ -186,7 +181,7 @@ export async function runOllama(
 
             let activeToolNames: string[] = [];
             if ((await getModelCapabilities(AiProvider.OLLAMA, model, "tools"))?.tools?.supported) {
-                const availableOllamaTools: Tool[] = adapter.rankTools(config, {forCreator: msg.from?.id === Environment.CREATOR_ID}) as Tool[];
+                const availableOllamaTools: Tool[] = getOllamaTools(msg.from?.id === Environment.CREATOR_ID) as Tool[];
 
                 aiLog("debug", "ollama.tools.available", {
                     round,
@@ -194,25 +189,21 @@ export async function runOllama(
                     rankerEnabled: !!config.ollamaToolRankerTarget,
                 });
 
-                const rankResult = await runToolRankStage({
-                    provider: AiProvider.OLLAMA,
-                    model,
-                    round,
-                    config,
+                const rankerSelection = await new OllamaToolRanker(config).selectTools({
+                    userQuery: latestUserTextFromOllamaMessages(messages),
                     availableTools: availableOllamaTools,
-                    messages,
-                    streamMessage,
+                    round,
                     signal,
                 });
 
-                const filteredTools = [...new Set(ensureToolsSelected(availableOllamaTools, rankResult.filteredTools as Tool[], MEMORY_TOOL_NAMES) as Tool[])];
+                const filteredTools = [...new Set(rankerSelection.tools)];
                 activeToolNames = filteredTools.map(t => t.function.name ?? "");
                 if (filteredTools.length > 0) {
                     request.tools = [...filteredTools];
                     request.options = {
                         ...request.options,
                         temperature: 0
-                    };
+                    }
 
                     const newMessage = messages[messages.length - 1];
                     if (newMessage) {
@@ -229,27 +220,31 @@ export async function runOllama(
                     delete request.tools;
                 }
 
+                // TODO: 14.05.2026, Danil Nikolaev: check if model supports tools
+
+
                 aiLog("debug", "ollama.tools.selected", {
                     round,
                     tools: activeToolNames,
                     count: activeToolNames.length,
-                    usedRanker: rankResult.usedRanker,
+                    usedRanker: rankerSelection.usedRanker,
                 });
             }
 
             if (!stream) {
-                const response = await runSingleModelRequest({
-                    execute: () => adapter.callModel(request, () => ollama.chat({
-                        ...request,
-                        stream: false
-                    })),
+                const response = await ollama.chat({
+                    ...request,
+                    stream: false
                 });
 
                 const message = response.message;
                 const rawContent = message?.content ?? "";
 
                 const nativeCalls = dedupeToolCalls(
-                    adapter.extractToolCalls(message),
+                    normalizeOllamaToolCalls(
+                        message?.tool_calls as readonly OllamaToolCallLike[] | undefined,
+                        round,
+                    ),
                 );
 
                 const responseText = rawContent;
@@ -274,10 +269,10 @@ export async function runOllama(
 
                 if (!nativeCalls.length) {
                     aiLog("success", "ollama.run.done", {round, duration: aiLogDuration(runnerStartedAt)});
-                    return {shouldContinue: false};
+                    break;
                 }
 
-                const calls = adapter.extractToolCalls(message).length ? adapter.extractToolCalls(message) : nativeCalls;
+                const calls = nativeCalls;
 
                 aiLog("info", "ollama.tool_calls", {
                     round,
@@ -295,44 +290,19 @@ export async function runOllama(
                     })),
                 });
 
-                await executeToolBatchWithAdapter({
-                    userId: msg.from?.id,
-                    toolCalls: calls,
-                    streamMessage,
-                    toolContext: {
-                        ...toolContext,
-                        provider: AiProvider.OLLAMA,
-                        runtimeTarget: target,
-                    },
-                    toolMemory,
-                    adapter,
-                    appendTargets: [messages],
-                });
+                appendOllamaToolResults(
+                    messages,
+                    calls,
+                    await executeToolBatch(msg.from?.id, calls, streamMessage, toolContext, toolMemory),
+                );
 
-                const continuation = decideToolLoopContinuation({
-                    round,
-                    maxRounds: MAX_TOOL_ROUNDS,
-                    toolCalls: calls,
-                });
-                if (!continuation.continue && continuation.reason === "max_rounds_reached") {
-                    aiLog("warn", "ollama.tool_loop.max_rounds_reached", {
-                        round,
-                        maxRounds: MAX_TOOL_ROUNDS,
-                    });
-                }
-
-                return {shouldContinue: true};
+                continue;
             }
 
-            aiLog("debug", "ollama.stream.messages", {
-                round,
-                messageCount: request.messages?.length ?? 0,
-            });
-            const response = await runSingleModelRequest({
-                execute: () => adapter.callModel(request, () => ollama.chat({
-                    ...request,
-                    stream: true
-                })),
+            console.log("MESSAGES", JSON.stringify(request.messages));
+            const response = await ollama.chat({
+                ...request,
+                stream: true
             });
 
             aiLog("debug", "ollama.stream.open", {round});
@@ -343,16 +313,14 @@ export async function runOllama(
             if (signal.aborted) abortOllamaResponse();
             try {
                 for await (const chunk of response) {
-                    aiLog("trace", "ollama.stream.chunk", {
-                        round,
-                        contentPreview: chunk.message.content?.slice(0, 240),
-                        hasToolCalls: !!chunk.message.tool_calls?.length,
-                        hasThinking: !!chunk.message.thinking,
-                    });
+                    console.log("OLLAMA_CHUNK: ", chunk);
 
                     const localToolCalls: ToolCallData[] = [];
 
-                    localToolCalls.push(...adapter.extractStreamingToolCalls(chunk.message));
+                    localToolCalls.push(...normalizeOllamaToolCalls(
+                        chunk.message.tool_calls as readonly OllamaToolCallLike[] | undefined,
+                        round,
+                    ));
 
                     const newStatus = roundStatus(round, firstRoundStatus, chunk.message.content, localToolCalls, !!chunk.message.thinking);
                     const previousStatus = streamMessage.getStatus();
@@ -372,10 +340,13 @@ export async function runOllama(
                     }
 
                     if (!(chunk.message?.thinking && streamMessage.getStatus() !== Environment.reasoningText)) {
-                        streamMessage.append(adapter.extractTextDelta(chunk));
+                        streamMessage.append(chunk.message?.content ?? "");
                     }
 
-                    calls.push(...adapter.extractStreamingToolCalls(chunk.message));
+                    calls.push(...normalizeOllamaToolCalls(
+                        chunk.message?.tool_calls as readonly OllamaToolCallLike[] | undefined,
+                        round,
+                    ));
 
                     if (chunk.done) {
                         aiLog("debug", "ollama.stream.done", {
@@ -408,7 +379,7 @@ export async function runOllama(
                     duration: aiLogDuration(runnerStartedAt),
                 });
 
-                return {shouldContinue: false};
+                break;
             }
 
             calls.splice(0, calls.length, ...dedupeToolCalls(calls));
@@ -431,31 +402,7 @@ export async function runOllama(
                 })),
             });
 
-            const toolResults = await executeToolBatchWithAdapter({
-                userId: msg.from?.id,
-                toolCalls: calls,
-                streamMessage,
-                toolContext: {
-                    ...toolContext,
-                    provider: AiProvider.OLLAMA,
-                    runtimeTarget: target,
-                },
-                toolMemory,
-                adapter,
-                appendTargets: [messages],
-            });
-
-            const continuation = decideToolLoopContinuation({
-                round,
-                maxRounds: MAX_TOOL_ROUNDS,
-                toolCalls: calls,
-            });
-            if (!continuation.continue && continuation.reason === "max_rounds_reached") {
-                aiLog("warn", "ollama.tool_loop.max_rounds_reached", {
-                    round,
-                    maxRounds: MAX_TOOL_ROUNDS,
-                });
-            }
+            const toolResults = await executeToolBatch(msg.from?.id, calls, streamMessage, toolContext, toolMemory);
 
             let successGetNoteFileResult: GetNoteFileResult | undefined = undefined;
 
@@ -473,25 +420,18 @@ export async function runOllama(
             }
 
             if (successGetNoteFileResult && "attachment" in successGetNoteFileResult) {
-                const attachmentPath = path.join(notesDir, successGetNoteFileResult.attachment.relativePath);
-                if (!fs.existsSync(attachmentPath)) {
-                    throw new Error(`Attachment file does not exist: ${attachmentPath}`);
-                }
-
                 await bot.sendDocument({
                     chat_id: msg.chat.id,
                     reply_parameters: {
                         message_id: msg.message_id,
                     },
-                    document: fs.createReadStream(attachmentPath),
+                    document: fs.createReadStream(path.join(notesDir, successGetNoteFileResult.attachment.relativePath)),
                 }).catch(logError);
             }
 
-            return {shouldContinue: true};
-        },
-        });
+            appendOllamaToolResults(messages, calls, toolResults);
+        }
     } finally {
         if (interval) clearInterval(interval);
-        await adapter.finalize().catch(() => undefined);
     }
-}
+}

src/ai/unified-ai-runner.openai-compatible.ts

@@ -1,419 +0,0 @@
-import {Message} from "typescript-telegram-bot-api";
-import type {
-    ChatCompletionCreateParamsNonStreaming,
-    ChatCompletionCreateParamsStreaming,
-    ChatCompletionTool,
-} from "openai/resources/chat/completions";
-import {Environment} from "../common/environment.js";
-import {TelegramStreamMessage} from "./telegram-stream-message";
-import {ToolRuntimeContext} from "./tools/runtime";
-import {OpenAIChatMessage, OpenAICompatibleChatMessage} from "./openai-chat-message";
-import {createOpenAiClient} from "./ai-runtime-target";
-import {aiLog, aiLogDuration, aiLogMessageIdentity, aiLogProviderTarget, aiLogToolCall} from "../logging/ai-logger";
-import type {BoundaryValue} from "../common/boundary-types.js";
-import {
-    AsyncIterableStream,
-    buildSystemInstruction,
-    MAX_TOOL_ROUNDS,
-    OpenAiChatCompletionResponseLike,
-    OpenAiChatCompletionStreamChunkLike,
-    RuntimeConfigSnapshot,
-    safeJsonParseObject,
-    ToolCallData,
-    ToolExecutionMemory,
-} from "./unified-ai-runner.shared";
-import {mergeToolCallChunks, normalizeStreamingTextDelta} from "./provider-adapter-contract.js";
-import {buildUserMemoryPrompt} from "./tools/user-memory.js";
-import {executeToolBatchWithAdapter} from "./tool-batch-runner";
-import {decideToolLoopContinuation} from "./tool-loop-control";
-import {runToolLoopRounds} from "./tool-loop-runner";
-import {runSingleModelRequest} from "./model-call-stage";
-import {ensureToolsSelected, getOpenAICompatibleTools} from "./tool-mappers.js";
-import {MEMORY_TOOL_NAMES} from "./tools/user-memory.js";
-import {logError} from "../util/utils";
-import {DEFAULT_AI_RESPONSE_LANGUAGE} from "../common/user-ai-settings";
-import {AiDownloadedFile} from "./telegram-attachments";
-import {AiProvider} from "../model/ai-provider";
-import {getProviderAdapter} from "./provider-adapters";
-import {runToolRankStage} from "./tool-rank-stage";
-import type {AiProviderAdapter} from "./provider-adapters.js";
-import {tryToUploadFiles} from "./openai-upload-files.js";
-import {buildAssistantToolMessage, openAiResponseMessagesToChatCompletions} from "./openai-chat-completions.js";
-
-function describeOpenAiCompatibleError(error: unknown): Record<string, unknown> {
-    const err = error as {
-        message?: unknown;
-        status?: unknown;
-        code?: unknown;
-        type?: unknown;
-        error?: unknown;
-    } | undefined;
-
-    return {
-        errorSummary: typeof err?.message === "string" ? err.message : String(error),
-        httpStatus: err?.status,
-        errorCode: err?.code,
-        errorType: err?.type,
-    };
-}
-
-async function executeChatCompletionWithOptionalToolFallback<T>(params: {
-    openAi: ReturnType<typeof createOpenAiClient>;
-    request: ChatCompletionCreateParamsNonStreaming | ChatCompletionCreateParamsStreaming;
-    signal: AbortSignal;
-    stream: boolean;
-}): Promise<T> {
-    try {
-        return await params.openAi.chat.completions.create(params.request as never, {signal: params.signal}) as T;
-    } catch (error) {
-        const requestWithTools = params.request as {tools?: unknown[]};
-        if (!requestWithTools.tools || !Array.isArray(requestWithTools.tools) || requestWithTools.tools.length === 0) {
-            aiLog("error", "openai_compatible.request.failed", {
-                stream: params.stream,
-                hasTools: false,
-                error: describeOpenAiCompatibleError(error),
-            });
-            throw error;
-        }
-
-        aiLog("warn", "openai_compatible.tools.retry_without_tools", {
-            stream: params.stream,
-            error: describeOpenAiCompatibleError(error),
-        });
-
-        const retryRequest = {...params.request} as ChatCompletionCreateParamsNonStreaming | ChatCompletionCreateParamsStreaming & {tools?: unknown[]};
-        delete retryRequest.tools;
-
-        try {
-            return await params.openAi.chat.completions.create(retryRequest as never, {signal: params.signal}) as T;
-        } catch (retryError) {
-            aiLog("error", "openai_compatible.request.retry_without_tools.failed", {
-                stream: params.stream,
-                hasTools: true,
-                error: describeOpenAiCompatibleError(retryError),
-            });
-            throw retryError;
-        }
-    }
-}
-
-function makeChatCompletionAdapter(): AiProviderAdapter {
-    const baseAdapter = getProviderAdapter(AiProvider.OPENAI);
-
-    return {
-        ...baseAdapter,
-        callModel: baseAdapter.callModel.bind(baseAdapter),
-        mapMessages(messages: readonly unknown[]): unknown[] {
-            return openAiResponseMessagesToChatCompletions(messages as OpenAIChatMessage[]);
-        },
-        rankTools(config: RuntimeConfigSnapshot, options?: {forCreator?: boolean; vectorStoreIds?: string[]}): readonly BoundaryValue[] {
-            void config;
-            void options?.vectorStoreIds;
-            return getOpenAICompatibleTools(options?.forCreator) as BoundaryValue[];
-        },
-        extractTextDelta(input: unknown): string {
-            const chunk = input as OpenAiChatCompletionStreamChunkLike | undefined;
-            return chunk?.choices?.[0]?.delta?.content ?? "";
-        },
-        extractToolCalls(input: unknown): ToolCallData[] {
-            const response = input as OpenAiChatCompletionResponseLike | undefined;
-            const toolCalls = response?.choices?.[0]?.message?.tool_calls ?? [];
-
-            return toolCalls
-                .map((call, index) => ({
-                    id: typeof call?.id === "string" && call.id.trim().length > 0 ? call.id : `openai_chat_${index}`,
-                    name: typeof call?.function?.name === "string" ? call.function.name : typeof call?.name === "string" ? call.name : "",
-                    argumentsText: typeof call?.function?.arguments === "string"
-                        ? call.function.arguments
-                        : JSON.stringify(call?.function?.arguments ?? call?.arguments ?? {}),
-                }))
-                .filter(call => call.name.length > 0);
-        },
-        extractStreamingToolCalls(input: unknown): ToolCallData[] {
-            const chunk = input as OpenAiChatCompletionStreamChunkLike | undefined;
-            const toolCalls = chunk?.choices?.[0]?.delta?.tool_calls ?? [];
-
-            return toolCalls
-                .map((call, index) => ({
-                    id: typeof call?.id === "string" && call.id.trim().length > 0
-                        ? call.id
-                        : `openai_chat_${typeof call?.index === "number" ? call.index : index}`,
-                    name: typeof call?.function?.name === "string" ? call.function.name : typeof call?.name === "string" ? call.name : "",
-                    argumentsText: typeof call?.function?.arguments === "string"
-                        ? call.function.arguments
-                        : call?.function?.arguments
-                            ? JSON.stringify(call.function.arguments)
-                            : typeof call?.arguments === "string"
-                                ? call.arguments
-                                : "",
-                }))
-                .filter(call => call.id.length > 0);
-        },
-        appendToolResults(messages: unknown[], calls: ToolCallData[], results: string[]): void {
-            for (const [index, call] of calls.entries()) {
-                messages.push({
-                    role: "tool",
-                    tool_call_id: call.id,
-                    content: results[index] ?? "",
-                });
-            }
-        },
-        finalize: baseAdapter.finalize.bind(baseAdapter),
-    };
-}
-
-export async function runOpenAiCompatible(
-    msg: Message,
-    messages: OpenAIChatMessage[],
-    streamMessage: TelegramStreamMessage,
-    signal: AbortSignal,
-    stream: boolean,
-    sourceMessage: Message,
-    config: RuntimeConfigSnapshot,
-    toolContext: ToolRuntimeContext,
-    downloads: AiDownloadedFile[] = [],
-): Promise<void> {
-    void downloads;
-    const runnerStartedAt = Date.now();
-    const openAi = createOpenAiClient(config.openAiChatTarget);
-    const adapter = makeChatCompletionAdapter();
-    const systemPrompt = buildSystemInstruction(
-        config,
-        DEFAULT_AI_RESPONSE_LANGUAGE,
-        false,
-        config.openAiChatTarget.systemPromptAdditions,
-        await buildUserMemoryPrompt(msg.from?.id),
-    );
-    let conversationMessages = [...openAiResponseMessagesToChatCompletions(messages)];
-
-    if (systemPrompt.trim().length) {
-        conversationMessages.unshift({role: "system", content: systemPrompt});
-    }
-
-    const availableTools = getOpenAICompatibleTools(msg.from?.id === Environment.CREATOR_ID) as ChatCompletionTool[];
-
-    aiLog("info", "openai_compatible.run.start", {
-        stream,
-        target: aiLogProviderTarget(config.openAiChatTarget),
-        inputMessages: messages.length,
-        sourceMessage: aiLogMessageIdentity(sourceMessage),
-        hasToolInputFiles: !!toolContext.pythonInputFiles?.length,
-        backend: config.openAiBackend,
-    });
-
-    const toolMemory: ToolExecutionMemory = new Map();
-
-    try {
-        await runToolLoopRounds({
-            maxRounds: MAX_TOOL_ROUNDS,
-            onRound: async (round) => {
-                const roundStartedAt = Date.now();
-                aiLog("debug", "openai_compatible.round.start", {round, inputMessages: conversationMessages.length, stream});
-
-                const rankResult = await runToolRankStage({
-                    provider: AiProvider.OPENAI,
-                    model: config.openAiChatTarget.model,
-                    round,
-                    config,
-                    availableTools: availableTools as readonly BoundaryValue[],
-                    messages,
-                    streamMessage,
-                    signal,
-                });
-
-                const requestTools = ensureToolsSelected(
-                    availableTools,
-                    rankResult.filteredTools as ChatCompletionTool[],
-                    MEMORY_TOOL_NAMES,
-                );
-
-                if (!stream) {
-                    const request: ChatCompletionCreateParamsNonStreaming = {
-                        model: config.openAiChatTarget.model,
-                        messages: conversationMessages,
-                        tools: requestTools.length ? requestTools : undefined,
-                    };
-
-                    const response = await runSingleModelRequest({
-                        execute: () => adapter.callModel(request, () => executeChatCompletionWithOptionalToolFallback<OpenAiChatCompletionResponseLike>({
-                            openAi,
-                            request,
-                            signal,
-                            stream: false,
-                        })),
-                    }) as OpenAiChatCompletionResponseLike;
-
-                    const message = response.choices?.[0]?.message;
-                    const responseText = typeof message?.content === "string" ? message.content : "";
-                    streamMessage.append(responseText);
-                    aiLog("debug", "openai_compatible.response.received", {
-                        round,
-                        duration: aiLogDuration(roundStartedAt),
-                        textChars: responseText.length,
-                        hasToolCalls: !!message?.tool_calls?.length,
-                    });
-
-                    const calls = adapter.extractToolCalls(response);
-                    aiLog(calls.length ? "info" : "success", calls.length ? "openai_compatible.tool_calls" : "openai_compatible.run.done", {
-                        round,
-                        duration: calls.length ? aiLogDuration(roundStartedAt) : aiLogDuration(runnerStartedAt),
-                        calls: calls.map(call => ({
-                            id: call.id,
-                            name: call.name,
-                            arguments: safeJsonParseObject(call.argumentsText)
-                        })),
-                    });
-                    if (!calls.length) return {shouldContinue: false};
-
-                    const toolCalls = calls.map(call => ({
-                        id: call.id,
-                        name: call.name,
-                        argumentsText: call.argumentsText,
-                    }));
-                    const toolMessages: OpenAICompatibleChatMessage[] = [];
-                    const toolResults = await executeToolBatchWithAdapter({
-                        userId: msg.from?.id,
-                        toolCalls,
-                        streamMessage,
-                        toolContext: {
-                            ...toolContext,
-                            provider: AiProvider.OPENAI,
-                            runtimeTarget: config.openAiChatTarget,
-                        },
-                        toolMemory,
-                        adapter,
-                        appendTargets: [toolMessages],
-                    });
-
-                    const uploadFilesResult = await tryToUploadFiles(msg, toolResults);
-                    if (uploadFilesResult.found && !uploadFilesResult.uploaded && uploadFilesResult.toolIndex >= 0) {
-                        const toolMessage = toolMessages[uploadFilesResult.toolIndex];
-                        if (toolMessage && toolMessage.role === "tool") {
-                            toolMessage.content = "Error: " + uploadFilesResult.error;
-                        }
-                    }
-
-                    const continuation = decideToolLoopContinuation({
-                        round,
-                        maxRounds: MAX_TOOL_ROUNDS,
-                        toolCalls: calls,
-                    });
-                    if (!continuation.continue && continuation.reason === "max_rounds_reached") {
-                        aiLog("warn", "openai_compatible.tool_loop.max_rounds_reached", {
-                            round,
-                            maxRounds: MAX_TOOL_ROUNDS,
-                        });
-                    }
-
-                    conversationMessages = [...conversationMessages, buildAssistantToolMessage(calls, responseText), ...toolMessages];
-                    return {shouldContinue: true};
-                }
-
-                const request: ChatCompletionCreateParamsStreaming = {
-                    model: config.openAiChatTarget.model,
-                    messages: conversationMessages,
-                    stream: true,
-                    tools: requestTools.length ? requestTools : undefined,
-                };
-
-                const response = await runSingleModelRequest({
-                    execute: () => adapter.callModel(request, () => executeChatCompletionWithOptionalToolFallback<AsyncIterableStream<OpenAiChatCompletionStreamChunkLike>>({
-                        openAi,
-                        request,
-                        signal,
-                        stream: true,
-                    })),
-                }) as AsyncIterableStream<OpenAiChatCompletionStreamChunkLike>;
-
-                aiLog("debug", "openai_compatible.stream.open", {round});
-
-                let responseText = "";
-                let toolCallState: ToolCallData[] = [];
-                for await (const chunk of response) {
-                    if (signal.aborted) throw new Error("Aborted");
-
-                    const deltaText = adapter.extractTextDelta(chunk);
-                    if (deltaText) {
-                        const appendedText = normalizeStreamingTextDelta(responseText, deltaText);
-                        responseText += appendedText;
-                        streamMessage.append(appendedText);
-                    }
-
-                    const streamedCalls = adapter.extractStreamingToolCalls(chunk);
-                    if (streamedCalls.length) {
-                        toolCallState = mergeToolCallChunks(toolCallState, streamedCalls);
-                        const activeCalls = toolCallState.filter(call => call.name.length > 0);
-                        aiLog("info", "openai_compatible.stream.tool_call.added", {
-                            round,
-                            toolCalls: activeCalls.map(aiLogToolCall),
-                        });
-                        streamMessage.setStatus(Environment.getUseToolText(activeCalls));
-                        await streamMessage.flush();
-                    }
-                }
-
-                const calls = toolCallState.filter(call => call.name.length > 0);
-                aiLog(calls.length ? "info" : "success", calls.length ? "openai_compatible.tool_calls" : "openai_compatible.stream.done", {
-                    round,
-                    duration: aiLogDuration(roundStartedAt),
-                    textChars: responseText.length,
-                    calls: calls.map(call => ({
-                        id: call.id,
-                        name: call.name,
-                        arguments: safeJsonParseObject(call.argumentsText)
-                    })),
-                });
-                if (!calls.length) return {shouldContinue: false};
-
-                streamMessage.clearStatus();
-                await streamMessage.flush();
-
-                const toolMessages: OpenAICompatibleChatMessage[] = [];
-                const toolResults = await executeToolBatchWithAdapter({
-                    userId: msg.from?.id,
-                    toolCalls: calls,
-                    streamMessage,
-                    toolContext: {
-                        ...toolContext,
-                        provider: AiProvider.OPENAI,
-                        runtimeTarget: config.openAiChatTarget,
-                    },
-                    toolMemory,
-                    adapter,
-                    appendTargets: [toolMessages],
-                });
-
-                const uploadFilesResult = await tryToUploadFiles(msg, toolResults);
-                if (uploadFilesResult.found && !uploadFilesResult.uploaded && uploadFilesResult.toolIndex >= 0) {
-                    const toolMessage = toolMessages[uploadFilesResult.toolIndex];
-                    if (toolMessage && toolMessage.role === "tool") {
-                        toolMessage.content = "Error: " + uploadFilesResult.error;
-                    }
-                }
-
-                const continuation = decideToolLoopContinuation({
-                    round,
-                    maxRounds: MAX_TOOL_ROUNDS,
-                    toolCalls: calls,
-                });
-                if (!continuation.continue && continuation.reason === "max_rounds_reached") {
-                    aiLog("warn", "openai_compatible.tool_loop.max_rounds_reached", {
-                        round,
-                        maxRounds: MAX_TOOL_ROUNDS,
-                    });
-                }
-
-                conversationMessages = [...conversationMessages, buildAssistantToolMessage(calls, responseText), ...toolMessages];
-                return {shouldContinue: true};
-            },
-        });
-    } catch (error) {
-        aiLog("error", "openai_compatible.run.failed", {
-            duration: aiLogDuration(runnerStartedAt),
-            error: describeOpenAiCompatibleError(error),
-        });
-        throw error;
-    } finally {
-        await adapter.finalize().catch(logError);
-    }
-}

src/ai/unified-ai-runner.openai.ts

@@ -1,5 +1,5 @@
+// OpenAI and OpenAI-compatible provider runners extracted from unified-ai-runner.ts.
 import {Message} from "typescript-telegram-bot-api";
-import {OpenAI, toFile} from "openai";
 import {Environment} from "../common/environment";
 import {TelegramStreamMessage} from "./telegram-stream-message";
 import {ToolRuntimeContext} from "./tools/runtime";
@@ -12,14 +12,16 @@ import type {
 } from "openai/resources/responses/responses";
 import {createOpenAiClient} from "./ai-runtime-target";
 import {aiLog, aiLogDuration, aiLogMessageIdentity, aiLogProviderTarget, aiLogToolCall} from "../logging/ai-logger";
-import {buildUserMemoryPrompt} from "./tools/user-memory.js";
 
 import {
     AsyncIterableStream,
     buildSystemInstruction,
     collectOpenAiResponseCodeInterpreterCalls,
+    collectOpenAiResponseFunctionCalls,
     collectOpenAiResponseImages,
     collectOpenAiResponseText,
+    executeToolBatch,
+    getOpenAIResponsesToolsWithImage,
     MAX_TOOL_ROUNDS,
     OPENAI_IMAGE_PARTIALS,
     openAiResponseItemCallId,
@@ -29,22 +31,14 @@ import {
     safeJsonParseObject,
     showOpenAiGeneratedImage,
     ToolCallData,
-    ToolExecutionMemory,
-    allToolSchemaNames
+    ToolExecutionMemory
 } from "./unified-ai-runner.shared";
-import {executeToolBatchWithAdapter} from "./tool-batch-runner";
-import {decideToolLoopContinuation} from "./tool-loop-control";
-import {runToolLoopRounds} from "./tool-loop-runner";
-import {runSingleModelRequest} from "./model-call-stage";
-import {ensureToolsSelected} from "./tool-mappers.js";
-import {MEMORY_TOOL_NAMES} from "./tools/user-memory.js";
+import {bot, filesDir} from "../index";
+import fs from "node:fs";
+import path from "node:path";
 import {logError} from "../util/utils";
+import {SendFileAttachmentResult, SendFileAttachmentResultSchema} from "./tools/files";
 import {DEFAULT_AI_RESPONSE_LANGUAGE} from "../common/user-ai-settings";
-import {AiDownloadedFile} from "./telegram-attachments";
-import {AiProvider} from "../model/ai-provider";
-import {getProviderAdapter} from "./provider-adapters";
-import {runToolRankStage} from "./tool-rank-stage";
-import {tryToUploadFiles} from "./openai-upload-files.js";
 
 export async function runOpenAi(
     msg: Message,
@@ -55,27 +49,12 @@ export async function runOpenAi(
     sourceMessage: Message,
     config: RuntimeConfigSnapshot,
     toolContext: ToolRuntimeContext,
-    downloads: AiDownloadedFile[] = [],
-    documentRag?: OpenAiDocumentRagContext,
 ): Promise<void> {
     const runnerStartedAt = Date.now();
+    let responseInput: unknown[] = [...messages];
     const openAi = createOpenAiClient(config.openAiChatTarget);
-    const ownsDocumentRag = !documentRag;
-    const preparedDocumentRag = documentRag ?? await prepareOpenAiDocumentRag(openAi, downloads.filter(download => download.kind === "document"));
-    const adapter = getProviderAdapter(AiProvider.OPENAI);
-    let responseInput: Array<ResponseInputItem | OpenAiResponseOutputItem> = adapter.mapMessages(messages) as unknown as Array<ResponseInputItem | OpenAiResponseOutputItem>;
-    const availableTools = adapter.rankTools(config, {
-        forCreator: msg.from?.id === Environment.CREATOR_ID,
-        vectorStoreIds: preparedDocumentRag?.vectorStoreIds ?? [],
-    });
 
-    const systemPrompt = buildSystemInstruction(
-        config,
-        DEFAULT_AI_RESPONSE_LANGUAGE,
-        false,
-        config.openAiChatTarget.systemPromptAdditions,
-        await buildUserMemoryPrompt(msg.from?.id),
-    );
+    const systemPrompt = buildSystemInstruction(config, DEFAULT_AI_RESPONSE_LANGUAGE, false);
 
     aiLog("info", "openai.run.start", {
         stream,
@@ -88,275 +67,28 @@ export async function runOpenAi(
 
     const toolMemory: ToolExecutionMemory = new Map();
 
-    try {
-        await runToolLoopRounds({
-            maxRounds: MAX_TOOL_ROUNDS,
-            onRound: async (round) => {
-            const roundStartedAt = Date.now();
-            aiLog("debug", "openai.round.start", {round, inputItems: responseInput.length, stream});
-            const rankResult = await runToolRankStage({
-                provider: AiProvider.OPENAI,
-                model: config.openAiChatTarget.model,
-                round,
-                config,
-                availableTools,
-                messages,
-                streamMessage,
-                signal,
-            });
-            const filteredTools = rankResult.filteredTools;
-            const requestTools = preparedDocumentRag?.vectorStoreIds.length
-                ? (() => {
-                    const tools = [...filteredTools];
-                    const hasFileSearch = allToolSchemaNames(tools).includes("file_search");
-                    if (!hasFileSearch) {
-                        const fileSearchTool = availableTools.find(tool => allToolSchemaNames([tool]).includes("file_search"));
-                        if (fileSearchTool) {
-                            tools.unshift(fileSearchTool);
-                        }
-                    }
-                    const withMemory = ensureToolsSelected(availableTools, tools, MEMORY_TOOL_NAMES);
-                    return withMemory.length ? withMemory : undefined;
-                })()
-                : (() => {
-                    const withMemory = ensureToolsSelected(availableTools, filteredTools, MEMORY_TOOL_NAMES);
-                    return withMemory.length ? withMemory : undefined;
-                })();
+    for (let round = 0; round < MAX_TOOL_ROUNDS; round++) {
+        const roundStartedAt = Date.now();
+        aiLog("debug", "openai.round.start", {round, inputItems: responseInput.length, stream});
 
-            if (!stream) {
-                const request: ResponseCreateParamsNonStreaming = {
-                    model: config.openAiChatTarget.model,
-                    input: responseInput as ResponseInputItem[],
-                    tools: requestTools as ResponseCreateParamsNonStreaming["tools"],
-                    instructions: systemPrompt,
-                };
-                const response = await runSingleModelRequest({
-                    execute: () => adapter.callModel(request, () => openAi.responses.create(request, {signal})),
-                }) as OpenAiResponseLike;
-
-                const responseText = collectOpenAiResponseText(response);
-                streamMessage.append(responseText);
-                aiLog("debug", "openai.response.received", {
-                    round,
-                    duration: aiLogDuration(roundStartedAt),
-                    textChars: responseText.length,
-                    outputItems: response?.output?.length ?? 0,
-                });
-                const images = collectOpenAiResponseImages(response);
-                if (images.length) {
-                    await showOpenAiGeneratedImage(
-                        streamMessage,
-                        sourceMessage,
-                        images[images.length - 1],
-                        `final_${round}`,
-                        Environment.getImageGenDoneText(config.openAiImageTarget.model),
-                        true,
-                    );
-                }
-
-                const codeInterpreterCalls = collectOpenAiResponseCodeInterpreterCalls(response);
-                if (codeInterpreterCalls.length) {
-                    aiLog("info", "openai.code_interpreter_calls", {
-                        round,
-                        duration: aiLogDuration(roundStartedAt),
-                        calls: codeInterpreterCalls.map(call => ({
-                            id: call.id,
-                            status: call.status,
-                            containerId: call.containerId,
-                            codeChars: call.code?.length ?? 0,
-                            outputItems: call.outputs.length,
-                        })),
-                    });
-                }
-
-                const calls = adapter.extractToolCalls(response);
-                aiLog(calls.length ? "info" : "success", calls.length ? "openai.tool_calls" : "openai.run.done", {
-                    round,
-                    duration: calls.length ? aiLogDuration(roundStartedAt) : aiLogDuration(runnerStartedAt),
-                    calls: calls.map(call => ({
-                        id: call.id,
-                        name: call.name,
-                        arguments: safeJsonParseObject(call.argumentsText)
-                    })),
-                });
-                if (!calls.length) return {shouldContinue: false};
-
-                const toolCalls = calls.map(call => ({
-                    id: call.id,
-                    name: call.name,
-                    argumentsText: call.argumentsText,
-                }));
-                const toolOutputs: Array<{type: "function_call_output"; call_id: string; output: string}> = [];
-                const toolResults = await executeToolBatchWithAdapter({
-                    userId: msg.from?.id,
-                    toolCalls,
-                    streamMessage,
-                    toolContext: {
-                        ...toolContext,
-                        provider: AiProvider.OPENAI,
-                        runtimeTarget: config.openAiChatTarget,
-                    },
-                    toolMemory,
-                    adapter,
-                    appendTargets: [toolOutputs],
-                });
-
-                const uploadFilesResult = await tryToUploadFiles(msg, toolResults);
-                if (uploadFilesResult.found) {
-                    if (!uploadFilesResult.uploaded) {
-                        const old = toolOutputs[uploadFilesResult.toolIndex];
-                        const callId = old?.call_id;
-                        if (uploadFilesResult.toolIndex >= 0) {
-                            delete toolOutputs[uploadFilesResult.toolIndex];
-                        }
-                        if (callId) {
-                            toolOutputs.push({
-                                type: "function_call_output" as const,
-                                call_id: callId,
-                                output: "Error: " + uploadFilesResult.error
-                            });
-                        }
-                    }
-                }
-
-                const continuation = decideToolLoopContinuation({
-                    round,
-                    maxRounds: MAX_TOOL_ROUNDS,
-                    toolCalls: calls,
-                });
-                if (!continuation.continue && continuation.reason === "max_rounds_reached") {
-                    aiLog("warn", "openai.tool_loop.max_rounds_reached", {
-                        round,
-                        maxRounds: MAX_TOOL_ROUNDS,
-                    });
-                }
-
-                responseInput = [...responseInput, ...(response.output ?? []), ...toolOutputs];
-                return {shouldContinue: true};
-            }
-
-            let completedResponse: OpenAiResponseLike | null = null;
-            const request: ResponseCreateParamsStreaming = {
+        if (!stream) {
+            const request: ResponseCreateParamsNonStreaming = {
                 model: config.openAiChatTarget.model,
                 input: responseInput as ResponseInputItem[],
-                stream: true,
-                tools: requestTools as ResponseCreateParamsStreaming["tools"],
-                parallel_tool_calls: true,
-                instructions: systemPrompt
+                tools: getOpenAIResponsesToolsWithImage(config, msg.from?.id === Environment.CREATOR_ID) as ResponseCreateParamsNonStreaming["tools"],
+                instructions: systemPrompt,
             };
-            const response = await runSingleModelRequest({
-                execute: () => adapter.callModel(request, () => openAi.responses.create(request, {signal})),
-            }) as AsyncIterableStream<ResponseStreamEvent>;
+            const response = await openAi.responses.create(request, {signal}) as unknown as OpenAiResponseLike;
 
-            aiLog("debug", "openai.stream.open", {round});
-
-            let localToolCalls: ToolCallData[] = [];
-            for await (const event of response) {
-                if (signal.aborted) throw new Error("Aborted");
-
-                switch (event.type) {
-                    case "response.output_text.delta":
-                        streamMessage.append(adapter.extractTextDelta(event));
-                        break;
-                    case "response.image_generation_call.in_progress":
-                        streamMessage.setStatus(Environment.startingImageGenText);
-                        await streamMessage.flush();
-                        break;
-                    case "response.image_generation_call.generating":
-                        streamMessage.setStatus(Environment.imageGenText);
-                        await streamMessage.flush();
-                        break;
-                    case "response.image_generation_call.partial_image": {
-                        const iteration = (event.partial_image_index ?? 0) + 1;
-                        await showOpenAiGeneratedImage(
-                            streamMessage,
-                            sourceMessage,
-                            event.partial_image_b64,
-                            `partial_${round}_${iteration}`,
-                            Environment.getPartialImageGenText(iteration, OPENAI_IMAGE_PARTIALS),
-                            false,
-                        );
-                        break;
-                    }
-                    case "response.image_generation_call.completed":
-                        streamMessage.setStatus(Environment.finalizingImageGenText);
-                        await streamMessage.flush();
-                        break;
-                    case "response.file_search_call.in_progress":
-                    case "response.file_search_call.searching":
-                        streamMessage.setStatus(Environment.getUseToolText(["file_search"]));
-                        await streamMessage.flush();
-                        break;
-                    case "response.file_search_call.completed":
-                        streamMessage.clearStatus();
-                        await streamMessage.flush();
-                        break;
-                    case "response.code_interpreter_call.in_progress":
-                    case "response.code_interpreter_call.interpreting":
-                        streamMessage.setStatus(Environment.getUseToolText(["code_interpreter"]));
-                        await streamMessage.flush();
-                        break;
-                    case "response.code_interpreter_call.completed":
-                        streamMessage.clearStatus();
-                        await streamMessage.flush();
-                        break;
-                    case "response.code_interpreter_call_code.delta":
-                    case "response.code_interpreter_call_code.done":
-                        break;
-                    case "response.output_item.added":
-                        {
-                            const streamedCalls = adapter.extractStreamingToolCalls(event);
-                            if (streamedCalls.length) {
-                                localToolCalls.push(...streamedCalls);
-                            }
-                            aiLog("info", "openai.stream.tool_call.added", {
-                                round,
-                                toolCalls: localToolCalls.map(aiLogToolCall)
-                            });
-                            streamMessage.setStatus(Environment.getUseToolText(localToolCalls));
-                            await streamMessage.flush();
-                        }
-                        break;
-                    case "response.output_item.done":
-                        if (event.item.type === "function_call" && event.item.name) {
-                            const item = event.item as OpenAiResponseOutputItem & { id?: string };
-                            const itemId = openAiResponseItemCallId(item);
-                            const index = localToolCalls.findIndex(c => c.id === itemId);
-                            if (index !== -1) {
-                                localToolCalls.splice(index, 1);
-                                if (localToolCalls.length === 0) {
-                                    streamMessage.clearStatus();
-                                } else {
-                                    streamMessage.setStatus(Environment.getUseToolText(localToolCalls));
-                                }
-                                await streamMessage.flush();
-                            }
-                        }
-                        break;
-                    case "response.function_call_arguments.delta":
-                        break;
-                    case "response.function_call_arguments.done":
-                        break;
-
-                    case "response.completed":
-                        completedResponse = event.response as OpenAiResponseLike;
-                        break;
-                    case "response.failed":
-                        throw new Error(event.response?.error?.message ?? "OpenAI response failed");
-                    case "error":
-                        throw new Error(event.message ?? event?.message ?? "OpenAI stream error");
-                }
-            }
-
-            if (!completedResponse) throw new Error("OpenAI did not return the final response.completed event.");
-
-            aiLog("debug", "openai.stream.completed", {
+            const responseText = collectOpenAiResponseText(response);
+            streamMessage.append(responseText);
+            aiLog("debug", "openai.response.received", {
                 round,
                 duration: aiLogDuration(roundStartedAt),
-                outputItems: completedResponse?.output?.length ?? 0,
+                textChars: responseText.length,
+                outputItems: response?.output?.length ?? 0,
             });
-
-            const images = collectOpenAiResponseImages(completedResponse);
+            const images = collectOpenAiResponseImages(response);
             if (images.length) {
                 await showOpenAiGeneratedImage(
                     streamMessage,
@@ -368,7 +100,7 @@ export async function runOpenAi(
                 );
             }
 
-            const codeInterpreterCalls = collectOpenAiResponseCodeInterpreterCalls(completedResponse);
+            const codeInterpreterCalls = collectOpenAiResponseCodeInterpreterCalls(response);
             if (codeInterpreterCalls.length) {
                 aiLog("info", "openai.code_interpreter_calls", {
                     round,
@@ -383,143 +115,287 @@ export async function runOpenAi(
                 });
             }
 
-            const calls = adapter.extractToolCalls(completedResponse);
+            const calls = collectOpenAiResponseFunctionCalls(response);
             aiLog(calls.length ? "info" : "success", calls.length ? "openai.tool_calls" : "openai.run.done", {
                 round,
                 duration: calls.length ? aiLogDuration(roundStartedAt) : aiLogDuration(runnerStartedAt),
                 calls: calls.map(call => ({
-                    id: call.id,
+                    id: call.callId,
                     name: call.name,
                     arguments: safeJsonParseObject(call.argumentsText)
                 })),
             });
-            if (!calls.length) return {shouldContinue: false};
+            if (!calls.length) return;
 
             const toolCalls = calls.map(call => ({
-                id: call.id,
+                id: call.callId,
                 name: call.name,
                 argumentsText: call.argumentsText,
             }));
-            const toolOutputs: Array<{type: "function_call_output"; call_id: string; output: string}> = [];
-            const toolResults = await executeToolBatchWithAdapter({
-                userId: msg.from?.id,
-                toolCalls,
-                streamMessage,
-                toolContext: {
-                    ...toolContext,
-                    provider: AiProvider.OPENAI,
-                    runtimeTarget: config.openAiChatTarget,
-                },
-                toolMemory,
-                adapter,
-                appendTargets: [toolOutputs],
-            });
+            const toolResults = await executeToolBatch(msg.from?.id, toolCalls, streamMessage, toolContext, toolMemory);
+            const toolOutputs = calls.map((call, index) => ({
+                type: "function_call_output" as const,
+                call_id: call.callId,
+                output: toolResults[index] ?? "",
+            }));
 
             const uploadFilesResult = await tryToUploadFiles(msg, toolResults);
             if (uploadFilesResult.found) {
                 if (!uploadFilesResult.uploaded) {
                     const old = toolOutputs[uploadFilesResult.toolIndex];
-                    const callId = old?.call_id;
-                    if (uploadFilesResult.toolIndex >= 0) {
-                        delete toolOutputs[uploadFilesResult.toolIndex];
-                    }
-                    if (callId) {
-                        toolOutputs.push({
-                            type: "function_call_output" as const,
-                            call_id: callId,
-                            output: "Error: " + uploadFilesResult.error
-                        });
-                    }
+                    delete toolOutputs[uploadFilesResult.toolIndex];
+                    toolOutputs.push({
+                        type: "function_call_output" as const,
+                        call_id: old.call_id,
+                        output: "Error: " + uploadFilesResult.error
+                    });
                 }
             }
 
-            const continuation = decideToolLoopContinuation({
+            responseInput = [...responseInput, ...(response.output ?? []), ...toolOutputs];
+            continue;
+        }
+
+        let completedResponse: OpenAiResponseLike | null = null;
+        const request: ResponseCreateParamsStreaming = {
+            model: config.openAiChatTarget.model,
+            input: responseInput as ResponseInputItem[],
+            stream: true,
+            tools: getOpenAIResponsesToolsWithImage(config, msg.from?.id === Environment.CREATOR_ID) as ResponseCreateParamsStreaming["tools"],
+            parallel_tool_calls: true,
+            instructions: systemPrompt
+        };
+        const response = await openAi.responses.create(request, {signal}) as unknown as AsyncIterableStream<ResponseStreamEvent>;
+
+        aiLog("debug", "openai.stream.open", {round});
+
+        let localToolCalls: ToolCallData[] = [];
+        for await (const event of response) {
+            if (signal.aborted) throw new Error("Aborted");
+
+            switch (event.type) {
+                case "response.output_text.delta":
+                    streamMessage.append(event.delta ?? "");
+                    break;
+                case "response.image_generation_call.in_progress":
+                    streamMessage.setStatus(Environment.startingImageGenText);
+                    await streamMessage.flush();
+                    break;
+                case "response.image_generation_call.generating":
+                    streamMessage.setStatus(Environment.imageGenText);
+                    await streamMessage.flush();
+                    break;
+                case "response.image_generation_call.partial_image": {
+                    const iteration = (event.partial_image_index ?? 0) + 1;
+                    await showOpenAiGeneratedImage(
+                        streamMessage,
+                        sourceMessage,
+                        event.partial_image_b64,
+                        `partial_${round}_${iteration}`,
+                        Environment.getPartialImageGenText(iteration, OPENAI_IMAGE_PARTIALS),
+                        false,
+                    );
+                    break;
+                }
+                case "response.image_generation_call.completed":
+                    streamMessage.setStatus(Environment.finalizingImageGenText);
+                    await streamMessage.flush();
+                    break;
+                case "response.code_interpreter_call.in_progress":
+                case "response.code_interpreter_call.interpreting":
+                    streamMessage.setStatus(Environment.getUseToolText(["code_interpreter"]));
+                    await streamMessage.flush();
+                    break;
+                case "response.code_interpreter_call.completed":
+                    streamMessage.clearStatus();
+                    await streamMessage.flush();
+                    break;
+                case "response.code_interpreter_call_code.delta":
+                case "response.code_interpreter_call_code.done":
+                    break;
+                case "response.output_item.added":
+                    if (event.item.type === "function_call" && event.item.name) {
+                        const item = event.item as OpenAiResponseOutputItem & { id?: string };
+                        localToolCalls.push({
+                            id: openAiResponseItemCallId(item),
+                            name: item.name ?? "",
+                            argumentsText: item.arguments ?? "{}",
+                        });
+
+                        aiLog("info", "openai.stream.tool_call.added", {
+                            round,
+                            toolCalls: localToolCalls.map(aiLogToolCall)
+                        });
+                        streamMessage.setStatus(Environment.getUseToolText(localToolCalls));
+                        await streamMessage.flush();
+                    }
+                    break;
+                case "response.output_item.done":
+                    if (event.item.type === "function_call" && event.item.name) {
+                        const item = event.item as OpenAiResponseOutputItem & { id?: string };
+                        const itemId = openAiResponseItemCallId(item);
+                        const index = localToolCalls.findIndex(c => c.id === itemId);
+                        if (index !== -1) {
+                            localToolCalls.splice(index, 1);
+                            if (localToolCalls.length === 0) {
+                                streamMessage.clearStatus();
+                            } else {
+                                streamMessage.setStatus(Environment.getUseToolText(localToolCalls));
+                            }
+                            await streamMessage.flush();
+                        }
+                    }
+                    break;
+                case "response.function_call_arguments.delta":
+                    break;
+                case "response.function_call_arguments.done":
+                    break;
+
+                case "response.completed":
+                    completedResponse = event.response as unknown as OpenAiResponseLike;
+                    break;
+                case "response.failed":
+                    throw new Error(event.response?.error?.message ?? "OpenAI response failed");
+                case "error":
+                    throw new Error(event.message ?? event?.message ?? "OpenAI stream error");
+            }
+        }
+
+        if (!completedResponse) throw new Error("OpenAI did not return the final response.completed event.");
+
+        aiLog("debug", "openai.stream.completed", {
+            round,
+            duration: aiLogDuration(roundStartedAt),
+            outputItems: completedResponse?.output?.length ?? 0,
+        });
+
+        const images = collectOpenAiResponseImages(completedResponse);
+        if (images.length) {
+            await showOpenAiGeneratedImage(
+                streamMessage,
+                sourceMessage,
+                images[images.length - 1],
+                `final_${round}`,
+                Environment.getImageGenDoneText(config.openAiImageTarget.model),
+                true,
+            );
+        }
+
+        const codeInterpreterCalls = collectOpenAiResponseCodeInterpreterCalls(completedResponse);
+        if (codeInterpreterCalls.length) {
+            aiLog("info", "openai.code_interpreter_calls", {
                 round,
-                maxRounds: MAX_TOOL_ROUNDS,
-                toolCalls: calls,
+                duration: aiLogDuration(roundStartedAt),
+                calls: codeInterpreterCalls.map(call => ({
+                    id: call.id,
+                    status: call.status,
+                    containerId: call.containerId,
+                    codeChars: call.code?.length ?? 0,
+                    outputItems: call.outputs.length,
+                })),
             });
-            if (!continuation.continue && continuation.reason === "max_rounds_reached") {
-                aiLog("warn", "openai.tool_loop.max_rounds_reached", {
-                    round,
-                    maxRounds: MAX_TOOL_ROUNDS,
+        }
+
+        const calls = collectOpenAiResponseFunctionCalls(completedResponse);
+        aiLog(calls.length ? "info" : "success", calls.length ? "openai.tool_calls" : "openai.run.done", {
+            round,
+            duration: calls.length ? aiLogDuration(roundStartedAt) : aiLogDuration(runnerStartedAt),
+            calls: calls.map(call => ({
+                id: call.callId,
+                name: call.name,
+                arguments: safeJsonParseObject(call.argumentsText)
+            })),
+        });
+        if (!calls.length) return;
+
+        const toolCalls = calls.map(call => ({
+            id: call.callId,
+            name: call.name,
+            argumentsText: call.argumentsText,
+        }));
+        const toolResults = await executeToolBatch(msg.from?.id, toolCalls, streamMessage, toolContext, toolMemory);
+        const toolOutputs = calls.map((call, index) => ({
+            type: "function_call_output",
+            call_id: call.callId,
+            output: toolResults[index] ?? "",
+        }));
+
+        const uploadFilesResult = await tryToUploadFiles(msg, toolResults);
+        if (uploadFilesResult.found) {
+            if (!uploadFilesResult.uploaded) {
+                const old = toolOutputs[uploadFilesResult.toolIndex];
+                delete toolOutputs[uploadFilesResult.toolIndex];
+                toolOutputs.push({
+                    type: "function_call_output" as const,
+                    call_id: old.call_id,
+                    output: "Error: " + uploadFilesResult.error
                 });
             }
-
-            responseInput = [...responseInput, ...(completedResponse.output ?? []), ...toolOutputs];
-            return {shouldContinue: true};
-        },
-        });
-    } finally {
-        if (ownsDocumentRag) {
-            await preparedDocumentRag?.cleanup().catch(logError);
         }
-        await adapter.finalize().catch(logError);
+
+        responseInput = [...responseInput, ...(completedResponse.output ?? []), ...toolOutputs];
     }
 }
 
-export type OpenAiDocumentRagContext = {
-    vectorStoreIds: string[];
-    uploadedFileIds: string[];
-    cleanup: () => Promise<void>;
-};
+async function tryToUploadFiles(
+    msg: Message,
+    toolResults: string[]
+): Promise<
+    | { found: false }
+    | { found: true, uploaded: true }
+    | { found: boolean, uploaded: false, error: string, toolIndex: number }
+> {
+    let sendFileAttachment: {
+        result: SendFileAttachmentResult & { success: true },
+        toolIndex: number
+    } | null = null;
 
-export async function prepareOpenAiDocumentRag(openAi: OpenAI, downloads: AiDownloadedFile[]): Promise<OpenAiDocumentRagContext | undefined> {
-    if (!downloads.length) return undefined;
-
-    const vectorStore = await openAi.vectorStores.create({
-        name: `tg-chat-bot-${Date.now()}`,
-        description: "Temporary document RAG for a single Telegram request.",
-        expires_after: {
-            anchor: "last_active_at",
-            days: 1,
-        },
-    });
-
-    const uploadedFileIds: string[] = [];
+    let found = false;
 
     try {
-        for (const download of downloads) {
-            const uploaded = await openAi.files.create({
-                file: await toFile(download.buffer, download.fileName, {
-                    type: download.mimeType ?? "application/octet-stream",
-                }),
-                purpose: "user_data",
-            });
-            uploadedFileIds.push(uploaded.id);
+        for (const toolResult of toolResults) {
+            const raw = JSON.parse(toolResult);
+            const res = SendFileAttachmentResultSchema.safeParse(raw);
+
+            if (res.success) {
+                found = true;
+
+                if (res.data.success) {
+                    sendFileAttachment = {result: res.data, toolIndex: toolResults.indexOf(toolResult)};
+                }
+            }
         }
 
-        const batch = await openAi.vectorStores.fileBatches.createAndPoll(vectorStore.id, {
-            file_ids: uploadedFileIds,
-        });
-
-        if (batch.file_counts.failed > 0) {
-            throw new Error(`OpenAI file_search failed to index ${batch.file_counts.failed} document(s).`);
+        if (!found) {
+            return {found: false};
         }
 
-        return {
-            vectorStoreIds: [vectorStore.id],
-            uploadedFileIds,
-            cleanup: async () => {
-                await cleanupOpenAiDocumentRag(openAi, vectorStore.id, uploadedFileIds);
+        await bot.sendDocument({
+            chat_id: msg.chat.id,
+            reply_parameters: {
+                message_id: msg.message_id,
             },
+            document: fs.createReadStream(path.join(filesDir, String(msg.from?.id), sendFileAttachment?.result?.attachment?.relativePath ?? "")),
+        })
+
+        return {found: true, uploaded: true};
+    } catch (e: unknown) {
+        logError(e);
+        return {
+            found: found,
+            uploaded: false,
+            error: (e as any)?.message ?? "",
+            toolIndex: sendFileAttachment?.toolIndex ?? -1
         };
-    } catch (error) {
-        await cleanupOpenAiDocumentRag(openAi, vectorStore.id, uploadedFileIds).catch(() => undefined);
-        throw error;
     }
 }
 
-async function cleanupOpenAiDocumentRag(openAi: OpenAI, vectorStoreId: string, fileIds: string[]): Promise<void> {
-    await openAi.vectorStores.delete(vectorStoreId).catch(() => undefined);
-    for (const fileId of fileIds) {
-        await openAi.files.delete(fileId).catch(() => undefined);
-    }
-}
-
-// function openAiResponseContentToText(content: string | readonly { text?: string; refusal?: string }[]): string {
+// function openAiResponseContentToText(content: unknown): string {
 //     if (typeof content === "string") return content;
 //     if (!Array.isArray(content)) return "";
 //     return content.map(part => isRecord(part) ? part.text ?? part.content ?? part.refusal ?? "" : "").join("");
+// }
+
 // function openAiResponseMessagesToChatCompletions(messages: OpenAIChatMessage[]): OpenAiCompatibleChatMessage[] {
 //     return messages.map((message): OpenAiCompatibleChatMessage => {
 //         if (message.role === "system" || message.role === "assistant") {
@@ -548,6 +424,7 @@ async function cleanupOpenAiDocumentRag(openAi: OpenAI, vectorStoreId: string, f
 //         return {role: "user", content};
 //     });
 // }
+
 // function normalizeOpenAiChatToolCalls(toolCalls: OpenAiChatToolCallLike[] = []): ToolCallData[] {
 //     return toolCalls.map((call, i) => ({
 //         id: call.id || `openai_chat_${Date.now()}_${i}`,
@@ -557,6 +434,7 @@ async function cleanupOpenAiDocumentRag(openAi: OpenAI, vectorStoreId: string, f
 //             : JSON.stringify(call.function?.arguments ?? call.arguments ?? {}),
 //     })).filter(call => call.name);
 // }
+
 // async function appendOpenAiChatToolResults(
 //     messages: OpenAiCompatibleChatMessage[],
 //     calls: ToolCallData[],
@@ -570,3 +448,178 @@ async function cleanupOpenAiDocumentRag(openAi: OpenAI, vectorStoreId: string, f
 //         });
 //     }
 // }
+
+// export async function runOpenAiCompatibleChat(
+//     msg: Message,
+//     messages: OpenAIChatMessage[],
+//     streamMessage: TelegramStreamMessage,
+//     signal: AbortSignal,
+//     stream: boolean,
+//     firstRoundStatus: string,
+//     config: RuntimeConfigSnapshot,
+//     toolContext: ToolRuntimeContext,
+// ): Promise<void> {
+//     const runnerStartedAt = Date.now();
+//     const geminiOpenAi = createGeminiOpenAiClient(config.geminiChatTarget);
+//     const chatMessages = openAiResponseMessagesToChatCompletions(messages);
+//     const toolMemory: ToolExecutionMemory = new Map();
+//
+//     aiLog("info", "openai_compatible.run.start", {
+//         stream,
+//         target: aiLogProviderTarget(config.geminiChatTarget),
+//         inputMessages: messages.length,
+//         chatMessages: chatMessages.length,
+//         hasToolInputFiles: !!toolContext.pythonInputFiles?.length,
+//     });
+//
+//     for (let round = 0; round < MAX_TOOL_ROUNDS; round++) {
+//         const roundStartedAt = Date.now();
+//         aiLog("debug", "openai_compatible.round.start", {round, messages: chatMessages.length, stream});
+//         streamMessage.setStatus(roundStatus(round, firstRoundStatus) ?? "");
+//         await streamMessage.flush();
+//
+//         if (!stream) {
+//             const request: ChatCompletionCreateParamsNonStreaming = {
+//                 model: config.geminiChatTarget.model,
+//                 messages: chatMessages,
+//                 tools: getOpenAITools(msg.from?.id === Environment.CREATOR_ID),
+//                 // temperature: 0.6,
+//             };
+//             const response = await geminiOpenAi.chat.completions.create(request, {signal}) as unknown as OpenAiChatCompletionResponseLike;
+//             const message = response.choices?.[0]?.message;
+//             streamMessage.append(message?.content ?? "");
+//             const calls = normalizeOpenAiChatToolCalls(message?.tool_calls ?? []);
+//             aiLog(calls.length ? "info" : "success", calls.length ? "openai_compatible.tool_calls" : "openai_compatible.run.done", {
+//                 round,
+//                 duration: calls.length ? aiLogDuration(roundStartedAt) : aiLogDuration(runnerStartedAt),
+//                 textChars: message?.content?.length ?? 0,
+//                 calls: calls.map(aiLogToolCall),
+//             });
+//             if (!calls.length) return;
+//
+//             chatMessages.push({
+//                 role: "assistant",
+//                 content: message?.content ?? "",
+//                 tool_calls: calls.map(call => ({
+//                     id: call.id,
+//                     type: "function" as const,
+//                     function: {
+//                         name: call.name,
+//                         arguments: call.argumentsText,
+//                     },
+//                 })),
+//             });
+//
+//             const toolResults = await executeToolBatch(calls, streamMessage, toolContext, toolMemory);
+//
+//             let successGetNoteFileResult: GetNoteFileResult | undefined = undefined;
+//
+//             for (const toolResult of toolResults) {
+//                 try {
+//                     const raw = JSON.parse(toolResult);
+//                     const res = GetNoteFileResultSchema.safeParse(raw);
+//
+//                     if (res.success && res.data.success) {
+//                         successGetNoteFileResult = res.data;
+//                     }
+//                 } catch {
+//                     // Not every tool result is JSON.
+//                 }
+//             }
+//
+//             if (successGetNoteFileResult && "attachment" in successGetNoteFileResult) {
+//                 await bot.sendDocument({
+//                     chat_id: msg.chat.id,
+//                     reply_parameters: {
+//                         message_id: msg.message_id,
+//                     },
+//                     document: fs.createReadStream(path.join(notesDir, successGetNoteFileResult.attachment.relativePath)),
+//                 }).catch(logError);
+//             }
+//
+//             await appendOpenAiChatToolResults(chatMessages, calls, toolResults);
+//             continue;
+//         }
+//
+//         const request: ChatCompletionCreateParamsStreaming = {
+//             model: config.geminiChatTarget.model,
+//             messages: chatMessages,
+//             tools: getOpenAITools(msg.from?.id === Environment.CREATOR_ID),
+//             // temperature: 0.6,
+//             stream: true,
+//             parallel_tool_calls: true
+//         };
+//         const response = await geminiOpenAi.chat.completions.create(request, {signal}) as unknown as AsyncIterableStream<OpenAiChatCompletionStreamChunkLike>;
+//
+//         aiLog("debug", "openai_compatible.stream.open", {round});
+//         // const streamToolCalls: OpenAiChatToolCallLike[] = [];
+//         const roundTextStart = streamMessage.getText().length;
+//         const toolCallAccumulator = new StreamingToolCallAccumulator("openai_chat_stream", round);
+//         let calls: ToolCallData[] = [];
+//
+//         for await (const chunk of response) {
+//             if (signal.aborted) throw new Error("Aborted");
+//
+//             const delta = chunk.choices?.[0]?.delta;
+//             streamMessage.append(delta?.content ?? "");
+//
+//             if (delta?.tool_calls?.length) {
+//                 calls = toolCallAccumulator.add(delta.tool_calls);
+//                 streamMessage.setStatus(Environment.getUseToolText(calls));
+//                 await streamMessage.flush();
+//             }
+//         }
+//
+//         // const calls = collectOpenAiChatStreamToolCalls(streamToolCalls);
+//         aiLog(calls.length ? "info" : "success", calls.length ? "openai_compatible.tool_calls" : "openai_compatible.run.done", {
+//             round,
+//             duration: calls.length ? aiLogDuration(roundStartedAt) : aiLogDuration(runnerStartedAt),
+//             textChars: streamMessage.getText().slice(roundTextStart).length,
+//             calls: calls.map(aiLogToolCall),
+//         });
+//         if (!calls.length) return;
+//
+//         const roundText = streamMessage.getText().slice(roundTextStart);
+//         chatMessages.push({
+//             role: "assistant",
+//             content: roundText,
+//             tool_calls: calls.map(call => ({
+//                 id: call.id,
+//                 type: "function",
+//                 function: {
+//                     name: call.name,
+//                     arguments: call.argumentsText,
+//                 },
+//             })),
+//         });
+//
+//         const toolResults = await executeToolBatch(calls, streamMessage, toolContext, toolMemory);
+//
+//         let successGetNoteFileResult: GetNoteFileResult | undefined = undefined;
+//
+//         for (const toolResult of toolResults) {
+//             try {
+//                 const raw = JSON.parse(toolResult);
+//                 const res = GetNoteFileResultSchema.safeParse(raw);
+//
+//                 if (res.success && res.data.success) {
+//                     successGetNoteFileResult = res.data;
+//                 }
+//             } catch {
+//                 // Not every tool result is JSON.
+//             }
+//         }
+//
+//         if (successGetNoteFileResult && "attachment" in successGetNoteFileResult) {
+//             await bot.sendDocument({
+//                 chat_id: msg.chat.id,
+//                 reply_parameters: {
+//                     message_id: msg.message_id,
+//                 },
+//                 document: fs.createReadStream(path.join(notesDir, successGetNoteFileResult.attachment.relativePath)),
+//             }).catch(logError);
+//         }
+//
+//         await appendOpenAiChatToolResults(chatMessages, calls, toolResults);
+//     }
+// }

src/ai/unified-ai-runner.shared.ts

@@ -1,40 +1,41 @@
 import {Message} from "typescript-telegram-bot-api";
 import * as fs from "node:fs";
+import {Blob} from "node:buffer";
 import path from "node:path";
-import type {BoundaryValue} from "../common/boundary-types";
-import {AiProvider} from "../model/ai-provider.js";
-import {ToolRankerFallbackPolicy} from "../common/policies.js";
-import {Environment, type OpenAiBackend} from "../common/environment.js";
-import {delay, logError, replyToMessage} from "../util/utils.js";
-import {MessageStore} from "../common/message-store.js";
-import type {OpenAiResponseTool} from "./tool-mappers.js";
-import {AiProviderName, getOpenAICodeInterpreterTool, getOpenAIResponsesTools} from "./tool-mappers.js";
-import {TelegramArtifactFile, TelegramStreamMessage} from "./telegram-stream-message.js";
-import {AiDownloadedFile} from "./telegram-attachments.js";
-import {getRuntimeCapabilities} from "./provider-model-runtime.js";
-import {StoredAttachment} from "../model/stored-attachment.js";
-import {AiChatMessage, ChatMessage} from "./chat-messages-types.js";
+import {AiProvider} from "../model/ai-provider";
+import {Environment} from "../common/environment";
+import {photoGenDir} from "../index";
+import {collectReplyChainText, delay, logError, replyToMessage} from "../util/utils";
+import {MessageStore} from "../common/message-store";
+import type {OpenAiResponseTool} from "./tool-mappers";
+import {AiProviderName, getOpenAICodeInterpreterTool, getOpenAIResponsesTools} from "./tool-mappers";
+import {TelegramArtifactFile, TelegramStreamMessage} from "./telegram-stream-message";
+import {AiDownloadedFile} from "./telegram-attachments";
+import {getRuntimeCapabilities} from "./provider-model-runtime";
+import {StoredAttachment} from "../model/stored-attachment";
+import {AiChatMessage, ChatMessage} from "./chat-messages-types";
 import {ListResponse, Ollama} from "ollama";
-import {executeToolCall, ToolRuntimeContext} from "./tools/runtime.js";
-import {MessageImagePart, MessagePart} from "../common/message-part.js";
-import {KeyedAsyncLock} from "../util/async-lock.js";
-import {type AiRequestQueueTarget} from "./provider-request-queue.js";
-import {PYTHON_INTERPRETER_TOOL_NAME, pythonInterpreterToolPrompt} from "./tools/python-interpretator.js";
-import {getResponseLanguageInstruction, UserAiResponseLanguage, UserAiVoiceMode} from "../common/user-ai-settings.js";
+import {executeToolCall, ToolRuntimeContext} from "./tools/runtime";
+import {MessageImagePart, MessagePart} from "../common/message-part";
+import {KeyedAsyncLock} from "../util/async-lock";
+import {type AiRequestQueueTarget} from "./provider-request-queue";
+import {PYTHON_INTERPRETER_TOOL_NAME, pythonInterpreterToolPrompt} from "./tools/python-interpretator";
+import {getResponseLanguageInstruction, UserAiResponseLanguage, UserAiVoiceMode} from "../common/user-ai-settings";
 import {
     isTranscribableAudioDownload,
     resolveSpeechToTextProviderForUser,
     transcribeSpeechDownloads
-} from "./speech-to-text.js";
+} from "./speech-to-text";
+import {OpenAIChatMessage} from "./openai-chat-message";
+import type {ResponseInputContent, ResponseInputMessageContentList} from "openai/resources/responses/responses";
 import type {ChatCompletionMessageParam} from "openai/resources/chat/completions";
-import {MistralChatMessage} from "./mistral-chat-message.js";
-import {prepareTelegramMarkdownV2} from "../util/markdown-v2-renderer.js";
-import {AiRuntimeTarget, createMistralClient, resolveAiRuntimeTarget} from "./ai-runtime-target.js";
-import {aiLog, aiLogDuration, aiLogProviderTarget, aiLogToolCall} from "../logging/ai-logger.js";
-import {buildConversationSnapshot, serializeConversationSnapshot} from "./conversation-pipeline.js";
-import type {ResponseInputMessageContentList} from "openai/resources/responses/responses";
-import {persistToolResultArtifactAttachment} from "./tool-result-artifact-store.js";
-import {filterUserInputStoredAttachments} from "../common/attachment-visibility.js";
+import type {GenerateContentParameters} from "@google/genai";
+import {MistralChatMessage} from "./mistral-chat-message";
+import {OllamaChatMessage} from "./ollama-chat-message";
+import {GeminiMessage} from "./gemini-chat-message";
+import {prepareTelegramMarkdownV2} from "../util/markdown-v2-renderer";
+import {AiRuntimeTarget, createMistralClient, getGeminiApiMode, resolveAiRuntimeTarget} from "./ai-runtime-target";
+import {aiLog, aiLogDuration, aiLogProviderTarget, aiLogToolCall} from "../logging/ai-logger";
 
 export type {Message} from "typescript-telegram-bot-api";
 export type {AiRuntimeTarget} from "./ai-runtime-target";
@@ -46,6 +47,7 @@ export type {MessageImagePart, MessagePart} from "../common/message-part";
 export type {OpenAIChatMessage} from "./openai-chat-message";
 export type {MistralChatMessage} from "./mistral-chat-message";
 export type {OllamaChatMessage} from "./ollama-chat-message";
+export type {GeminiMessage} from "./gemini-chat-message";
 export type {TelegramArtifactFile} from "./telegram-stream-message";
 export {TelegramStreamMessage} from "./telegram-stream-message";
 export type {ChatRequest, ListResponse, Ollama, Tool} from "ollama";
@@ -61,6 +63,8 @@ export type {
     ChatCompletionCreateParamsStreaming,
     ChatCompletionMessageParam,
 } from "openai/resources/chat/completions";
+export type {GenerateContentParameters} from "@google/genai";
+
 export const TELEGRAM_LIMIT = 4096;
 export const MAX_TOOL_ROUNDS = 40;
 export const MAX_IDENTICAL_TOOL_CALLS = 1;
@@ -71,19 +75,13 @@ export const MAX_OLLAMA_CONTEXT_SIZE = 262144;
 export const DEFAULT_OLLAMA_CONTEXT_SIZE = 32768;
 export const toolResourceLocks = new KeyedAsyncLock();
 
-function photoGenDir(): string {
-    return path.join(Environment.DATA_PATH, "cache", "photo", "gen");
-}
-
 export type UnifiedRunOptions = {
     provider: AiProvider;
     msg: Message;
-    requestId?: string;
     isGuestMsg?: boolean;
     text: string;
     stream?: boolean;
     think?: Think;
-    synthesizeSpeechResponse?: boolean;
     responseLanguage?: UserAiResponseLanguage;
     contextSize?: number;
     voiceMode?: UserAiVoiceMode;
@@ -101,7 +99,7 @@ export type JsonValue = JsonPrimitive | JsonObject | JsonValue[];
 export type JsonObject = { [key: string]: JsonValue };
 
 // SDKs sometimes expose loose object-shaped payloads. Keep the looseness at the boundary,
-// but do not spread it through the rest of the code.
+// but do not spread `unknown` through the rest of the code.
 export type LooseRecord = Record<string, JsonValue | object | undefined>;
 
 export type OpenAiResponsesFunctionCall = {
@@ -183,6 +181,22 @@ export type OpenAiResponseLike = {
     output_text?: string;
 };
 
+export type GeminiFunctionCallLike = {
+    id?: string;
+    name?: string;
+    args?: JsonObject;
+};
+
+export type GeminiResponsePartLike = {
+    text?: string;
+    functionCall?: GeminiFunctionCallLike;
+};
+
+export type GeminiResponseLike = {
+    functionCalls?: GeminiFunctionCallLike[];
+    candidates?: Array<{ content?: { parts?: GeminiResponsePartLike[] } }>;
+};
+
 export type OpenAiCompatibleContentPart =
     | { type: "text"; text: string }
     | { type: "image_url"; image_url: { url: string } };
@@ -199,11 +213,13 @@ export type OpenAiChatCompletionStreamChunkLike = {
 
 export type AsyncIterableStream<T> = AsyncIterable<T>;
 
-export function isRecord(value: BoundaryValue): value is LooseRecord {
+export type GeminiGenerationRequest = GenerateContentParameters;
+
+export function isRecord(value: unknown): value is LooseRecord {
     return value !== null && typeof value === "object" && !Array.isArray(value);
 }
 
-export function toJsonValue(value: BoundaryValue): JsonValue | undefined {
+export function toJsonValue(value: unknown): JsonValue | undefined {
     if (value === null) return null;
 
     switch (typeof value) {
@@ -229,16 +245,16 @@ export function toJsonValue(value: BoundaryValue): JsonValue | undefined {
     }
 }
 
-export function toJsonObject(value: BoundaryValue): JsonObject | undefined {
+export function toJsonObject(value: unknown): JsonObject | undefined {
     const json = toJsonValue(value);
     return json !== null && typeof json === "object" && !Array.isArray(json) ? json : undefined;
 }
 
-export function asOptionalString(value: BoundaryValue): string | undefined {
+export function asOptionalString(value: unknown): string | undefined {
     return typeof value === "string" && value.trim().length > 0 ? value.trim() : undefined;
 }
 
-export function isAbortError(error: BoundaryValue): boolean {
+export function isAbortError(error: unknown): boolean {
     return error instanceof Error ? error.message.includes("Aborted") : String(error).includes("Aborted");
 }
 
@@ -251,7 +267,6 @@ export type RuntimeConfigSnapshot = {
     useSystemPrompt: boolean;
     systemPrompt?: string;
     rankerToolPrompt?: string;
-    toolRankerFallbackPolicy: ToolRankerFallbackPolicy;
 
     ollamaChatTarget: AiRuntimeTarget;
     ollamaToolRankerTarget?: AiRuntimeTarget;
@@ -268,13 +283,14 @@ export type RuntimeConfigSnapshot = {
     ollamaRagMaxArchiveFiles: number;
     ollamaRagMaxArchiveBytes: number;
     ollamaRagMaxArchiveDepth: number;
+
+    geminiChatTarget: AiRuntimeTarget;
+    geminiImageTarget: AiRuntimeTarget;
+
     mistralChatTarget: AiRuntimeTarget;
-    mistralToolRankerTarget?: AiRuntimeTarget;
 
     openAiChatTarget: AiRuntimeTarget;
     openAiImageTarget: AiRuntimeTarget;
-    openAiToolRankerTarget?: AiRuntimeTarget;
-    openAiBackend: OpenAiBackend;
 };
 
 export function snapshotRuntimeConfig(): RuntimeConfigSnapshot {
@@ -284,7 +300,6 @@ export function snapshotRuntimeConfig(): RuntimeConfigSnapshot {
 
         systemPrompt: Environment.SYSTEM_PROMPT,
         rankerToolPrompt: Environment.RANKER_TOOL_PROMPT,
-        toolRankerFallbackPolicy: Environment.TOOL_RANKER_FALLBACK_POLICY,
 
         ollamaChatTarget: resolveAiRuntimeTarget(AiProvider.OLLAMA, "chat"),
         ollamaToolRankerTarget: resolveAiRuntimeTarget(AiProvider.OLLAMA, "toolRank"),
@@ -302,20 +317,16 @@ export function snapshotRuntimeConfig(): RuntimeConfigSnapshot {
         ollamaRagMaxArchiveBytes: Environment.OLLAMA_RAG_MAX_ARCHIVE_BYTES,
         ollamaRagMaxArchiveDepth: Environment.OLLAMA_RAG_MAX_ARCHIVE_DEPTH,
 
+        geminiChatTarget: resolveAiRuntimeTarget(AiProvider.GEMINI, "chat"),
+        geminiImageTarget: resolveAiRuntimeTarget(AiProvider.GEMINI, "vision"),
+
         mistralChatTarget: resolveAiRuntimeTarget(AiProvider.MISTRAL, "chat"),
-        mistralToolRankerTarget: resolveAiRuntimeTarget(AiProvider.MISTRAL, "toolRank"),
 
         openAiChatTarget: resolveAiRuntimeTarget(AiProvider.OPENAI, "chat"),
         openAiImageTarget: resolveAiRuntimeTarget(AiProvider.OPENAI, "outputImages"),
-        openAiToolRankerTarget: resolveAiRuntimeTarget(AiProvider.OPENAI, "toolRank"),
-        openAiBackend: Environment.OPENAI_BACKEND,
     };
 }
 
-export function isOpenAiCompatibleBackend(config: RuntimeConfigSnapshot): boolean {
-    return config.openAiBackend === "compatible";
-}
-
 export function getMessageImageParts(part: MessagePart): MessageImagePart[] {
     if (part.imageParts?.length) return part.imageParts;
     return (part.images ?? []).map(data => ({data, mimeType: "image/jpeg"}));
@@ -325,10 +336,33 @@ export function openAiImageDataUrl(image: MessageImagePart): string {
     return `data:${image.mimeType || "image/jpeg"};base64,${image.data}`;
 }
 
+export function geminiAudioMimeType(mimeType: string | undefined): string {
+    const normalized = mimeType?.toLowerCase();
+    switch (normalized) {
+        case "audio/wav":
+        case "audio/mp3":
+        case "audio/aiff":
+        case "audio/aac":
+        case "audio/ogg":
+        case "audio/flac":
+        case "audio/mpeg":
+        case "audio/m4a":
+        case "audio/l16":
+        case "audio/opus":
+        case "audio/alaw":
+        case "audio/mulaw":
+            return normalized;
+        default:
+            return "audio/wav";
+    }
+}
+
 export function snapshotModel(provider: AiProvider, config: RuntimeConfigSnapshot): string {
     switch (provider) {
         case AiProvider.OLLAMA:
             return config.ollamaChatTarget.model;
+        case AiProvider.GEMINI:
+            return config.geminiChatTarget.model;
         case AiProvider.MISTRAL:
             return config.mistralChatTarget.model;
         case AiProvider.OPENAI:
@@ -348,27 +382,12 @@ export function providerTargets(provider: AiProvider, config: RuntimeConfigSnaps
                 config.ollamaAudioTarget,
                 config.ollamaDocumentsTarget
             ].filter((target): target is AiRuntimeTarget => !!target);
+        case AiProvider.GEMINI:
+            return [config.geminiChatTarget];
         case AiProvider.MISTRAL:
-            return [
-                config.mistralChatTarget,
-                config.mistralToolRankerTarget,
-            ].filter((target): target is AiRuntimeTarget => !!target);
+            return [config.mistralChatTarget];
         case AiProvider.OPENAI:
-            return [
-                config.openAiChatTarget,
-                config.openAiToolRankerTarget,
-            ].filter((target): target is AiRuntimeTarget => !!target);
-    }
-}
-
-export function providerChatTarget(provider: AiProvider, config: RuntimeConfigSnapshot): AiRuntimeTarget {
-    switch (provider) {
-        case AiProvider.OLLAMA:
-            return config.ollamaChatTarget;
-        case AiProvider.MISTRAL:
-            return config.mistralChatTarget;
-        case AiProvider.OPENAI:
-            return config.openAiChatTarget;
+            return [config.openAiChatTarget];
     }
 }
 
@@ -376,6 +395,8 @@ export function providerName(provider: AiProvider): AiProviderName {
     switch (provider) {
         case AiProvider.OLLAMA:
             return "ollama";
+        case AiProvider.GEMINI:
+            return "gemini";
         case AiProvider.MISTRAL:
             return "mistral";
         case AiProvider.OPENAI:
@@ -387,14 +408,10 @@ export function buildSystemInstruction(
     config: RuntimeConfigSnapshot,
     responseLanguage: UserAiResponseLanguage,
     includePythonToolPrompt: boolean,
-    additions?: string | null,
-    memoryInstruction?: string | null,
 ): string {
     return [
         config.useSystemPrompt ? getResponseLanguageInstruction(responseLanguage) : null,
         config.systemPrompt && config.useSystemPrompt ? config.systemPrompt : null,
-        additions?.trim() ? additions.trim() : null,
-        memoryInstruction?.trim() ? memoryInstruction.trim() : null,
         includePythonToolPrompt ? pythonInterpreterToolPrompt : null,
     ].filter(Boolean).join("\n\n");
 }
@@ -425,6 +442,8 @@ export function resolveAiRequestQueueTarget(
             if (hasAudioAttachmentKind(requestedAttachmentKinds)) return config.ollamaAudioTarget;
             if (requestedAttachmentKinds.has("image")) return config.ollamaVisionTarget;
             return options.think ? config.ollamaThinkingTarget : config.ollamaChatTarget;
+        case AiProvider.GEMINI:
+            return config.geminiChatTarget;
         case AiProvider.MISTRAL:
             return config.mistralChatTarget;
         case AiProvider.OPENAI:
@@ -524,13 +543,13 @@ export function addMessageAttachmentKinds(msg: Message | undefined, kinds: Set<A
     if (msg.video) kinds.add("video");
 }
 
-export async function collectStoredReplyChainAttachments(msg: Message, limit: number = 40): Promise<StoredAttachment[]> {
+export async function collectStoredReplyChainAttachments(msg: Message, limit: number = 1): Promise<StoredAttachment[]> {
     const attachments: StoredAttachment[] = [];
     const seen = new Set<string>();
     let current = await MessageStore.get(msg.chat.id, msg.message_id);
 
     for (let i = 0; current && i < limit; i++) {
-        for (const attachment of filterUserInputStoredAttachments(current?.attachments ?? [])) {
+        for (const attachment of current?.attachments ?? []) {
             const key = [
                 attachment.kind,
                 attachment.fileUniqueId || attachment.fileId,
@@ -550,6 +569,13 @@ export async function hasStoredReplyChainImage(msg: Message): Promise<boolean> {
     const attachments = await collectStoredReplyChainAttachments(msg);
     if (attachments.some(attachment => attachment.kind === "image")) return true;
 
+    let current = await MessageStore.get(msg.chat.id, msg.message_id);
+
+    for (let i = 0; current && i < 40; i++) {
+        if (current.photoMaxSizeFilePath?.length) return true;
+        current = await MessageStore.get(current.chatId, current.replyToMessageId);
+    }
+
     return false;
 }
 
@@ -622,6 +648,7 @@ export async function rejectUnsupportedAttachments(
     if (!unsupported) return false;
 
     if (!kinds.has("audio")) {
+        // TODO: 13.05.2026, Danil Nikolaev: add "Regenerate" button
         await replyToMessage({
             message: msg,
             text: unsupportedAttachmentText(provider, effectiveModel, unsupported),
@@ -685,7 +712,7 @@ export function parseToolArgumentsObject(argumentsText?: string): ToolArgumentsP
     }
 }
 
-export function errorMessage(error: BoundaryValue): string {
+export function errorMessage(error: unknown): string {
     return error instanceof Error ? error.message : String(error);
 }
 
@@ -776,30 +803,191 @@ export function normalizeOllamaToolCalls(calls: readonly OllamaToolCallLike[] =
         .filter(call => !!call.name);
 }
 
+export function buildOpenAiResponseMessage(part: MessagePart, getContent: (part: MessagePart) => string): OpenAIChatMessage {
+    const content: Array<ResponseInputContent | any> = [{
+        type: part.bot ? "output_text" : "input_text",
+        text: getContent(part),
+    }];
+
+    if (!part.bot) {
+        for (const image of getMessageImageParts(part)) {
+            content.push({type: "input_image", image_url: openAiImageDataUrl(image), detail: "auto"});
+        }
+    }
+
+    return {role: part.bot ? "assistant" : "user", content, type: "message"};
+}
+
+export function buildGeminiMessage(part: MessagePart, getContent: (part: MessagePart) => string): GeminiMessage {
+    const parts: GeminiMessage["parts"] = [{text: getContent(part)}];
+
+    if (!part.bot) {
+        for (const image of getMessageImageParts(part)) {
+            parts.push({
+                inlineData: {
+                    data: image.data,
+                    mimeType: image.mimeType || "image/jpeg",
+                },
+            });
+        }
+
+        const audioParts = part.audioParts?.length
+            ? part.audioParts
+            : (part.audios ?? []).map(data => ({data, mimeType: "audio/wav"}));
+
+        for (const audio of audioParts) {
+            parts.push({
+                inlineData: {
+                    data: audio.data,
+                    mimeType: geminiAudioMimeType(audio.mimeType),
+                },
+            });
+        }
+
+        for (const videoNote of part.videoNotes ?? []) {
+            parts.push({
+                inlineData: {
+                    data: videoNote,
+                    mimeType: "audio/wav",
+                },
+            });
+        }
+    }
+
+    return {
+        role: part.bot ? "model" : "user",
+        parts,
+    };
+}
+
 export async function collectTextMessages(
     msg: Message,
     textOverride: string,
     provider: AiProvider,
     downloads: AiDownloadedFile[],
     config: RuntimeConfigSnapshot,
-    runtimeTarget: AiRuntimeTarget,
     responseLanguage: UserAiResponseLanguage,
 ): Promise<{
     chatMessages: AiChatMessage[];
     imageCount: number
 }> {
-    const includePythonToolPrompt = Environment.ENABLE_PYTHON_INTERPRETER && msg.from?.id === Environment.CREATOR_ID;
-    const snapshot = await buildConversationSnapshot(
-        msg,
-        textOverride,
-        downloads,
-        config,
-        runtimeTarget,
-        responseLanguage,
-        includePythonToolPrompt,
-    );
+    const storedMsg = await MessageStore.get(msg.chat.id, msg.message_id);
+    const messageParts = await collectReplyChainText({triggerMsg: storedMsg, downloads: downloads});
 
-    return serializeConversationSnapshot(snapshot, provider, Environment.USE_NAMES_IN_PROMPT);
+    const cleanTextOverride = textOverride?.trim();
+    if (messageParts.length && cleanTextOverride) {
+        const latest = messageParts[0];
+        if (!latest.bot) latest.content = textOverride.trim();
+    }
+
+    const ordered = messageParts.reverse();
+    const imageCount = ordered.reduce((sum, p) => sum + (p.bot ? 0 : getMessageImageParts(p).length), 0);
+    const includePythonToolPrompt = Environment.ENABLE_PYTHON_INTERPRETER && msg.from?.id === Environment.CREATOR_ID;
+    const systemInstruction = buildSystemInstruction(config, responseLanguage, includePythonToolPrompt);
+
+    const getContent = (part: MessagePart): string => {
+        if (part.bot) return part.content;
+
+        const userInfo = [
+            "[user_info]:",
+            `name: ${part.name}`,
+            `username: @${part.userName}`,
+            ""
+        ].join("\n");
+
+        const finalContent = [
+            part.content
+        ];
+
+        if (Environment.USE_NAMES_IN_PROMPT) {
+            finalContent.unshift(userInfo);
+        }
+
+        return finalContent.join("\n");
+    };
+
+    if (provider === AiProvider.OPENAI) {
+        const messages: OpenAIChatMessage[] = ordered.map(part => buildOpenAiResponseMessage(part, getContent));
+
+        if (systemInstruction) {
+            messages.unshift({role: "system", content: systemInstruction, type: "message"});
+        }
+        return {chatMessages: messages, imageCount};
+    }
+
+    if (provider === AiProvider.MISTRAL) {
+        const messages: MistralChatMessage[] = ordered.map(part => {
+            if (part.bot) {
+                return {
+                    role: "assistant",
+                    content: [{type: "text", text: getContent(part)}]
+                };
+            } else {
+                return {
+                    role: "user",
+                    content: [
+                        {type: "text", text: getContent(part)},
+                        ...getMessageImageParts(part).map(p => {
+                            return {
+                                type: "image_url" as const,
+                                imageUrl: `data:${p.mimeType || "image/jpeg"};base64,${p.data}`
+                            };
+                        })
+                    ]
+                };
+            }
+        });
+
+        if (systemInstruction) {
+            messages.unshift({role: "system", content: systemInstruction});
+        }
+        return {chatMessages: messages, imageCount};
+    }
+
+    if (provider === AiProvider.OLLAMA) {
+        const messages: OllamaChatMessage[] = ordered.map(part => ({
+            role: part.bot ? "assistant" : "user",
+            content: getContent(part),
+            images: part.bot ? undefined : part.images,
+            imageParts: part.imageParts,
+            audios: part.audios,
+            audioParts: part.audioParts,
+            videos: part.videos,
+            videoNotes: part.videoNotes
+        }));
+
+        if (systemInstruction) {
+            messages.unshift({
+                role: "system",
+                content: systemInstruction
+            });
+        }
+
+        return {chatMessages: messages, imageCount};
+    }
+
+    if (provider === AiProvider.GEMINI) {
+        if (getGeminiApiMode(config.geminiChatTarget) === "openai") {
+            const messages: OpenAIChatMessage[] = ordered.map(part => buildOpenAiResponseMessage(part, getContent));
+            if (systemInstruction) {
+                messages.unshift({role: "system", content: systemInstruction, type: "message"});
+            }
+
+            return {chatMessages: messages, imageCount};
+        }
+
+        const messages: GeminiMessage[] = ordered.map(part => buildGeminiMessage(part, getContent));
+        if (systemInstruction) {
+            messages.unshift({
+                role: "user",
+                parts: [{text: systemInstruction}],
+            });
+        }
+
+        return {chatMessages: messages, imageCount};
+    }
+
+    return {chatMessages: [], imageCount: -1};
 }
 
 export async function transcribeAudioIfNeeded(provider: AiProvider, userId: number | undefined, downloads: AiDownloadedFile[], message: TelegramStreamMessage, signal: AbortSignal): Promise<string> {
@@ -838,7 +1026,7 @@ export async function transcribeAudioIfNeeded(provider: AiProvider, userId: numb
         });
         return transcript;
     } catch (e) {
-        aiLog("error", "speech_to_text.failed", {duration: aiLogDuration(startedAt), error: e instanceof Error ? e : String(e)});
+        aiLog("error", "speech_to_text.failed", {duration: aiLogDuration(startedAt), error: e});
         throw e;
     }
 }
@@ -855,11 +1043,20 @@ export function stripAudioFromRunnerMessages(parts: AiChatMessage[]): void {
         if ("videoNotes" in part) {
             delete part.videoNotes;
         }
+
+        if ("parts" in part && Array.isArray(part.parts)) {
+            part.parts = part.parts.filter(geminiPart => {
+                if (!("inlineData" in geminiPart)) return true;
+                const mimeType = geminiPart.inlineData.mimeType.toLowerCase();
+                return !mimeType.startsWith("audio/") && !mimeType.startsWith("video/");
+            });
+        }
     }
 }
 
 export function appendTranscriptToChatMessages(
     chatMessages: AiChatMessage[],
+    provider: AiProvider,
     transcript: string,
 ): void {
     const lastUser = [...chatMessages].reverse().find(message => "role" in message && message.role === "user");
@@ -868,6 +1065,11 @@ export function appendTranscriptToChatMessages(
     const text = transcript.trim();
     if (!text) return;
 
+    if (provider === AiProvider.GEMINI && "parts" in lastUser && Array.isArray(lastUser.parts)) {
+        lastUser.parts.push({text});
+        return;
+    }
+
     if (!("content" in lastUser)) return;
 
     if (typeof lastUser.content === "string") {
@@ -883,7 +1085,8 @@ export function appendTranscriptToChatMessages(
             // narrows it to the Chat Completions union (`text | image_url | thinking`),
             // which makes comparisons with Responses parts (`input_text | input_image`)
             // look impossible even though this is a runtime mixed-provider guard.
-            const partType = (part as {type?: string}).type;
+            const record: Record<string, unknown> = part;
+            const partType = record["type"];
 
             return partType === "input_text" || partType === "input_image";
         });
@@ -906,8 +1109,8 @@ export async function deleteMistralLibrary(libraryId: string | undefined, target
         await mistralAi.beta.libraries.delete({libraryId});
         aiLog("success", "mistral.library.delete.done", {libraryId, duration: aiLogDuration(startedAt)});
     } catch (e) {
-        aiLog("error", "mistral.library.delete.failed", {libraryId, duration: aiLogDuration(startedAt), error: e instanceof Error ? e : String(e)});
-        logError(e instanceof Error ? e : String(e));
+        aiLog("error", "mistral.library.delete.failed", {libraryId, duration: aiLogDuration(startedAt), error: e});
+        logError(e);
     }
 }
 
@@ -1058,7 +1261,7 @@ export async function prepareMistralDocuments(downloads: AiDownloadedFile[], mes
         aiLog("error", "mistral.documents.prepare.failed", {
             libraryId,
             duration: aiLogDuration(startedAt),
-            error: e instanceof Error ? e : String(e),
+            error: e,
         });
         await deleteMistralLibrary(libraryId, target);
         throw e;
@@ -1109,47 +1312,35 @@ export async function executeTool(
 
         return result;
     } catch (error) {
-        if (isAbortError(error instanceof Error ? error : String(error))) {
+        if (isAbortError(error)) {
             throw error;
         }
 
-        const result = toolFailureResult("execution_failed", errorMessage(error instanceof Error ? error : String(error)));
+        const result = toolFailureResult("execution_failed", errorMessage(error));
 
         aiLog("error", "tool.failed.returned_to_model", {
             name: toolCall.name,
             duration: aiLogDuration(startedAt),
-            error: error instanceof Error ? error : String(error),
+            error,
         });
 
         return result;
     }
 }
 
-export function toolResourceKeys(toolCall: ToolCallData, userId?: number | undefined | null): string[] {
+export function toolResourceKeys(toolCall: ToolCallData): string[] {
     const args = safeJsonParseObject(toolCall.argumentsText);
     const pathValue = typeof args.path === "string" ? args.path : undefined;
     const sourcePath = typeof args.sourcePath === "string" ? args.sourcePath : undefined;
     const targetPath = typeof args.targetPath === "string" ? args.targetPath : undefined;
-    const memoryScope = toolCall.name.endsWith("_user_info") ? "user"
-        : toolCall.name.endsWith("_system_info") ? "system"
-            : undefined;
 
     switch (toolCall.name) {
-        case "read_user_info":
-        case "read_system_info":
         case "get_datetime":
         case "web_search":
         case "get_weather":
         case "read_file":
         case "list_directory":
             return [];
-        case "add_user_info":
-        case "add_system_info":
-        case "remove_user_info":
-        case "remove_system_info":
-        case "replace_user_info":
-        case "replace_system_info":
-            return userId && memoryScope ? [`memory:${userId}:${memoryScope}`] : [];
         case "create_file":
         case "create_directory":
         case "update_file":
@@ -1182,7 +1373,7 @@ export async function executeScheduledTool(
     message: TelegramStreamMessage,
     context: ToolRuntimeContext,
 ): Promise<string> {
-    const keys = toolResourceKeys(toolCall, userId);
+    const keys = toolResourceKeys(toolCall);
     if (!keys.length) return executeTool(userId, toolCall, message, context);
     return runWithToolLocks(keys, () => executeTool(userId, toolCall, message, context));
 }
@@ -1263,33 +1454,6 @@ export async function executeToolBatch(
         message.setStatus(Environment.getUseToolText(statusCalls));
         await message.flush();
 
-        const finishedAt = new Date().toISOString();
-        await Promise.all(results.map(async (resultText, index) => {
-            const toolCall = toolCalls[index];
-            if (!toolCall) return;
-
-            message.recordToolExecution({
-                toolName: toolCall.name,
-                callId: toolCall.id,
-                argumentsText: toolCall.argumentsText,
-                resultChars: resultText.length,
-                startedAt: new Date(startedAt).toISOString(),
-                finishedAt,
-            });
-
-            try {
-                const attachment = await persistToolResultArtifactAttachment({
-                    toolCall,
-                    resultText,
-                    chatId: message.sourceChatId(),
-                    messageId: message.sourceMessageId(),
-                });
-                await message.storeInternalAttachment(attachment);
-            } catch (error) {
-                logError(error instanceof Error ? error : String(error));
-            }
-        }));
-
         aiLog("success", "tool.batch.done", {
             count: toolCalls.length,
             uniqueCount: statusCalls.length,
@@ -1301,7 +1465,7 @@ export async function executeToolBatch(
         aiLog("error", "tool.batch.failed", {
             count: toolCalls.length,
             duration: aiLogDuration(startedAt),
-            error: e instanceof Error ? e : String(e),
+            error: e,
         });
 
         throw e;
@@ -1318,7 +1482,7 @@ export function appendOllamaToolResults(messages: ChatMessage[], calls: ToolCall
     }
 }
 
-export function stringifyToolExecutionResult(result: BoundaryValue): string {
+export function stringifyToolExecutionResult(result: unknown): string {
     if (typeof result === "string") return result;
     const json = JSON.stringify(toJsonValue(result) ?? String(result));
     return json ?? String(result);
@@ -1326,7 +1490,7 @@ export function stringifyToolExecutionResult(result: BoundaryValue): string {
 
 export type ToolExecutionMemory = Map<string, { count: number; result: string }>;
 
-export function stableJsonStringify(value: BoundaryValue): string {
+export function stableJsonStringify(value: unknown): string {
     if (Array.isArray(value)) {
         return `[${value.map(stableJsonStringify).join(",")}]`;
     }
@@ -1441,14 +1605,14 @@ export type NormalizedRouterPlan = {
     m: string; // Missing
 };
 
-export function toolSchemaName(tool: BoundaryValue): string | undefined {
+export function toolSchemaName(tool: unknown): string | undefined {
     if (!isRecord(tool)) return undefined;
     const fn = isRecord(tool.function) ? tool.function : undefined;
-    const directName = fn?.name ?? tool.name ?? (typeof tool.type === "string" && tool.type !== "function" ? tool.type : undefined);
+    const directName = fn?.name ?? tool.name;
     return asOptionalString(directName);
 }
 
-export function toolSchemaNames(tool: BoundaryValue): string[] {
+export function toolSchemaNames(tool: unknown): string[] {
     if (!isRecord(tool)) return [];
 
     if (Array.isArray(tool.functionDeclarations)) {
@@ -1461,16 +1625,12 @@ export function toolSchemaNames(tool: BoundaryValue): string[] {
     return name ? [name] : [];
 }
 
-export function allToolSchemaNames(tools: readonly BoundaryValue[]): string[] {
+export function allToolSchemaNames(tools: readonly unknown[]): string[] {
     return [...new Set(tools.flatMap(toolSchemaNames))];
 }
 
-export function getOpenAIResponsesToolsWithImage(
-    config: RuntimeConfigSnapshot,
-    forCreator?: boolean,
-    vectorStoreIds: string[] = [],
-): Array<OpenAiResponseTool | LooseRecord> {
-    const tools: Array<OpenAiResponseTool | LooseRecord> = [
+export function getOpenAIResponsesToolsWithImage(config: RuntimeConfigSnapshot, forCreator?: boolean): Array<OpenAiResponseTool | LooseRecord> {
+    return [
         ...getOpenAIResponsesTools(forCreator),
         getOpenAICodeInterpreterTool(),
         {
@@ -1481,17 +1641,8 @@ export function getOpenAIResponsesToolsWithImage(
             output_format: "png",
             partial_images: OPENAI_IMAGE_PARTIALS,
         },
-        {type: "web_search"},
+        {type: "web_search"}
     ];
-
-    if (vectorStoreIds.length) {
-        tools.unshift({
-            type: "file_search",
-            vector_store_ids: vectorStoreIds,
-        });
-    }
-
-    return tools;
 }
 
 export function collectOpenAiResponseText(response: OpenAiResponseLike): string {
@@ -1529,7 +1680,7 @@ export function collectOpenAiResponseCodeInterpreterCalls(response: OpenAiRespon
             id: item.id!,
             code: item.code ?? null,
             containerId: item.container_id!,
-            status: item.status ?? "unrecognized",
+            status: item.status ?? "unknown",
             outputs: Array.isArray(item.outputs) ? item.outputs : [],
         }));
 }
@@ -1540,16 +1691,11 @@ export function collectOpenAiResponseImages(response: OpenAiResponseLike): strin
         .map(item => item.result!);
 }
 
-export function writeOpenAiGeneratedImage(sourceMessage: Message, b64: string, label: string): {
-    buffer: Buffer;
-    cachePath: string;
-    fileName: string;
-} {
-    const buffer = Buffer.from(b64, "base64");
+export function writeOpenAiGeneratedImage(sourceMessage: Message, b64: string, label: string): Buffer {
+    const imageBuffer = Buffer.from(b64, "base64");
     const fileName = `${sourceMessage.chat.id}_${sourceMessage.message_id}_${Date.now()}_${label}.png`;
-    const cachePath = path.join(photoGenDir(), fileName);
-    fs.writeFileSync(cachePath, buffer);
-    return {buffer, cachePath, fileName};
+    fs.writeFileSync(path.join(photoGenDir, fileName), imageBuffer);
+    return imageBuffer;
 }
 
 export async function showOpenAiGeneratedImage(
@@ -1560,21 +1706,14 @@ export async function showOpenAiGeneratedImage(
     status: string,
     final: boolean,
 ): Promise<void> {
-    const image = writeOpenAiGeneratedImage(sourceMessage, b64, label);
-    const attachment: StoredAttachment = {
-        kind: "image",
-        fileId: image.cachePath,
-        fileName: image.fileName,
-        mimeType: "image/png",
-        cachePath: image.cachePath,
-    };
+    const imageBuffer = writeOpenAiGeneratedImage(sourceMessage, b64, label);
     if (final && !streamMessage.getText().trim()) {
         streamMessage.replaceText(status);
         streamMessage.clearStatus();
     } else {
         streamMessage.setStatus(status);
     }
-    await streamMessage.showImage(image.buffer, attachment);
+    await streamMessage.showImage(imageBuffer);
 }
 
 export function openAiResponseItemCallId(item: OpenAiResponseOutputItem & { id?: string }): string {

src/ai/unified-ai-runner.tool-ranker.ts

@@ -1,248 +1,219 @@
-import type {ChatCompletionCreateParamsNonStreaming, ChatCompletionMessageParam} from "openai/resources/chat/completions";
-import {ChatRequest} from "ollama";
-import {BoundaryValue} from "../common/boundary-types.js";
-import {ToolRankerFallbackPolicy} from "../common/policies.js";
-import {AiProvider} from "../model/ai-provider.js";
-import {createMistralClient, createOllamaClient, createOpenAiClient, sameRuntimeEndpoint} from "./ai-runtime-target.js";
-import {aiLog, aiLogDuration, aiLogProviderTarget} from "../logging/ai-logger.js";
-import {providerChatTarget, RuntimeConfigSnapshot} from "./unified-ai-runner.shared.js";
+import {Tool} from "ollama";
+import {createOllamaClient} from "./ai-runtime-target";
+import {aiLog, aiLogDuration, aiLogProviderTarget} from "../logging/ai-logger";
 import {
-    buildRankerContext,
-    buildRankerTarget,
-    buildToolRankerPrompt,
-    filterRankedTools,
-    ToolRankerSelection,
-} from "./tool-ranker-pipeline.js";
-import {allToolSchemaNames} from "./unified-ai-runner.shared.js";
-import {sanitizeToolRankerResult} from "./tool-ranker-metadata.js";
-import {resolveToolRankerFallbackSelection} from "./tool-ranker-fallback.js";
+    allToolSchemaNames,
+    isRecord,
+    RuntimeConfigSnapshot,
+    toolSchemaNames
+} from "./unified-ai-runner.shared";
+import {z} from "zod";
+import {PYTHON_INTERPRETER_TOOL_NAME} from "./tools/python-interpretator";
 
-export class ToolRanker {
+export type ToolRankerSelection = {
+    tools: Tool[];
+    usedRanker: boolean;
+};
+
+export class OllamaToolRanker {
     constructor(private readonly config: RuntimeConfigSnapshot) {
     }
 
     async selectTools(args: {
-        provider: AiProvider;
         userQuery: string;
-        availableTools: readonly BoundaryValue[];
+        availableTools: Tool[];
         round: number;
         signal: AbortSignal;
-        messages?: readonly { role?: string; content?: string | readonly { text?: string }[] }[];
-        runRanker?: (
-            provider: AiProvider,
-            target: NonNullable<ReturnType<typeof buildRankerTarget>>,
-            prompt: string,
-            userQuery: string,
-        ) => Promise<string>;
     }): Promise<ToolRankerSelection> {
-        const {availableTools, provider, round, signal, userQuery} = args;
-        const runRanker = args.runRanker ?? this.runRanker.bind(this);
-        const availableNames = allToolSchemaNames(availableTools);
-        const fallbackPolicy = this.config.toolRankerFallbackPolicy;
-        const configuredTarget = buildRankerTarget(this.config, provider);
-        const mainModelTarget = providerChatTarget(provider, this.config);
+        const {availableTools, round, signal, userQuery} = args;
+        const target = this.config.ollamaToolRankerTarget;
 
         if (!availableTools.length) {
-            return {toolNames: [], usedRanker: false};
+            return {tools: [], usedRanker: false};
         }
 
-        const target = configuredTarget ?? (fallbackPolicy === ToolRankerFallbackPolicy.MAIN_MODEL ? mainModelTarget : undefined);
-
-        if (!target) {
-            return resolveToolRankerFallbackSelection({
-                fallbackPolicy,
-                availableToolNames: availableNames,
-            });
+        // Ranker disabled/unconfigured: keep old behavior and expose all allowed tools.
+        if (!target?.model) {
+            return {
+                tools: availableTools,
+                usedRanker: false,
+            };
         }
 
         const startedAt = Date.now();
-        const ranker = buildToolRankerPrompt(buildRankerContext(this.config, provider, target, round, userQuery, availableTools));
+        const availableNames = new Set(allToolSchemaNames(availableTools));
+        // const prompt = this.config.rankerToolPrompt?.trim() || DEFAULT_TOOL_RANKER_PROMPT;
 
-        aiLog("debug", "tool_ranker.start", {
-            provider,
+        const availableToolNames = availableTools.map(t => "- " + (t.function.name ?? ""));
+
+        const toolRouterPrompt = () => [
+            "You are a tool routing model.",
+            "Select the best tool.",
+            "Return ONLY valid JSON.",
+            "",
+            "Available tools:",
+            "- no_tool",
+            // "- ask_clarification",
+            // "- user_sad",
+            // "- user_angry",
+            availableToolNames.join("\n"),
+            "",
+            "Never explain reasoning.",
+            // "If user is sounds aggressive/angry, then pick `user_angry` tool.",
+            // "If the user's request is unclear, then pick `ask_clarification` tool.",
+            availableToolNames.find(t => t === "web_search") ?
+                "If you don't know the answer, then pick `search_web` tool." : null,
+            availableToolNames.find(t => t == PYTHON_INTERPRETER_TOOL_NAME) ?
+                "If user asks to write/execute Python code, then use `" + PYTHON_INTERPRETER_TOOL_NAME + "`" : null,
+            "",
+
+            "Return valid JSON ONLY in this format (NO ARGUMENTS): {\"toolNames\": [\"$toolName\", ... \"lastToolName\"]}",
+        ].filter(Boolean).join("\n");
+
+        const routerSchema = {
+            type: "object",
+            properties: {
+                name: {
+                    type: "string",
+                    enum: [
+                        "no_tool",
+                        "ask_clarification",
+                        ...availableToolNames
+                    ],
+                },
+                arguments: {
+                    type: "object",
+                    additionalProperties: true,
+                },
+            },
+            required: ["name"],
+            additionalProperties: false,
+        } as const;
+
+        // const toolsForPrompt = availableTools.map(tool => ({
+        //     names: toolSchemaNames(tool),
+        //     schema: tool,
+        // }));
+
+        aiLog("debug", "ollama.tool_ranker.start", {
             round,
             target: aiLogProviderTarget(target),
             queryChars: userQuery.length,
-            availableTools: availableNames,
-            fallbackPolicy,
-            usedMainModelFallback: !configuredTarget && fallbackPolicy === ToolRankerFallbackPolicy.MAIN_MODEL,
+            availableTools: [...availableNames],
         });
 
         try {
-            if (signal.aborted) throw new Error("Aborted");
-            const raw = await runRanker(provider, target, ranker.prompt, userQuery);
-            if (signal.aborted) throw new Error("Aborted");
-            const selectedNames = sanitizeToolRankerResult({
-                raw,
-                availableToolNames: availableNames,
-            });
-            const filtered = filterRankedTools(availableTools, selectedNames);
-            const toolNames = allToolSchemaNames(filtered);
+            const ollama = createOllamaClient(target);
+            // const response = await ollama.chat({
+            //     model: target.model,
+            //     messages: [
+            //         {role: "system", content: prompt},
+            //         {
+            //             role: "user",
+            //             content: JSON.stringify({
+            //                 q: userQuery,
+            //                 tools: toolsForPrompt,
+            //             }),
+            //         },
+            //     ],
+            //     stream: false,
+            //     options: {
+            //         temperature: 0,
+            //         num_ctx: 8192,
+            //     },
+            // });
 
-            aiLog("debug", "tool_ranker.done", {
-                provider,
+            const then = performance.now();
+
+            const response = await ollama.chat({
+                model: target?.model ?? "",
+                messages: [
+                    {
+                        role: "system",
+                        content: toolRouterPrompt()
+                    },
+                    {
+                        role: "user",
+                        content: userQuery,
+                    }
+                ],
+                stream: false,
+                think: false,
+                format: routerSchema,
+                options: {
+                    temperature: 0,
+                    top_p: 0.8,
+                    top_k: 20,
+                    repeat_penalty: 1.05,
+                    num_ctx: 8192,
+                    num_predict: 256
+                },
+            });
+
+            const now = performance.now();
+            const diff = now - then;
+            console.log("TOOK " + diff + "ms");
+
+            console.log("OLLAMA_RESPONSE: ", JSON.stringify(response));
+
+            if (signal.aborted) throw new Error("Aborted");
+
+            const raw = response.message?.content?.trim() ?? "";
+            const schema = z.object({
+                toolNames: z.array(z.string())
+            });
+            const res = schema.safeParse(JSON.parse(raw));
+
+            const selectedNames: string[] = [];
+
+            if (res.success) {
+                selectedNames.push(...res.data.toolNames);
+            }
+
+            const selectedNameSet = new Set(selectedNames);
+            const tools = availableTools.filter(tool => toolSchemaNames(tool).some(name => selectedNameSet.has(name)));
+
+            aiLog("debug", "ollama.tool_ranker.done", {
                 round,
                 duration: aiLogDuration(startedAt),
                 selectedNames,
-                selectedCount: toolNames.length,
+                selectedCount: tools.length,
                 rawPreview: raw.slice(0, 800),
             });
 
-            return {toolNames, usedRanker: true};
+            // Important: if the plan is valid and empty, use NO tools. Do not fall back to all tools.
+            return {tools, usedRanker: true};
         } catch (error) {
-            if (error instanceof Error && error.message.includes("Aborted")) throw error;
-            let failureMessage = error instanceof Error ? error.message : String(error);
+            if (String(error).includes("Aborted")) throw error;
 
-            const canRetryOnMainModel = fallbackPolicy === ToolRankerFallbackPolicy.MAIN_MODEL
-                && (
-                    target.model !== mainModelTarget.model
-                    || !sameRuntimeEndpoint(target, mainModelTarget)
-                );
-
-            if (canRetryOnMainModel) {
-                try {
-                    aiLog("warn", "tool_ranker.failed.retry_main_model", {
-                        provider,
-                        round,
-                        target: aiLogProviderTarget(target),
-                        fallbackTarget: aiLogProviderTarget(mainModelTarget),
-                        duration: aiLogDuration(startedAt),
-                        errorSummary: failureMessage,
-                    });
-
-                    const fallbackRanker = buildToolRankerPrompt(
-                        buildRankerContext(this.config, provider, mainModelTarget, round, userQuery, availableTools),
-                    );
-                    const raw = await runRanker(provider, mainModelTarget, fallbackRanker.prompt, userQuery);
-                    const selectedNames = sanitizeToolRankerResult({
-                        raw,
-                        availableToolNames: availableNames,
-                    });
-                    const filtered = filterRankedTools(availableTools, selectedNames);
-                    const toolNames = allToolSchemaNames(filtered);
-
-                    aiLog("debug", "tool_ranker.done", {
-                        provider,
-                        round,
-                        duration: aiLogDuration(startedAt),
-                        selectedNames,
-                        selectedCount: toolNames.length,
-                        rawPreview: raw.slice(0, 800),
-                        fallbackUsed: true,
-                    });
-
-                    return {toolNames, usedRanker: true};
-                } catch (fallbackError) {
-                    if (fallbackError instanceof Error && fallbackError.message.includes("Aborted")) throw fallbackError;
-
-                    const fallbackErrorMessage = fallbackError instanceof Error ? fallbackError.message : String(fallbackError);
-                    aiLog("warn", "tool_ranker.failed.main_model_fallback_failed", {
-                        provider,
-                        round,
-                        target: aiLogProviderTarget(target),
-                        fallbackTarget: aiLogProviderTarget(mainModelTarget),
-                        duration: aiLogDuration(startedAt),
-                        errorSummary: fallbackErrorMessage,
-                    });
-
-                    failureMessage = fallbackErrorMessage;
-                }
-            }
-
-            aiLog("warn", "tool_ranker.failed.fallback_all_allowed", {
-                provider,
+            aiLog("warn", "ollama.tool_ranker.failed.fallback_all_allowed", {
                 round,
                 target: aiLogProviderTarget(target),
-                fallbackPolicy,
                 duration: aiLogDuration(startedAt),
-                errorSummary: failureMessage,
+                error,
             });
 
-            return resolveToolRankerFallbackSelection({
-                fallbackPolicy,
-                availableToolNames: availableNames,
-            });
-        }
-    }
-
-    private async runRanker(
-        provider: AiProvider,
-        target: NonNullable<ReturnType<typeof buildRankerTarget>>,
-        prompt: string,
-        userQuery: string,
-    ): Promise<string> {
-        switch (provider) {
-            case AiProvider.OLLAMA: {
-                const ollama = createOllamaClient(target);
-                const request = {
-                    model: target.model,
-                    messages: [
-                        {role: "system", content: prompt},
-                        {role: "user", content: userQuery},
-                    ],
-                    stream: false as const,
-                    think: false,
-                    format: {
-                        type: "object",
-                        properties: {
-                            toolNames: {
-                                type: "array",
-                                items: {type: "string"},
-                            },
-                        },
-                        required: ["toolNames"],
-                        additionalProperties: false,
-                    },
-                    options: {
-                        temperature: 0,
-                        top_p: 0.8,
-                        top_k: 20,
-                        repeat_penalty: 1.05,
-                        num_ctx: 8192,
-                        num_predict: 256,
-                    },
-                } satisfies ChatRequest & { stream: false };
-
-                const response = await ollama.chat(request);
-                return response.message?.content?.trim() ?? "";
-            }
-            case AiProvider.MISTRAL: {
-                const mistral = createMistralClient(target);
-                const request: Parameters<typeof mistral.chat.complete>[0] = {
-                    model: target.model,
-                    messages: [
-                        {role: "system", content: prompt},
-                        {role: "user", content: userQuery},
-                    ],
-                    temperature: 0,
-                };
-                const response = await mistral.chat.complete(request);
-                const message = response.choices?.[0]?.message;
-                return typeof message?.content === "string" ? message.content.trim() : "";
-            }
-            case AiProvider.OPENAI: {
-                const openAi = createOpenAiClient(target);
-                const messages = [
-                    {role: "system", content: prompt},
-                    {role: "user", content: userQuery},
-                ] satisfies ChatCompletionMessageParam[];
-
-                // OpenAI-compatible servers often reject `response_format`, so keep JSON mode
-                // only for official OpenAI endpoints.
-                const request: ChatCompletionCreateParamsNonStreaming = {
-                    model: target.model,
-                    messages,
-                };
-
-                if (!target.baseUrl) {
-                    // gpt-5 family ranker targets reject temperature=0; use the model default instead.
-                    request.response_format = {type: "json_object"};
-                }
-
-                const response = await openAi.chat.completions.create(request);
-
-                return response.choices[0]?.message?.content?.trim() ?? "";
-            }
+            // Ranker transport/model failure is different from "ranker returned empty plan".
+            // In that case, preserve availability rather than silently disabling tools.
+            return {
+                tools: availableTools,
+                usedRanker: false,
+            };
         }
     }
 }
+
+export function latestUserTextFromOllamaMessages(messages: readonly { role?: string; content?: unknown }[]): string {
+    for (let i = messages.length - 1; i >= 0; i--) {
+        const message = messages[i];
+        if (message?.role !== "user") continue;
+        if (typeof message.content === "string") return message.content;
+        if (Array.isArray(message.content)) {
+            return message.content
+                .map(part => isRecord(part) && typeof part.text === "string" ? part.text : "")
+                .filter(Boolean)
+                .join("\n");
+        }
+    }
+    return "";
+}

src/ai/unified-ai-runner.ts

@@ -5,37 +5,53 @@ import {ifTrue, logError, replyToMessage} from "../util/utils";
 import {createAiCancelRequest, finishAiRequest, setAiCancelMessageId} from "./cancel-registry";
 import {TelegramStreamMessage} from "./telegram-stream-message";
 import {AiDownloadedFile, attachmentsToDownloadedFiles, cleanupDownloads} from "./telegram-attachments";
+import {ChatMessage} from "./chat-messages-types";
 import {aiProviderRequestQueue} from "./provider-request-queue";
+import {prepareOllamaDocumentRag} from "./ollama-rag";
 import {
     AI_VOICE_MODE_TRANSCRIPT,
+    DEFAULT_AI_RESPONSE_LANGUAGE,
     resolveAiContextSizeForUser,
-    resolveAiImageOutputModeForUser,
     resolveAiResponseLanguageForUser,
     resolveAiVoiceModeForUser
 } from "../common/user-ai-settings";
+import {isTranscribableAudioDownload} from "./speech-to-text";
+import {OpenAIChatMessage} from "./openai-chat-message";
+import {MistralChatMessage} from "./mistral-chat-message";
+import {OllamaChatMessage} from "./ollama-chat-message";
 import {buildAiRegenerateCallbackData} from "./regenerate-callback";
+import {createOllamaClient} from "./ai-runtime-target";
 import {aiLog, aiLogDuration, aiLogMessageIdentity, aiLogProviderTarget} from "../logging/ai-logger";
 
+import {runOpenAi} from "./unified-ai-runner.openai";
+import {runOllama} from "./unified-ai-runner.ollama";
+import {runMistral} from "./unified-ai-runner.mistral";
 import {
     AI_REQUEST_TIMEOUT_MS,
+    appendTranscriptToChatMessages,
     collectCachedMessageAttachments,
     collectRequestedAttachmentKinds,
+    collectTextMessages,
+    deleteMistralLibrary,
+    GeminiMessage,
     hasAudioAttachmentKind,
+    initialStatus,
     isAbortError,
+    prepareMistralDocuments,
     providerName,
     rejectUnsupportedAttachments,
     resolveAiRequestQueueTarget,
     RuntimeConfigSnapshot,
     snapshotModel,
     snapshotRuntimeConfig,
+    stripAudioFromRunnerMessages,
+    TELEGRAM_LIMIT,
+    toolRuntimeContextFromDownloads,
+    transcribeAudioIfNeeded,
     UnifiedRunOptions
 } from "./unified-ai-runner.shared";
-import {prepareUnifiedAiRequestPipeline} from "./unified-ai-request-pipeline";
-import {persistErrorArtifactAttachment} from "./final-response-artifact-store";
-import {runUnifiedAiResponsePipeline} from "./unified-ai-response-pipeline";
-import {AiRequestStore} from "../common/ai-request-store";
-import type {StoredAiRequestStatus} from "../model/stored-ai-request";
-import {recordAiRequestFinish, recordAiRequestStart} from "../common/ai-observability.js";
+import {runGemini} from "./unified-ai-runner.gemini";
+import {resolveTextToSpeechProviderForUser, sendSynthesizedSpeech, synthesizeSpeech} from "./text-to-speech";
 
 export type {ToolCallData} from "./unified-ai-runner.shared";
 export {snapshotModel, providerTargets, ollamaModelNames} from "./unified-ai-runner.shared";
@@ -46,11 +62,9 @@ async function executeUnifiedAiRequest(
     downloads: AiDownloadedFile[],
     controller: AbortController,
     streamMessage: TelegramStreamMessage,
-): Promise<void> {
+): Promise<{ mistralLibraryId?: string }> {
     const requestStartedAt = Date.now();
-    let preparedRequest: Awaited<ReturnType<typeof prepareUnifiedAiRequestPipeline>> | undefined;
     aiLog("info", "request.execute.start", {
-        requestId: options.requestId,
         provider: providerName(options.provider),
         stream: options.stream ?? true,
         think: options.think,
@@ -66,63 +80,165 @@ async function executeUnifiedAiRequest(
         })),
     });
 
-    preparedRequest = await prepareUnifiedAiRequestPipeline({
-        options,
-        config,
+    const {
+        chatMessages,
+        imageCount
+    } = await collectTextMessages(
+        options.msg,
+        options.text,
+        options.provider,
         downloads,
-        streamMessage,
-        controller,
-    });
-    if (preparedRequest.finishAfterTranscript) return;
-
+        config,
+        options.responseLanguage ?? DEFAULT_AI_RESPONSE_LANGUAGE,
+    );
+    const firstRoundStatus = initialStatus(downloads, imageCount);
+    const toolContext = toolRuntimeContextFromDownloads(downloads);
     aiLog("debug", "request.messages.collected", {
-        requestId: options.requestId,
         provider: providerName(options.provider),
-        chatMessages: preparedRequest.chatMessages.length,
-        imageCount: preparedRequest.imageCount,
-        firstRoundStatus: preparedRequest.firstRoundStatus,
-        hasToolInputFiles: !!preparedRequest.toolContext.pythonInputFiles?.length,
+        chatMessages: chatMessages.length,
+        imageCount,
+        firstRoundStatus,
+        hasToolInputFiles: !!toolContext.pythonInputFiles?.length,
     });
 
+    streamMessage.setStatus(firstRoundStatus);
+    await streamMessage.flush();
+
+    const hasDocument = downloads.some(d => d.kind === "document");
+    if (hasDocument && options.provider !== AiProvider.MISTRAL && options.provider !== AiProvider.OLLAMA) {
+        aiLog("warn", "request.documents.unsupported_provider", {provider: providerName(options.provider)});
+        throw new Error(Environment.documentsUnifiedRunnerUnsupportedText);
+    }
+
+    let mistralLibraryId: string | undefined;
+
+    const transcript = await transcribeAudioIfNeeded(options.provider, options.msg.from?.id, downloads, streamMessage, controller.signal).catch(e => {
+        if (downloads.some(isTranscribableAudioDownload)) throw e;
+        return "";
+    });
+
+    if (transcript.trim()) {
+        if (options.voiceMode === AI_VOICE_MODE_TRANSCRIPT) {
+            // TODO: 12.05.2026: extract to string
+            streamMessage.replaceText(`[Расшифровка]\n${transcript.trim()}`);
+            await streamMessage.finish();
+            return {mistralLibraryId};
+        }
+
+        appendTranscriptToChatMessages(chatMessages, options.provider, transcript);
+        stripAudioFromRunnerMessages(chatMessages);
+        aiLog("debug", "request.transcript.appended", {
+            provider: providerName(options.provider),
+            transcriptChars: transcript.length,
+            chatMessages: chatMessages.length,
+        });
+    }
+
     try {
-        await runUnifiedAiResponsePipeline({
-            options,
-            config,
-            downloads,
-            prepared: preparedRequest,
-            streamMessage,
-            controller,
-        });
+        const preparedMistral = options.provider === AiProvider.MISTRAL
+            ? await prepareMistralDocuments(downloads, chatMessages as MistralChatMessage[], streamMessage, config.mistralChatTarget, controller.signal)
+            : {documents: []};
+        const documents = preparedMistral.documents;
+        mistralLibraryId = preparedMistral.libraryId;
+
+        if (options.provider === AiProvider.OLLAMA) {
+            await prepareOllamaDocumentRag({
+                downloads,
+                messages: chatMessages as OllamaChatMessage[],
+                userQuery: options.text,
+                message: streamMessage,
+                config: {
+                    embeddingModel: config.ollamaDocumentsTarget.model,
+                    embeddingClient: createOllamaClient(config.ollamaDocumentsTarget),
+                    chunkSize: config.ollamaRagChunkSize,
+                    chunkOverlap: config.ollamaRagChunkOverlap,
+                    topK: config.ollamaRagTopK,
+                    maxContextChars: config.ollamaRagMaxContextChars,
+                    minScore: config.ollamaRagMinScore,
+                    maxArchiveFiles: config.ollamaRagMaxArchiveFiles,
+                    maxArchiveBytes: config.ollamaRagMaxArchiveBytes,
+                    maxArchiveDepth: config.ollamaRagMaxArchiveDepth,
+                },
+            });
+        }
+
+        aiLog("info", "request.provider.dispatch", {provider: providerName(options.provider)});
+
+        switch (options.provider) {
+            case AiProvider.OPENAI:
+                await runOpenAi(options.msg, chatMessages as OpenAIChatMessage[], streamMessage, controller.signal, options.stream ?? true, options.msg, config, toolContext);
+                break;
+            case AiProvider.OLLAMA:
+                const currentModel = config.ollamaChatTarget.model;
+                if (currentModel?.includes("gpt-oss")) {
+                    if (options.think) {
+                        options.think = "high";
+                    }
+                }
+
+                await runOllama(options.msg, chatMessages as ChatMessage[], streamMessage, controller.signal, ifTrue(options.stream), options.think ?? false, firstRoundStatus, config, toolContext, options.contextSize);
+                break;
+            case AiProvider.MISTRAL:
+                await runMistral(options.msg, chatMessages as MistralChatMessage[], documents, streamMessage, controller.signal, options.stream ?? true, firstRoundStatus, config, toolContext);
+                break;
+            case AiProvider.GEMINI:
+                await runGemini(options.msg, chatMessages as GeminiMessage[], streamMessage, controller.signal, options.stream ?? true, firstRoundStatus, config, toolContext);
+                break;
+        }
+
+        if (streamMessage.getText().length > TELEGRAM_LIMIT) {
+            streamMessage.replaceText(streamMessage.getText().slice(0, TELEGRAM_LIMIT - 3) + "...");
+        }
+        await streamMessage.finish();
+        // await sendVoiceResponseIfNeeded(options, downloads, streamMessage.getText());
+
         aiLog("success", "request.execute.done", {
-            requestId: options.requestId,
             provider: providerName(options.provider),
             duration: aiLogDuration(requestStartedAt),
             responseChars: streamMessage.getText().length,
-            mistralLibraryId: preparedRequest?.preparedDocumentRag?.provider === AiProvider.MISTRAL ? preparedRequest.preparedDocumentRag.libraryId : undefined,
+            mistralLibraryId,
         });
-        return;
+        return {mistralLibraryId};
     } catch (e) {
         aiLog("error", "request.execute.failed", {
-            requestId: options.requestId,
             provider: providerName(options.provider),
             duration: aiLogDuration(requestStartedAt),
-            error: e instanceof Error ? e : String(e),
+            error: e,
         });
+        if (mistralLibraryId) {
+            await deleteMistralLibrary(mistralLibraryId, config.mistralChatTarget);
+        }
         throw e;
     }
 }
 
+// noinspection JSUnusedLocalSymbols
+// @ts-ignore
+async function sendVoiceResponseIfNeeded(options: UnifiedRunOptions, downloads: AiDownloadedFile[], text: string): Promise<void> {
+    if (!downloads.some(isTranscribableAudioDownload)) return;
+    if (!options.msg.from?.id) return;
+
+    const trimmed = text.trim();
+    if (!trimmed) return;
+
+    try {
+        const provider = (await resolveTextToSpeechProviderForUser(options.msg.from.id)).provider;
+        const speech = await synthesizeSpeech({provider, text: trimmed});
+        await sendSynthesizedSpeech(options.msg, speech);
+    } catch (e) {
+        logError(e);
+    }
+}
+
 export async function runUnifiedAi(options: UnifiedRunOptions): Promise<void> {
     const startedAt = Date.now();
     const config = snapshotRuntimeConfig();
     options.responseLanguage ??= await resolveAiResponseLanguageForUser(options.msg.from?.id);
     options.contextSize ??= await resolveAiContextSizeForUser(options.msg.from?.id);
     options.voiceMode ??= await resolveAiVoiceModeForUser(options.msg.from?.id);
-    const imageOutputMode = await resolveAiImageOutputModeForUser(options.msg.from?.id);
     const requestedAttachmentKinds = await collectRequestedAttachmentKinds(options.msg);
 
     aiLog("info", "run.start", {
-        requestId: options.requestId ?? `pending:${options.msg.chat.id}:${options.msg.message_id}`,
         provider: providerName(options.provider),
         model: snapshotModel(options.provider, config),
         message: aiLogMessageIdentity(options.msg),
@@ -139,7 +255,6 @@ export async function runUnifiedAi(options: UnifiedRunOptions): Promise<void> {
 
     if (await rejectUnsupportedAttachments(options.provider, snapshotModel(options.provider, config), options.msg, config, requestedAttachmentKinds)) {
         aiLog("warn", "run.rejected.unsupported_attachment", {
-            requestId: options.requestId ?? `pending:${options.msg.chat.id}:${options.msg.message_id}`,
             provider: providerName(options.provider),
             requestedAttachmentKinds: [...requestedAttachmentKinds],
         });
@@ -157,7 +272,6 @@ export async function runUnifiedAi(options: UnifiedRunOptions): Promise<void> {
             text: Environment.getAttachmentMissingFromCacheText(cached.missing[0].fileName),
         }).catch(logError);
         aiLog("warn", "run.rejected.missing_attachment_cache", {
-            requestId: options.requestId ?? `pending:${options.msg.chat.id}:${options.msg.message_id}`,
             missing: cached.missing.map(a => ({kind: a.kind, fileName: a.fileName, cachePath: a.cachePath})),
         });
         return;
@@ -165,17 +279,12 @@ export async function runUnifiedAi(options: UnifiedRunOptions): Promise<void> {
 
     const controller = new AbortController();
     const timeout = setTimeout(() => controller.abort(), AI_REQUEST_TIMEOUT_MS);
-    let aiRequestStatus: StoredAiRequestStatus = "running";
-    let aiRequestError: string | undefined;
-    let responseMessageId: number | undefined;
     const cancel = createAiCancelRequest({
         chatId: options.msg.chat.id,
         fromId: options.msg.from?.id ?? 0,
         provider: providerName(options.provider),
         controller
     });
-    options.requestId ??= cancel.id;
-    const requestId = options.requestId;
     const streamMessage = new TelegramStreamMessage(
         options.msg,
         cancel.id,
@@ -185,42 +294,17 @@ export async function runUnifiedAi(options: UnifiedRunOptions): Promise<void> {
             : buildAiRegenerateCallbackData(options.provider, !!options.think),
         options.targetMessage,
         options.provider,
-        options.isGuestMsg,
-        imageOutputMode
+        options.isGuestMsg
     );
     cancel.onCancel = () => streamMessage.cancel(cancel.provider);
+    let mistralLibraryId: string | undefined;
     const queueTarget = resolveAiRequestQueueTarget(options, config, requestedAttachmentKinds);
-    aiLog("debug", "run.queue.target", {requestId, target: aiLogProviderTarget(queueTarget), cancelId: cancel.id});
-    const aiRequestStartedAt = new Date().toISOString();
-    recordAiRequestStart();
-    await AiRequestStore.put({
-        requestId,
-        chatId: options.msg.chat.id,
-        messageId: options.msg.message_id,
-        fromId: options.msg.from?.id ?? 0,
-        provider: options.provider,
-        model: snapshotModel(options.provider, config),
-        status: "running",
-        startedAt: aiRequestStartedAt,
-    }).catch(logError);
+    aiLog("debug", "run.queue.target", {target: aiLogProviderTarget(queueTarget), cancelId: cancel.id});
 
     try {
         const queueMessage = await streamMessage.start(Environment.waitThinkText);
-        responseMessageId = queueMessage.message_id;
-        await AiRequestStore.put({
-            requestId,
-            chatId: options.msg.chat.id,
-            messageId: options.msg.message_id,
-            responseMessageId,
-            fromId: options.msg.from?.id ?? 0,
-            provider: options.provider,
-            model: snapshotModel(options.provider, config),
-            status: "running",
-            startedAt: aiRequestStartedAt,
-        }).catch(logError);
-        setAiCancelMessageId(requestId, queueMessage.message_id);
+        setAiCancelMessageId(cancel.id, queueMessage.message_id);
         aiLog("info", "run.queue.enter", {
-            requestId,
             cancelId: cancel.id,
             queueMessageId: queueMessage.message_id,
             target: aiLogProviderTarget(queueTarget),
@@ -229,16 +313,15 @@ export async function runUnifiedAi(options: UnifiedRunOptions): Promise<void> {
         await aiProviderRequestQueue.enqueue(queueTarget, {
             signal: controller.signal,
             onPositionChange: async requestsBefore => {
-                aiLog("debug", "run.queue.position", {requestId, cancelId: cancel.id, requestsBefore});
+                aiLog("debug", "run.queue.position", {cancelId: cancel.id, requestsBefore});
                 streamMessage.setStatus(Environment.getAiQueueText(options.provider, requestsBefore));
                 await streamMessage.flush();
             },
-            run: async (): Promise<null> => {
+            run: async () => {
                 const queueWaitFinishedAt = Date.now();
-                aiLog("info", "run.queue.dequeued", {requestId, cancelId: cancel.id});
+                aiLog("info", "run.queue.dequeued", {cancelId: cancel.id});
                 const downloads = attachmentsToDownloadedFiles(cached.attachments);
                 aiLog("debug", "run.downloads.ready", {
-                    requestId,
                     count: downloads.length,
                     downloads: downloads.map(d => ({
                         kind: d.kind,
@@ -249,70 +332,41 @@ export async function runUnifiedAi(options: UnifiedRunOptions): Promise<void> {
                     })),
                 });
                 try {
-                    await executeUnifiedAiRequest(options, config, downloads, controller, streamMessage);
-                    aiRequestStatus = "succeeded";
+                    const result = await executeUnifiedAiRequest(options, config, downloads, controller, streamMessage);
+                    mistralLibraryId = result.mistralLibraryId;
                     aiLog("success", "run.queue.task.done", {
-                        requestId,
                         cancelId: cancel.id,
                         duration: aiLogDuration(queueWaitFinishedAt),
+                        mistralLibraryId,
                     });
                 } finally {
                     cleanupDownloads(downloads);
-                    aiLog("debug", "run.downloads.cleaned", {requestId, cancelId: cancel.id, count: downloads.length});
+                    aiLog("debug", "run.downloads.cleaned", {cancelId: cancel.id, count: downloads.length});
                 }
-                return null;
             },
         });
     } catch (e) {
-        if (controller.signal.aborted || isAbortError(e instanceof Error ? e : String(e))) {
-            aiRequestStatus = "aborted";
-            aiRequestError = e instanceof Error ? e.message : String(e);
-            aiLog("warn", "run.aborted", {requestId, cancelId: cancel.id, duration: aiLogDuration(startedAt), error: e instanceof Error ? e : String(e)});
+        if (controller.signal.aborted || isAbortError(e)) {
+            aiLog("warn", "run.aborted", {cancelId: cancel.id, duration: aiLogDuration(startedAt), error: e});
             streamMessage.replaceText(streamMessage.getText());
             await streamMessage.finish();
         } else {
-            aiRequestStatus = "failed";
-            aiRequestError = e instanceof Error ? e.message : String(e);
-            aiLog("error", "run.failed", {requestId, cancelId: cancel.id, duration: aiLogDuration(startedAt), error: e instanceof Error ? e : String(e)});
-            const errorMessage = e instanceof Error ? e.message : String(e);
-            await streamMessage.fail(e instanceof Error ? e : String(e));
-            try {
-                await streamMessage.storeInternalAttachment(await persistErrorArtifactAttachment({
-                    provider: options.provider,
-                    model: snapshotModel(options.provider, config),
-                    message: errorMessage,
-                    recoverable: false,
-                    chatId: options.msg.chat.id,
-                    messageId: options.msg.message_id,
-                }));
-            } catch (artifactError) {
-                logError(artifactError instanceof Error ? artifactError : String(artifactError));
-            }
-            logError(errorMessage);
+            aiLog("error", "run.failed", {cancelId: cancel.id, duration: aiLogDuration(startedAt), error: e});
+            await streamMessage.fail(e);
+            logError(e);
         }
     } finally {
         clearTimeout(timeout);
-        await AiRequestStore.put({
-            requestId,
-            chatId: options.msg.chat.id,
-            messageId: options.msg.message_id,
-            responseMessageId,
-            fromId: options.msg.from?.id ?? 0,
-            provider: options.provider,
-            model: snapshotModel(options.provider, config),
-            status: aiRequestStatus,
-            startedAt: aiRequestStartedAt,
-            finishedAt: new Date().toISOString(),
-            error: aiRequestError,
-        }).catch(logError);
-        recordAiRequestFinish(aiRequestStatus);
-        finishAiRequest(requestId);
+        finishAiRequest(cancel.id);
+        if (mistralLibraryId) {
+            aiLog("debug", "run.mistral_library.cleanup", {mistralLibraryId});
+            await deleteMistralLibrary(mistralLibraryId, config.mistralChatTarget);
+        }
         aiLog("success", "run.finished", {
-            requestId,
             cancelId: cancel.id,
             provider: providerName(options.provider),
             duration: aiLogDuration(startedAt),
             aborted: controller.signal.aborted,
         });
     }
-}
+}

src/ai/user-request-pipeline/blueprint.ts

@@ -1,73 +0,0 @@
-import type {PipelineFallbackPolicy, PipelineStageName} from "./types.js";
-import {PIPELINE_ATTACHMENT_LIMIT_BYTES} from "./types.js";
-
-export const USER_REQUEST_PIPELINE_STAGES: readonly PipelineStageName[] = [
-    "receive_request",
-    "audit_start",
-    "load_user_settings",
-    "collect_conversation_context",
-    "input_size_gate",
-    "download_attachments",
-    "normalize_attachments",
-    "persist_input_attachments",
-    "prepare_text_context",
-    "build_system_prompt",
-    "resolve_runtime",
-    "speech_to_text",
-    "document_rag",
-    "map_provider_messages",
-    "tool_rank",
-    "filter_tools",
-    "model_call",
-    "tool_loop",
-    "persist_output_artifacts",
-    "output_size_gate",
-    "text_to_speech",
-    "send_response",
-    "cleanup",
-    "audit_finish",
-];
-
-export const USER_REQUEST_ATTACHMENT_LIMIT_BYTES = PIPELINE_ATTACHMENT_LIMIT_BYTES;
-
-export const DEFAULT_PIPELINE_FALLBACK_POLICIES: readonly PipelineFallbackPolicy[] = [
-    {
-        stage: "input_size_gate",
-        onUnavailable: "fail_request",
-        onFailed: "notify_user",
-    },
-    {
-        stage: "speech_to_text",
-        onUnavailable: "continue_without_stage",
-        onFailed: "continue_without_stage",
-    },
-    {
-        stage: "document_rag",
-        onUnavailable: "continue_without_stage",
-        onFailed: "notify_user",
-    },
-    {
-        stage: "tool_rank",
-        onUnavailable: "use_alternate_target",
-        onFailed: "use_alternate_target",
-    },
-    {
-        stage: "tool_loop",
-        onUnavailable: "continue_without_stage",
-        onFailed: "notify_user",
-    },
-    {
-        stage: "output_size_gate",
-        onUnavailable: "fail_request",
-        onFailed: "notify_user",
-    },
-    {
-        stage: "text_to_speech",
-        onUnavailable: "continue_without_stage",
-        onFailed: "continue_without_stage",
-    },
-];
-
-export function isPipelineStageName(value: string): value is PipelineStageName {
-    return (USER_REQUEST_PIPELINE_STAGES as readonly string[]).includes(value);
-}

src/ai/user-request-pipeline/fallback-executor.ts

@@ -1,61 +0,0 @@
-import type {
-    PipelineFallbackAction,
-    PipelineFallbackPolicy,
-    PipelineStageName,
-    PipelineStageStatus,
-} from "./types.js";
-
-export type PipelineFallbackReason = "unavailable" | "failed";
-
-export type PipelineFallbackDecision = {
-    stage: PipelineStageName;
-    reason: PipelineFallbackReason;
-    action: PipelineFallbackAction;
-    shouldContinue: boolean;
-    shouldNotifyUser: boolean;
-    shouldFailRequest: boolean;
-};
-
-const DEFAULT_ACTION_BY_REASON: Record<PipelineFallbackReason, PipelineFallbackAction> = {
-    unavailable: "continue_without_stage",
-    failed: "fail_request",
-};
-
-export function resolvePipelineFallbackAction(params: {
-    stage: PipelineStageName;
-    reason: PipelineFallbackReason;
-    policies: readonly PipelineFallbackPolicy[];
-}): PipelineFallbackAction {
-    const policy = params.policies.find(item => item.stage === params.stage);
-    if (!policy) return DEFAULT_ACTION_BY_REASON[params.reason];
-
-    return params.reason === "unavailable"
-        ? policy.onUnavailable
-        : policy.onFailed;
-}
-
-export function decidePipelineFallback(params: {
-    stage: PipelineStageName;
-    reason: PipelineFallbackReason;
-    policies: readonly PipelineFallbackPolicy[];
-}): PipelineFallbackDecision {
-    const action = resolvePipelineFallbackAction(params);
-
-    return {
-        stage: params.stage,
-        reason: params.reason,
-        action,
-        shouldContinue: action === "ignore"
-            || action === "continue_without_stage"
-            || action === "notify_user"
-            || action === "use_alternate_target",
-        shouldNotifyUser: action === "notify_user",
-        shouldFailRequest: action === "fail_request",
-    };
-}
-
-export function fallbackReasonFromStageStatus(status: PipelineStageStatus): PipelineFallbackReason | undefined {
-    if (status === "skipped") return "unavailable";
-    if (status === "failed") return "failed";
-    return undefined;
-}

src/ai/user-request-pipeline/fallback-failure.ts

@@ -1,12 +0,0 @@
-import type {PipelineFallbackDecision} from "./fallback-executor.js";
-
-export class PipelineRequestFailure extends Error {
-    constructor(public readonly decision: PipelineFallbackDecision, message: string) {
-        super(message);
-        this.name = "PipelineRequestFailure";
-    }
-}
-
-export function raisePipelineRequestFailure(decision: PipelineFallbackDecision, stageName: string): never {
-    throw new PipelineRequestFailure(decision, `Pipeline send failed at stage ${stageName} with fallback action ${decision.action}`);
-}

src/ai/user-request-pipeline/fallback-notifier-registry.ts

@@ -1,16 +0,0 @@
-import type {PipelineFallbackDecision} from "./fallback-executor.js";
-
-export function fallbackNotificationKey(requestId: string, decision: PipelineFallbackDecision): string {
-    return `${requestId}:${decision.stage}:${decision.action}`;
-}
-
-export class PipelineFallbackNotificationRegistry {
-    private readonly notifiedKeys = new Set<string>();
-
-    claim(requestId: string, decision: PipelineFallbackDecision): boolean {
-        const key = fallbackNotificationKey(requestId, decision);
-        if (this.notifiedKeys.has(key)) return false;
-        this.notifiedKeys.add(key);
-        return true;
-    }
-}

src/ai/user-request-pipeline/fallback-notifier-text.ts

@@ -1,26 +0,0 @@
-import {Localization} from "../../common/localization.js";
-import type {PipelineFallbackAction, PipelineStageName} from "./types.js";
-
-export function resolvePipelineFallbackText(
-    stage: PipelineStageName,
-    action: PipelineFallbackAction,
-    locale?: string,
-): string | undefined {
-    if (action === "continue_without_stage") return undefined;
-    if (action === "fail_request") return Localization.text("pipelineFallback.failRequest", {}, "⚠️ I could not finish this request.", locale);
-
-    switch (stage) {
-        case "speech_to_text":
-            return Localization.text("pipelineFallback.speechToText", {}, "⚠️ Speech transcription failed, so I will continue without the audio transcript.", locale);
-        case "document_rag":
-            return Localization.text("pipelineFallback.documentRag", {}, "⚠️ Document retrieval failed, so I will answer without RAG.", locale);
-        case "tool_loop":
-            return Localization.text("pipelineFallback.toolLoop", {}, "⚠️ Tool execution failed, so I will continue without that tool.", locale);
-        case "text_to_speech":
-            return Localization.text("pipelineFallback.textToSpeech", {}, "⚠️ Text-to-speech failed, so I will continue without audio output.", locale);
-        default:
-            return action === "notify_user"
-                ? Localization.text("pipelineFallback.notifyUser", {}, "⚠️ I hit a problem and need to continue with a fallback.", locale)
-                : Localization.text("pipelineFallback.generic", {}, "⚠️ I had to skip part of the request, but I can continue.", locale);
-    }
-}

src/ai/user-request-pipeline/fallback-notifier.ts

@@ -1,43 +0,0 @@
-import type {Message} from "typescript-telegram-bot-api";
-import {Localization} from "../../common/localization.js";
-import {replyToMessage, logError} from "../../util/utils.js";
-import type {PipelineFallbackDecision} from "./fallback-executor.js";
-import {PipelineFallbackNotificationRegistry} from "./fallback-notifier-registry.js";
-import {resolvePipelineFallbackText} from "./fallback-notifier-text.js";
-
-export class PipelineFallbackNotifier {
-    private readonly registry = new PipelineFallbackNotificationRegistry();
-
-    constructor(
-        private readonly sourceMessage: Message,
-        private readonly responseLanguage?: string,
-        private readonly sendFallbackMessage: (text: string) => Promise<void> = async text => {
-            await replyToMessage({
-                message: this.sourceMessage,
-                text,
-            });
-        },
-    ) {}
-
-    async notify(requestId: string, decision: PipelineFallbackDecision): Promise<{notified: boolean; text?: string}> {
-        if (!this.registry.claim(requestId, decision)) {
-            return {notified: false};
-        }
-
-        const locale = this.responseLanguage === "default"
-            ? Localization.currentLocale()
-            : Localization.normalizeLocale(this.responseLanguage) ?? Localization.currentLocale();
-        const text = resolvePipelineFallbackText(decision.stage, decision.action, locale);
-        if (!text) {
-            return {notified: false};
-        }
-
-        try {
-            await this.sendFallbackMessage(text);
-            return {notified: true, text};
-        } catch (error) {
-            logError(error instanceof Error ? error : String(error));
-            return {notified: false, text};
-        }
-    }
-}

src/ai/user-request-pipeline/fallback-target-details.ts

@@ -1,15 +0,0 @@
-import {AiProvider} from "../../model/ai-provider.js";
-import type {RuntimeConfigSnapshot} from "../unified-ai-runner.shared.js";
-import {aiLogProviderTarget} from "../../logging/ai-logger.js";
-import {buildRankerTarget} from "../tool-ranker-pipeline.js";
-import {providerChatTarget} from "../unified-ai-runner.shared.js";
-
-export function buildToolRankFallbackTargetDetails(provider: AiProvider, config: RuntimeConfigSnapshot) {
-    const sourceTarget = buildRankerTarget(config, provider);
-    const alternateTarget = providerChatTarget(provider, config);
-
-    return {
-        sourceTarget: aiLogProviderTarget(sourceTarget),
-        alternateTarget: aiLogProviderTarget(alternateTarget),
-    };
-}

src/ai/user-request-pipeline/index.ts

@@ -1,6 +0,0 @@
-export * from "./blueprint.js";
-export * from "./fallback-executor.js";
-export * from "./pipeline.js";
-export * from "./size-gate.js";
-export * from "./telegram-message-stages.js";
-export * from "./types.js";

src/ai/user-request-pipeline/pipeline.ts

@@ -1,134 +0,0 @@
-import {DEFAULT_PIPELINE_FALLBACK_POLICIES, USER_REQUEST_PIPELINE_STAGES} from "./blueprint.js";
-import {decidePipelineFallback, type PipelineFallbackDecision} from "./fallback-executor.js";
-import {raisePipelineRequestFailure} from "./fallback-failure.js";
-import type {
-    PipelineAuditEvent,
-    PipelineFallbackPolicy,
-    PipelineStageName,
-    PipelineStageResult,
-    UserRequestPipelineStage,
-    UserRequestPipelineState,
-} from "./types.js";
-
-export type UserRequestPipelineOptions = {
-    stages: UserRequestPipelineStage[];
-    stageNames?: readonly PipelineStageName[];
-    fallbackPolicies?: readonly PipelineFallbackPolicy[];
-    onFallback?: (decision: PipelineFallbackDecision) => Promise<void> | void;
-};
-
-function nowIso(): string {
-    return new Date().toISOString();
-}
-
-function durationMs(startedAt: number): number {
-    return Date.now() - startedAt;
-}
-
-function stageEvent(event: PipelineAuditEvent): PipelineAuditEvent {
-    return event;
-}
-
-export class UserRequestPipeline {
-    private readonly stages = new Map<PipelineStageName, UserRequestPipelineStage>();
-    private readonly stageNames: readonly PipelineStageName[];
-    private readonly fallbackPolicies: readonly PipelineFallbackPolicy[];
-    private readonly onFallback?: (decision: PipelineFallbackDecision) => Promise<void> | void;
-
-    constructor(options: UserRequestPipelineOptions) {
-        for (const stage of options.stages) {
-            this.stages.set(stage.name, stage);
-        }
-        this.stageNames = options.stageNames ?? USER_REQUEST_PIPELINE_STAGES;
-        this.fallbackPolicies = options.fallbackPolicies ?? DEFAULT_PIPELINE_FALLBACK_POLICIES;
-        this.onFallback = options.onFallback;
-    }
-
-    async run(state: UserRequestPipelineState, signal: AbortSignal): Promise<UserRequestPipelineState> {
-        for (const stageName of this.stageNames) {
-            if (signal.aborted) throw new Error("Aborted");
-
-            const stage = this.stages.get(stageName);
-            if (!stage) {
-                const decision = decidePipelineFallback({
-                    stage: stageName,
-                    reason: "unavailable",
-                    policies: this.fallbackPolicies,
-                });
-                await this.onFallback?.(decision);
-                state.audit.push(stageEvent({
-                    stage: stageName,
-                    status: "skipped",
-                    startedAt: nowIso(),
-                    finishedAt: nowIso(),
-                    details: {
-                        reason: "stage_not_registered",
-                        fallbackAction: decision.action,
-                    },
-                }));
-                if (decision.shouldFailRequest) {
-                    raisePipelineRequestFailure(decision, stageName);
-                }
-                continue;
-            }
-
-            const startedAtMs = Date.now();
-            const startedAt = nowIso();
-            state.audit.push(stageEvent({
-                stage: stageName,
-                status: "running",
-                startedAt,
-            }));
-
-            try {
-                const result = await stage.run(state, signal);
-                this.applyStageResult(state, result);
-                state.audit.push(stageEvent({
-                    stage: stageName,
-                    status: result.status,
-                    startedAt,
-                    finishedAt: nowIso(),
-                    durationMs: durationMs(startedAtMs),
-                    details: result.fallbackAction || result.details
-                        ? {
-                            ...(result.details ?? {}),
-                            ...(result.fallbackAction ? {fallbackAction: result.fallbackAction} : {}),
-                        }
-                        : undefined,
-                }));
-            } catch (error) {
-                const decision = decidePipelineFallback({
-                    stage: stageName,
-                    reason: "failed",
-                    policies: this.fallbackPolicies,
-                });
-                await this.onFallback?.(decision);
-                state.audit.push(stageEvent({
-                    stage: stageName,
-                    status: "failed",
-                    startedAt,
-                    finishedAt: nowIso(),
-                    durationMs: durationMs(startedAtMs),
-                    details: {fallbackAction: decision.action},
-                    error: error instanceof Error ? error.message : String(error),
-                }));
-                if (decision.shouldFailRequest) {
-                    raisePipelineRequestFailure(decision, stageName);
-                }
-            }
-        }
-
-        return state;
-    }
-
-    private applyStageResult(state: UserRequestPipelineState, result: PipelineStageResult): void {
-        if (result.artifacts?.length) {
-            state.artifacts.push(...result.artifacts);
-        }
-
-        if (result.attachments?.length) {
-            state.outputAttachments.push(...result.attachments.filter(attachment => attachment.direction === "output"));
-            state.inputAttachments.push(...result.attachments.filter(attachment => attachment.direction === "input"));
-        }
-    }
-}

src/ai/user-request-pipeline/size-gate.ts

@@ -1,51 +0,0 @@
-import {PIPELINE_ATTACHMENT_LIMIT_BYTES, type PersistentAttachment} from "./types.js";
-
-export type AttachmentSizeGateResult =
-    | {
-        ok: true;
-        attachment: PersistentAttachment;
-    }
-    | {
-        ok: false;
-        attachment: PersistentAttachment;
-        limitBytes: number;
-        reason: string;
-    };
-
-export function validateAttachmentSize(
-    attachment: PersistentAttachment,
-    limitBytes: number = PIPELINE_ATTACHMENT_LIMIT_BYTES,
-): AttachmentSizeGateResult {
-    if (attachment.sizeBytes <= limitBytes) {
-        return {ok: true, attachment};
-    }
-
-    return {
-        ok: false,
-        attachment,
-        limitBytes,
-        reason: `Attachment ${attachment.fileName} is larger than ${limitBytes} bytes.`,
-    };
-}
-
-export function splitAttachmentsBySize(
-    attachments: readonly PersistentAttachment[],
-    limitBytes: number = PIPELINE_ATTACHMENT_LIMIT_BYTES,
-): {
-    accepted: PersistentAttachment[];
-    rejected: AttachmentSizeGateResult[];
-} {
-    const accepted: PersistentAttachment[] = [];
-    const rejected: AttachmentSizeGateResult[] = [];
-
-    for (const attachment of attachments) {
-        const result = validateAttachmentSize(attachment, limitBytes);
-        if (result.ok) {
-            accepted.push(result.attachment);
-        } else {
-            rejected.push(result);
-        }
-    }
-
-    return {accepted, rejected};
-}

src/ai/user-request-pipeline/telegram-message-stages.ts

@@ -1,189 +0,0 @@
-import type {Message} from "typescript-telegram-bot-api";
-import {AiProvider} from "../../model/ai-provider";
-import type {StoredMessage} from "../../model/stored-message";
-import type {StoredAttachment} from "../../model/stored-attachment";
-import {MessageStore} from "../../common/message-store";
-import {Environment} from "../../common/environment";
-import {
-    DEFAULT_AI_IMAGE_OUTPUT_MODE,
-    DEFAULT_AI_RESPONSE_LANGUAGE,
-    DEFAULT_AI_VOICE_MODE,
-} from "../../common/user-ai-settings";
-import {
-    cacheMessageAttachmentsWithRejections,
-    collectTelegramAttachmentDescriptors,
-    type RejectedTelegramAttachment,
-} from "../telegram-attachments";
-import {PIPELINE_ATTACHMENT_LIMIT_BYTES, type PersistentAttachment, type UserRequestPipelineState} from "./types";
-import {UserRequestPipeline} from "./pipeline";
-import type {UserRequestPipelineStage} from "./types";
-
-type TelegramMessageAttachmentPipelineResult = {
-    state: UserRequestPipelineState;
-    storedMessage: StoredMessage;
-    attachments: StoredAttachment[];
-    rejected: RejectedTelegramAttachment[];
-};
-
-function nowIso(): string {
-    return new Date().toISOString();
-}
-
-function requestIdFor(msg: Message): string {
-    return `telegram:${msg.chat.id}:${msg.message_id}:${Date.now()}`;
-}
-
-function rejectedKey(attachment: Pick<RejectedTelegramAttachment, "fileId" | "fileName">): string {
-    return `${attachment.fileId}:${attachment.fileName}`;
-}
-
-function dedupeRejected(attachments: RejectedTelegramAttachment[]): RejectedTelegramAttachment[] {
-    const seen = new Set<string>();
-    const result: RejectedTelegramAttachment[] = [];
-
-    for (const attachment of attachments) {
-        const key = rejectedKey(attachment);
-        if (seen.has(key)) continue;
-        seen.add(key);
-        result.push(attachment);
-    }
-
-    return result;
-}
-
-function storedToPersistentAttachment(msg: Message, attachment: StoredAttachment): PersistentAttachment {
-    return {
-        direction: "input",
-        kind: attachment.kind,
-        fileId: attachment.fileId,
-        fileUniqueId: attachment.fileUniqueId,
-        fileName: attachment.fileName,
-        mimeType: attachment.mimeType,
-        sizeBytes: attachment.sizeBytes ?? 0,
-        cachePath: attachment.cachePath,
-        sha256: attachment.sha256,
-        sourceChatId: msg.chat.id,
-        sourceMessageId: msg.message_id,
-    };
-}
-
-export async function runTelegramMessageAttachmentPipeline(
-    msg: Message,
-    storedMessage: StoredMessage,
-): Promise<TelegramMessageAttachmentPipelineResult> {
-    let downloadedAttachments: StoredAttachment[] = [];
-    let rejectedAttachments: RejectedTelegramAttachment[] = [];
-    let persistedMessage = storedMessage;
-
-    const state: UserRequestPipelineState = {
-        requestId: requestIdFor(msg),
-        chatId: msg.chat.id,
-        messageId: msg.message_id,
-        replyToMessageId: msg.reply_to_message?.message_id,
-        fromId: msg.from?.id ?? storedMessage.fromId,
-        receivedAt: nowIso(),
-        text: storedMessage.text ?? msg.text ?? msg.caption ?? "",
-        settings: {
-            provider: Environment.DEFAULT_AI_PROVIDER ?? AiProvider.OLLAMA,
-            responseLanguage: DEFAULT_AI_RESPONSE_LANGUAGE,
-            voiceMode: DEFAULT_AI_VOICE_MODE,
-            imageOutputMode: DEFAULT_AI_IMAGE_OUTPUT_MODE,
-        },
-        inputAttachments: [],
-        outputAttachments: [],
-        artifacts: [],
-        toolRankDecisions: [],
-        audit: [],
-    };
-
-    const stages: UserRequestPipelineStage[] = [
-        {
-            name: "input_size_gate",
-            async run() {
-                rejectedAttachments = dedupeRejected([
-                    ...rejectedAttachments,
-                    ...collectTelegramAttachmentDescriptors(msg)
-                        .filter(attachment => (attachment.sizeBytes ?? 0) > PIPELINE_ATTACHMENT_LIMIT_BYTES)
-                        .map(attachment => ({
-                            kind: attachment.kind,
-                            fileId: attachment.fileId,
-                            fileUniqueId: attachment.fileUniqueId,
-                            fileName: attachment.fileName,
-                            mimeType: attachment.mimeType,
-                            sizeBytes: attachment.sizeBytes ?? 0,
-                            limitBytes: PIPELINE_ATTACHMENT_LIMIT_BYTES,
-                            reason: "too_large" as const,
-                        })),
-                ]);
-
-                return {
-                    stage: "input_size_gate",
-                    status: rejectedAttachments.length ? "fallback" : "succeeded",
-                    fallbackAction: rejectedAttachments.length ? "notify_user" : undefined,
-                };
-            },
-        },
-        {
-            name: "download_attachments",
-            async run() {
-                const result = await cacheMessageAttachmentsWithRejections(msg);
-                downloadedAttachments = result.attachments;
-                rejectedAttachments = dedupeRejected([...rejectedAttachments, ...result.rejected]);
-
-                return {
-                    stage: "download_attachments",
-                    status: "succeeded",
-                };
-            },
-        },
-        {
-            name: "normalize_attachments",
-            async run() {
-                return {
-                    stage: "normalize_attachments",
-                    status: "succeeded",
-                    attachments: downloadedAttachments.map(attachment => storedToPersistentAttachment(msg, attachment)),
-                };
-            },
-        },
-        {
-            name: "persist_input_attachments",
-            async run() {
-                if (downloadedAttachments.length) {
-                    persistedMessage = {
-                        ...persistedMessage,
-                        attachments: downloadedAttachments,
-                    };
-                    persistedMessage = await MessageStore.put(persistedMessage);
-                }
-
-                return {
-                    stage: "persist_input_attachments",
-                    status: "succeeded",
-                };
-            },
-        },
-    ];
-
-    const pipeline = new UserRequestPipeline({
-        stages,
-        stageNames: [
-            "input_size_gate",
-            "download_attachments",
-            "normalize_attachments",
-            "persist_input_attachments",
-        ],
-    });
-    await pipeline.run(state, new AbortController().signal);
-    persistedMessage = await MessageStore.put({
-        ...persistedMessage,
-        pipelineAudit: state.audit,
-    });
-
-    return {
-        state,
-        storedMessage: persistedMessage,
-        attachments: downloadedAttachments,
-        rejected: rejectedAttachments,
-    };
-}

src/ai/user-request-pipeline/types.ts

@@ -1,233 +0,0 @@
-import type {AiProvider} from "../../model/ai-provider";
-import type {StoredAttachmentKind} from "../../model/stored-attachment";
-import type {
-    UserAiImageOutputMode,
-    UserAiResponseLanguage,
-    UserAiVoiceMode,
-} from "../../common/user-ai-settings";
-
-export const PIPELINE_ATTACHMENT_LIMIT_BYTES = 50 * 1024 * 1024;
-
-export type PipelineStageName =
-    | "receive_request"
-    | "audit_start"
-    | "load_user_settings"
-    | "collect_conversation_context"
-    | "input_size_gate"
-    | "download_attachments"
-    | "normalize_attachments"
-    | "persist_input_attachments"
-    | "prepare_text_context"
-    | "build_system_prompt"
-    | "resolve_runtime"
-    | "speech_to_text"
-    | "document_rag"
-    | "map_provider_messages"
-    | "tool_rank"
-    | "filter_tools"
-    | "model_call"
-    | "tool_loop"
-    | "persist_output_artifacts"
-    | "output_size_gate"
-    | "text_to_speech"
-    | "send_response"
-    | "cleanup"
-    | "audit_finish";
-
-export type PipelineStageStatus =
-    | "pending"
-    | "running"
-    | "succeeded"
-    | "skipped"
-    | "failed"
-    | "fallback";
-
-export type PipelineFallbackAction =
-    | "ignore"
-    | "notify_user"
-    | "continue_without_stage"
-    | "use_alternate_target"
-    | "fail_request";
-
-export type PipelineFallbackPolicy = {
-    stage: PipelineStageName;
-    onUnavailable: PipelineFallbackAction;
-    onFailed: PipelineFallbackAction;
-};
-
-export type PipelineUserSettings = {
-    provider: AiProvider;
-    responseLanguage: UserAiResponseLanguage;
-    contextSize?: number;
-    voiceMode: UserAiVoiceMode;
-    imageOutputMode: UserAiImageOutputMode;
-};
-
-export type PipelineRuntimeTarget = {
-    provider: AiProvider;
-    purpose:
-        | "chat"
-        | "toolRank"
-        | "documents"
-        | "speechToText"
-        | "textToSpeech"
-        | "outputImages"
-        | "tools";
-    model: string;
-    baseUrl?: string;
-};
-
-export type PipelineRuntimePlan = {
-    chat: PipelineRuntimeTarget;
-    toolRank?: PipelineRuntimeTarget;
-    documents?: PipelineRuntimeTarget;
-    speechToText?: PipelineRuntimeTarget;
-    textToSpeech?: PipelineRuntimeTarget;
-    outputImages?: PipelineRuntimeTarget;
-    tools?: PipelineRuntimeTarget;
-};
-
-export type PipelineAttachmentDirection = "input" | "output";
-
-export type PersistentAttachment = {
-    id?: string;
-    direction: PipelineAttachmentDirection;
-    kind: StoredAttachmentKind | "file";
-    fileId?: string;
-    fileUniqueId?: string;
-    fileName: string;
-    mimeType?: string;
-    sizeBytes: number;
-    cachePath?: string;
-    sha256?: string;
-    sourceChatId?: number;
-    sourceMessageId?: number;
-};
-
-export type PipelineArtifactKind =
-    | "transcript"
-    | "rag"
-    | "tool_result"
-    | "generated_file"
-    | "tts_audio"
-    | "final_text"
-    | "error";
-
-export type PipelineArtifactBase = {
-    id?: string;
-    kind: PipelineArtifactKind;
-    stage: PipelineStageName;
-    requestId?: string;
-    messageChatId?: number;
-    messageId?: number;
-    createdAt: string;
-};
-
-export type TranscriptArtifact = PipelineArtifactBase & {
-    kind: "transcript";
-    text: string;
-    sourceAttachmentIds: string[];
-    model?: string;
-};
-
-export type RagArtifact = PipelineArtifactBase & {
-    kind: "rag";
-    sourceAttachmentIds: string[];
-    provider: AiProvider;
-    extractedText?: string;
-    chunks?: Array<{
-        id: string;
-        sourceName: string;
-        text: string;
-        score?: number;
-    }>;
-    providerState?: {
-        vectorStoreIds?: string[];
-        libraryId?: string;
-        documentIds?: string[];
-    };
-};
-
-export type ToolResultArtifact = PipelineArtifactBase & {
-    kind: "tool_result";
-    toolName: string;
-    callId: string;
-    resultText: string;
-    outputAttachmentIds?: string[];
-};
-
-export type GeneratedFileArtifact = PipelineArtifactBase & {
-    kind: "generated_file" | "tts_audio";
-    attachmentId: string;
-};
-
-export type FinalTextArtifact = PipelineArtifactBase & {
-    kind: "final_text";
-    text: string;
-};
-
-export type ErrorArtifact = PipelineArtifactBase & {
-    kind: "error";
-    errorCode?: string;
-    message: string;
-    recoverable: boolean;
-};
-
-export type PipelineArtifact =
-    | TranscriptArtifact
-    | RagArtifact
-    | ToolResultArtifact
-    | GeneratedFileArtifact
-    | FinalTextArtifact
-    | ErrorArtifact;
-
-export type PipelineAuditEvent = {
-    stage: PipelineStageName;
-    status: PipelineStageStatus;
-    startedAt?: string;
-    finishedAt?: string;
-    durationMs?: number;
-    provider?: AiProvider;
-    model?: string;
-    details?: Record<string, unknown>;
-    error?: string;
-};
-
-export type ToolRankDecision = {
-    provider: AiProvider;
-    round: number;
-    availableTools: string[];
-    selectedTools: string[];
-    usedRanker: boolean;
-};
-
-export type UserRequestPipelineState = {
-    requestId: string;
-    chatId: number;
-    messageId: number;
-    replyToMessageId?: number;
-    fromId: number;
-    receivedAt: string;
-    text: string;
-    settings: PipelineUserSettings;
-    runtime?: PipelineRuntimePlan;
-    inputAttachments: PersistentAttachment[];
-    outputAttachments: PersistentAttachment[];
-    artifacts: PipelineArtifact[];
-    toolRankDecisions: ToolRankDecision[];
-    audit: PipelineAuditEvent[];
-};
-
-export type PipelineStageResult = {
-    stage: PipelineStageName;
-    status: PipelineStageStatus;
-    artifacts?: PipelineArtifact[];
-    attachments?: PersistentAttachment[];
-    details?: Record<string, unknown>;
-    fallbackAction?: PipelineFallbackAction;
-};
-
-export interface UserRequestPipelineStage {
-    readonly name: PipelineStageName;
-    run(state: UserRequestPipelineState, signal: AbortSignal): Promise<PipelineStageResult>;
-}

src/base/dao.ts

@@ -1,9 +1,9 @@
-export abstract class Dao<I, GetByIdParams, GetByIdsParams, InsertParams> {
+export abstract class Dao<I> {
     abstract getAll(): Promise<I[]>;
 
-    abstract getById(params: GetByIdParams): Promise<I | null>;
+    abstract getById(params: never): Promise<I | null>
 
-    abstract getByIds(params: GetByIdsParams): Promise<I[]>;
+    abstract getByIds(params: never): Promise<I[]>
 
-    abstract insert(items: InsertParams): Promise<true>;
-}
+    abstract insert(items: never[]): Promise<true>
+}

src/callback_commands/ai-cancel.ts

@@ -72,41 +72,46 @@ export class AiCancel extends CallbackCommand {
         const cancelledText = buildCancelledGenerationText(baseText, providerName, limit);
         const replyMarkup = this.regenerateKeyboard(regenerateProvider);
         const formatted = prepareTelegramMarkdownV2(cancelledText, {mode: "final"});
-        const deletedByBotAt = Math.floor(Date.now() / 1000);
 
         try {
-            await enqueueTelegramApiCall(
-                () => isCaption
-                    ? bot.editMessageCaption({
+            const result = isCaption
+                ? await enqueueTelegramApiCall(
+                    () => bot.editMessageCaption({
                         chat_id: message.chat.id,
                         message_id: message.message_id,
                         caption: formatted,
                         parse_mode: "MarkdownV2",
                         reply_markup: replyMarkup,
-                    })
-                    : bot.editMessageText({
+                    }),
+                    {method: "editMessageCaption", chatId: message.chat.id, chatType: message.chat.type}
+                )
+                : await enqueueTelegramApiCall(
+                    () => bot.editMessageText({
                         chat_id: message.chat.id,
                         message_id: message.message_id,
                         text: formatted,
                         parse_mode: "MarkdownV2",
                         reply_markup: replyMarkup,
                     }),
-                {method: isCaption ? "editMessageCaption" : "editMessageText", chatId: message.chat.id, chatType: message.chat.type}
-            );
+                    {method: "editMessageText", chatId: message.chat.id, chatType: message.chat.type}
+                );
 
-            await MessageStore.put({
-                chatId: message.chat.id,
-                id: message.message_id,
-                replyToMessageId: stored?.replyToMessageId ?? this.replyToMessageId(message),
-                fromId: message.from?.id ?? stored?.fromId ?? 0,
-                text: cancelledText,
-                quoteText: stored?.quoteText,
-                date: message.date ?? stored?.date ?? deletedByBotAt,
-                deletedByBotAt,
-                attachments: stored?.attachments,
-            });
+            if (result) {
+                await MessageStore.put({...(result as object), text: cancelledText} as Message);
+            } else {
+                await MessageStore.put({
+                    chatId: message.chat.id,
+                    id: message.message_id,
+                    replyToMessageId: stored?.replyToMessageId ?? this.replyToMessageId(message),
+                    fromId: message.from?.id ?? stored?.fromId ?? 0,
+                    text: cancelledText,
+                    date: message.date ?? stored?.date ?? Math.floor(Date.now() / 1000),
+                    photoMaxSizeFilePath: stored?.photoMaxSizeFilePath,
+                    attachments: stored?.attachments,
+                });
+            }
         } catch (e) {
-            logError(e instanceof Error ? e : String(e));
+            logError(e);
         }
     }
 

src/callback_commands/user-settings.ts

@@ -4,14 +4,12 @@ import {UserStore} from "../common/user-store";
 import {
     ensureValidUserAiSettings,
     normalizeAiContextSizeChoice,
-    normalizeAiImageOutputMode,
     normalizeAiProviderChoice,
     normalizeAiResponseLanguage,
     normalizeAiVoiceMode,
     normalizeInterfaceLanguage,
     resolveInterfaceLocaleForUser,
     setUserAiContextSizeChoice,
-    setUserAiImageOutputMode,
     setUserAiProviderChoice,
     setUserAiResponseLanguage,
     setUserAiVoiceMode,
@@ -89,15 +87,6 @@ export class UserSettingsCallback extends CallbackCommand {
             screen = "voiceMode";
         }
 
-        if (parsed.screen === "imageOutput" && parsed.imageOutputMode) {
-            const mode = normalizeAiImageOutputMode(parsed.imageOutputMode);
-            if (mode) {
-                const result = await setUserAiImageOutputMode(query.from.id, mode);
-                settings = result.settings;
-            }
-            screen = "imageOutput";
-        }
-
         const locale = await resolveInterfaceLocaleForUser(query.from.id, query.from.language_code);
 
         await Localization.runWithLocale(locale, () => editMessageText({