Add OpenAI compatible chat backend

.env.example

@@ -11,6 +11,18 @@ 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)
 # ============================================
@@ -31,9 +43,27 @@ 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
 
@@ -44,17 +74,6 @@ 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
@@ -84,6 +103,10 @@ 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
@@ -92,20 +115,29 @@ 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, GEMINI, MISTRAL, OPENAI
+# Providers: OLLAMA, 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,
-# GEMINI_BASE_URL, OLLAMA_ADDRESS or OLLAMA_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

@@ -0,0 +1,55 @@
+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

@@ -0,0 +1,314 @@
+# 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

@@ -1,12 +1,50 @@
 # Telegram Chat Bot
 
-Bot for Telegram with a lot of commands and AI (Ollama/Gemini/Mistral) written in TypeScript + NodeJS/Bun runtime + Drizzle ORM (SQLite DB)
+Bot for Telegram with a lot of commands and AI (Ollama/Mistral/OpenAI) written in TypeScript + NodeJS/Bun runtime + SQLite/PostgreSQL/in-memory storage
 
 ## Quick Start
 
 ```bash
 cp .env.example .env
-# Edit .env: add BOT_TOKEN, CREATOR_ID and configure optional AI models (GEMINI_API_KEY, MISTRAL_API_KEY, OLLAMA_ADDRESS)
+# 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
 ```
 
 For local Ollama document RAG, install an embedding model locally and set it in `.env`:
@@ -16,24 +54,19 @@ ollama pull nomic-embed-text
 OLLAMA_EMBEDDING_MODEL=nomic-embed-text
 ```
 
-**With Bun (Recommended):**
+Tool ranker fallback is configurable via `TOOL_RANKER_FALLBACK_POLICY`:
-```bash
-bun install
-bunx drizzle-kit generate && bunx drizzle-kit migrate
-bun run build && bun start
-```
 
-**With Node.js:**
+- `MAIN_MODEL` - use the provider's main chat model to rank tools if a dedicated ranker target is missing or fails
-```bash
+- `ALL_TOOLS` - skip tool ranking fallback and allow all tools
-npm install
+- `NO_TOOLS` - skip tool ranking fallback and allow no tools
-npx drizzle-kit generate && npx drizzle-kit migrate
+
-npm run build && npm start
+The default is `ALL_TOOLS`.
-```
 
 **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
@@ -49,13 +82,13 @@ docker run -d --env-file .env -v $(pwd)/data:/config/data tg-bot-bun
 
 ## Requirements
 
-- Node.js >= 20 OR Bun >= 1.0
+- Node.js >= 20.19 OR Bun >= 1.0
 - Docker (optional)
 
 
 ## Features
 
-- AI chat (Gemini, Mistral, Ollama)
+- AI chat (Mistral, Ollama, OpenAI)
 - 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": "^1.16.0",
+        "axios": "^1.16.1",
         "dotenv": "^17.4.2",
         "drizzle-orm": "0.45.2",
         "emoji-regex": "^10.6.0",
         "fluent-ffmpeg": "^2.1.3",
         "ollama": "^0.6.3",
-        "openai": "^6.37.0",
+        "openai": "^6.38.0",
+        "pg": "^8.21.0",
         "qrcode": "^1.5.4",
         "sharp": "^0.34.5",
         "systeminformation": "^5.31.6",
@@ -24,77 +24,48 @@
         "zod": "^4.4.3",
       },
       "devDependencies": {
-        "@types/bun": "^1.3.13",
+        "@eslint/js": "^9.39.4",
+        "@types/bun": "^1.3.14",
         "@types/fluent-ffmpeg": "^2.1.28",
-        "@types/node": "^25.6.1",
+        "@types/node": "^25.9.1",
+        "@types/pg": "^8.20.0",
         "@types/qrcode": "^1.5.6",
-        "drizzle-kit": "^0.31.10",
+        "eslint": "^9.39.4",
         "typescript": "^6.0.3",
+        "typescript-eslint": "^8.59.4",
       },
     },
   },
   "packages": {
-    "@drizzle-team/brocli": ["@drizzle-team/brocli@0.10.2", "", {}, "sha512-z33Il7l5dKjUgGULTqBsQBQwckHh5AbIuxhdsIxDDiZAzBOrZO6q9ogcWC65kU382AfynTfgNumVcNIjuIua6w=="],
-
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-    "@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=="],
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-    "@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=="],
 
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@@ -146,8 +117,6 @@
 
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@@ -202,70 +171,76 @@
 
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+    "@types/estree": ["@types/estree@1.0.9", "", {}, "sha512-GhdPgy1el4/ImP05X05Uw4cw2/M93BCUmnEvWZNStlCzEKME4Fkk+YpoA5OiHNQmoS7Cafb8Xa3Pya8m1Qrzeg=="],
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+    "@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=="],
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+    "@typescript-eslint/types": ["@typescript-eslint/types@8.59.4", "", {}, "sha512-F1o7WJcCq+bc8dwcO/YsSEOudAH8RDtaOhM6wcAQhcUsFhnWQl81JKy48q1hoxAU0qrzM89+31GYh1515Zde3Q=="],
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+    "@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=="],
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+    "@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=="],
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+    "@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=="],
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+    "acorn": ["acorn@8.16.0", "", { "bin": { "acorn": "bin/acorn" } }, "sha512-UVJyE9MttOsBQIDKw1skb9nAwQuR5wuGD3+82K6JgJlm/Y+KI92oNsMNGZCYdDsVtRHSak0pcV5Dno5+4jh9sw=="],
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+    "acorn-jsx": ["acorn-jsx@5.3.2", "", { "peerDependencies": { "acorn": "^6.0.0 || ^7.0.0 || ^8.0.0" } }, "sha512-rq9s+JNhf0IChjtDXxllJ7g41oZk5SlXtp0LHwyA5cejwn7vKmKp4pPri6YEePv2PU65sAsegbXtIinmDFDXgQ=="],
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+
+    "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=="],
 
     "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@1.16.0", "", { "dependencies": { "follow-redirects": "^1.16.0", "form-data": "^4.0.5", "proxy-from-env": "^2.1.0" } }, "sha512-6hp5CwvTPlN2A31g5dxnwAX0orzM7pmCRDLnZSX772mv8WDqICwFjowHuPs04Mc8deIld1+ejhtaMn5vp6b+1w=="],
+    "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=="],
 
     "balanced-match": ["balanced-match@1.0.2", "", {}, "sha512-3oSeUO0TMV67hN1AmbXsK4yaqU7tjiHlbxRDZOpH0KW9+CeX4bRAaX0Anxt0tx2MrpRpWwQaPwIlISEJhYU5Pw=="],
 
-    "base64-js": ["base64-js@1.5.1", "", {}, "sha512-AKpaYlHn8t4SVbOHCy+b5+KKgvR4vrsD8vbvrbiQJps7fKDTkjkDry6ji0rUJjC0kzbNePLwzxq8iypo41qeWA=="],
+    "brace-expansion": ["brace-expansion@1.1.14", "", { "dependencies": { "balanced-match": "^1.0.0", "concat-map": "0.0.1" } }, "sha512-MWPGfDxnyzKU7rNOW9SP/c50vi3xrmrua/+6hfPbCS2ABNWfx24vPidzvC7krjU/RTo235sV776ymlsMtGKj8g=="],
 
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+    "bun-types": ["bun-types@1.3.14", "", { "dependencies": { "@types/node": "*" } }, "sha512-4N0ig0fEomHt5R0KCFWjovxow98rIoRwKolrYdCcknNwMekCXRnWEUvgu5soYV8QXtVsrUD8B95MBOZGPvr6KQ=="],
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-
-    "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=="],
@@ -274,14 +249,16 @@
 
     "combined-stream": ["combined-stream@1.0.8", "", { "dependencies": { "delayed-stream": "~1.0.0" } }, "sha512-FQN4MRfuJeHf7cBbBMJFXhKSDq+2kAArBlmRBvcvFE5BB1HZKXtSFASDhdlz9zOYwxh8lDdnvmMOe/+5cdoEdg=="],
 
-    "cross-spawn": ["cross-spawn@7.0.6", "", { "dependencies": { "path-key": "^3.1.0", "shebang-command": "^2.0.0", "which": "^2.0.1" } }, "sha512-uV2QOWP2nWzsy2aMp8aRibhi9dlzF5Hgh5SHaB9OiTGEyDTiJJyx0uy51QXdyWbtAHNua4XJzUKca3OzKUd3vA=="],
+    "concat-map": ["concat-map@0.0.1", "", {}, "sha512-/Srv4dswyQNBfohGpz9o6Yb3Gz3SrUDqBH5rTuhGR7ahtlbYKnVxw2bCFMRljaA7EXHaXZ8wsHdodFvbkhKmqg=="],
 
-    "data-uri-to-buffer": ["data-uri-to-buffer@4.0.1", "", {}, "sha512-0R9ikRb668HB7QDxT1vkpuUBtqc53YyAwMwGeUFKRojY/NWKvdZ+9UYtRfGmhqNbRkTSVpMbmyhXipFFv2cb/A=="],
+    "cross-spawn": ["cross-spawn@7.0.6", "", { "dependencies": { "path-key": "^3.1.0", "shebang-command": "^2.0.0", "which": "^2.0.1" } }, "sha512-uV2QOWP2nWzsy2aMp8aRibhi9dlzF5Hgh5SHaB9OiTGEyDTiJJyx0uy51QXdyWbtAHNua4XJzUKca3OzKUd3vA=="],
 
     "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=="],
@@ -290,16 +267,10 @@
 
     "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=="],
@@ -310,53 +281,65 @@
 
     "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=="],
 
-    "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=="],
+    "escape-string-regexp": ["escape-string-regexp@4.0.0", "", {}, "sha512-TtpcNJ3XAzx3Gq8sWRzJaVajRs0uVxA2YAkdb1jm2YkPz4G6egUFAyA3n5vtEIZefPk5Wa4UXbKuS5fKkJWdgA=="],
 
-    "extend": ["extend@3.0.2", "", {}, "sha512-fjquC59cD7CyW6urNXK0FBufkZcoiGG80wTuPujX590cB5Ttln20E2UB4S/WARVqhXffZl2LNgS+gQdPIIim/g=="],
+    "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=="],
 
-    "fetch-blob": ["fetch-blob@3.2.0", "", { "dependencies": { "node-domexception": "^1.0.0", "web-streams-polyfill": "^3.0.3" } }, "sha512-7yAQpD2UMJzLi1Dqv7qFYnPbaPx7ZfFK6PiIxQ4PfkGPyNyl2Ugx+a/umUonmKqjhM4DnfbMvdX6otXq83soQQ=="],
+    "eslint-scope": ["eslint-scope@8.4.0", "", { "dependencies": { "esrecurse": "^4.3.0", "estraverse": "^5.2.0" } }, "sha512-sNXOfKCn74rt8RICKMvJS7XKV/Xk9kA7DyJr8mJik3S7Cwgy3qlkkmyS2uQB3jiJg6VNdZd/pDBJu0nvG2NlTg=="],
 
-    "find-up": ["find-up@4.1.0", "", { "dependencies": { "locate-path": "^5.0.0", "path-exists": "^4.0.0" } }, "sha512-PpOwAdQ/YlXQ2vj8a3h8IipDuYRi3wceVQQGYWxNINccq40Anw7BlsEXCMbt1Zt+OLA6Fq9suIpIWD0OsnISlw=="],
+    "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=="],
 
     "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=="],
 
-    "get-tsconfig": ["get-tsconfig@4.14.0", "", { "dependencies": { "resolve-pkg-maps": "^1.0.0" } }, "sha512-yTb+8DXzDREzgvYmh6s9vHsSVCHeC0G3PI5bEXNBHtmshPnO+S5O7qgLEOn0I5QvMy6kpZN8K1NKGyilLb93wA=="],
+    "glob-parent": ["glob-parent@6.0.2", "", { "dependencies": { "is-glob": "^4.0.3" } }, "sha512-XxwI8EOhVQgWp6iDL+3b0r86f4d6AX6zSU55HfB4ydCEuXLXc5FcYeOu+nnGftS4TEju/11rt4KJPTMgbfmv4A=="],
 
-    "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=="],
+    "globals": ["globals@14.0.0", "", {}, "sha512-oahGvuMGQlPw/ivIYBjVSrWAfWLBeku5tpPE2fOPLi+WHffIWbuh2tCjhyQhTBPMf5E9jDEH4FOmTYgYwbKwtQ=="],
-
-    "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=="],
 
-    "gtoken": ["gtoken@8.0.0", "", { "dependencies": { "gaxios": "^7.0.0", "jws": "^4.0.0" } }, "sha512-+CqsMbHPiSTdtSO14O51eMNlrp9N79gmeqmXeouJOhfucAedHw9noVe/n5uJk3tbKE6a+6ZCQg3RPhVhHByAIw=="],
+    "has-flag": ["has-flag@4.0.0", "", {}, "sha512-EykJT/Q1KjTWctppgIAgfSO0tKVuZUjhgMr17kqTumMl6Afv3EISleU7qZUzoXDFTAHTDC4NOoG/ZxU3EvlMPQ=="],
 
     "has-symbols": ["has-symbols@1.1.0", "", {}, "sha512-1cDNdwJ2Jaohmb3sg4OmKaMBwuC48sYni5HUw2DvsC8LjGTLK9h+eb1X6RyuOHe4hT0ULCW68iomhjUoKUqlPQ=="],
 
@@ -364,31 +347,43 @@
 
     "hasown": ["hasown@2.0.2", "", { "dependencies": { "function-bind": "^1.1.2" } }, "sha512-0hJU9SCPvmMzIBdZFqNPXWa6dqh7WdH0cII9y+CyS8rG3nL48Bclra9HmKhVVUHyPWNH5Y7xDwAB7bfgSjkUMQ=="],
 
-    "https-proxy-agent": ["https-proxy-agent@7.0.6", "", { "dependencies": { "agent-base": "^7.1.2", "debug": "4" } }, "sha512-vK9P5/iUfdl95AI+JVyUuIcVtd4ofvtrOr3HNtM2yxC9bnMbEdp3x01OhQNnjb8IJYi38VlTE3mBXwcfvywuSw=="],
+    "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=="],
 
     "is-fullwidth-code-point": ["is-fullwidth-code-point@3.0.0", "", {}, "sha512-zymm5+u+sCsSWyD9qNaejV3DFvhCKclKdizYaJUuHA83RLjb7nSuGnddCHGv0hk+KY7BMAlsWeK4Ueg6EV6XQg=="],
 
-    "isexe": ["isexe@2.0.0", "", {}, "sha512-RHxMLp9lnKHGHRng9QFhRCMbYAcVpn69smSGcq3f36xjgVVWThj4qqLbTLlq7Ssj8B+fIQ1EuCEGI2lKsyQeIw=="],
+    "is-glob": ["is-glob@4.0.3", "", { "dependencies": { "is-extglob": "^2.1.1" } }, "sha512-xelSayHH36ZgE7ZWhli7pW34hNbNl8Ojv5KVmkJD4hBdD3th8Tfk9vYasLM+mXWOZhFkgZfxhLSnrwRr4elSSg=="],
 
-    "jackspeak": ["jackspeak@3.4.3", "", { "dependencies": { "@isaacs/cliui": "^8.0.2" }, "optionalDependencies": { "@pkgjs/parseargs": "^0.11.0" } }, "sha512-OGlZQpz2yfahA/Rd1Y8Cd9SIEsqvXkLVoSw/cgwhnhFMDbsQFeZYoJJ7bIZBS9BcamUW96asq/npPWugM+RQBw=="],
+    "isexe": ["isexe@2.0.0", "", {}, "sha512-RHxMLp9lnKHGHRng9QFhRCMbYAcVpn69smSGcq3f36xjgVVWThj4qqLbTLlq7Ssj8B+fIQ1EuCEGI2lKsyQeIw=="],
 
     "js-base64": ["js-base64@3.7.8", "", {}, "sha512-hNngCeKxIUQiEUN3GPJOkz4wF/YvdUdbNL9hsBcMQTkKzboD7T/q3OYOuuPZLUE6dBxSGpwhk5mwuDud7JVAow=="],
 
-    "json-bigint": ["json-bigint@1.0.0", "", { "dependencies": { "bignumber.js": "^9.0.0" } }, "sha512-SiPv/8VpZuWbvLSMtTDU8hEfrZWg/mH/nV/b4o0CYbSxu1UIQPLdwKOCIyLQX+VIPO5vrLX3i8qtqFyhdPSUSQ=="],
+    "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=="],
 
     "jsonfile": ["jsonfile@5.0.0", "", { "dependencies": { "universalify": "^0.1.2" }, "optionalDependencies": { "graceful-fs": "^4.1.6" } }, "sha512-NQRZ5CRo74MhMMC3/3r5g2k4fjodJ/wh8MxjFbCViWKFjxrnudWSY5vomh+23ZaXzAS7J3fBZIR2dV6WbmfM0w=="],
 
-    "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=="],
+    "keyv": ["keyv@4.5.4", "", { "dependencies": { "json-buffer": "3.0.1" } }, "sha512-oxVHkHR/EJf2CNXnWxRLW6mg7JyCCUcG0DtEGmL2ctUo1PNTin1PUil+r/+4r5MpVgC/fn1kjsx7mjSujKqIpw=="],
 
-    "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=="],
+    "levn": ["levn@0.4.1", "", { "dependencies": { "prelude-ls": "^1.2.1", "type-check": "~0.4.0" } }, "sha512-+bT2uH4E5LGE7h/n3evcS/sQlJXCpIp6ym8OWJ5eV6+67Dsql/LaaT7qJBAt2rzfoa/5QBGBhxDix1dMt2kQKQ=="],
 
     "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@5.0.0", "", { "dependencies": { "p-locate": "^4.1.0" } }, "sha512-t7hw9pI+WvuwNJXwk5zVHpyhIqzg2qTlklJOf0mVxGSbe3Fp2VieZcduNYjaLDoy6p9uGpQEGWG87WpMKlNq8g=="],
+    "locate-path": ["locate-path@6.0.0", "", { "dependencies": { "p-locate": "^5.0.0" } }, "sha512-iPZK6eYjbxRu3uB4/WZ3EsEIMJFMqAoopl3R+zuq0UjcAm/MO6KCweDgPfP3elTztoKP3KtnVHxTn2NHBSDVUw=="],
 
-    "long": ["long@5.3.2", "", {}, "sha512-mNAgZ1GmyNhD7AuqnTG3/VQ26o760+ZYBPKjPvugO8+nLbYfX6TVpJPseBvopbdY+qpZ/lKUnmEc1LeZYS3QAA=="],
+    "lodash.merge": ["lodash.merge@4.6.2", "", {}, "sha512-0KpjqXRVvrYyCsX1swR/XTK0va6VQkQM6MNo7PqW77ByjAhoARA8EfrP1N4+KlKj8YS0ZUCtRT/YUuhyYDujIQ=="],
-
-    "lru-cache": ["lru-cache@10.4.3", "", {}, "sha512-JNAzZcXrCt42VGLuYz0zfAzDfAvJWW6AfYlDBQyDV5DClI2m5sAmK+OIO7s59XfsRsWHp02jAJrRadPRGTt6SQ=="],
 
     "math-intrinsics": ["math-intrinsics@1.1.0", "", {}, "sha512-/IXtbwEk5HTPyEwyKX6hGkYXxM9nbj64B+ilVJnC/R6B0pH5G4V3b0pVbL7DBj4tkhBAppbQUlf6F6Xl9LHu1g=="],
 
@@ -396,57 +391,73 @@
 
     "mime-types": ["mime-types@2.1.29", "", { "dependencies": { "mime-db": "1.46.0" } }, "sha512-Y/jMt/S5sR9OaqteJtslsFZKWOIIqMACsJSiHghlCAyhf7jfVYjKBmLiX8OgpWeW+fjJ2b+Az69aPFPkUOY6xQ=="],
 
-    "minimatch": ["minimatch@9.0.5", "", { "dependencies": { "brace-expansion": "^2.0.1" } }, "sha512-G6T0ZX48xgozx7587koeX9Ys2NYy6Gmv//P89sEte9V9whIapMNF4idKxnW2QtCcLiTWlb/wfCabAtAFWhhBow=="],
+    "minimatch": ["minimatch@3.1.5", "", { "dependencies": { "brace-expansion": "^1.1.7" } }, "sha512-VgjWUsnnT6n+NUk6eZq77zeFdpW2LWDzP6zFGrCbHXiYNul5Dzqk2HHQ5uFH2DNW5Xbp8+jVzaeNt94ssEEl4w=="],
-
-    "minipass": ["minipass@7.1.2", "", {}, "sha512-qOOzS1cBTWYF4BH8fVePDBOO9iptMnGUEZwNc/cMWnTV2nVLZ7VoNWEPHkYczZA0pdoA7dl6e7FL659nX9S2aw=="],
 
     "ms": ["ms@2.1.3", "", {}, "sha512-6FlzubTLZG3J2a/NVCAleEhjzq5oxgHyaCU9yYXvcLsvoVaHJq/s5xXI6/XXP6tz7R9xAOtHnSO/tXtF3WRTlA=="],
 
-    "node-domexception": ["node-domexception@1.0.0", "", {}, "sha512-/jKZoMpw0F8GRwl4/eLROPA3cfcXtLApP0QzLmUT/HuPCZWyB7IY9ZrMeKw2O/nFIqPQB3PVM9aYm0F312AXDQ=="],
+    "natural-compare": ["natural-compare@1.4.0", "", {}, "sha512-OWND8ei3VtNC9h7V60qff3SVobHr996CTwgxubgyQYEpg290h9J0buyECNNJexkFm5sOajh5G116RYA1c8ZMSw=="],
-
-    "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@6.37.0", "", { "peerDependencies": { "ws": "^8.18.0", "zod": "^3.25 || ^4.0" }, "optionalPeers": ["ws", "zod"], "bin": { "openai": "bin/cli" } }, "sha512-0H5dEGFmmLv6KSd0W1w2nyL8WsLkX6yoLeQpU+dZAOuGcany5qkYQMmj35ZrKgb6yiyYqpUzFOpR8mZQkgqeEQ=="],
+    "openai": ["openai@6.38.0", "", { "peerDependencies": { "ws": "^8.18.0", "zod": "^3.25 || ^4.0" }, "optionalPeers": ["ws", "zod"], "bin": { "openai": "bin/cli" } }, "sha512-AoMplt2UalrpgUDMh3L09QWjNRlgJPipclQvA6sYAaeF6nHNBMgmikAZGmcYLn8on4d9sQY9Q8bOLfrBS7Lc8g=="],
 
-    "p-limit": ["p-limit@2.3.0", "", { "dependencies": { "p-try": "^2.0.0" } }, "sha512-//88mFWSJx8lxCzwdAABTJL2MyWB12+eIY7MDL2SqLmAkeKU9qxRvWuSyTjm3FUmpBEMuFfckAIqEaVGUDxb6w=="],
+    "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-locate": ["p-locate@4.1.0", "", { "dependencies": { "p-limit": "^2.2.0" } }, "sha512-R79ZZ/0wAxKGu3oYMlz8jy/kbhsNrS7SKZ7PxEHBgJ5+F2mtFW2fK2cOtBh1cHYkQsbzFV7I+EoRKe6Yt0oK7A=="],
+    "p-limit": ["p-limit@3.1.0", "", { "dependencies": { "yocto-queue": "^0.1.0" } }, "sha512-TYOanM3wGwNGsZN2cVTYPArw454xnXj5qmWF1bEoAc4+cU/ol7GVh7odevjp1FNHduHc3KZMcFduxU5Xc6uJRQ=="],
 
-    "p-retry": ["p-retry@4.6.2", "", { "dependencies": { "@types/retry": "0.12.0", "retry": "^0.13.1" } }, "sha512-312Id396EbJdvRONlngUx0NydfrIQ5lsYu0znKVUzVvArzEIt08V1qhtyESbGVd1FGX7UKtiFp5uwKZdM8wIuQ=="],
+    "p-locate": ["p-locate@5.0.0", "", { "dependencies": { "p-limit": "^3.0.2" } }, "sha512-LaNjtRWUBY++zB5nE/NwcaoMylSPk+S+ZHNB1TzdbMJMny6dynpAGt7X/tl/QYq3TIeE6nxHppbo2LGymrG5Pw=="],
 
     "p-try": ["p-try@2.2.0", "", {}, "sha512-R4nPAVTAU0B9D35/Gk3uJf/7XYbQcyohSKdvAxIRSNghFl4e71hVoGnBNQz9cWaXxO2I10KTC+3jMdvvoKw6dQ=="],
 
-    "package-json-from-dist": ["package-json-from-dist@1.0.1", "", {}, "sha512-UEZIS3/by4OC8vL3P2dTXRETpebLI2NiI5vIrjaD/5UtrkFX/tNbwjTSRAGC/+7CAo2pIcBaRgWmcBBHcsaCIw=="],
+    "parent-module": ["parent-module@1.0.1", "", { "dependencies": { "callsites": "^3.0.0" } }, "sha512-GQ2EWRpQV8/o+Aw8YqtfZZPfNRWZYkbidE9k5rpl/hC3vtHHBfGm2Ifi6qWV+coDGkrUKZAxE3Lot5kcsRlh+g=="],
 
     "path-exists": ["path-exists@4.0.0", "", {}, "sha512-ak9Qy5Q7jYb2Wwcey5Fpvg2KoAc/ZIhLSLOSBmRmygPsGwkVVt0fZa0qrtMz+m6tJTAHfZQ8FnmB4MG4LWy7/w=="],
 
     "path-key": ["path-key@3.1.1", "", {}, "sha512-ojmeN0qd+y0jszEtoY48r0Peq5dwMEkIlCOu6Q5f41lfkswXuKtYrhgoTpLnyIcHm24Uhqx+5Tqm2InSwLhE6Q=="],
 
-    "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=="],
+    "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=="],
 
     "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=="],
 
-    "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=="],
-
     "proxy-from-env": ["proxy-from-env@2.1.0", "", {}, "sha512-cJ+oHTW1VAEa8cJslgmUZrc+sjRKgAKl3Zyse6+PV38hZe/V6Z14TbCuXcan9F9ghlz4QrFr2c92TNF82UkYHA=="],
 
+    "punycode": ["punycode@2.3.1", "", {}, "sha512-vYt7UD1U9Wg6138shLtLOvdAu+8DsC/ilFtEVHcH+wydcSpNE20AfSOduf6MkRFahL5FY7X1oU7nKVZFtfq8Fg=="],
+
     "qrcode": ["qrcode@1.5.4", "", { "dependencies": { "dijkstrajs": "^1.0.1", "pngjs": "^5.0.0", "yargs": "^15.3.1" }, "bin": { "qrcode": "bin/qrcode" } }, "sha512-1ca71Zgiu6ORjHqFBDpnSMTR2ReToX4l1Au1VFLyVeBTFavzQnv5JxMFr3ukHVKpSrSA2MCk0lNJSykjUfz7Zg=="],
 
     "require-directory": ["require-directory@2.1.1", "", {}, "sha512-fGxEI7+wsG9xrvdjsrlmL22OMTTiHRwAMroiEeMgq8gzoLC/PQr7RsRDSTLUg/bZAZtF+TVIkHc6/4RIKrui+Q=="],
 
     "require-main-filename": ["require-main-filename@2.0.0", "", {}, "sha512-NKN5kMDylKuldxYLSUfrbo5Tuzh4hd+2E8NPPX02mZtn1VuREQToYe/ZdlJy+J3uCpfaiGF05e7B8W0iXbQHmg=="],
 
-    "resolve-pkg-maps": ["resolve-pkg-maps@1.0.0", "", {}, "sha512-seS2Tj26TBVOC2NIc2rOe2y2ZO7efxITtLZcGSOnHHNOQ7CkiUBfw0Iw2ck6xkIhPwLhKNLS8BO+hEpngQlqzw=="],
+    "resolve-from": ["resolve-from@4.0.0", "", {}, "sha512-pb/MYmXstAkysRFx8piNI1tGFNQIFA3vkE3Gq4EuA1dF6gHp/+vgZqsCGJapvy8N3Q+4o7FwvquPJcnZ7RYy4g=="],
-
-    "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=="],
 
@@ -458,39 +469,41 @@
 
     "shebang-regex": ["shebang-regex@3.0.0", "", {}, "sha512-7++dFhtcx3353uBaq8DDR4NuxBetBzC7ZQOhmTQInHEd6bSrXdiEyzCvG07Z44UYdLShWUyXt5M/yhz8ekcb1A=="],
 
-    "signal-exit": ["signal-exit@4.1.0", "", {}, "sha512-bzyZ1e88w9O1iNJbKnOlvYTrWPDl46O1bG0D3XInv+9tkPrxrN8jUUTiFlDkkmKWgn1M6CfIA13SuGqOa9Korw=="],
+    "split2": ["split2@4.2.0", "", {}, "sha512-UcjcJOWknrNkF6PLX83qcHM6KHgVKNkV62Y8a5uYDVv9ydGQVwAHMKqHdJje1VTWpljG0WYpCDhrCdAOYH4TWg=="],
-
-    "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-ansi-cjs": ["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=="],
 
     "systeminformation": ["systeminformation@5.31.6", "", { "os": "!aix", "bin": { "systeminformation": "lib/cli.js" } }, "sha512-Uv2b2uGGM6ns+26czgW2cYRabYdnswM0ddSOOlryHOaelzsmDSet1iM/NT7VOYxW8x/BW+HkY+b1Ve2pLTSGSA=="],
 
-    "tslib": ["tslib@2.8.1", "", {}, "sha512-oJFu94HQb+KVduSUQL7wnpmqnfmLsOA/nAh6b6EH0wCEoK0/mPeXU6c3wKDV83MkOuHPRHtSXKKU99IBazS/2w=="],
+    "tinyglobby": ["tinyglobby@0.2.16", "", { "dependencies": { "fdir": "^6.5.0", "picomatch": "^4.0.4" } }, "sha512-pn99VhoACYR8nFHhxqix+uvsbXineAasWm5ojXoN8xEwK5Kd3/TrhNn1wByuD52UxWRLy8pu+kRMniEi6Eq9Zg=="],
 
-    "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=="],
+    "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=="],
 
     "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@7.19.2", "", {}, "sha512-qYVnV5OEm2AW8cJMCpdV20CDyaN3g0AjDlOGf1OW4iaDEx8MwdtChUp4zu4H0VP3nDRF/8RKWH+IPp9uW0YGZg=="],
+    "undici-types": ["undici-types@7.24.6", "", {}, "sha512-WRNW+sJgj5OBN4/0JpHFqtqzhpbnV0GuB+OozA9gCL7a993SmU+1JBZCzLNxYsbMfIeDL+lTsphD5jN5N+n0zg=="],
 
     "universalify": ["universalify@0.1.2", "", {}, "sha512-rBJeI5CXAlmy1pV+617WB9J63U6XcazHHF2f2dbJix4XzpUF0RS3Zbj0FGIOCAva5P/d/GBOYaACQ1w+0azUkg=="],
 
-    "web-streams-polyfill": ["web-streams-polyfill@3.3.3", "", {}, "sha512-d2JWLCivmZYTSIoge9MsgFCZrt571BikcWGYkjC1khllbTeDlGqZ2D8vD8E/lJa8WGWbb7Plm8/XJYV7IJHZZw=="],
+    "uri-js": ["uri-js@4.4.1", "", { "dependencies": { "punycode": "^2.1.0" } }, "sha512-7rKUyy33Q1yc98pQ1DAmLtwX109F7TIfWlW1Ydo8Wl1ii1SeHieeh0HHfPeL2fMXK6z0s8ecKs9frCuLJvndBg=="],
 
     "whatwg-fetch": ["whatwg-fetch@3.6.20", "", {}, "sha512-EqhiFU6daOA8kpjOWTL0olhVOF3i7OrFzSYiGsEMB8GcXS+RrzauAERX65xMeNWVqxA6HXH2m69Z9LaKKdisfg=="],
 
@@ -498,29 +511,27 @@
 
     "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=="],
 
-    "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=="],
-
     "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=="],
 
+    "xtend": ["xtend@4.0.2", "", {}, "sha512-LKYU1iAXJXUgAXn9URjiu+MWhyUXHsvfp7mcuYm9dSUKK0/CjtrUwFAxD82/mCWbtLsGjFIad0wIsod4zrTAEQ=="],
+
     "y18n": ["y18n@4.0.3", "", {}, "sha512-JKhqTOwSrqNA1NY5lSztJ1GrBiUodLMmIZuLiDaMRJ+itFd+ABVE8XBjOvIWL+rSqNDC74LCSFmlb/U4UZ4hJQ=="],
 
     "yargs": ["yargs@15.4.1", "", { "dependencies": { "cliui": "^6.0.0", "decamelize": "^1.2.0", "find-up": "^4.1.0", "get-caller-file": "^2.0.1", "require-directory": "^2.1.1", "require-main-filename": "^2.0.0", "set-blocking": "^2.0.0", "string-width": "^4.2.0", "which-module": "^2.0.0", "y18n": "^4.0.0", "yargs-parser": "^18.1.2" } }, "sha512-aePbxDmcYW++PaqBsJ+HYUFwCdv4LVvdnhBy78E57PIor8/OVvhMrADFFEDh8DHDFRv/O9i3lPhsENjO7QX0+A=="],
 
     "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=="],
 
-    "@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=="],
+    "@eslint-community/eslint-utils/eslint-visitor-keys": ["eslint-visitor-keys@3.4.3", "", {}, "sha512-wpc+LXeiyiisxPlEkUzU6svyS1frIO3Mgxj1fdy7Pm8Ygzguax2N3Fa/D/ag1WqbOprdI+uY6wMUl8/a2G+iag=="],
-
-    "@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=="],
 
@@ -528,11 +539,19 @@
 
     "@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=="],
 
-    "bun-types/@types/node": ["@types/node@25.6.0", "", { "dependencies": { "undici-types": "~7.19.0" } }, "sha512-+qIYRKdNYJwY3vRCZMdJbPLJAtGjQBudzZzdzwQYkEPQd+PJGixUL5QfvCLDaULoLv+RhT3LDkwEfKaAkgSmNQ=="],
+    "@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=="],
 
     "cross-spawn/which": ["which@2.0.2", "", { "dependencies": { "isexe": "^2.0.0" }, "bin": { "node-which": "./bin/node-which" } }, "sha512-BLI3Tl1TW3Pvl70l3yq3Y64i+awpwXqsGBYWkkqMtnbXgrMD+yj7rhW0kuEDxzJaYXGjEW5ogapKNMEKNMjibA=="],
 
@@ -540,124 +559,30 @@
 
     "libsql/detect-libc": ["detect-libc@2.0.2", "", {}, "sha512-UX6sGumvvqSaXgdKGUsgZWqcUyIXZ/vZTrlRT/iobiKhGL0zL4d3osHj3uqllWJK+i+sixDS/3COVEOFbupFyw=="],
 
-    "protobufjs/@types/node": ["@types/node@25.0.10", "", { "dependencies": { "undici-types": "~7.16.0" } }, "sha512-zWW5KPngR/yvakJgGOmZ5vTBemDoSqF3AcV/LrO5u5wTWyEAVVh+IT39G4gtyAkh3CtTZs8aX/yRM82OfzHJRg=="],
+    "pg/pg-protocol": ["pg-protocol@1.14.0", "", {}, "sha512-n5taZ1kO3s9ngDTVxsEznOqCyToTgz0FLuPq0B33COy5pPpuWJpY3/2oRBVETuOgzdqRXfWpM9HIhp2LBBT1BA=="],
 
     "string-width/emoji-regex": ["emoji-regex@8.0.0", "", {}, "sha512-MSjYzcWNOA0ewAHpz0MxpYFvwg6yjy1NG3xteoqz644VCo/RPgnr1/GGt+ic3iJTzQ8Eu3TdM14SawnVUmGE6A=="],
 
-    "string-width-cjs/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=="],
 
-    "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=="],
+    "yargs/find-up": ["find-up@4.1.0", "", { "dependencies": { "locate-path": "^5.0.0", "path-exists": "^4.0.0" } }, "sha512-PpOwAdQ/YlXQ2vj8a3h8IipDuYRi3wceVQQGYWxNINccq40Anw7BlsEXCMbt1Zt+OLA6Fq9suIpIWD0OsnISlw=="],
-
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-
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-    "@esbuild-kit/core-utils/esbuild/@esbuild/sunos-x64": ["@esbuild/sunos-x64@0.18.20", "", { "os": "sunos", "cpu": "x64" }, "sha512-kDbFRFp0YpTQVVrqUd5FTYmWo45zGaXe0X8E1G/LKFC0v8x0vWrhOWSLITcCn63lmZIxfOMXtCfti/RxN/0wnQ=="],
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-    "@esbuild-kit/core-utils/esbuild/@esbuild/win32-arm64": ["@esbuild/win32-arm64@0.18.20", "", { "os": "win32", "cpu": "arm64" }, "sha512-ddYFR6ItYgoaq4v4JmQQaAI5s7npztfV4Ag6NrhiaW0RrnOXqBkgwZLofVTlq1daVTQNhtI5oieTvkRPfZrePg=="],
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-
-    "@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=="],
 
-    "protobufjs/@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=="],
 
-    "tsx/esbuild/@esbuild/aix-ppc64": ["@esbuild/aix-ppc64@0.27.2", "", { "os": "aix", "cpu": "ppc64" }, "sha512-GZMB+a0mOMZs4MpDbj8RJp4cw+w1WV5NYD6xzgvzUJ5Ek2jerwfO2eADyI6ExDSUED+1X8aMbegahsJi+8mgpw=="],
+    "yargs/find-up/locate-path": ["locate-path@5.0.0", "", { "dependencies": { "p-locate": "^4.1.0" } }, "sha512-t7hw9pI+WvuwNJXwk5zVHpyhIqzg2qTlklJOf0mVxGSbe3Fp2VieZcduNYjaLDoy6p9uGpQEGWG87WpMKlNq8g=="],
 
-    "tsx/esbuild/@esbuild/android-arm": ["@esbuild/android-arm@0.27.2", "", { "os": "android", "cpu": "arm" }, "sha512-DVNI8jlPa7Ujbr1yjU2PfUSRtAUZPG9I1RwW4F4xFB1Imiu2on0ADiI/c3td+KmDtVKNbi+nffGDQMfcIMkwIA=="],
+    "@typescript-eslint/typescript-estree/minimatch/brace-expansion/balanced-match": ["balanced-match@4.0.4", "", {}, "sha512-BLrgEcRTwX2o6gGxGOCNyMvGSp35YofuYzw9h1IMTRmKqttAZZVU67bdb9Pr2vUHA8+j3i2tJfjO6C6+4myGTA=="],
 
-    "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-locate@4.1.0", "", { "dependencies": { "p-limit": "^2.2.0" } }, "sha512-R79ZZ/0wAxKGu3oYMlz8jy/kbhsNrS7SKZ7PxEHBgJ5+F2mtFW2fK2cOtBh1cHYkQsbzFV7I+EoRKe6Yt0oK7A=="],
 
-    "tsx/esbuild/@esbuild/android-x64": ["@esbuild/android-x64@0.27.2", "", { "os": "android", "cpu": "x64" }, "sha512-z8Ank4Byh4TJJOh4wpz8g2vDy75zFL0TlZlkUkEwYXuPSgX8yzep596n6mT7905kA9uHZsf/o2OJZubl2l3M7A=="],
+    "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/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=="],
-
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-
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-
-    "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=="],
-
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-
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-
-    "tsx/esbuild/@esbuild/linux-s390x": ["@esbuild/linux-s390x@0.27.2", "", { "os": "linux", "cpu": "s390x" }, "sha512-p4bm9+wsPwup5Z8f4EpfN63qNagQ47Ua2znaqGH6bqLlmJ4bx97Y9JdqxgGZ6Y8xVTixUnEkoKSHcpRlDnNr5w=="],
-
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-
-    "tsx/esbuild/@esbuild/netbsd-arm64": ["@esbuild/netbsd-arm64@0.27.2", "", { "os": "none", "cpu": "arm64" }, "sha512-Kj6DiBlwXrPsCRDeRvGAUb/LNrBASrfqAIok+xB0LxK8CHqxZ037viF13ugfsIpePH93mX7xfJp97cyDuTZ3cw=="],
-
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-
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-
-    "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:latest
+    image: ghcr.io/melod1n/tg-chat-bot:${IMAGE_TAG:-1.0.0}
     restart: unless-stopped
     env_file:
       - .env

drizzle.config.ts

@@ -1,17 +0,0 @@
-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

@@ -1,31 +1,42 @@
-const tsParser = require("@typescript-eslint/parser");
+import js from "@eslint/js";
-const tsPlugin = require("@typescript-eslint/eslint-plugin");
+import {defineConfig} from "eslint/config";
+import tseslint from "typescript-eslint";
 
-module.exports = [
+export default defineConfig(
     {
         ignores: [
             "dist/**",
+            "data/**",
             "node_modules/**",
+            "**/*.tsbuildinfo",
         ],
     },
+    js.configs.recommended,
+    tseslint.configs.recommended,
     {
-        files: ["**/*.ts"],
+        files: ["src/**/*.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

@@ -8,6 +8,13 @@
   },
   "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...",
@@ -62,18 +69,21 @@
   "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",
@@ -81,6 +91,8 @@
   "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...",
@@ -136,6 +148,7 @@
   "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",
@@ -170,6 +183,9 @@
   "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",
@@ -179,10 +195,6 @@
     "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

@@ -8,6 +8,13 @@
   },
   "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...",
@@ -88,18 +95,21 @@
   "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",
@@ -107,6 +117,8 @@
   "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...",
@@ -162,6 +174,7 @@
   "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",
@@ -196,6 +209,9 @@
   "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",
@@ -205,10 +221,6 @@
     "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

@@ -8,6 +8,13 @@
   },
   "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...",
@@ -87,18 +94,21 @@
   "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",
@@ -106,6 +116,8 @@
   "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...",
@@ -161,6 +173,7 @@
   "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",
@@ -195,6 +208,9 @@
   "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

@@ -4,35 +4,42 @@
   "version": "1.0.0",
   "type": "module",
   "scripts": {
-    "build": "tsgo -p tsconfig.json",
+    "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",
     "start": "node dist/index.js",
     "bun:start": "bun run src/index.ts"
   },
   "dependencies": {
-    "@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",
+    "@mistralai/mistralai": "^2.2.1",
     "@napi-rs/canvas": "^1.0.0",
-    "axios": "^1.16.0",
+    "axios": "^1.16.1",
     "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": {
-    "@types/bun": "^1.3.13",
+    "@eslint/js": "^9.39.4",
+    "@types/bun": "^1.3.14",
     "@types/fluent-ffmpeg": "^2.1.28",
-    "@types/node": "^25.6.1",
+    "@types/node": "^25.9.1",
+    "@types/pg": "^8.20.0",
     "@types/qrcode": "^1.5.6",
-    "drizzle-kit": "^0.31.10",
+    "eslint": "^9.39.4",
-    "typescript": "^6.0.3"
+    "typescript": "^6.0.3",
+    "typescript-eslint": "^8.59.4"
   }
 }

src/ai/ai-runtime-target.ts

@@ -1,13 +1,12 @@
 import {Mistral} from "@mistralai/mistralai";
-import {GoogleGenAI} from "@google/genai";
 import {Ollama} from "ollama";
 import {OpenAI} from "openai";
-import {Environment} from "../common/environment";
+import {Environment} from "../common/environment.js";
-import {AiModelCapabilities} from "../model/ai-model-capabilities";
+import {AiModelCapabilities} from "../model/ai-model-capabilities.js";
-import {AiProvider} from "../model/ai-provider";
+import {AiProvider} from "../model/ai-provider.js";
 
 export type AiCapabilityName = keyof AiModelCapabilities;
-export type AiRuntimePurpose = AiCapabilityName | "chat";
+export type AiRuntimePurpose = AiCapabilityName | "chat" | "memoryCompress";
 
 export type AiRuntimeTarget = {
     provider: AiProvider;
@@ -15,12 +14,9 @@ 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"],
@@ -28,6 +24,7 @@ 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"],
@@ -72,13 +69,18 @@ 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:
@@ -90,8 +92,6 @@ 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:
@@ -118,19 +118,6 @@ 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":
@@ -164,8 +151,28 @@ 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};
+    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);
 }
 
 export function sameRuntimeEndpoint(left: AiRuntimeTarget, right: AiRuntimeTarget): boolean {
@@ -181,26 +188,6 @@ 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

@@ -1,6 +1,5 @@
 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";
@@ -31,27 +30,6 @@ 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,
@@ -64,6 +42,4 @@ export function asMistralChatMessage(message: ChatMessage): MistralChatMessage {
 //
 //     }
 // }
-
+export type AiChatMessage = OpenAIChatMessage | OllamaChatMessage | MistralChatMessage;
-
-export type AiChatMessage = | OpenAIChatMessage | OllamaChatMessage | MistralChatMessage | GeminiMessage;

src/ai/conversation-pipeline.ts

@@ -0,0 +1,358 @@
+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

@@ -0,0 +1,102 @@
+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

@@ -0,0 +1,58 @@
+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

@@ -1,84 +0,0 @@
-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

@@ -0,0 +1,102 @@
+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

@@ -0,0 +1,421 @@
+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

@@ -0,0 +1,106 @@
+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

@@ -0,0 +1,123 @@
+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

@@ -0,0 +1,165 @@
+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: Record<string, unknown> | string;
+    arguments: AiJsonObject | string;
 };
 
 export type MistralToolCall = {
@@ -110,3 +110,4 @@ export type MistralChatMessage =
     | MistralSystemMessage
     | MistralToolMessage
     | MistralUserMessage
+import {AiJsonObject} from "./tool-types";

src/ai/model-call-stage.ts

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

src/ai/ollama-rag.ts

@@ -476,6 +476,40 @@ 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;
@@ -587,7 +621,7 @@ function reserveArchiveFile(
     return true;
 }
 
-function pushArchiveSkip(state: ArchiveExtractionState, fileName: string, reason: unknown): void {
+function pushArchiveSkip(state: ArchiveExtractionState, fileName: string, reason: Error | string | object | null | undefined): void {
     state.skipped.push({
         fileName,
         reason: reason instanceof Error ? reason.message : String(reason),
@@ -607,7 +641,7 @@ function extractArchiveChildDocuments(
     try {
         return extractRagDocumentsFromFile(child, config, state, depth + 1);
     } catch (e) {
-        pushArchiveSkip(state, child.fileName, e);
+        pushArchiveSkip(state, child.fileName, e instanceof Error ? e : String(e));
         return [];
     }
 }
@@ -641,7 +675,7 @@ function extractZipArchiveDocuments(
             const buffer = readZipEntry(doc.buffer, entry);
             documents.push(...extractArchiveChildDocuments(doc, normalizedName, buffer, config, state, depth));
         } catch (e) {
-            pushArchiveSkip(state, displayName, e);
+            pushArchiveSkip(state, displayName, e instanceof Error ? e : String(e));
         }
     }
 
@@ -1235,6 +1269,48 @@ 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");
 
@@ -1258,7 +1334,7 @@ export async function buildOllamaDocumentRagContext(params: {
     userQuery: string;
     config: OllamaDocumentRagConfig;
     onStatus?: (status: string) => Promise<void> | void;
-}): Promise<string | null> {
+}): Promise<{context: string; artifact: OllamaRagArtifactDetails} | null> {
     const docs = params.downloads.filter(download => download.kind === "document");
     if (!docs.length) return null;
 
@@ -1333,7 +1409,10 @@ export async function buildOllamaDocumentRagContext(params: {
         throw new Error(Environment.localRagNoSuitableFragmentsText);
     }
 
-    return formatRagContext(selected, chunks.length, documents, skippedDocuments);
+    return {
+        context: formatRagContext(selected, chunks.length, documents, skippedDocuments),
+        artifact: buildOllamaRagArtifactDetails(buildRetrievalQuery(params.userQuery, params.messages), documents, selected, skippedDocuments, params.config),
+    };
 }
 
 export async function prepareOllamaDocumentRag(params: {
@@ -1342,7 +1421,7 @@ export async function prepareOllamaDocumentRag(params: {
     userQuery: string;
     message: TelegramStreamMessage;
     config: OllamaDocumentRagConfig;
-}): Promise<boolean> {
+}): Promise<{prepared: boolean; artifact?: OllamaRagArtifactDetails}> {
     const context = await buildOllamaDocumentRagContext({
         downloads: params.downloads,
         messages: params.messages,
@@ -1354,7 +1433,7 @@ export async function prepareOllamaDocumentRag(params: {
         },
     });
 
-    if (!context) return false;
+    if (!context) return {prepared: false};
-    injectOllamaRagContext(params.messages, context);
+    injectOllamaRagContext(params.messages, context.context);
-    return true;
+    return {prepared: true, artifact: context.artifact};
 }

src/ai/openai-chat-completions.ts

@@ -0,0 +1,66 @@
+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

@@ -1,7 +1,22 @@
-import type {ResponseInputMessageContentList} from "openai/resources/responses/responses";
+import type {
+    ResponseInputMessageContentList,
+    ResponseOutputMessage,
+} from "openai/resources/responses/responses";
+import type {ChatCompletionMessageParam} from "openai/resources/chat/completions";
 
-export type OpenAIChatMessage = {
+type OpenAIInputChatMessage = {
     type: "message";
-    role: "system" | "user" | "assistant";
+    role: "system" | "user";
     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

@@ -0,0 +1,74 @@
+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

@@ -0,0 +1,198 @@
+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

@@ -0,0 +1,196 @@
+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

@@ -0,0 +1,18 @@
+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

@@ -7,12 +7,9 @@ import {isOllamaSpeechToTextModel} from "./speech-to-text-models";
 import {
     AiCapabilityName,
     AiRuntimeTarget,
-    createGeminiOpenAiClient,
-    createGoogleGenAiClient,
     createMistralClient,
     createOllamaClient,
     createOpenAiClient,
-    getGeminiApiMode,
     resolveAiRuntimeTarget,
     sameRuntimeEndpoint,
 } from "./ai-runtime-target";
@@ -35,8 +32,6 @@ 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:
@@ -49,9 +44,6 @@ 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;
@@ -111,12 +103,6 @@ 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;
@@ -125,16 +111,6 @@ 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,
@@ -167,26 +143,6 @@ 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});
@@ -220,6 +176,7 @@ 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),
@@ -228,7 +185,7 @@ export async function getModelCapabilities(
         }
 
     } catch (e) {
-        logError(e);
+        logError(e instanceof Error ? e : String(e));
         return undefined;
     }
 }
@@ -239,9 +196,14 @@ export async function getRuntimeCapabilities(
     target?: AiRuntimeTarget
 ): Promise<AiModelCapabilities> {
     const runtimeTarget = target ?? resolveAiRuntimeTarget(provider, "chat", model ?? getRuntimeModel(provider));
-    const result = await getModelCapabilities(provider, runtimeTarget.model, target?.purpose ?? "chat") ?? buildCapabilities({});
+    const targetPurpose = target?.purpose && target.purpose !== "memoryCompress" ? target.purpose : "chat";
+    const result = await getModelCapabilities(provider, runtimeTarget.model, targetPurpose) ?? 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;
 
@@ -322,23 +284,6 @@ export async function listProviderModels(provider: AiProvider): Promise<string[]
                 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

@@ -1,6 +1,7 @@
 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");
 
@@ -13,16 +14,16 @@ export type AiRequestQueueTarget = {
 type QueueEntry = {
     target: AiRequestQueueTarget;
     queueKey: string;
-    run: () => Promise<unknown>;
+    run: () => Promise<BoundaryValue>;
-    resolve: (value: unknown) => void;
+    resolve: (value: BoundaryValue) => void;
-    reject: (reason?: unknown) => void;
+    reject: (reason?: Error | string | BoundaryValue | null | undefined) => void;
     onPositionChange: (requestsBefore: number) => Promise<void> | void;
     signal?: AbortSignal;
     abortHandler?: () => void;
     started: boolean;
 };
 
-type EnqueueOptions<T> = {
+type EnqueueOptions<T extends BoundaryValue> = {
     signal?: AbortSignal;
     onPositionChange: (requestsBefore: number) => Promise<void> | void;
     run: () => Promise<T>;
@@ -32,7 +33,7 @@ class AiProviderRequestQueue {
     private readonly waiting = new Map<string, QueueEntry[]>();
     private readonly active = new Map<string, number>();
 
-    enqueue<T>(target: AiRequestQueueTarget, options: EnqueueOptions<T>): Promise<T> {
+    enqueue<T extends BoundaryValue>(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"));
@@ -160,8 +161,9 @@ 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) {
-            logger.error("entry.failed", {provider: entry.target.provider, model: entry.target.model, baseUrl: entry.target.baseUrl, error: e});
+            const error = e instanceof Error ? e : String(e);
-            entry.reject(e);
+            logger.error("entry.failed", {provider: entry.target.provider, model: entry.target.model, baseUrl: entry.target.baseUrl, error});
+            entry.reject(error);
         } finally {
             this.setActiveCount(entry.queueKey, this.activeCount(entry.queueKey) - 1);
             this.schedule(entry.target);
@@ -178,10 +180,10 @@ 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});
+                    logger.error("position_update.failed", {provider: target.provider, model: target.model, reason: result.reason instanceof Error ? result.reason : String(result.reason)});
                 }
             }
-        }).catch(error => logger.error("position_updates.failed", {provider: target.provider, model: target.model, error}));
+        }).catch(error => logger.error("position_updates.failed", {provider: target.provider, model: target.model, error: error instanceof Error ? error : String(error)}));
     }
 
     private deleteQueueIfIdle(queueKey: string, queue: QueueEntry[]): void {

src/ai/rag-artifact-payload.ts

@@ -0,0 +1,77 @@
+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

@@ -0,0 +1,100 @@
+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

@@ -0,0 +1,75 @@
+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

@@ -0,0 +1,117 @@
+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

@@ -0,0 +1,39 @@
+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

@@ -0,0 +1,19 @@
+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

@@ -2,19 +2,13 @@ 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 {
+import {createMistralClient, createOllamaClient, createOpenAiClient, resolveAiRuntimeTarget} from "./ai-runtime-target";
-    createGoogleGenAiClient,
-    createMistralClient,
-    createOllamaClient,
-    createOpenAiClient,
-    resolveAiRuntimeTarget
-} from "./ai-runtime-target";
 import {Environment} from "../common/environment";
 
 export type TranscribedSpeech = {
@@ -39,10 +33,6 @@ 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"));
@@ -53,9 +43,6 @@ 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;
@@ -78,7 +65,7 @@ export async function resolveSpeechToTextProviderForUser(
 
     if (preferredProvider) {
         if (!allowedProviders.includes(preferredProvider)) {
-            throw new Error(Environment.getProviderNotAvailableForAccessText(providerName(preferredProvider)));
+            throw new Error(Environment.getProviderNotAvailableForAccessText(providerDisplayName(preferredProvider)));
         }
 
         if (isSpeechToTextConfigured(preferredProvider)) {
@@ -86,7 +73,7 @@ export async function resolveSpeechToTextProviderForUser(
         }
 
         if (!allowFallback) {
-            throw new Error(Environment.getProviderSpeechToTextUnsupportedText(providerName(preferredProvider)));
+            throw new Error(Environment.getProviderSpeechToTextUnsupportedText(providerDisplayName(preferredProvider)));
         }
     }
 
@@ -112,8 +99,6 @@ 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:
@@ -177,37 +162,6 @@ 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");
 
@@ -239,20 +193,3 @@ 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

@@ -9,6 +9,8 @@ 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;
@@ -17,6 +19,33 @@ 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();
@@ -91,7 +120,113 @@ function cachePathFor(kind: StoredAttachmentKind, fileUniqueId: string | undefin
     return path.join(cacheDirFor(kind), `${base}${ext || ""}`);
 }
 
-async function downloadToCache(kind: StoredAttachmentKind, fileId: string, fileName: string, mimeType?: string, fileUniqueId?: string): Promise<StoredAttachment | null> {
+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> {
     const startedAt = Date.now();
     logger.debug("download.start", {kind, fileId, fileName, mimeType});
     const file = await bot.getFile({file_id: fileId});
@@ -117,7 +252,17 @@ async function downloadToCache(kind: StoredAttachmentKind, fileId: string, fileN
         logger.debug("download.saved", {kind, location, bytes: buffer.length, duration: logger.duration(startedAt)});
     });
 
-    return {kind, fileId, fileUniqueId, fileName: finalFileName, mimeType, cachePath: location};
+    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),
+    };
 }
 
 async function convertAudioToWav(input: string, output: string, noVideo = false): Promise<void> {
@@ -153,24 +298,29 @@ 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});
+                logger.error("audio.convert.failed", {input, output, error: e instanceof Error ? e : String(e)});
                 throw e;
             }
         });
     });
 }
 
-export async function cacheMessageAttachments(msg: Message): Promise<StoredAttachment[]> {
+export async function cacheMessageAttachmentsWithRejections(msg: Message): Promise<MessageAttachmentCacheResult> {
     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 file = await downloadToCache("image", size.file_id, `${size.file_unique_id || size.file_id}.jpg`, "image/jpeg", size.file_unique_id);
+            const fileName = `${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);
             }
+        }
 
         if (msg.document) {
             const doc = msg.document;
@@ -179,12 +329,19 @@ export async function cacheMessageAttachments(msg: Message): Promise<StoredAttac
                 : doc.mime_type?.startsWith("audio/")
                     ? "audio"
                     : "document";
-            const file = await downloadToCache(kind, doc.file_id, doc.file_name || `${doc.file_unique_id || doc.file_id}`, doc.mime_type, doc.file_unique_id);
+            const fileName = doc.file_name || `${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);
             }
+        }
 
         if (msg.voice) {
-            const file = await downloadToCache("audio", msg.voice.file_id, `${msg.voice.file_unique_id || msg.voice.file_id}.ogg`, msg.voice.mime_type || "audio/ogg", msg.voice.file_unique_id);
+            const fileName = `${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);
             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 {
@@ -192,8 +349,10 @@ export async function cacheMessageAttachments(msg: Message): Promise<StoredAttac
                     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);
+                    logError(e instanceof Error ? e : String(e));
                 }
             }
 
@@ -201,12 +360,19 @@ export async function cacheMessageAttachments(msg: Message): Promise<StoredAttac
         }
 
         if (msg.audio) {
-            const file = await downloadToCache("audio", msg.audio.file_id, msg.audio.file_name || `${msg.audio.file_unique_id || msg.audio.file_id}.mp3`, msg.audio.mime_type, msg.audio.file_unique_id);
+            const fileName = msg.audio.file_name || `${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);
             }
+        }
 
         if (msg.video_note) {
-            const file = await downloadToCache("video-note", msg.video_note.file_id, `${msg.video_note.file_unique_id || msg.video_note.file_id}.mp4`, "video/mp4", msg.video_note.file_unique_id);
+            const fileName = `${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);
             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 {
@@ -214,33 +380,61 @@ export async function cacheMessageAttachments(msg: Message): Promise<StoredAttac
                     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);
+                    logError(e instanceof Error ? e : String(e));
                 }
             }
 
             if (file) result.push(file);
         }
     } catch (e) {
-        logError(e);
+        logError(e instanceof Error ? e : String(e));
     }
 
-    logger.debug("message.cache.done", {chatId: msg.chat?.id, messageId: msg.message_id, attachments: result.length, duration: logger.duration(startedAt)});
+    logger.debug("message.cache.done", {
-    return result;
+        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;
 }
 
 export function attachmentsToDownloadedFiles(attachments: StoredAttachment[]): AiDownloadedFile[] {
     logger.trace("downloaded_files.build", {attachments: attachments.length});
     return attachments
         .filter(attachment => fs.existsSync(attachment.cachePath))
-        .map(attachment => ({
+        .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,
+            }];
+        });
 }
 
 export function cleanupDownloads(files: AiDownloadedFile[]): void {

src/ai/telegram-stream-message.ts

@@ -5,17 +5,22 @@ 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";
@@ -25,6 +30,23 @@ 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;
@@ -34,8 +56,11 @@ 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,
@@ -45,7 +70,9 @@ 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 {
@@ -74,18 +101,8 @@ export class TelegramStreamMessage {
         };
     }
 
-    private isMessageNotModified(error: unknown): boolean {
+    private isMessageNotModified(message: string): boolean {
-        const textToLookUp = "message is not modified";
+        return message.includes("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> {
@@ -105,7 +122,8 @@ export class TelegramStreamMessage {
                 }
             );
         } catch (e) {
-            if (!this.isMessageNotModified(e)) logError(e);
+            const message = e instanceof Error ? e.message : String(e);
+            if (!this.isMessageNotModified(message)) logError(e instanceof Error ? e : message);
         }
     }
 
@@ -166,7 +184,8 @@ export class TelegramStreamMessage {
                 this.startFlushTimer();
                 return this.waitMessage;
             } catch (e) {
-                if (this.isMessageNotModified(e)) {
+                const message = e instanceof Error ? e.message : String(e);
+                if (this.isMessageNotModified(message)) {
                     this.lastSent = rawText;
                     await this.updateKeyboard(this.keyboard());
                     await this.store();
@@ -174,7 +193,7 @@ export class TelegramStreamMessage {
                     return this.waitMessage;
                 }
 
-                logError(e);
+                logError(e instanceof Error ? e : message);
                 this.waitMessage = null;
                 this.mediaMode = false;
             }
@@ -220,6 +239,44 @@ 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));
     }
@@ -292,13 +349,14 @@ export class TelegramStreamMessage {
             }
             if (shouldRemoveKeyboard) await this.removeKeyboard();
             this.lastSent = next;
-        } catch (e: unknown) {
+        } catch (e) {
-            if (shouldRemoveKeyboard && this.isMessageNotModified(e)) {
+            const message = e instanceof Error ? e.message : String(e);
+            if (shouldRemoveKeyboard && this.isMessageNotModified(message)) {
                 await this.removeKeyboard();
                 this.lastSent = next;
                 return;
             }
-            if (!this.isMessageNotModified(e)) logError(e);
+            if (!this.isMessageNotModified(message)) logError(e instanceof Error ? e : message);
         }
     }
 
@@ -313,22 +371,27 @@ export class TelegramStreamMessage {
         await this.store();
     }
 
-    async showImage(image: Buffer): Promise<void> {
+    async showImage(image: Buffer, attachment?: StoredAttachment): Promise<void> {
-        return this.enqueueEdit(() => this.showImageUnsafe(image));
+        return this.enqueueEdit(() => this.showImageUnsafe(image, attachment));
     }
 
     async sendArtifact(file: TelegramArtifactFile): Promise<Message | null> {
         return this.enqueueEdit(() => this.sendArtifactUnsafe(file));
     }
 
-    private async showImageUnsafe(image: Buffer): Promise<void> {
+    private async showImageUnsafe(image: Buffer, attachment?: StoredAttachment): Promise<void> {
         if (this.cancelled) return;
         const next = this.visibleCaption();
+        const useDocument = this.sendImagesAsDocuments;
 
         if (!this.waitMessage) {
             if (this.stream) return;
 
-            this.waitMessage = await enqueueTelegramApiCall(
+            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,
@@ -342,17 +405,29 @@ export class TelegramStreamMessage {
                             chatType: this.sourceMessage.chat.type,
                         }
                     );
+            } finally {
+                if (upload) this.destroyUpload(upload);
+            }
             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: {
+                    media: useDocument
+                        ? {
+                            type: "document",
+                            media: upload!,
+                            caption: prepareTelegramMarkdownV2(next, {mode: "final"}),
+                            parse_mode: "MarkdownV2",
+                        }
+                        : {
                             type: "photo",
                             media: image,
                             caption: prepareTelegramMarkdownV2(next, {mode: "final"}),
@@ -369,19 +444,50 @@ export class TelegramStreamMessage {
             if (result && result !== true) this.waitMessage = result;
             this.mediaMode = true;
             this.lastSent = next;
-        } catch (e: unknown) {
+            await this.storeMediaMessage(this.waitMessage, attachment);
+        } catch (e) {
             const message = e instanceof Error ? e.message : String(e);
-            if (!message.includes("message is not modified")) logError(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);
+        }
+    }
+
+    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 > TELEGRAM_FILE_LIMIT_BYTES) {
+        if (file.sizeBytes > PIPELINE_ATTACHMENT_LIMIT_BYTES) {
             throw new Error(Environment.getTelegramFileTooLargeText(
                 file.fileName,
-                TELEGRAM_FILE_LIMIT_BYTES / 1024 / 1024,
+                PIPELINE_ATTACHMENT_LIMIT_BYTES / 1024 / 1024,
             ));
         }
 
@@ -424,7 +530,7 @@ export class TelegramStreamMessage {
                     }
                 );
             } catch (e) {
-                logError(e);
+                logError(e instanceof Error ? e : String(e));
                 sent = await this.sendArtifactAsDocument(file, caption);
             }
         } else {
@@ -432,15 +538,37 @@ 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,
@@ -454,6 +582,23 @@ 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 () => {
@@ -487,6 +632,9 @@ export class TelegramStreamMessage {
             fileName: file.fileName,
             mimeType: file.mimeType,
             cachePath: file.path,
+            sizeBytes: file.sizeBytes,
+            scope: "bot_output",
+            artifactKind: "generated_file",
         };
 
         const stored: StoredMessage = {
@@ -502,6 +650,44 @@ 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;
@@ -523,7 +709,7 @@ export class TelegramStreamMessage {
         await this.store();
     }
 
-    async fail(error: unknown): Promise<void> {
+    async fail(error: Error | string | object | null | undefined): Promise<void> {
         if (this.timer) clearInterval(this.timer);
         this.timer = null;
         this.status = "";
@@ -536,7 +722,7 @@ export class TelegramStreamMessage {
         try {
             await MessageStore.put({...this.waitMessage, text: this.visibleText()} as Message);
         } catch (e) {
-            logError(e);
+            logError(e instanceof Error ? e : String(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 {createGoogleGenAiClient, createMistralClient, createOpenAiClient, resolveAiRuntimeTarget} from "./ai-runtime-target";
+import {createMistralClient, createOpenAiClient, resolveAiRuntimeTarget} from "./ai-runtime-target";
+import {PIPELINE_ATTACHMENT_LIMIT_BYTES} from "./user-request-pipeline";
 
 const MAX_TTS_TEXT_CHARS = 4096;
-const TELEGRAM_FILE_LIMIT_BYTES = 50 * 1024 * 1024;
 
 export type TextToSpeechFormat = "mp3" | "wav" | "flac" | "opus" | "aac" | "pcm";
 
@@ -54,10 +54,6 @@ 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) {
@@ -76,9 +72,6 @@ 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;
@@ -98,11 +91,11 @@ export async function resolveTextToSpeechProviderForUser(
 
     if (explicitProvider) {
         if (!allowedProviders.includes(explicitProvider)) {
-            throw new Error(Environment.getProviderNotAvailableForAccessText(providerName(explicitProvider)));
+            throw new Error(Environment.getProviderNotAvailableForAccessText(providerDisplayName(explicitProvider)));
         }
 
         if (!isTextToSpeechConfigured(explicitProvider)) {
-            throw new Error(Environment.getProviderTextToSpeechUnsupportedText(providerName(explicitProvider)));
+            throw new Error(Environment.getProviderTextToSpeechUnsupportedText(providerDisplayName(explicitProvider)));
         }
 
         return {provider: explicitProvider, fallback: false};
@@ -127,8 +120,6 @@ 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:
@@ -171,7 +162,7 @@ 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 unknown as {audioData?: string; audio_data?: string};
+    const response = await mistralAi.audio.speech.complete(request) as {audioData?: string; audio_data?: string};
     const audioData = response?.audioData ?? response?.audio_data;
     if (typeof audioData !== "string" || !audioData.trim()) {
         throw new Error(Environment.mistralTtsNoAudioDataText);
@@ -189,130 +180,6 @@ 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});
 
@@ -346,11 +213,11 @@ function destroyUpload(upload: FileOptions): void {
 }
 
 export async function sendSynthesizedSpeech(sourceMessage: Message, speech: SynthesizedSpeech): Promise<Message> {
-    if (speech.sizeBytes > TELEGRAM_FILE_LIMIT_BYTES) {
+    if (speech.sizeBytes > PIPELINE_ATTACHMENT_LIMIT_BYTES) {
         throw new Error(Environment.speechFileTooLargeText);
     }
 
-    const caption = Environment.getTextToSpeechCaption(providerName(speech.provider), speech.model, speech.voice);
+    const caption = Environment.getTextToSpeechCaption(providerDisplayName(speech.provider), speech.model, speech.voice);
 
     await enqueueTelegramApiCall(
         () => bot.sendChatAction({
@@ -374,13 +241,13 @@ export async function sendSynthesizedSpeech(sourceMessage: Message, speech: Synt
                             reply_parameters: {message_id: sourceMessage.message_id},
                         });
                     } finally {
-                        destroyUpload(upload);
+                        // destroyUpload(upload);
                     }
                 },
                 {method: "sendVoice", chatId: sourceMessage.chat.id, chatType: sourceMessage.chat.type}
             );
     } catch (e) {
-            logError(e);
+        logError(e instanceof Error ? e : String(e));
         sent = await sendSpeechDocument(sourceMessage, speech, caption);
     }
     } else {
@@ -391,6 +258,16 @@ 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 () => {
@@ -419,6 +296,15 @@ 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

@@ -0,0 +1,28 @@
+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

@@ -0,0 +1,39 @@
+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

@@ -0,0 +1,38 @@
+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

@@ -0,0 +1,22 @@
+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

@@ -0,0 +1,56 @@
+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

@@ -1,36 +1,42 @@
 import {AiTool} from "./tool-types";
-import {AiProvider} from "../model/ai-provider";
+import {AiProvider} from "../model/ai-provider.js";
-import {getTools} from "./tools/registry";
+import {getTools} from "./tools/registry.js";
-import {WEB_SEARCH_TOOL_NAME} from "./tools/brave-search";
+import {WEB_SEARCH_TOOL_NAME} from "./tools/web-search.js";
-import {PYTHON_INTERPRETER_TOOL_NAME} from "./tools/python-interpretator";
+import {PYTHON_INTERPRETER_TOOL_NAME} from "./tools/python-interpretator.js";
+import {toolSchemaNames} from "./tool-schema-utils.js";
 
-export type AiProviderName = "ollama" | "openai" | "gemini" | "mistral";
+export type AiProviderName = "ollama" | "openai" | "mistral";
 
-export function getOllamaTools(): AiTool[] {
+export function getOllamaTools(forCreator?: boolean): AiTool[] {
-    return getTools();
+    return getTools(forCreator);
 }
 
 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(): AiTool[] {
+export function getOpenAITools(forCreator?: boolean): AiTool[] {
-    return getTools().filter(allowedOpenAiTool).map(tool => ({
+    return getTools(forCreator).filter(allowedOpenAiTool).map(tool => ({
         type: "function",
         function: tool.function,
     }));
 }
 
+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?: unknown;
+    parameters?: object;
     strict: false;
 };
 
@@ -43,8 +49,8 @@ export type OpenAiCodeInterpreterTool = {
     } | string;
 };
 
-export function getOpenAIResponsesTools(): OpenAiResponseTool[] {
+export function getOpenAIResponsesTools(forCreator?: boolean): OpenAiResponseTool[] {
-    return getTools().filter(allowedOpenAiTool).map(tool => ({
+    return getOpenAITools(forCreator).map(tool => ({
         type: "function",
         name: tool.function.name,
         description: tool.function.description,
@@ -62,40 +68,37 @@ export function getOpenAICodeInterpreterTool(): OpenAiCodeInterpreterTool {
     };
 }
 
-export function getMistralTools(): AiTool[] {
+export function getMistralTools(forCreator?: boolean): AiTool[] {
-    return getTools().map(tool => ({
+    return getTools(forCreator).map(tool => ({
         type: "function",
         function: tool.function,
     }));
 }
 
-export type GeminiTool = {
+export function getProviderTools(provider: AiProvider, forCreator?: boolean): AiTool[] {
-    functionDeclarations: Array<{
-        name: string;
-        description?: string;
-        parametersJsonSchema?: unknown;
-    }>;
-}
-
-export function getGeminiTools(): GeminiTool[] {
-    const functionDeclarations = getTools().map(tool => ({
-        name: tool.function.name,
-        description: tool.function.description,
-        parametersJsonSchema: tool.function.parameters,
-    }));
-
-    return functionDeclarations.length ? [{functionDeclarations}] : [];
-}
-
-export function getProviderTools(provider: AiProvider): AiTool[] {
     switch (provider) {
         case AiProvider.OLLAMA:
-            return getOllamaTools();
+            return getOllamaTools(forCreator);
-        case AiProvider.GEMINI:
-            return getTools();
         case AiProvider.MISTRAL:
-            return getMistralTools();
+            return getMistralTools(forCreator);
         case AiProvider.OPENAI:
-            return getOpenAITools();
+            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

@@ -0,0 +1,146 @@
+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

@@ -0,0 +1,56 @@
+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

@@ -0,0 +1,669 @@
+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

@@ -0,0 +1,116 @@
+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

@@ -0,0 +1,28 @@
+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

@@ -0,0 +1,33 @@
+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

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

src/ai/tools/create-note.ts

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

src/ai/tools/datetime.ts

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

src/ai/tools/file-system.ts

@@ -1,852 +0,0 @@
-import fs from "node:fs";
-import path from "node:path";
-import {Environment} from "../../common/environment";
-import {AiTool} from "../tool-types";
-import {MAX_COPY_ENTRIES, MAX_COPY_TOTAL_BYTES, MAX_DIRECTORY_ENTRIES, MAX_FILE_READ_BYTES, MAX_FILE_WRITE_BYTES} from "./limits";
-import {asBoolean, asNonEmptyString, asPositiveInt, asString} from "./utils";
-
-export const readFileTool = {
-    type: "function",
-    function: {
-        name: "read_file",
-        description:
-            "Read a UTF-8 text file inside the hardcoded root directory. Use only relative paths. Going up with ../ and absolute paths are forbidden.",
-        parameters: {
-            type: "object",
-            properties: {
-                path: {
-                    type: "string",
-                    description: "Relative file path inside the root directory, for example notes/task.txt.",
-                },
-                maxBytes: {
-                    type: "number",
-                    description: `Optional max bytes to read. Maximum allowed value is ${MAX_FILE_READ_BYTES}.`,
-                },
-            },
-            required: ["path"],
-        },
-    },
-} satisfies AiTool;
-
-export const listDirectoryTool = {
-    type: "function",
-    function: {
-        name: "list_directory",
-        description:
-            "List files and directories inside the hardcoded root directory. Use only relative paths. Going up with ../ and absolute paths are forbidden.",
-        parameters: {
-            type: "object",
-            properties: {
-                path: {
-                    type: "string",
-                    description: "Relative directory path inside the root directory. Use . for root.",
-                },
-            },
-            required: [],
-        },
-    },
-} satisfies AiTool;
-
-export const createFileTool = {
-    type: "function",
-    function: {
-        name: "create_file",
-        description:
-            "Create a UTF-8 text file inside the hardcoded root directory. Use only relative paths. Going up with ../ and absolute paths are forbidden.",
-        parameters: {
-            type: "object",
-            properties: {
-                path: {
-                    type: "string",
-                    description: "Relative file path inside the root directory.",
-                },
-                content: {
-                    type: "string",
-                    description: "File content.",
-                },
-                overwrite: {
-                    type: "boolean",
-                    description: "Whether to overwrite the file if it already exists. Default is false.",
-                },
-                createParents: {
-                    type: "boolean",
-                    description: "Whether to create parent directories automatically. Default is true.",
-                },
-            },
-            required: ["path"],
-        },
-    },
-} satisfies AiTool;
-
-export const createDirectoryTool = {
-    type: "function",
-    function: {
-        name: "create_directory",
-        description:
-            "Create a directory inside the hardcoded root directory. Use only relative paths. Going up with ../ and absolute paths are forbidden.",
-        parameters: {
-            type: "object",
-            properties: {
-                path: {
-                    type: "string",
-                    description: "Relative directory path inside the root directory.",
-                },
-                recursive: {
-                    type: "boolean",
-                    description: "Whether to create parent directories automatically. Default is true.",
-                },
-            },
-            required: ["path"],
-        },
-    },
-} satisfies AiTool;
-
-export const copyPathTool = {
-    type: "function",
-    function: {
-        name: "copy_path",
-        description:
-            "Copy a file or directory inside the hardcoded root directory. Use only relative paths. Going up with ../ and absolute paths are forbidden. Directory copy requires recursive=true. Symlinks are forbidden.",
-        parameters: {
-            type: "object",
-            properties: {
-                sourcePath: {
-                    type: "string",
-                    description: "Relative source file or directory path inside the root directory.",
-                },
-                targetPath: {
-                    type: "string",
-                    description: "Relative target file or directory path inside the root directory.",
-                },
-                recursive: {
-                    type: "boolean",
-                    description: "Required for copying directories. Default is false.",
-                },
-                overwrite: {
-                    type: "boolean",
-                    description: "Whether to overwrite existing files. Directory merge is allowed, but existing directories are not deleted. Default is false.",
-                },
-                createParents: {
-                    type: "boolean",
-                    description: "Whether to create target parent directories automatically. Default is true.",
-                },
-            },
-            required: ["sourcePath", "targetPath"],
-        },
-    },
-} satisfies AiTool;
-
-export const updateFileTool = {
-    type: "function",
-    function: {
-        name: "update_file",
-        description:
-            "Update a UTF-8 text file inside the hardcoded root directory. Supports replace, append and prepend. Use only relative paths. Going up with ../ and absolute paths are forbidden.",
-        parameters: {
-            type: "object",
-            properties: {
-                path: {
-                    type: "string",
-                    description: "Relative file path inside the root directory.",
-                },
-                content: {
-                    type: "string",
-                    description: "Content to write.",
-                },
-                mode: {
-                    type: "string",
-                    enum: ["replace", "append", "prepend"],
-                    description: "Update mode. Default is replace.",
-                },
-                createIfMissing: {
-                    type: "boolean",
-                    description: "Whether to create the file if it does not exist. Default is false.",
-                },
-            },
-            required: ["path", "content"],
-        },
-    },
-} satisfies AiTool;
-
-export const renamePathTool = {
-    type: "function",
-    function: {
-        name: "rename_path",
-        description:
-            "Rename or move a file/directory inside the hardcoded root directory. This is the main directory modification tool. Use only relative paths. Going up with ../ and absolute paths are forbidden.",
-        parameters: {
-            type: "object",
-            properties: {
-                sourcePath: {
-                    type: "string",
-                    description: "Relative source path inside the root directory.",
-                },
-                targetPath: {
-                    type: "string",
-                    description: "Relative target path inside the root directory.",
-                },
-                overwrite: {
-                    type: "boolean",
-                    description: "Whether to overwrite an existing target file. Directory overwrite is not supported. Default is false.",
-                },
-                createParents: {
-                    type: "boolean",
-                    description: "Whether to create target parent directories automatically. Default is false.",
-                },
-            },
-            required: ["sourcePath", "targetPath"],
-        },
-    },
-} satisfies AiTool;
-
-export const deletePathTool = {
-    type: "function",
-    function: {
-        name: "delete_path",
-        description:
-            "Delete a file or directory inside the hardcoded root directory. Use only relative paths. Going up with ../ and absolute paths are forbidden. Recursive deletion requires recursive=true.",
-        parameters: {
-            type: "object",
-            properties: {
-                path: {
-                    type: "string",
-                    description: "Relative file or directory path inside the root directory.",
-                },
-                recursive: {
-                    type: "boolean",
-                    description: "Whether to delete non-empty directories recursively. Default is false.",
-                },
-            },
-            required: ["path"],
-        },
-    },
-} satisfies AiTool;
-
-export const fileToolsToolPrompt = [
-    "Filesystem tool rules:",
-    "- You have access to filesystem tools working only inside the hardcoded root directory.",
-    "- All filesystem paths must be relative to the root directory.",
-    "- You may go into child directories.",
-    "- You must never go up to parent directories.",
-    "- Do not use ../ paths.",
-    "- Do not use absolute paths.",
-    "- Do not try to access symlinks.",
-    "- Use read_file for reading files.",
-    "- Use list_directory for reading directories.",
-    "- Use create_file for creating files.",
-    "- Use create_directory for creating directories.",
-    "- Use update_file for replacing, appending or prepending file content.",
-    "- Use rename_path for renaming or moving files/directories inside the root.",
-    "- Use delete_path for deleting files/directories inside the root.",
-    ""
-].join("\n");
-
-const requireFileToolsRootDir = () => <string>Environment.FILE_TOOLS_ROOT_DIR;
-
-async function ensureFileToolsRootExists(): Promise<void> {
-    await fs.promises.mkdir(requireFileToolsRootDir(), {recursive: true});
-
-    const stat = await fs.promises.stat(requireFileToolsRootDir());
-
-    if (!stat.isDirectory()) {
-        throw new Error(`File tools root is not a directory: ${requireFileToolsRootDir()}`);
-    }
-}
-
-function resolveSafeToolPath(inputPath: unknown, fallback = "."): {
-    absolutePath: string;
-    relativePath: string;
-} {
-    const rawPath = asNonEmptyString(inputPath) ?? fallback;
-
-    if (rawPath.includes("\0")) {
-        throw new Error("Path must not contain null bytes.");
-    }
-
-    if (
-        path.isAbsolute(rawPath) ||
-        path.win32.isAbsolute(rawPath) ||
-        path.posix.isAbsolute(rawPath)
-    ) {
-        throw new Error("Absolute paths are not allowed. Use only relative paths inside the root directory.");
-    }
-
-    const normalizedInputPath = rawPath.replace(/[\\/]+/g, path.sep);
-
-    const absolutePath = path.resolve(requireFileToolsRootDir(), normalizedInputPath);
-    const relativePath = path.relative(requireFileToolsRootDir(), absolutePath);
-
-    if (
-        relativePath.startsWith("..") ||
-        path.isAbsolute(relativePath)
-    ) {
-        throw new Error("Path escapes the root directory. Going up is not allowed.");
-    }
-
-    return {
-        absolutePath,
-        relativePath: relativePath || ".",
-    };
-}
-
-function assertTargetIsNotInsideSource(sourceAbsolutePath: string, targetAbsolutePath: string): void {
-    const relative = path.relative(sourceAbsolutePath, targetAbsolutePath);
-
-    if (
-        relative === "" ||
-        (!relative.startsWith("..") && !path.isAbsolute(relative))
-    ) {
-        throw new Error("Cannot copy a directory into itself.");
-    }
-}
-
-async function assertNoSymlinkInPath(
-    absolutePath: string,
-    options?: {
-        allowMissingTail?: boolean;
-    }
-): Promise<void> {
-    await ensureFileToolsRootExists();
-
-    const relativePath = path.relative(requireFileToolsRootDir(), absolutePath);
-
-    if (!relativePath || relativePath === ".") {
-        return;
-    }
-
-    const parts = relativePath.split(path.sep).filter(Boolean);
-
-    let currentPath = requireFileToolsRootDir();
-
-    for (const part of parts) {
-        currentPath = path.join(currentPath, part);
-
-        try {
-            const stat = await fs.promises.lstat(currentPath);
-
-            if (stat.isSymbolicLink()) {
-                throw new Error("Symlinks are not allowed in file tool paths.");
-            }
-        } catch (e: unknown) {
-            if ((e as NodeJS.ErrnoException).code === "ENOENT" && options?.allowMissingTail) {
-                return;
-            }
-
-            throw e;
-        }
-    }
-}
-
-async function pathExists(absolutePath: string): Promise<boolean> {
-    try {
-        await fs.promises.lstat(absolutePath);
-        return true;
-    } catch (e: unknown) {
-        if ((e as NodeJS.ErrnoException).code === "ENOENT") return false;
-        throw e;
-    }
-}
-
-function assertNotRoot(relativePath: string): void {
-    if (relativePath === ".") {
-        throw new Error("Operation on the root directory itself is not allowed.");
-    }
-}
-
-function getEntryType(stat: fs.Stats): "file" | "directory" | "symlink" | "other" {
-    if (stat.isSymbolicLink()) return "symlink";
-    if (stat.isFile()) return "file";
-    if (stat.isDirectory()) return "directory";
-    return "other";
-}
-
-export async function readFile(args?: Record<string, unknown>) {
-    const {absolutePath, relativePath} = resolveSafeToolPath(args?.path);
-
-    await assertNoSymlinkInPath(absolutePath);
-
-    const stat = await fs.promises.lstat(absolutePath);
-
-    if (!stat.isFile()) {
-        throw new Error(`Path is not a file: ${relativePath}`);
-    }
-
-    const maxBytes = asPositiveInt(args?.maxBytes, MAX_FILE_READ_BYTES, MAX_FILE_READ_BYTES);
-
-    if (stat.size > maxBytes) {
-        throw new Error(`File is too large: ${stat.size} bytes. Max allowed: ${maxBytes} bytes.`);
-    }
-
-    const buffer = await fs.promises.readFile(absolutePath);
-
-    if (buffer.includes(0)) {
-        throw new Error("Binary files are not supported.");
-    }
-
-    return {
-        ok: true,
-        path: relativePath,
-        sizeBytes: stat.size,
-        content: buffer.toString("utf8"),
-    };
-}
-
-export async function listDirectory(args?: Record<string, unknown>) {
-    const {absolutePath, relativePath} = resolveSafeToolPath(args?.path, ".");
-
-    await assertNoSymlinkInPath(absolutePath);
-
-    const stat = await fs.promises.lstat(absolutePath);
-
-    if (!stat.isDirectory()) {
-        throw new Error(`Path is not a directory: ${relativePath}`);
-    }
-
-    const dirEntries = await fs.promises.readdir(absolutePath, {
-        withFileTypes: true,
-    });
-
-    const limitedEntries = dirEntries.slice(0, MAX_DIRECTORY_ENTRIES);
-
-    const entries = await Promise.all(limitedEntries.map(async entry => {
-        const entryAbsolutePath = path.join(absolutePath, entry.name);
-        const entryRelativePath = relativePath === "."
-            ? entry.name
-            : path.join(relativePath, entry.name);
-
-        const entryStat = await fs.promises.lstat(entryAbsolutePath);
-
-        return {
-            name: entry.name,
-            path: entryRelativePath,
-            type: getEntryType(entryStat),
-            sizeBytes: entryStat.isFile() ? entryStat.size : null,
-            modifiedAt: entryStat.mtime.toISOString(),
-        };
-    }));
-
-    return {
-        ok: true,
-        path: relativePath,
-        entries,
-        totalEntries: dirEntries.length,
-        returnedEntries: entries.length,
-        truncated: dirEntries.length > entries.length,
-    };
-}
-
-export async function createFile(args?: Record<string, unknown>) {
-    const {absolutePath, relativePath} = resolveSafeToolPath(args?.path);
-
-    assertNotRoot(relativePath);
-
-    const content = asString(args?.content, "");
-    const overwrite = asBoolean(args?.overwrite, false);
-    const createParents = asBoolean(args?.createParents, true);
-
-    const contentSizeBytes = Buffer.byteLength(content, "utf8");
-
-    if (contentSizeBytes > MAX_FILE_WRITE_BYTES) {
-        throw new Error(`Content is too large: ${contentSizeBytes} bytes. Max allowed: ${MAX_FILE_WRITE_BYTES} bytes.`);
-    }
-
-    const parentPath = path.dirname(absolutePath);
-
-    if (createParents) {
-        await assertNoSymlinkInPath(parentPath, {allowMissingTail: true});
-        await fs.promises.mkdir(parentPath, {recursive: true});
-    } else {
-        await assertNoSymlinkInPath(parentPath);
-    }
-
-    if (await pathExists(absolutePath)) {
-        const stat = await fs.promises.lstat(absolutePath);
-
-        if (stat.isSymbolicLink()) {
-            throw new Error("Symlink targets are not allowed.");
-        }
-
-        if (stat.isDirectory()) {
-            throw new Error(`Path is a directory, not a file: ${relativePath}`);
-        }
-
-        if (!overwrite) {
-            throw new Error(`File already exists: ${relativePath}`);
-        }
-    }
-
-    await fs.promises.writeFile(absolutePath, content, {
-        encoding: "utf8",
-        flag: overwrite ? "w" : "wx",
-    });
-
-    return {
-        ok: true,
-        path: relativePath,
-        sizeBytes: contentSizeBytes,
-        overwritten: overwrite,
-    };
-}
-
-type CopyPathStats = {
-    entries: number;
-    totalBytes: number;
-};
-
-async function copyPathRecursive(params: {
-    sourceAbsolutePath: string;
-    targetAbsolutePath: string;
-    overwrite: boolean;
-    stats: CopyPathStats;
-}): Promise<void> {
-    const {
-        sourceAbsolutePath,
-        targetAbsolutePath,
-        overwrite,
-        stats,
-    } = params;
-
-    if (stats.entries >= MAX_COPY_ENTRIES) {
-        throw new Error(`Too many entries to copy. Max allowed: ${MAX_COPY_ENTRIES}.`);
-    }
-
-    stats.entries++;
-
-    const sourceStat = await fs.promises.lstat(sourceAbsolutePath);
-
-    if (sourceStat.isSymbolicLink()) {
-        throw new Error("Symlinks are not allowed in copied paths.");
-    }
-
-    if (sourceStat.isFile()) {
-        stats.totalBytes += sourceStat.size;
-
-        if (stats.totalBytes > MAX_COPY_TOTAL_BYTES) {
-            throw new Error(`Copied data is too large. Max allowed: ${MAX_COPY_TOTAL_BYTES} bytes.`);
-        }
-
-        if (await pathExists(targetAbsolutePath)) {
-            const targetStat = await fs.promises.lstat(targetAbsolutePath);
-
-            if (targetStat.isSymbolicLink()) {
-                throw new Error("Symlink targets are not allowed.");
-            }
-
-            if (targetStat.isDirectory()) {
-                throw new Error("Cannot overwrite a directory with a file.");
-            }
-
-            if (!overwrite) {
-                throw new Error(`Target file already exists: ${path.relative(requireFileToolsRootDir(), targetAbsolutePath)}`);
-            }
-        }
-
-        await fs.promises.copyFile(
-            sourceAbsolutePath,
-            targetAbsolutePath,
-            overwrite ? 0 : fs.constants.COPYFILE_EXCL,
-        );
-
-        return;
-    }
-
-    if (sourceStat.isDirectory()) {
-        if (await pathExists(targetAbsolutePath)) {
-            const targetStat = await fs.promises.lstat(targetAbsolutePath);
-
-            if (targetStat.isSymbolicLink()) {
-                throw new Error("Symlink targets are not allowed.");
-            }
-
-            if (!targetStat.isDirectory()) {
-                throw new Error("Cannot overwrite a file with a directory.");
-            }
-        } else {
-            await fs.promises.mkdir(targetAbsolutePath);
-        }
-
-        const entries = await fs.promises.readdir(sourceAbsolutePath);
-
-        for (const entry of entries) {
-            const childSourcePath = path.join(sourceAbsolutePath, entry);
-            const childTargetPath = path.join(targetAbsolutePath, entry);
-
-            await copyPathRecursive({
-                sourceAbsolutePath: childSourcePath,
-                targetAbsolutePath: childTargetPath,
-                overwrite,
-                stats,
-            });
-        }
-
-        return;
-    }
-
-    throw new Error("Only files and directories can be copied.");
-}
-
-export async function copyPath(args?: Record<string, unknown>) {
-    const source = resolveSafeToolPath(args?.sourcePath);
-    const target = resolveSafeToolPath(args?.targetPath);
-
-    assertNotRoot(source.relativePath);
-    assertNotRoot(target.relativePath);
-
-    await assertNoSymlinkInPath(source.absolutePath);
-
-    const sourceStat = await fs.promises.lstat(source.absolutePath);
-
-    if (sourceStat.isSymbolicLink()) {
-        throw new Error("Symlink sources are not allowed.");
-    }
-
-    const recursive = asBoolean(args?.recursive, false);
-    const overwrite = asBoolean(args?.overwrite, false);
-    const createParents = asBoolean(args?.createParents, true);
-
-    if (sourceStat.isDirectory() && !recursive) {
-        throw new Error("Source is a directory. Set recursive=true to copy directories.");
-    }
-
-    if (sourceStat.isDirectory()) {
-        assertTargetIsNotInsideSource(source.absolutePath, target.absolutePath);
-    }
-
-    const targetParentPath = path.dirname(target.absolutePath);
-
-    if (createParents) {
-        await assertNoSymlinkInPath(targetParentPath, {
-            allowMissingTail: true,
-        });
-
-        await fs.promises.mkdir(targetParentPath, {
-            recursive: true,
-        });
-
-        await assertNoSymlinkInPath(targetParentPath);
-    } else {
-        await assertNoSymlinkInPath(targetParentPath);
-    }
-
-    const stats: CopyPathStats = {
-        entries: 0,
-        totalBytes: 0,
-    };
-
-    await copyPathRecursive({
-        sourceAbsolutePath: source.absolutePath,
-        targetAbsolutePath: target.absolutePath,
-        overwrite,
-        stats,
-    });
-
-    return {
-        ok: true,
-        from: source.relativePath,
-        to: target.relativePath,
-        recursive,
-        overwrite,
-        entriesCopied: stats.entries,
-        bytesCopied: stats.totalBytes,
-    };
-}
-
-export async function createDirectory(args?: Record<string, unknown>) {
-    const {absolutePath, relativePath} = resolveSafeToolPath(args?.path);
-
-    const recursive = asBoolean(args?.recursive, true);
-
-    await assertNoSymlinkInPath(absolutePath, {
-        allowMissingTail: true,
-    });
-
-    await fs.promises.mkdir(absolutePath, {
-        recursive,
-    });
-
-    return {
-        ok: true,
-        path: relativePath,
-        recursive,
-    };
-}
-
-export async function updateFile(args?: Record<string, unknown>) {
-    const {absolutePath, relativePath} = resolveSafeToolPath(args?.path);
-
-    assertNotRoot(relativePath);
-
-    const content = asString(args?.content, "");
-    const mode = (asNonEmptyString(args?.mode) ?? "replace").toLowerCase();
-    const createIfMissing = asBoolean(args?.createIfMissing, false);
-
-    if (!["replace", "append", "prepend"].includes(mode)) {
-        throw new Error(`Unsupported update mode: ${mode}`);
-    }
-
-    const contentSizeBytes = Buffer.byteLength(content, "utf8");
-
-    if (contentSizeBytes > MAX_FILE_WRITE_BYTES) {
-        throw new Error(`Content is too large: ${contentSizeBytes} bytes. Max allowed: ${MAX_FILE_WRITE_BYTES} bytes.`);
-    }
-
-    const parentPath = path.dirname(absolutePath);
-
-    await assertNoSymlinkInPath(parentPath);
-
-    const exists = await pathExists(absolutePath);
-
-    if (!exists && !createIfMissing) {
-        throw new Error(`File does not exist: ${relativePath}`);
-    }
-
-    if (exists) {
-        await assertNoSymlinkInPath(absolutePath);
-
-        const stat = await fs.promises.lstat(absolutePath);
-
-        if (!stat.isFile()) {
-            throw new Error(`Path is not a file: ${relativePath}`);
-        }
-    }
-
-    if (mode === "replace") {
-        await fs.promises.writeFile(absolutePath, content, {
-            encoding: "utf8",
-            flag: "w",
-        });
-    } else if (mode === "append") {
-        await fs.promises.appendFile(absolutePath, content, {
-            encoding: "utf8",
-        });
-    } else {
-        const oldContent = exists
-            ? await fs.promises.readFile(absolutePath, "utf8")
-            : "";
-
-        const resultSizeBytes = Buffer.byteLength(content + oldContent, "utf8");
-
-        if (resultSizeBytes > MAX_FILE_WRITE_BYTES) {
-            throw new Error(`Result file content is too large: ${resultSizeBytes} bytes. Max allowed: ${MAX_FILE_WRITE_BYTES} bytes.`);
-        }
-
-        await fs.promises.writeFile(absolutePath, content + oldContent, {
-            encoding: "utf8",
-            flag: "w",
-        });
-    }
-
-    const newStat = await fs.promises.stat(absolutePath);
-
-    return {
-        ok: true,
-        path: relativePath,
-        mode,
-        sizeBytes: newStat.size,
-        created: !exists,
-    };
-}
-
-export async function renamePath(args?: Record<string, unknown>) {
-    const source = resolveSafeToolPath(args?.sourcePath);
-    const target = resolveSafeToolPath(args?.targetPath);
-
-    assertNotRoot(source.relativePath);
-    assertNotRoot(target.relativePath);
-
-    await assertNoSymlinkInPath(source.absolutePath);
-
-    const sourceStat = await fs.promises.lstat(source.absolutePath);
-
-    if (sourceStat.isSymbolicLink()) {
-        throw new Error("Symlink targets are not allowed.");
-    }
-
-    const relativeTargetInsideSource = path.relative(source.absolutePath, target.absolutePath);
-
-    if (
-        relativeTargetInsideSource === "" ||
-        (!relativeTargetInsideSource.startsWith("..") && !path.isAbsolute(relativeTargetInsideSource))
-    ) {
-        throw new Error("Cannot move a directory into itself.");
-    }
-
-    const overwrite = asBoolean(args?.overwrite, false);
-    const createParents = asBoolean(args?.createParents, false);
-
-    const targetParentPath = path.dirname(target.absolutePath);
-
-    if (createParents) {
-        await assertNoSymlinkInPath(targetParentPath, {allowMissingTail: true});
-        await fs.promises.mkdir(targetParentPath, {recursive: true});
-    } else {
-        await assertNoSymlinkInPath(targetParentPath);
-    }
-
-    if (await pathExists(target.absolutePath)) {
-        const targetStat = await fs.promises.lstat(target.absolutePath);
-
-        if (targetStat.isSymbolicLink()) {
-            throw new Error("Symlink targets are not allowed.");
-        }
-
-        if (!overwrite) {
-            throw new Error(`Target already exists: ${target.relativePath}`);
-        }
-
-        if (sourceStat.isDirectory() || targetStat.isDirectory()) {
-            throw new Error("Overwrite for directories is not supported.");
-        }
-
-        await fs.promises.rm(target.absolutePath, {
-            force: false,
-        });
-    }
-
-    await fs.promises.rename(source.absolutePath, target.absolutePath);
-
-    return {
-        ok: true,
-        from: source.relativePath,
-        to: target.relativePath,
-        overwrite,
-    };
-}
-
-export async function deletePath(args?: Record<string, unknown>) {
-    const {absolutePath, relativePath} = resolveSafeToolPath(args?.path);
-
-    assertNotRoot(relativePath);
-
-    await assertNoSymlinkInPath(absolutePath);
-
-    const stat = await fs.promises.lstat(absolutePath);
-
-    if (stat.isSymbolicLink()) {
-        throw new Error("Symlink targets are not allowed.");
-    }
-
-    const recursive = asBoolean(args?.recursive, false);
-
-    if (stat.isDirectory()) {
-        if (recursive) {
-            await fs.promises.rm(absolutePath, {
-                recursive: true,
-                force: false,
-            });
-        } else {
-            await fs.promises.rmdir(absolutePath);
-        }
-    } else {
-        await fs.promises.rm(absolutePath, {
-            force: false,
-        });
-    }
-
-    return {
-        ok: true,
-        path: relativePath,
-        recursive,
-        deleted: true,
-    };
-}

src/ai/tools/limits.ts

@@ -3,3 +3,15 @@ export const MAX_FILE_WRITE_BYTES = 128 * 1024 * 1024;
 export const MAX_DIRECTORY_ENTRIES = 200;
 export const MAX_COPY_TOTAL_BYTES = 10 * 1024 * 1024;
 export const MAX_COPY_ENTRIES = 500;
+export const MAX_PATCH_OPERATIONS = 20;
+export const MAX_PATCH_SEARCH_BYTES = 64 * 1024;
+export const MAX_PATCH_REPLACE_BYTES = 256 * 1024;
+export const MAX_PATCH_PREVIEW_CHARS = 6000;
+export const MAX_FILE_SEARCH_ENTRIES = 5000;
+export const MAX_FILE_SEARCH_RESULTS = 100;
+export const MAX_FILE_SEARCH_CONTENT_BYTES = 512 * 1024;
+export const MAX_FILE_SEARCH_SNIPPET_CHARS = 300;
+export const MAX_FILE_WRITE_CHUNK_BYTES = 64 * 1024;
+export const MAX_STREAM_WRITE_SESSIONS = 20;
+export const MAX_STREAM_WRITE_IDLE_MS = 15 * 60 * 1000;
+export const MAX_FILE_ATTACHMENT_BYTES = 20 * 1024 * 1024;

src/ai/tools/market-rates.ts

@@ -1,15 +1,16 @@
-import {AiTool} from "../tool-types";
+import {AiTool} from "../tool-types.js";
 import axios from "axios";
-import {toolsLogger} from "./tool-logger";
+import {toolsLogger} from "./tool-logger.js";
+import {AiJsonObject} from "../tool-types.js";
 
 const logger = toolsLogger.child("market-rates");
 
-export const GET_FINANCIAL_MARKET_DATA = "get_financial_market_data";
+export const GET_FINANCIAL_MARKET_DATA_TOOL_NAME = "get_financial_market_data";
 
 export const getFinancialMarketData = {
     type: "function",
     function: {
-        name: GET_FINANCIAL_MARKET_DATA,
+        name: GET_FINANCIAL_MARKET_DATA_TOOL_NAME,
         description:
             "Retrieve the latest exchange rates for supported currency, crypto, and precious metal pairs, including 24-hour change data when available. Supported pairs: USD/RUB, USD/EUR, USD/KZT, USD/UAH, USD/BYN, USD/GBP, USD/CNY, TON/USD, BTC/USD, ETH/USD, SOL/USD, and XAU/USD. Use this tool when the user asks for current rates, currency conversion, crypto prices, gold price, or recent 24-hour movement. This tool takes no parameters.",
         parameters: {
@@ -20,11 +21,11 @@ export const getFinancialMarketData = {
     },
 } satisfies AiTool;
 
-export const financialMarketDataToolPrompt = [
+export const getFinancialMarketDataToolPrompt = [
     "Currency rates tool rules:",
-    `- Use \`${GET_FINANCIAL_MARKET_DATA}\` whenever the answer depends on current exchange rates, crypto prices, or gold price.`,
+    `- Use \`${GET_FINANCIAL_MARKET_DATA_TOOL_NAME}\` whenever the answer depends on current exchange rates, crypto prices, or gold price.`,
-    `- Use \`${GET_FINANCIAL_MARKET_DATA}\` when the user asks whether a supported asset went up or down recently.`,
+    `- Use \`${GET_FINANCIAL_MARKET_DATA_TOOL_NAME}\` when the user asks whether a supported asset went up or down recently.`,
-    `- Use \`${GET_FINANCIAL_MARKET_DATA}\` when the user asks for the 24-hour change, percentage change, or movement direction for a supported pair.`,
+    `- Use \`${GET_FINANCIAL_MARKET_DATA_TOOL_NAME}\` when the user asks for the 24-hour change, percentage change, or movement direction for a supported pair.`,
     "- Never guess current rates, prices, or 24-hour changes. Call the tool first.",
     "- Do not use this tool for unsupported pairs unless the user asks about one of the supported pairs listed below.",
     "- Do not use this tool for historical rates beyond the provided 24-hour comparison.",
@@ -63,15 +64,15 @@ export const financialMarketDataToolPrompt = [
     "- When the user asks for all rates, group fiat currencies separately from crypto and gold.",
 ].join("\n");
 
-export async function getMarketRates(): Promise<unknown | undefined> {
+export async function getMarketRates(): Promise<AiJsonObject | 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 (e: unknown) {
+    } catch (error) {
-        logger.error("failed", {duration: logger.duration(startedAt), error: e});
+        logger.error("failed", {duration: logger.duration(startedAt), error: error instanceof Error ? error : String(error)});
         return undefined;
     }
 }

src/ai/tools/notes.ts

@@ -1,9 +1,11 @@
-import {AiTool} from "../tool-types";
+import {AiTool} from "../tool-types.js";
 import path from "node:path";
-import {readdir, readFile, unlink, writeFile} from "node:fs/promises";
+import {readdir, readFile, stat, unlink, writeFile} from "node:fs/promises";
-import {notesDir, notesRootFile} from "../../index";
+import {notesDir, notesRootFile} from "../../index.js";
-import {asNonEmptyString} from "./utils";
+import {asNonEmptyString} from "./utils.js";
-import {toolsLogger} from "./tool-logger";
+import {toolsLogger} from "./tool-logger.js";
+import {z} from "zod";
+import {AiJsonObject} from "../tool-types.js";
 
 const logger = toolsLogger.child("notes");
 
@@ -98,14 +100,14 @@ 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});
+        logger.error("list.failed", {duration: logger.duration(startedAt), error: error instanceof Error ? error : String(error)});
         const errorMessage = error instanceof Error ? error.message : String(error);
         return {success: false, error: `Failed to list notes: ${errorMessage}`};
     }
 }
 
 export async function getNoteContent(
-    args?: Record<string, unknown>,
+    args?: AiJsonObject,
 ): Promise<GetNoteContentResult> {
     const startedAt = Date.now();
     logger.debug("get_content.start", {args});
@@ -144,7 +146,7 @@ export async function getNoteContent(
             content,
         };
     } catch (error) {
-        logger.error("list.failed", {duration: logger.duration(startedAt), error});
+        logger.error("list.failed", {duration: logger.duration(startedAt), error: error instanceof Error ? error : String(error)});
         const errorMessage = error instanceof Error ? error.message : String(error);
         return {success: false, error: `Failed to read note: ${errorMessage}`};
     }
@@ -235,7 +237,7 @@ export const deleteNoteTool = {
 } satisfies AiTool;
 
 export async function updateNoteContent(
-    args?: Record<string, unknown>,
+    args?: AiJsonObject,
 ): Promise<UpdateNoteContentResult> {
     const startedAt = Date.now();
     logger.debug("update_content.start", {args});
@@ -271,14 +273,14 @@ export async function updateNoteContent(
 
         return {success: true, filePath: noteFilePath};
     } catch (error) {
-        logger.error("list.failed", {duration: logger.duration(startedAt), error});
+        logger.error("list.failed", {duration: logger.duration(startedAt), error: error instanceof Error ? error : String(error)});
         const errorMessage = error instanceof Error ? error.message : String(error);
         return {success: false, error: `Failed to update note: ${errorMessage}`};
     }
 }
 
 export async function deleteNote(
-    args?: Record<string, unknown>,
+    args?: AiJsonObject,
 ): Promise<DeleteNoteResult> {
     const startedAt = Date.now();
     logger.debug("delete.start", {args});
@@ -304,7 +306,7 @@ export async function deleteNote(
 
         return {success: true, filePath: noteFilePath};
     } catch (error) {
-        logger.error("list.failed", {duration: logger.duration(startedAt), error});
+        logger.error("list.failed", {duration: logger.duration(startedAt), error: error instanceof Error ? error : String(error)});
         const errorMessage = error instanceof Error ? error.message : String(error);
         return {success: false, error: `Failed to delete note: ${errorMessage}`};
     }
@@ -338,3 +340,110 @@ async function removeNoteLinkFromRoot(noteFilePath: string): Promise<void> {
 function escapeRegExp(value: string): string {
     return value.replace(/[.*+?^${}()|[\]\\]/g, "\\$&");
 }
+
+export type NoteFileAttachment = {
+    type: "local_file";
+    fileName: string;
+    // filePath: string;
+    relativePath: string;
+    mimeType: "text/markdown";
+    sizeBytes: number;
+};
+
+export type GetNoteFileResult =
+    | {
+    success: true;
+    attachment: NoteFileAttachment;
+} | { success: false; error: string };
+
+export const NoteFileAttachmentSchema = z.object({
+    type: z.literal("local_file"),
+    fileName: z.string(),
+    // filePath: z.string(),
+    relativePath: z.string(),
+    mimeType: z.literal("text/markdown"),
+    sizeBytes: z.number(),
+});
+
+export const GetNoteFileResultSchema = z.discriminatedUnion("success", [
+    z.object({
+        success: z.literal(true),
+        attachment: NoteFileAttachmentSchema,
+    }),
+    z.object({
+        success: z.literal(false),
+        error: z.string(),
+    }),
+]);
+
+export const sendNoteAsFileTool = {
+    type: "function",
+    function: {
+        name: "send_note_as_file",
+        description:
+            "Prepare a Markdown note file to be sent to the user as a .md attachment. Returns a local file descriptor that the host application should use to upload or send the file.",
+        parameters: {
+            type: "object",
+            properties: {
+                fileName: {
+                    type: "string",
+                    description:
+                        "The file name of the note to send. It may be provided with or without the .md extension. Must not contain forbidden or unsafe characters such as /, \\, :, *, ?, \", <, >, |, or control characters.",
+                },
+            },
+            required: ["fileName"],
+        },
+    },
+} satisfies AiTool;
+
+export async function sendNoteAsFile(
+    args?: AiJsonObject,
+): Promise<GetNoteFileResult> {
+    logger.debug("start", {args});
+
+    const fileName = asNonEmptyString(args?.fileName) ?? "";
+    if (!fileName.trim().length) {
+        return {success: false, error: "No file name provided"};
+    }
+
+    const noteFilePath = buildSafeNoteFilePath(fileName);
+    if (!noteFilePath) {
+        return {success: false, error: "Invalid or unsafe file name provided"};
+    }
+
+    try {
+        // Проверяем, что файл существует и действительно читается.
+        await readFile(noteFilePath, "utf-8");
+
+        const fileStat = await stat(noteFilePath);
+        if (!fileStat.isFile()) {
+            return {success: false, error: "Note path is not a file"};
+        }
+
+        const normalizedFileName = path.basename(noteFilePath);
+        const relativePath = path.relative(path.dirname(notesRootFile), noteFilePath);
+
+        const result: GetNoteFileResult = {
+            success: true,
+            attachment: {
+                type: "local_file",
+                fileName: normalizedFileName,
+                // filePath: noteFilePath,
+                relativePath,
+                mimeType: "text/markdown",
+                sizeBytes: fileStat.size,
+            },
+        };
+
+        logger.debug("done", {
+            fileName: result.attachment.fileName,
+            relativePath: result.attachment.relativePath,
+            sizeBytes: result.attachment.sizeBytes
+        });
+
+        return result;
+    } catch (error) {
+        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

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

src/ai/tools/registry.ts

@@ -1,18 +1,22 @@
-import {Environment} from "../../common/environment";
+import {Environment} from "../../common/environment.js";
-import {AiTool} from "../tool-types";
+import {AiTool} from "../tool-types.js";
-import {braveSearchTool, webSearch} from "./brave-search";
+import {WEB_SEARCH_TOOL_NAME, webSearch, webSearchTool, webSearchToolPrompt} from "./web-search.js";
-import {getCurrentDateTime, getCurrentDateTimeTool} from "./datetime";
+import {getCurrentDateTime, getCurrentDateTimeTool} from "./datetime.js";
-import {shellExecute, shellExecuteTool} from "./shell";
+import {shellExecute, shellExecuteTool} from "./shell.js";
-import {ToolHandler} from "./types";
+import {ToolHandler} from "./types.js";
-import {getWeather, getWeatherTool} from "./weather";
+import {getWeather, getWeatherTool} from "./weather.js";
 import {
-    financialMarketDataToolPrompt,
+    GET_FINANCIAL_MARKET_DATA_TOOL_NAME,
-    GET_FINANCIAL_MARKET_DATA,
     getFinancialMarketData,
+    getFinancialMarketDataToolPrompt,
     getMarketRates
-} from "./market-rates";
+} from "./market-rates.js";
-import {pythonInterpreterTool, runPythonInterpreter} from "./python-interpretator";
+import {pythonInterpreterTool, runPythonInterpreter} from "./python-interpretator.js";
 import {
+    beginFileWrite,
+    beginFileWriteTool,
+    cancelFileWrite,
+    cancelFileWriteTool,
     copyPath,
     copyPathTool,
     createDirectory,
@@ -21,154 +25,231 @@ import {
     createFileTool,
     deletePath,
     deletePathTool,
+    editFilePatch,
+    editFilePatchTool,
+    fileToolsToolPrompt,
+    finishFileWrite,
+    finishFileWriteTool,
     listDirectory,
     listDirectoryTool,
     readFile,
     readFileTool,
     renamePath,
     renamePathTool,
+    searchFiles,
+    searchFilesTool,
+    sendFileAsAttachment,
+    sendFileAsAttachmentTool,
     updateFile,
-    updateFileTool
+    updateFileTool,
-} from "./file-system";
+    writeFileChunk,
-import {createNote, createNoteTool} from "./create-note";
+    writeFileChunkTool
-import {
+} from "./files.js";
-    deleteNote,
+import {executeMemoryTool, memoryToolPrompt, memoryTools, type MemoryToolName} from "./user-memory.js";
-    deleteNoteTool,
+import {getMcpToolHandlers, getMcpToolPrompts, getMcpTools} from "../mcp/mcp-registry.js";
-    getNoteContent,
-    getNoteContentTool,
-    listNotes,
-    listNotesTool,
-    updateNoteContent,
-    updateNoteContentTool
-} from "./list-notes";
-import {sendNoteAsFileTool, sendNoteAsFile} from "./send-note-as-file";
-import {searchNotes, searchNotesTool} from "./search-notes";
 
-export const getTools = () => {
+export const defaultTools: AiTool[] = [
-    const tools: AiTool[] = [
     getCurrentDateTimeTool,
     getFinancialMarketData,
-        createNoteTool,
+    ...memoryTools,
-        listNotesTool,
+];
-        getNoteContentTool,
-        updateNoteContentTool,
-        deleteNoteTool,
-        sendNoteAsFileTool,
-        searchNotesTool
-    ];
 
-    if (Environment.ENABLE_PYTHON_INTERPRETER) {
+export const fileTools = [
-        tools.push(pythonInterpreterTool);
+    readFileTool,
+    listDirectoryTool,
+    searchFilesTool,
+
+    createFileTool,
+    beginFileWriteTool,
+    writeFileChunkTool,
+    finishFileWriteTool,
+    cancelFileWriteTool,
+
+    sendFileAsAttachmentTool,
+
+    createDirectoryTool,
+    copyPathTool,
+    updateFileTool,
+    editFilePatchTool,
+    renamePathTool,
+    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 getTools = (forCreator?: boolean) => {
+    const tools: AiTool[] = [];
+
+    if (Environment.DISABLE_LOCAL_TOOLS) {
+        tools.push(...getMcpTools());
+        return tools;
     }
 
-    if (Environment.ENABLE_UNSAFE_EVAL) {
+    tools.push(...filterEnabledTools(defaultTools));
-        tools.push(shellExecuteTool);
-    }
 
     if (Environment.BRAVE_SEARCH_API_KEY) {
-        tools.push(braveSearchTool);
+        tools.push(...filterEnabledTools([webSearchTool]));
     }
 
     if (Environment.OPEN_WEATHER_MAP_API_KEY) {
-        tools.push(getWeatherTool);
+        tools.push(...filterEnabledTools([getWeatherTool]));
     }
 
     if (Environment.FILE_TOOLS_ROOT_DIR && Environment.ENABLE_FS_TOOLS) {
-        tools.push(
+        tools.push(...filterEnabledTools(fileTools));
-            readFileTool,
-            listDirectoryTool,
-            createFileTool,
-            createDirectoryTool,
-            updateFileTool,
-            renamePathTool,
-            copyPathTool,
-            deletePathTool,
-        );
     }
 
+    if (forCreator) {
+        if (Environment.ENABLE_PYTHON_INTERPRETER) {
+            tools.push(...filterEnabledTools([pythonInterpreterTool]));
+        }
+
+        if (Environment.ENABLE_UNSAFE_EVAL) {
+            tools.push(...filterEnabledTools([shellExecuteTool]));
+        }
+    }
+
+    tools.push(...getMcpTools());
 
     return tools;
-    // return [
+};
-    //     createNoteTool,
+
-    //     listNotesTool,
+export const fileToolHandlers = {
-    //     getNoteContentTool,
+    read_file: readFile,
-    //     updateNoteContentTool,
+    list_directory: listDirectory,
-    //     deleteNoteTool,
+    search_files: searchFiles,
-    //     getNoteFileTool,
+
-    //     searchNotesTool
+    create_file: createFile,
-    // ];
+    begin_file_write: beginFileWrite,
+    write_file_chunk: writeFileChunk,
+    finish_file_write: finishFileWrite,
+    cancel_file_write: cancelFileWrite,
+
+    send_file_as_attachment: sendFileAsAttachment,
+
+    create_directory: createDirectory,
+    copy_path: copyPath,
+    update_file: updateFile,
+    edit_file_patch: editFilePatch,
+    rename_path: renamePath,
+    delete_path: deletePath,
 };
 
 export const getToolHandlers = () => {
-    let handlers: Record<string, ToolHandler> = {
+    const handlers: Record<string, ToolHandler> = {
-        get_datetime: getCurrentDateTime,
+        ...getMcpToolHandlers(),
-        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
     };
 
-    if (Environment.ENABLE_PYTHON_INTERPRETER) {
+    if (Environment.DISABLE_LOCAL_TOOLS) {
-        handlers = {
+        return handlers;
-            python_interpreter: runPythonInterpreter,
+    }
-            ...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 (Environment.ENABLE_UNSAFE_EVAL) {
+    if (isLocalToolEnabled("read_file")) handlers.read_file = readFile;
-        handlers = {
+    if (isLocalToolEnabled("list_directory")) handlers.list_directory = listDirectory;
-            shell_execute: shellExecute,
+    if (isLocalToolEnabled("search_files")) handlers.search_files = searchFiles;
-            ...handlers,
+    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 (Environment.BRAVE_SEARCH_API_KEY) {
+    if (isLocalToolEnabled("python_interpreter")) handlers.python_interpreter = (args, _context) => runPythonInterpreter(args);
-        handlers = {
+    if (isLocalToolEnabled("shell_execute")) handlers.shell_execute = shellExecute;
-            web_search: webSearch,
+    if (isLocalToolEnabled("web_search")) handlers.web_search = webSearch;
-            ...handlers,
+    if (isLocalToolEnabled("get_weather")) handlers.get_weather = getWeather;
-        };
-    }
-
-    if (Environment.OPEN_WEATHER_MAP_API_KEY) {
-        handlers = {
-            get_weather: getWeather,
-            ...handlers,
-        };
-    }
-
-    if (Environment.FILE_TOOLS_ROOT_DIR && Environment.ENABLE_FS_TOOLS) {
-        handlers = {
-            read_file: readFile,
-            list_directory: listDirectory,
-            create_file: createFile,
-            create_directory: createDirectory,
-            update_file: updateFile,
-            rename_path: renamePath,
-            copy_path: copyPath,
-            delete_path: deletePath,
-            ...handlers,
-        };
-    }
 
     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:
+            case GET_FINANCIAL_MARKET_DATA_TOOL_NAME:
-                prompts.push(financialMarketDataToolPrompt);
+                prompts.push(getFinancialMarketDataToolPrompt);
+                break;
+            case WEB_SEARCH_TOOL_NAME:
+                prompts.push(webSearchToolPrompt);
                 break;
             default:
                 break;
         }
     }
 
+    prompts.push(...getMcpToolPrompts(toolNames));
     return prompts;
 }

src/ai/tools/runtime.ts

@@ -1,22 +1,29 @@
-import {getToolHandlers} from "./registry";
+import {getToolHandlers} from "./registry.js";
-import {normalizeToolArguments} from "./utils";
+import {normalizeToolArguments} from "./utils.js";
-import {PYTHON_INTERPRETER_TOOL_NAME, PythonInterpreterInputFile, runPythonInterpreter} from "./python-interpretator";
+import {PYTHON_INTERPRETER_TOOL_NAME, PythonInterpreterInputFile, runPythonInterpreter} from "./python-interpretator.js";
-import {toolsLogger} from "./tool-logger";
+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";
 
 const logger = toolsLogger.child("runtime");
 
 export type ToolRuntimeContext = {
     pythonInputFiles?: PythonInterpreterInputFile[];
-};
+    provider?: AiProvider;
+    runtimeTarget?: AiRuntimeTarget;
+} & MemoryRuntimeContext;
 
-function stringifyToolResult(result: unknown): string {
+function stringifyToolResult(result: AiJsonValue): string {
     if (typeof result === "string") return result;
     return JSON.stringify(result, null, 2);
 }
 
 export async function executeToolCall(
+    userId: number | undefined | null,
     name: string,
-    args?: unknown,
+    args?: string | AiJsonObject,
     context: ToolRuntimeContext = {},
 ): Promise<string> {
     const startedAt = Date.now();
@@ -31,7 +38,7 @@ export async function executeToolCall(
 
     try {
         if (name === PYTHON_INTERPRETER_TOOL_NAME) {
-            const result = await runPythonInterpreter(normalizeToolArguments(args), {
+            const result = await runPythonInterpreter(normalizeToolArguments(args, userId), {
                 executionTimeoutMs: 8_000,
                 syntaxTimeoutMs: 3_000,
                 maxCodeChars: 100_000,
@@ -45,12 +52,13 @@ export async function executeToolCall(
             return s;
         }
 
-        const result = await handler(normalizeToolArguments(args));
+        const arguments1 = normalizeToolArguments(args, userId);
+        const result = await handler(arguments1, context);
         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});
+        logger.error("execute.failed", {name, duration: logger.duration(startedAt), error: error instanceof Error ? error : String(error)});
         return stringifyToolResult({
             error: error instanceof Error ? error.message : String(error),
         });

src/ai/tools/search-notes.ts

@@ -1,9 +1,10 @@
-import {AiTool} from "../tool-types";
+import {AiTool} from "../tool-types.js";
 import path from "node:path";
 import {readdir, readFile} from "node:fs/promises";
-import {notesDir, notesRootFile} from "../../index";
+import {notesDir, notesRootFile} from "../../index.js";
-import {asNonEmptyString} from "./utils";
+import {asNonEmptyString} from "./utils.js";
-import {toolsLogger} from "./tool-logger";
+import {toolsLogger} from "./tool-logger.js";
+import {AiJsonObject, AiJsonValue} from "../tool-types.js";
 
 const logger = toolsLogger.child("search-notes");
 
@@ -52,7 +53,7 @@ export const searchNotesTool = {
 } satisfies AiTool;
 
 export async function searchNotes(
-    args?: Record<string, unknown>,
+    args?: AiJsonObject,
 ): Promise<SearchNotesResult> {
     const startedAt = Date.now();
     logger.debug("start", {args});
@@ -139,7 +140,7 @@ export async function searchNotes(
     }
 }
 
-function parseSearchLimit(value: unknown): number {
+function parseSearchLimit(value: AiJsonValue | undefined): number {
     const parsed =
         typeof value === "number"
             ? value

src/ai/tools/send-note-as-file.ts

@@ -1,113 +0,0 @@
-import {AiTool} from "../tool-types";
-import path from "node:path";
-import {readFile, stat} from "node:fs/promises";
-import {notesRootFile} from "../../index";
-import {asNonEmptyString} from "./utils";
-import {buildSafeNoteFilePath} from "./list-notes";
-import z from "zod";
-import {toolsLogger} from "./tool-logger";
-
-const logger = toolsLogger.child("get-note-file");
-
-export type NoteFileAttachment = {
-    type: "local_file";
-    fileName: string;
-    // filePath: string;
-    relativePath: string;
-    mimeType: "text/markdown";
-    sizeBytes: number;
-};
-
-export type GetNoteFileResult =
-    | {
-    success: true;
-    attachment: NoteFileAttachment;
-} | { success: false; error: string };
-
-export const NoteFileAttachmentSchema = z.object({
-    type: z.literal("local_file"),
-    fileName: z.string(),
-    // filePath: z.string(),
-    relativePath: z.string(),
-    mimeType: z.literal("text/markdown"),
-    sizeBytes: z.number(),
-});
-
-export const GetNoteFileResultSchema = z.discriminatedUnion("success", [
-    z.object({
-        success: z.literal(true),
-        attachment: NoteFileAttachmentSchema,
-    }),
-    z.object({
-        success: z.literal(false),
-        error: z.string(),
-    }),
-]);
-
-export const sendNoteAsFileTool = {
-    type: "function",
-    function: {
-        name: "send_note_as_file",
-        description:
-            "Prepare a Markdown note file to be sent to the user as a .md attachment. Returns a local file descriptor that the host application should use to upload or send the file.",
-        parameters: {
-            type: "object",
-            properties: {
-                fileName: {
-                    type: "string",
-                    description:
-                        "The file name of the note to send. It may be provided with or without the .md extension. Must not contain forbidden or unsafe characters such as /, \\, :, *, ?, \", <, >, |, or control characters.",
-                },
-            },
-            required: ["fileName"],
-        },
-    },
-} satisfies AiTool;
-
-export async function sendNoteAsFile(
-    args?: Record<string, unknown>,
-): Promise<GetNoteFileResult> {
-    logger.debug("start", {args});
-
-    const fileName = asNonEmptyString(args?.fileName) ?? "";
-    if (!fileName.trim().length) {
-        return {success: false, error: "No file name provided"};
-    }
-
-    const noteFilePath = buildSafeNoteFilePath(fileName);
-    if (!noteFilePath) {
-        return {success: false, error: "Invalid or unsafe file name provided"};
-    }
-
-    try {
-        // Проверяем, что файл существует и действительно читается.
-        await readFile(noteFilePath, "utf-8");
-
-        const fileStat = await stat(noteFilePath);
-        if (!fileStat.isFile()) {
-            return {success: false, error: "Note path is not a file"};
-        }
-
-        const normalizedFileName = path.basename(noteFilePath);
-        const relativePath = path.relative(path.dirname(notesRootFile), noteFilePath);
-
-        const result: GetNoteFileResult = {
-            success: true,
-            attachment: {
-                type: "local_file",
-                fileName: normalizedFileName,
-                // filePath: noteFilePath,
-                relativePath,
-                mimeType: "text/markdown",
-                sizeBytes: fileStat.size,
-            },
-        };
-
-        logger.debug("done", {fileName: result.attachment.fileName, relativePath: result.attachment.relativePath, sizeBytes: result.attachment.sizeBytes});
-
-        return result;
-    } catch (error) {
-        const errorMessage = error instanceof Error ? error.message : String(error);
-        return {success: false, error: `Failed to prepare note file: ${errorMessage}`};
-    }
-}

src/ai/tools/shell.ts

@@ -1,6 +1,7 @@
 import {AiTool} from "../tool-types";
-import {runCommand} from "../../util/utils";
+import {runCommand} from "../../util/utils.js";
-import {asNonEmptyString} from "./utils";
+import {asNonEmptyString} from "./utils.js";
+import {AiJsonObject} from "../tool-types";
 
 export const shellExecuteTool = {
     type: "function",
@@ -32,7 +33,7 @@ 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 unknown, first run a safe environment inspection command.",
+    "- If the current OS/shell is unclear, first run a safe environment inspection command.",
     "- Safe OS inspection examples:",
     "  - Node.js: `node -p \"process.platform\"`",
     "  - Node.js: `node -p \"process.cwd()\"`",
@@ -99,7 +100,7 @@ export const shellExecuteToolPrompt = [
     "",
 ].join("\n");
 
-export async function shellExecute(args?: Record<string, unknown>): Promise<string | undefined | null> {
+export async function shellExecute(args?: AiJsonObject): 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";
+import {appLogger} from "../../logging/logger.js";
 
 export const toolsLogger = appLogger.child("ai-tools");

src/ai/tools/types.ts

@@ -1 +1,4 @@
-export type ToolHandler = (args?: Record<string, unknown>) => Promise<unknown> | unknown;
+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;

src/ai/tools/user-memory.ts

@@ -0,0 +1,582 @@
+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

@@ -1,23 +1,25 @@
 import {Ollama} from "ollama";
-import {toolsLogger} from "./tool-logger";
+import {toolsLogger} from "./tool-logger.js";
+import {AiJsonObject, AiJsonValue} from "../tool-types";
+import type {BoundaryValue} from "../../common/boundary-types";
 
 const logger = toolsLogger.child("utils");
 
-export function asNonEmptyString(value: unknown): string | undefined {
+export function asNonEmptyString(value: BoundaryValue): string | undefined {
     return typeof value === "string" && value.trim().length > 0
         ? value.trim()
         : undefined;
 }
 
-export function normalizeToolArguments(args: unknown): Record<string, unknown> {
+export function normalizeToolArguments(args: string | AiJsonObject | undefined, userId?: number | null): AiJsonObject {
     if (!args) return {};
 
     if (typeof args === "string") {
         try {
-            const parsed = JSON.parse(args);
+            const parsed = JSON.parse(args) as AiJsonValue;
 
             if (parsed && typeof parsed === "object" && !Array.isArray(parsed)) {
-                return parsed as Record<string, unknown>;
+                return parsed as AiJsonObject;
             }
         } catch {
             return {
@@ -29,13 +31,17 @@ export function normalizeToolArguments(args: unknown): Record<string, unknown> {
     }
 
     if (typeof args === "object" && !Array.isArray(args)) {
-        return args as Record<string, unknown>;
+        const userIdObject = userId ? {"userId": userId} : {};
+        return {
+            ...args,
+            ...userIdObject,
+        } as AiJsonObject;
     }
 
     return {};
 }
 
-export function asBoolean(value: unknown, defaultValue = false): boolean {
+export function asBoolean(value: BoundaryValue, defaultValue = false): boolean {
     if (typeof value === "boolean") return value;
 
     if (typeof value === "string") {
@@ -48,11 +54,11 @@ export function asBoolean(value: unknown, defaultValue = false): boolean {
     return defaultValue;
 }
 
-export function asString(value: unknown, defaultValue = ""): string {
+export function asString(value: BoundaryValue, defaultValue = ""): string {
     return typeof value === "string" ? value : defaultValue;
 }
 
-export function asPositiveInt(value: unknown, defaultValue: number, maxValue: number): number {
+export function asPositiveInt(value: BoundaryValue, defaultValue: number, maxValue: number): number {
     const n = typeof value === "number"
         ? value
         : typeof value === "string"
@@ -83,7 +89,7 @@ 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});
+        logger.error("ollama.unload_all.failed", {exceptFor, error: error instanceof Error ? error : String(error)});
     }
 }
 
@@ -100,8 +106,8 @@ export async function loadOllamaModel(model: string, ollama: Ollama, contextLeng
         });
         logger.info("ollama.load.done", {model, contextLength});
         return true;
-    } catch (e: unknown) {
+    } catch (error) {
-        logger.error("ollama.load.failed", {model, contextLength, error: e});
+        logger.error("ollama.load.failed", {model, contextLength, error: error instanceof Error ? error : String(error)});
         return false;
     }
 }

src/ai/tools/weather.ts

@@ -1,11 +1,11 @@
 import axios from "axios";
-import {toolsLogger} from "./tool-logger";
+import {toolsLogger} from "./tool-logger.js";
 
 const logger = toolsLogger.child("weather");
-import {Environment} from "../../common/environment";
+import {Environment} from "../../common/environment.js";
-import {logError} from "../../util/utils";
+import {logError} from "../../util/utils.js";
-import {AiTool} from "../tool-types";
+import {AiJsonObject, AiTool} from "../tool-types.js";
-import {asNonEmptyString} from "./utils";
+import {asNonEmptyString} from "./utils.js";
 
 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?: Record<string, unknown>): Promise<Record<string, unknown> | null> {
+export async function getWeather(args?: AiJsonObject): Promise<AiJsonObject | null> {
     const startedAt = Date.now();
     logger.info("start", {args});
     try {
@@ -141,9 +141,9 @@ export async function getWeather(args?: Record<string, unknown>): Promise<Record
                 windSpeed: wind.speed,
             },
         };
-    } catch (e: unknown) {
+    } catch (error) {
-        logger.error("failed", {duration: logger.duration(startedAt), error: e});
+        logger.error("failed", {duration: logger.duration(startedAt), error: error instanceof Error ? error : String(error)});
-        logError(e);
+        logError(error instanceof Error ? error : String(error));
         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";
+import {toolsLogger} from "./tool-logger.js";
 
 const logger = toolsLogger.child("brave-search");
-import {Environment} from "../../common/environment";
+import {Environment} from "../../common/environment.js";
-import {logError} from "../../util/utils";
+import {logError} from "../../util/utils.js";
-import {AiTool} from "../tool-types";
+import {AiJsonObject, AiJsonValue, AiTool} from "../tool-types.js";
-import {asBoolean, asNonEmptyString} from "./utils";
+import {asBoolean, asNonEmptyString} from "./utils.js";
 
 type BraveSearchProfile = {
     name?: string;
@@ -83,16 +83,16 @@ type BraveSearchApiResponse = {
         results?: BraveSearchResult[];
     };
 
-    faq?: unknown;
+    faq?: AiJsonValue;
-    infobox?: unknown;
+    infobox?: AiJsonValue;
-    locations?: unknown;
+    locations?: AiJsonValue;
-    mixed?: unknown;
+    mixed?: AiJsonValue;
-    summarizer?: unknown;
+    summarizer?: AiJsonValue;
 };
 
 export const WEB_SEARCH_TOOL_NAME = "web_search";
 
-export const braveSearchTool = {
+export const webSearchTool = {
     type: "function",
     function: {
         name: WEB_SEARCH_TOOL_NAME,
@@ -163,7 +163,7 @@ export const braveSearchTool = {
     },
 } satisfies AiTool;
 
-export const braveSearchToolPrompt = [
+export const webSearchToolPrompt = [
     "Brave Search tool rules:",
     "- You have access to `web_search`.",
     "- Use `web_search` when the user asks for current information, recent events, fresh prices, documentation lookup, source lookup, product info, news, public facts, or anything that may have changed.",
@@ -197,7 +197,7 @@ export const braveSearchToolPrompt = [
 ].join("\n");
 
 function asIntegerInRange(
-    value: unknown,
+    value: AiJsonValue | undefined,
     fallback: number,
     min: number,
     max: number,
@@ -216,7 +216,7 @@ function asIntegerInRange(
 }
 
 function asEnum<T extends string>(
-    value: unknown,
+    value: AiJsonValue | undefined,
     allowed: readonly T[],
     fallback: T,
 ): T {
@@ -229,7 +229,7 @@ function asEnum<T extends string>(
         : fallback;
 }
 
-function cleanSearchText(value: unknown): string | null {
+function cleanSearchText(value: AiJsonValue | undefined): string | null {
     if (typeof value !== "string") return null;
 
     return value
@@ -243,7 +243,7 @@ function cleanSearchText(value: unknown): string | null {
         .trim() || null;
 }
 
-function normalizeBraveResultFilter(value: unknown): string {
+function normalizeBraveResultFilter(value: AiJsonValue | undefined): string {
     const allowed = new Set([
         "discussions",
         "faq",
@@ -268,7 +268,7 @@ function normalizeBraveResultFilter(value: unknown): string {
     return parts.length ? [...new Set(parts)].join(",") : "web";
 }
 
-export async function webSearch(args?: Record<string, unknown>) {
+export async function webSearch(args?: AiJsonObject) {
     const startedAt = Date.now();
     logger.info("start", {args});
 
@@ -362,17 +362,16 @@ export async function webSearch(args?: Record<string, unknown>) {
 
             note: "Use returned URLs as sources. Do not invent facts that are not present in the snippets/results.",
         };
-    } catch (e: unknown) {
+    } catch (error) {
-        logError(e);
+        logError(error instanceof Error ? error : String(error));
 
-        const axiosLike = e as {response?: {status?: unknown; data?: unknown}};
+        const status = axios.isAxiosError(error) ? error.response?.status : undefined;
-        const status = axiosLike.response?.status;
+        const data = axios.isAxiosError(error) ? error.response?.data : undefined;
-        const data = axiosLike.response?.data;
 
         return {
             ok: false,
             status: typeof status === "number" ? status : null,
-            error: e instanceof Error ? e.message : String(e),
+            error: error instanceof Error ? error.message : String(error),
             response: data ?? null,
         };
     } finally {

src/ai/transcript-artifact-store.ts

@@ -0,0 +1,42 @@
+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

@@ -0,0 +1,373 @@
+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

@@ -0,0 +1,486 @@
+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

@@ -1,176 +0,0 @@
-// 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";
-
-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(
-    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(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(calls, streamMessage, toolContext, toolMemory));
-    }
-}
-
-
-export class GeminiProviderRunner {
-    static run = runGemini;
-}

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

@@ -1,15 +1,32 @@
-// Mistral provider runner extracted from unified-ai-runner.ts.
 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 {MAX_TOOL_ROUNDS, MistralDeltaLike, MistralDocumentReference, RuntimeConfigSnapshot, StreamingToolCallAccumulator, ToolCallData, ToolExecutionMemory, contentFromMistralDelta, executeToolBatch, mistralToolCalls, normalizeMistralToolCalls, roundStatus} from "./unified-ai-runner.shared";
+import {
+    MAX_TOOL_ROUNDS,
+    MistralDocumentReference,
+    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(
+    msg: Message,
     messages: MistralChatMessage[],
     documents: MistralDocumentReference[],
     streamMessage: TelegramStreamMessage,
@@ -21,6 +38,9 @@ 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),
@@ -30,34 +50,51 @@ export async function runMistral(
     });
 
     const toolMemory: ToolExecutionMemory = new Map();
-
+    try {
-    for (let round = 0; round < MAX_TOOL_ROUNDS; round++) {
+        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;
+
             streamMessage.setStatus(roundStatus(round, firstRoundStatus) ?? "");
             await streamMessage.flush();
 
             if (!stream) {
                 const request = {
                     model: config.mistralChatTarget.model,
-                messages,
+                    messages: requestMessages,
-                tools: getMistralTools(),
+                    tools: requestTools,
                     documents: documents
-            } as unknown as Parameters<typeof mistralAi.chat.complete>[0];
+                } as Parameters<typeof mistralAi.chat.complete>[0];
-            const response = await mistralAi.chat.complete(request, {signal});
+                const response = await runSingleModelRequest({
-            const msg = response.choices?.[0]?.message;
+                    execute: () => adapter.callModel(request, () => mistralAi.chat.complete(request, {signal})),
-            const text = typeof msg?.content === "string" ? msg.content : JSON.stringify(msg?.content ?? "");
+                });
+                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(msg));
+                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;
+                if (!calls.length) return {shouldContinue: false};
                 messages.push({
                     role: "assistant",
                     content: text,
@@ -66,25 +103,50 @@ export async function runMistral(
                         function: {name: call.name, arguments: call.argumentsText},
                     })),
                 });
-            const toolResults = await executeToolBatch(calls, streamMessage, toolContext, toolMemory);
+                requestMessages.push({
-            for (const [index, call] of calls.entries()) {
+                    role: "assistant",
-                messages.push({
+                    content: text,
-                    role: "tool",
+                    toolCalls: calls.map(call => ({
-                    name: call.name,
+                        id: call.id,
-                    toolCallId: call.id,
+                        function: {name: call.name, arguments: call.argumentsText},
-                    content: toolResults[index] ?? "",
+                    })),
+                });
+                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,
                     });
                 }
-            continue;
+                return {shouldContinue: true};
             }
 
             const request = {
                 model: config.mistralChatTarget.model,
-            messages,
+                messages: requestMessages,
-            tools: getMistralTools(),
+                tools: requestTools,
                 documents: documents
-        } as unknown as Parameters<typeof mistralAi.chat.stream>[0];
+            } as Parameters<typeof mistralAi.chat.stream>[0];
-        const streamResponse = await mistralAi.chat.stream(request, {signal});
+            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;
@@ -95,11 +157,10 @@ export async function runMistral(
 
                 const choice = event.data?.choices?.[0];
                 const delta = choice?.delta;
-            const mistralDelta = delta as MistralDeltaLike;
+                const mistralDelta = delta;
+                streamMessage.append(adapter.extractTextDelta(mistralDelta));
 
-            streamMessage.append(contentFromMistralDelta(mistralDelta));
+                const rawDeltaCalls = adapter.extractStreamingToolCalls(mistralDelta);
-
-            const rawDeltaCalls = mistralToolCalls(mistralDelta);
                 if (rawDeltaCalls.length) {
                     calls = toolCallAccumulator.add(rawDeltaCalls);
                     streamMessage.setStatus(Environment.getUseToolText(calls));
@@ -112,26 +173,46 @@ export async function runMistral(
                 textChars: streamMessage.getText().slice(roundTextStart).length,
                 calls: calls.map(aiLogToolCall),
             });
-        if (!calls.length) return;
+            if (!calls.length) return {shouldContinue: false};
             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(calls, streamMessage, toolContext, toolMemory);
+            requestMessages.push({
-        for (const [index, call] of calls.entries()) {
+                role: "assistant",
-            messages.push({
+                content: roundText,
-                role: "tool",
+                toolCalls: calls.map(c => ({id: c.id, function: {name: c.name, arguments: c.argumentsText}}))
-                name: call.name,
+            });
-                toolCallId: call.id,
+            await executeToolBatchWithAdapter({
-                content: toolResults[index] ?? "",
+                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};
+        },
+        });
+    } finally {
+        await adapter.finalize().catch(() => undefined);
     }
 }
-
-
-export class MistralProviderRunner {
-    static run = runMistral;
-}

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

@@ -1,37 +1,32 @@
 // Ollama provider runner extracted from unified-ai-runner.ts.
-import {Message} from "typescript-telegram-bot-api";
 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";
 import {ToolRuntimeContext} from "./tools/runtime";
 import {enqueueTelegramApiCall} from "../util/telegram-api-queue";
-import {getCurrentDateTimeTool} from "./tools/datetime";
-import {getFinancialMarketData} from "./tools/market-rates";
-import {getWeatherTool} from "./tools/weather";
 import {loadOllamaModel, unloadAllOllamaModels} from "./tools/utils";
 import {createOllamaClient} from "./ai-runtime-target";
-import {GetNoteFileResult, GetNoteFileResultSchema, sendNoteAsFileTool} from "./tools/send-note-as-file";
 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,
@@ -39,11 +34,15 @@ import {
     ToolCallData,
     ToolExecutionMemory
 } from "./unified-ai-runner.shared";
-import {latestUserTextFromOllamaMessages, OllamaToolRanker} from "./unified-ai-runner.tool-ranker";
+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 {getToolPrompts} from "./tools/registry";
-import {createNoteTool} from "./tools/create-note";
+import {GetNoteFileResult, GetNoteFileResultSchema} from "./tools/notes";
-import {deleteNoteTool, getNoteContentTool, listNotesTool, updateNoteContentTool} from "./tools/list-notes";
+import {getModelCapabilities} from "./provider-model-runtime";
-import {searchNotesTool} from "./tools/search-notes";
+import {AiProvider} from "../model/ai-provider";
+import {Message} from "typescript-telegram-bot-api";
 
 export async function runOllama(
     msg: Message,
@@ -57,7 +56,6 @@ export async function runOllama(
     toolContext: ToolRuntimeContext,
     contextSize?: number,
 ): Promise<void> {
-    const fromId = msg.from?.id;
     const runnerStartedAt = Date.now();
 
     const audioCount = messages.reduce((sum, m) => sum + (m.audioParts?.length || m.audios?.length || 0), 0);
@@ -80,9 +78,8 @@ export async function runOllama(
 
     const ollama = createOllamaClient(target);
     const modelInfo = await ollama.show({model});
-    const modelInfoMap = isRecord(modelInfo.model_info) ? modelInfo.model_info : {};
+    const modelInfoMap: Record<string, BoundaryValue> = 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"
@@ -118,7 +115,7 @@ export async function runOllama(
             await unloadAllOllamaModels(ollama, modelsToLoad);
         }
     } catch (e) {
-        logError(e);
+        logError(e instanceof Error ? e : String(e));
     }
 
     if (!(await isOllamaModelActive(ollama, target))) {
@@ -160,9 +157,12 @@ export async function runOllama(
     }
 
     const toolMemory: ToolExecutionMemory = new Map();
+    const adapter = getProviderAdapter(AiProvider.OLLAMA);
 
     try {
-        for (let round = 0; round < MAX_TOOL_ROUNDS; round++) {
+        await runToolLoopRounds({
+            maxRounds: MAX_TOOL_ROUNDS,
+            onRound: async (round) => {
             const roundStartedAt = Date.now();
             aiLog("debug", "ollama.round.start", {
                 round,
@@ -185,20 +185,8 @@ export async function runOllama(
             };
 
             let activeToolNames: string[] = [];
-            // if ((await getModelCapabilities(AiProvider.OLLAMA, model, "tools"))?.tools?.supported) {
+            if ((await getModelCapabilities(AiProvider.OLLAMA, model, "tools"))?.tools?.supported) {
-            const availableOllamaTools: Tool[] =
+                const availableOllamaTools: Tool[] = adapter.rankTools(config, {forCreator: msg.from?.id === Environment.CREATOR_ID}) as Tool[];
-                fromId !== Environment.CREATOR_ID ? [
-                    getCurrentDateTimeTool,
-                    getFinancialMarketData,
-                    getWeatherTool,
-                    createNoteTool,
-                    listNotesTool,
-                    getNoteContentTool,
-                    updateNoteContentTool,
-                    deleteNoteTool,
-                    sendNoteAsFileTool,
-                    searchNotesTool
-                ] : getOllamaTools() as Tool[];
 
                 aiLog("debug", "ollama.tools.available", {
                     round,
@@ -206,20 +194,25 @@ export async function runOllama(
                     rankerEnabled: !!config.ollamaToolRankerTarget,
                 });
 
-            const rankerSelection = await new OllamaToolRanker(config).selectTools({
+                const rankResult = await runToolRankStage({
-                userQuery: latestUserTextFromOllamaMessages(messages),
+                    provider: AiProvider.OLLAMA,
-                availableTools: availableOllamaTools,
+                    model,
                     round,
+                    config,
+                    availableTools: availableOllamaTools,
+                    messages,
+                    streamMessage,
                     signal,
                 });
 
-            activeToolNames = rankerSelection.tools.map(t => t.function.name ?? "");
+                const filteredTools = [...new Set(ensureToolsSelected(availableOllamaTools, rankResult.filteredTools as Tool[], MEMORY_TOOL_NAMES) as Tool[])];
-            if (rankerSelection.tools.length > 0) {
+                activeToolNames = filteredTools.map(t => t.function.name ?? "");
-                request.tools = [...rankerSelection.tools, ...rankerSelection.tools];
+                if (filteredTools.length > 0) {
+                    request.tools = [...filteredTools];
                     request.options = {
                         ...request.options,
                         temperature: 0
-                }
+                    };
 
                     const newMessage = messages[messages.length - 1];
                     if (newMessage) {
@@ -236,31 +229,27 @@ 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: rankerSelection.usedRanker,
+                    usedRanker: rankResult.usedRanker,
                 });
-            // }
+            }
 
             if (!stream) {
-                const response = await ollama.chat({
+                const response = await runSingleModelRequest({
+                    execute: () => adapter.callModel(request, () => ollama.chat({
                         ...request,
                         stream: false
+                    })),
                 });
 
                 const message = response.message;
                 const rawContent = message?.content ?? "";
 
                 const nativeCalls = dedupeToolCalls(
-                    normalizeOllamaToolCalls(
+                    adapter.extractToolCalls(message),
-                        message?.tool_calls as readonly OllamaToolCallLike[] | undefined,
-                        round,
-                    ),
                 );
 
                 const responseText = rawContent;
@@ -285,10 +274,10 @@ export async function runOllama(
 
                 if (!nativeCalls.length) {
                     aiLog("success", "ollama.run.done", {round, duration: aiLogDuration(runnerStartedAt)});
-                    break;
+                    return {shouldContinue: false};
                 }
 
-                const calls = nativeCalls;
+                const calls = adapter.extractToolCalls(message).length ? adapter.extractToolCalls(message) : nativeCalls;
 
                 aiLog("info", "ollama.tool_calls", {
                     round,
@@ -306,19 +295,44 @@ export async function runOllama(
                     })),
                 });
 
-                appendOllamaToolResults(
+                await executeToolBatchWithAdapter({
-                    messages,
+                    userId: msg.from?.id,
-                    calls,
+                    toolCalls: calls,
-                    await executeToolBatch(calls, streamMessage, toolContext, toolMemory),
+                    streamMessage,
-                );
+                    toolContext: {
+                        ...toolContext,
+                        provider: AiProvider.OLLAMA,
+                        runtimeTarget: target,
+                    },
+                    toolMemory,
+                    adapter,
+                    appendTargets: [messages],
+                });
 
-                continue;
+                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,
+                    });
                 }
 
-            console.log("MESSAGES", JSON.stringify(request.messages));
+                return {shouldContinue: true};
-            const response = await ollama.chat({
+            }
+
+            aiLog("debug", "ollama.stream.messages", {
+                round,
+                messageCount: request.messages?.length ?? 0,
+            });
+            const response = await runSingleModelRequest({
+                execute: () => adapter.callModel(request, () => ollama.chat({
                     ...request,
                     stream: true
+                })),
             });
 
             aiLog("debug", "ollama.stream.open", {round});
@@ -329,14 +343,16 @@ export async function runOllama(
             if (signal.aborted) abortOllamaResponse();
             try {
                 for await (const chunk of response) {
-                    console.log("OLLAMA_CHUNK: ", chunk);
+                    aiLog("trace", "ollama.stream.chunk", {
+                        round,
+                        contentPreview: chunk.message.content?.slice(0, 240),
+                        hasToolCalls: !!chunk.message.tool_calls?.length,
+                        hasThinking: !!chunk.message.thinking,
+                    });
 
                     const localToolCalls: ToolCallData[] = [];
 
-                    localToolCalls.push(...normalizeOllamaToolCalls(
+                    localToolCalls.push(...adapter.extractStreamingToolCalls(chunk.message));
-                        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();
@@ -356,13 +372,10 @@ export async function runOllama(
                     }
 
                     if (!(chunk.message?.thinking && streamMessage.getStatus() !== Environment.reasoningText)) {
-                        streamMessage.append(chunk.message?.content ?? "");
+                        streamMessage.append(adapter.extractTextDelta(chunk));
                     }
 
-                    calls.push(...normalizeOllamaToolCalls(
+                    calls.push(...adapter.extractStreamingToolCalls(chunk.message));
-                        chunk.message?.tool_calls as readonly OllamaToolCallLike[] | undefined,
-                        round,
-                    ));
 
                     if (chunk.done) {
                         aiLog("debug", "ollama.stream.done", {
@@ -395,7 +408,7 @@ export async function runOllama(
                     duration: aiLogDuration(runnerStartedAt),
                 });
 
-                break;
+                return {shouldContinue: false};
             }
 
             calls.splice(0, calls.length, ...dedupeToolCalls(calls));
@@ -418,7 +431,31 @@ export async function runOllama(
                 })),
             });
 
-            const toolResults = await executeToolBatch(calls, streamMessage, toolContext, toolMemory);
+            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,
+                });
+            }
 
             let successGetNoteFileResult: GetNoteFileResult | undefined = undefined;
 
@@ -436,18 +473,25 @@ 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(path.join(notesDir, successGetNoteFileResult.attachment.relativePath)),
+                    document: fs.createReadStream(attachmentPath),
                 }).catch(logError);
             }
 
-            appendOllamaToolResults(messages, calls, toolResults);
+            return {shouldContinue: true};
-        }
+        },
+        });
     } finally {
         if (interval) clearInterval(interval);
+        await adapter.finalize().catch(() => undefined);
     }
 }

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

@@ -0,0 +1,419 @@
+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

@@ -1,7 +1,6 @@
-// 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 {getOpenAITools} from "./tool-mappers";
 import {TelegramStreamMessage} from "./telegram-stream-message";
 import {ToolRuntimeContext} from "./tools/runtime";
 import {OpenAIChatMessage} from "./openai-chat-message";
@@ -11,45 +10,41 @@ import type {
     ResponseInputItem,
     ResponseStreamEvent
 } from "openai/resources/responses/responses";
-import type {
+import {createOpenAiClient} from "./ai-runtime-target";
-    ChatCompletionCreateParamsNonStreaming,
-    ChatCompletionCreateParamsStreaming
-} from "openai/resources/chat/completions";
-import {createGeminiOpenAiClient, createOpenAiClient} from "./ai-runtime-target";
 import {aiLog, aiLogDuration, aiLogMessageIdentity, aiLogProviderTarget, aiLogToolCall} from "../logging/ai-logger";
+import {buildUserMemoryPrompt} from "./tools/user-memory.js";
 
 import {
     AsyncIterableStream,
-    collectOpenAiResponseFunctionCalls,
+    buildSystemInstruction,
     collectOpenAiResponseCodeInterpreterCalls,
     collectOpenAiResponseImages,
     collectOpenAiResponseText,
-    executeToolBatch,
-    getOpenAIResponsesToolsWithImage,
-    isRecord,
     MAX_TOOL_ROUNDS,
     OPENAI_IMAGE_PARTIALS,
-    OpenAiChatCompletionResponseLike,
-    OpenAiChatCompletionStreamChunkLike,
-    OpenAiChatToolCallLike,
-    OpenAiCompatibleChatMessage,
-    OpenAiCompatibleContentPart,
     openAiResponseItemCallId,
     OpenAiResponseLike,
     OpenAiResponseOutputItem,
-    roundStatus,
     RuntimeConfigSnapshot,
     safeJsonParseObject,
     showOpenAiGeneratedImage,
-    StreamingToolCallAccumulator,
     ToolCallData,
-    ToolExecutionMemory
+    ToolExecutionMemory,
+    allToolSchemaNames
 } from "./unified-ai-runner.shared";
-import {GetNoteFileResult, GetNoteFileResultSchema} from "./tools/send-note-as-file";
+import {executeToolBatchWithAdapter} from "./tool-batch-runner";
-import {bot, notesDir} from "../index";
+import {decideToolLoopContinuation} from "./tool-loop-control";
-import fs from "node:fs";
+import {runToolLoopRounds} from "./tool-loop-runner";
-import path from "node:path";
+import {runSingleModelRequest} from "./model-call-stage";
+import {ensureToolsSelected} 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 {tryToUploadFiles} from "./openai-upload-files.js";
 
 export async function runOpenAi(
     msg: Message,
@@ -57,18 +52,30 @@ export async function runOpenAi(
     streamMessage: TelegramStreamMessage,
     signal: AbortSignal,
     stream: boolean,
-    firstRoundStatus: string,
     sourceMessage: Message,
     config: RuntimeConfigSnapshot,
     toolContext: ToolRuntimeContext,
-    think?: boolean
+    downloads: AiDownloadedFile[] = [],
+    documentRag?: OpenAiDocumentRagContext,
 ): Promise<void> {
-    // TODO: 13.05.2026: remove
-    firstRoundStatus;
-    think;
     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),
+    );
 
     aiLog("info", "openai.run.start", {
         stream,
@@ -81,18 +88,51 @@ export async function runOpenAi(
 
     const toolMemory: ToolExecutionMemory = new Map();
 
-    for (let round = 0; round < MAX_TOOL_ROUNDS; round++) {
+    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;
+                })();
 
             if (!stream) {
                 const request: ResponseCreateParamsNonStreaming = {
                     model: config.openAiChatTarget.model,
                     input: responseInput as ResponseInputItem[],
-                tools: getOpenAIResponsesToolsWithImage(config) as ResponseCreateParamsNonStreaming["tools"],
+                    tools: requestTools as ResponseCreateParamsNonStreaming["tools"],
-                instructions: config.systemPrompt,
+                    instructions: systemPrompt,
                 };
-            const response = await openAi.responses.create(request, {signal}) as unknown as OpenAiResponseLike;
+                const response = await runSingleModelRequest({
+                    execute: () => adapter.callModel(request, () => openAi.responses.create(request, {signal})),
+                }) as OpenAiResponseLike;
 
                 const responseText = collectOpenAiResponseText(response);
                 streamMessage.append(responseText);
@@ -129,57 +169,70 @@ export async function runOpenAi(
                     });
                 }
 
-            const calls = collectOpenAiResponseFunctionCalls(response);
+                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.callId,
+                        id: call.id,
                         name: call.name,
                         arguments: safeJsonParseObject(call.argumentsText)
                     })),
                 });
-            if (!calls.length) return;
+                if (!calls.length) return {shouldContinue: false};
 
                 const toolCalls = calls.map(call => ({
-                id: call.callId,
+                    id: call.id,
                     name: call.name,
                     argumentsText: call.argumentsText,
                 }));
-            const toolResults = await executeToolBatch(toolCalls, streamMessage, toolContext, toolMemory);
+                const toolOutputs: Array<{type: "function_call_output"; call_id: string; output: string}> = [];
-
+                const toolResults = await executeToolBatchWithAdapter({
-            let successGetNoteFileResult: GetNoteFileResult | undefined = undefined;
+                    userId: msg.from?.id,
-
+                    toolCalls,
-            for (const toolResult of toolResults) {
+                    streamMessage,
-                try {
+                    toolContext: {
-                    const raw = JSON.parse(toolResult);
+                        ...toolContext,
-                    const res = GetNoteFileResultSchema.safeParse(raw);
+                        provider: AiProvider.OPENAI,
-
+                        runtimeTarget: config.openAiChatTarget,
-                    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)),
+                    toolMemory,
-                }).catch(logError);
+                    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,
+                    });
                 }
 
-            const toolOutputs = calls.map((call, index) => ({
-                type: "function_call_output" as const,
-                call_id: call.callId,
-                output: toolResults[index] ?? "",
-            }));
                 responseInput = [...responseInput, ...(response.output ?? []), ...toolOutputs];
-            continue;
+                return {shouldContinue: true};
             }
 
             let completedResponse: OpenAiResponseLike | null = null;
@@ -187,10 +240,13 @@ export async function runOpenAi(
                 model: config.openAiChatTarget.model,
                 input: responseInput as ResponseInputItem[],
                 stream: true,
-            tools: getOpenAIResponsesToolsWithImage(config) as ResponseCreateParamsStreaming["tools"],
+                tools: requestTools as ResponseCreateParamsStreaming["tools"],
-            parallel_tool_calls: true
+                parallel_tool_calls: true,
+                instructions: systemPrompt
             };
-        const response = await openAi.responses.create(request, {signal}) as unknown as AsyncIterableStream<ResponseStreamEvent>;
+            const response = await runSingleModelRequest({
+                execute: () => adapter.callModel(request, () => openAi.responses.create(request, {signal})),
+            }) as AsyncIterableStream<ResponseStreamEvent>;
 
             aiLog("debug", "openai.stream.open", {round});
 
@@ -200,7 +256,7 @@ export async function runOpenAi(
 
                 switch (event.type) {
                     case "response.output_text.delta":
-                    streamMessage.append(event.delta ?? "");
+                        streamMessage.append(adapter.extractTextDelta(event));
                         break;
                     case "response.image_generation_call.in_progress":
                         streamMessage.setStatus(Environment.startingImageGenText);
@@ -226,6 +282,15 @@ export async function runOpenAi(
                         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"]));
@@ -239,14 +304,11 @@ export async function runOpenAi(
                     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 };
+                            const streamedCalls = adapter.extractStreamingToolCalls(event);
-                        localToolCalls.push({
+                            if (streamedCalls.length) {
-                            id: openAiResponseItemCallId(item),
+                                localToolCalls.push(...streamedCalls);
-                            name: item.name ?? "",
+                            }
-                            argumentsText: item.arguments ?? "{}",
-                        });
-
                             aiLog("info", "openai.stream.tool_call.added", {
                                 round,
                                 toolCalls: localToolCalls.map(aiLogToolCall)
@@ -277,7 +339,7 @@ export async function runOpenAi(
                         break;
 
                     case "response.completed":
-                    completedResponse = event.response as unknown as OpenAiResponseLike;
+                        completedResponse = event.response as OpenAiResponseLike;
                         break;
                     case "response.failed":
                         throw new Error(event.response?.error?.message ?? "OpenAI response failed");
@@ -321,290 +383,190 @@ export async function runOpenAi(
                 });
             }
 
-        const calls = collectOpenAiResponseFunctionCalls(completedResponse);
+            const calls = adapter.extractToolCalls(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,
+                    id: call.id,
                     name: call.name,
                     arguments: safeJsonParseObject(call.argumentsText)
                 })),
             });
-        if (!calls.length) return;
+            if (!calls.length) return {shouldContinue: false};
 
             const toolCalls = calls.map(call => ({
-            id: call.callId,
+                id: call.id,
                 name: call.name,
                 argumentsText: call.argumentsText,
             }));
-        const toolResults = await executeToolBatch(toolCalls, streamMessage, toolContext, toolMemory);
+            const toolOutputs: Array<{type: "function_call_output"; call_id: string; output: string}> = [];
-
+            const toolResults = await executeToolBatchWithAdapter({
-        let successGetNoteFileResult: GetNoteFileResult | undefined = undefined;
+                userId: msg.from?.id,
-
+                toolCalls,
-        for (const toolResult of toolResults) {
+                streamMessage,
-            try {
+                toolContext: {
-                const raw = JSON.parse(toolResult);
+                    ...toolContext,
-                const res = GetNoteFileResultSchema.safeParse(raw);
+                    provider: AiProvider.OPENAI,
-
+                    runtimeTarget: config.openAiChatTarget,
-                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)),
+                toolMemory,
-            }).catch(logError);
+                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,
+                });
             }
 
-        const toolOutputs = calls.map((call, index) => ({
-            type: "function_call_output",
-            call_id: call.callId,
-            output: toolResults[index] ?? "",
-        }));
             responseInput = [...responseInput, ...(completedResponse.output ?? []), ...toolOutputs];
-    }
+            return {shouldContinue: true};
-}
+        },
-
+        });
-
+    } finally {
-function openAiResponseContentToText(content: unknown): string {
+        if (ownsDocumentRag) {
-    if (typeof content === "string") return content;
+            await preparedDocumentRag?.cleanup().catch(logError);
-    if (!Array.isArray(content)) return "";
+        }
-    return content.map(part => isRecord(part) ? part.text ?? part.content ?? part.refusal ?? "" : "").join("");
+        await adapter.finalize().catch(logError);
-}
+    }
-
+}
-function openAiResponseMessagesToChatCompletions(messages: OpenAIChatMessage[]): OpenAiCompatibleChatMessage[] {
+
-    return messages.map((message): OpenAiCompatibleChatMessage => {
+export type OpenAiDocumentRagContext = {
-        if (message.role === "system" || message.role === "assistant") {
+    vectorStoreIds: string[];
-            return {
+    uploadedFileIds: string[];
-                role: message.role,
+    cleanup: () => Promise<void>;
-                content: openAiResponseContentToText(message.content),
+};
-            };
+
-        }
+export async function prepareOpenAiDocumentRag(openAi: OpenAI, downloads: AiDownloadedFile[]): Promise<OpenAiDocumentRagContext | undefined> {
-
+    if (!downloads.length) return undefined;
-        const content = Array.isArray(message.content)
+
-            ? message.content.map((part): OpenAiCompatibleContentPart => {
+    const vectorStore = await openAi.vectorStores.create({
-                if (isRecord(part) && part.type === "input_image") {
+        name: `tg-chat-bot-${Date.now()}`,
-                    return {
+        description: "Temporary document RAG for a single Telegram request.",
-                        type: "image_url",
+        expires_after: {
-                        image_url: {url: String(part.image_url ?? "")},
+            anchor: "last_active_at",
-                    };
+            days: 1,
-                }
-
-                return {
-                    type: "text",
-                    text: isRecord(part) && typeof part.text === "string" ? part.text : "",
-                };
-            })
-            : message.content;
-
-        return {role: "user", content};
-    });
-}
-
-function normalizeOpenAiChatToolCalls(toolCalls: OpenAiChatToolCallLike[] = []): ToolCallData[] {
-    return toolCalls.map((call, i) => ({
-        id: call.id || `openai_chat_${Date.now()}_${i}`,
-        name: call.function?.name || call.name || "",
-        argumentsText: typeof call.function?.arguments === "string"
-            ? call.function.arguments
-            : JSON.stringify(call.function?.arguments ?? call.arguments ?? {}),
-    })).filter(call => call.name);
-}
-
-async function appendOpenAiChatToolResults(
-    messages: OpenAiCompatibleChatMessage[],
-    calls: ToolCallData[],
-    results: string[],
-): Promise<void> {
-    for (const [index, call] of calls.entries()) {
-        messages.push({
-            role: "tool",
-            tool_call_id: call.id,
-            content: results[index] ?? "",
-        });
-    }
-}
-
-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(),
-                // 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);
+    const uploadedFileIds: string[] = [];
 
-            let successGetNoteFileResult: GetNoteFileResult | undefined = undefined;
-
-            for (const toolResult of toolResults) {
     try {
-                    const raw = JSON.parse(toolResult);
+        for (const download of downloads) {
-                    const res = GetNoteFileResultSchema.safeParse(raw);
+            const uploaded = await openAi.files.create({
-
+                file: await toFile(download.buffer, download.fileName, {
-                    if (res.success && res.data.success) {
+                    type: download.mimeType ?? "application/octet-stream",
-                        successGetNoteFileResult = res.data;
+                }),
-                    }
+                purpose: "user_data",
-                } catch {
+            });
-                    // Not every tool result is JSON.
+            uploadedFileIds.push(uploaded.id);
-                }
         }
 
-            if (successGetNoteFileResult && "attachment" in successGetNoteFileResult) {
+        const batch = await openAi.vectorStores.fileBatches.createAndPoll(vectorStore.id, {
-                await bot.sendDocument({
+            file_ids: uploadedFileIds,
-                    chat_id: msg.chat.id,
+        });
-                    reply_parameters: {
+
-                        message_id: msg.message_id,
+        if (batch.file_counts.failed > 0) {
+            throw new Error(`OpenAI file_search failed to index ${batch.file_counts.failed} document(s).`);
+        }
+
+        return {
+            vectorStoreIds: [vectorStore.id],
+            uploadedFileIds,
+            cleanup: async () => {
+                await cleanupOpenAiDocumentRag(openAi, vectorStore.id, uploadedFileIds);
             },
-                    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(),
-            // temperature: 0.6,
-            stream: true,
-            parallel_tool_calls: true
         };
-        const response = await geminiOpenAi.chat.completions.create(request, {signal}) as unknown as AsyncIterableStream<OpenAiChatCompletionStreamChunkLike>;
+    } catch (error) {
-
+        await cleanupOpenAiDocumentRag(openAi, vectorStore.id, uploadedFileIds).catch(() => undefined);
-        aiLog("debug", "openai_compatible.stream.open", {round});
+        throw error;
-        // 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);
     }
 }
+
+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 {
+//     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") {
+//             return {
+//                 role: message.role,
+//                 content: openAiResponseContentToText(message.content),
+//             };
+//         }
+//
+//         const content = Array.isArray(message.content)
+//             ? message.content.map((part): OpenAiCompatibleContentPart => {
+//                 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 : "",
+//                 };
+//             })
+//             : message.content;
+//
+//         return {role: "user", content};
+//     });
+// }
+// function normalizeOpenAiChatToolCalls(toolCalls: OpenAiChatToolCallLike[] = []): ToolCallData[] {
+//     return toolCalls.map((call, i) => ({
+//         id: call.id || `openai_chat_${Date.now()}_${i}`,
+//         name: call.function?.name || call.name || "",
+//         argumentsText: typeof call.function?.arguments === "string"
+//             ? call.function.arguments
+//             : JSON.stringify(call.function?.arguments ?? call.arguments ?? {}),
+//     })).filter(call => call.name);
+// }
+// async function appendOpenAiChatToolResults(
+//     messages: OpenAiCompatibleChatMessage[],
+//     calls: ToolCallData[],
+//     results: string[],
+// ): Promise<void> {
+//     for (const [index, call] of calls.entries()) {
+//         messages.push({
+//             role: "tool",
+//             tool_call_id: call.id,
+//             content: results[index] ?? "",
+//         });
+//     }
+// }

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

@@ -1,41 +1,40 @@
 import {Message} from "typescript-telegram-bot-api";
 import * as fs from "node:fs";
-import {Blob} from "node:buffer";
 import path from "node:path";
-import {AiProvider} from "../model/ai-provider";
+import type {BoundaryValue} from "../common/boundary-types";
-import {Environment} from "../common/environment";
+import {AiProvider} from "../model/ai-provider.js";
-import {photoGenDir} from "../index";
+import {ToolRankerFallbackPolicy} from "../common/policies.js";
-import {collectReplyChainText, delay, logError, replyToMessage} from "../util/utils";
+import {Environment, type OpenAiBackend} from "../common/environment.js";
-import {MessageStore} from "../common/message-store";
+import {delay, logError, replyToMessage} from "../util/utils.js";
-import type {OpenAiResponseTool} from "./tool-mappers";
+import {MessageStore} from "../common/message-store.js";
-import {AiProviderName, getOpenAICodeInterpreterTool, getOpenAIResponsesTools} from "./tool-mappers";
+import type {OpenAiResponseTool} from "./tool-mappers.js";
-import {TelegramArtifactFile, TelegramStreamMessage} from "./telegram-stream-message";
+import {AiProviderName, getOpenAICodeInterpreterTool, getOpenAIResponsesTools} from "./tool-mappers.js";
-import {AiDownloadedFile} from "./telegram-attachments";
+import {TelegramArtifactFile, TelegramStreamMessage} from "./telegram-stream-message.js";
-import {getRuntimeCapabilities} from "./provider-model-runtime";
+import {AiDownloadedFile} from "./telegram-attachments.js";
-import {StoredAttachment} from "../model/stored-attachment";
+import {getRuntimeCapabilities} from "./provider-model-runtime.js";
-import {AiChatMessage, ChatMessage} from "./chat-messages-types";
+import {StoredAttachment} from "../model/stored-attachment.js";
+import {AiChatMessage, ChatMessage} from "./chat-messages-types.js";
 import {ListResponse, Ollama} from "ollama";
-import {executeToolCall, ToolRuntimeContext} from "./tools/runtime";
+import {executeToolCall, ToolRuntimeContext} from "./tools/runtime.js";
-import {MessageImagePart, MessagePart} from "../common/message-part";
+import {MessageImagePart, MessagePart} from "../common/message-part.js";
-import {KeyedAsyncLock} from "../util/async-lock";
+import {KeyedAsyncLock} from "../util/async-lock.js";
-import {type AiRequestQueueTarget} from "./provider-request-queue";
+import {type AiRequestQueueTarget} from "./provider-request-queue.js";
-import {PYTHON_INTERPRETER_TOOL_NAME, pythonInterpreterToolPrompt} from "./tools/python-interpretator";
+import {PYTHON_INTERPRETER_TOOL_NAME, pythonInterpreterToolPrompt} from "./tools/python-interpretator.js";
-import {getResponseLanguageInstruction, UserAiResponseLanguage, UserAiVoiceMode} from "../common/user-ai-settings";
+import {getResponseLanguageInstruction, UserAiResponseLanguage, UserAiVoiceMode} from "../common/user-ai-settings.js";
 import {
     isTranscribableAudioDownload,
     resolveSpeechToTextProviderForUser,
     transcribeSpeechDownloads
-} from "./speech-to-text";
+} from "./speech-to-text.js";
-import {OpenAIChatMessage} from "./openai-chat-message";
-import type {ResponseInputContent, ResponseInputMessageContentList} from "openai/resources/responses/responses";
 import type {ChatCompletionMessageParam} from "openai/resources/chat/completions";
-import type {GenerateContentParameters} from "@google/genai";
+import {MistralChatMessage} from "./mistral-chat-message.js";
-import {MistralChatMessage} from "./mistral-chat-message";
+import {prepareTelegramMarkdownV2} from "../util/markdown-v2-renderer.js";
-import {OllamaChatMessage} from "./ollama-chat-message";
+import {AiRuntimeTarget, createMistralClient, resolveAiRuntimeTarget} from "./ai-runtime-target.js";
-import {GeminiMessage} from "./gemini-chat-message";
+import {aiLog, aiLogDuration, aiLogProviderTarget, aiLogToolCall} from "../logging/ai-logger.js";
-import {prepareTelegramMarkdownV2} from "../util/markdown-v2-renderer";
+import {buildConversationSnapshot, serializeConversationSnapshot} from "./conversation-pipeline.js";
-import {AiRuntimeTarget, createMistralClient, getGeminiApiMode, resolveAiRuntimeTarget} from "./ai-runtime-target";
+import type {ResponseInputMessageContentList} from "openai/resources/responses/responses";
-import {aiLog, aiLogDuration, aiLogProviderTarget, aiLogToolCall} from "../logging/ai-logger";
+import {persistToolResultArtifactAttachment} from "./tool-result-artifact-store.js";
+import {filterUserInputStoredAttachments} from "../common/attachment-visibility.js";
 
 export type {Message} from "typescript-telegram-bot-api";
 export type {AiRuntimeTarget} from "./ai-runtime-target";
@@ -47,7 +46,6 @@ 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";
@@ -63,8 +61,6 @@ 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;
@@ -75,13 +71,19 @@ 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;
@@ -99,7 +101,7 @@ 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 `unknown` through the rest of the code.
+// but do not spread it through the rest of the code.
 export type LooseRecord = Record<string, JsonValue | object | undefined>;
 
 export type OpenAiResponsesFunctionCall = {
@@ -181,22 +183,6 @@ 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 } };
@@ -213,13 +199,11 @@ export type OpenAiChatCompletionStreamChunkLike = {
 
 export type AsyncIterableStream<T> = AsyncIterable<T>;
 
-export type GeminiGenerationRequest = GenerateContentParameters;
+export function isRecord(value: BoundaryValue): value is LooseRecord {
-
-export function isRecord(value: unknown): value is LooseRecord {
     return value !== null && typeof value === "object" && !Array.isArray(value);
 }
 
-export function toJsonValue(value: unknown): JsonValue | undefined {
+export function toJsonValue(value: BoundaryValue): JsonValue | undefined {
     if (value === null) return null;
 
     switch (typeof value) {
@@ -245,16 +229,16 @@ export function toJsonValue(value: unknown): JsonValue | undefined {
     }
 }
 
-export function toJsonObject(value: unknown): JsonObject | undefined {
+export function toJsonObject(value: BoundaryValue): JsonObject | undefined {
     const json = toJsonValue(value);
     return json !== null && typeof json === "object" && !Array.isArray(json) ? json : undefined;
 }
 
-export function asOptionalString(value: unknown): string | undefined {
+export function asOptionalString(value: BoundaryValue): string | undefined {
     return typeof value === "string" && value.trim().length > 0 ? value.trim() : undefined;
 }
 
-export function isAbortError(error: unknown): boolean {
+export function isAbortError(error: BoundaryValue): boolean {
     return error instanceof Error ? error.message.includes("Aborted") : String(error).includes("Aborted");
 }
 
@@ -267,6 +251,7 @@ export type RuntimeConfigSnapshot = {
     useSystemPrompt: boolean;
     systemPrompt?: string;
     rankerToolPrompt?: string;
+    toolRankerFallbackPolicy: ToolRankerFallbackPolicy;
 
     ollamaChatTarget: AiRuntimeTarget;
     ollamaToolRankerTarget?: AiRuntimeTarget;
@@ -283,14 +268,13 @@ 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 {
@@ -300,6 +284,7 @@ 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"),
@@ -317,16 +302,20 @@ 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"}));
@@ -336,33 +325,10 @@ 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:
@@ -382,12 +348,27 @@ 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];
+            return [
+                config.mistralChatTarget,
+                config.mistralToolRankerTarget,
+            ].filter((target): target is AiRuntimeTarget => !!target);
         case AiProvider.OPENAI:
-            return [config.openAiChatTarget];
+            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;
     }
 }
 
@@ -395,8 +376,6 @@ 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:
@@ -408,10 +387,14 @@ 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");
 }
@@ -442,8 +425,6 @@ 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:
@@ -543,13 +524,13 @@ export function addMessageAttachmentKinds(msg: Message | undefined, kinds: Set<A
     if (msg.video) kinds.add("video");
 }
 
-export async function collectStoredReplyChainAttachments(msg: Message, limit: number = 1): Promise<StoredAttachment[]> {
+export async function collectStoredReplyChainAttachments(msg: Message, limit: number = 40): 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 current?.attachments ?? []) {
+        for (const attachment of filterUserInputStoredAttachments(current?.attachments ?? [])) {
             const key = [
                 attachment.kind,
                 attachment.fileUniqueId || attachment.fileId,
@@ -569,13 +550,6 @@ 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;
 }
 
@@ -648,7 +622,6 @@ 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),
@@ -712,7 +685,7 @@ export function parseToolArgumentsObject(argumentsText?: string): ToolArgumentsP
     }
 }
 
-export function errorMessage(error: unknown): string {
+export function errorMessage(error: BoundaryValue): string {
     return error instanceof Error ? error.message : String(error);
 }
 
@@ -803,191 +776,30 @@ 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 storedMsg = await MessageStore.get(msg.chat.id, msg.message_id);
-    const messageParts = await collectReplyChainText({triggerMsg: storedMsg, downloads: downloads});
-
-    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 snapshot = await buildConversationSnapshot(
+        msg,
+        textOverride,
+        downloads,
+        config,
+        runtimeTarget,
+        responseLanguage,
+        includePythonToolPrompt,
+    );
 
-    const getContent = (part: MessagePart): string => {
+    return serializeConversationSnapshot(snapshot, provider, Environment.USE_NAMES_IN_PROMPT);
-        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> {
@@ -1026,7 +838,7 @@ export async function transcribeAudioIfNeeded(provider: AiProvider, userId: numb
         });
         return transcript;
     } catch (e) {
-        aiLog("error", "speech_to_text.failed", {duration: aiLogDuration(startedAt), error: e});
+        aiLog("error", "speech_to_text.failed", {duration: aiLogDuration(startedAt), error: e instanceof Error ? e : String(e)});
         throw e;
     }
 }
@@ -1043,20 +855,11 @@ 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");
@@ -1065,11 +868,6 @@ 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") {
@@ -1085,8 +883,7 @@ 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 record: Record<string, unknown> = part;
+            const partType = (part as {type?: string}).type;
-            const partType = record["type"];
 
             return partType === "input_text" || partType === "input_image";
         });
@@ -1109,8 +906,8 @@ 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});
+        aiLog("error", "mistral.library.delete.failed", {libraryId, duration: aiLogDuration(startedAt), error: e instanceof Error ? e : String(e)});
-        logError(e);
+        logError(e instanceof Error ? e : String(e));
     }
 }
 
@@ -1261,7 +1058,7 @@ export async function prepareMistralDocuments(downloads: AiDownloadedFile[], mes
         aiLog("error", "mistral.documents.prepare.failed", {
             libraryId,
             duration: aiLogDuration(startedAt),
-            error: e,
+            error: e instanceof Error ? e : String(e),
         });
         await deleteMistralLibrary(libraryId, target);
         throw e;
@@ -1269,6 +1066,7 @@ export async function prepareMistralDocuments(downloads: AiDownloadedFile[], mes
 }
 
 export async function executeTool(
+    userId: number | undefined | null,
     toolCall: ToolCallData,
     message: TelegramStreamMessage,
     context: ToolRuntimeContext,
@@ -1298,7 +1096,7 @@ export async function executeTool(
     }
 
     try {
-        const rawResult = await executeToolCall(toolCall.name, parsedArgs.args, context);
+        const rawResult = await executeToolCall(userId, toolCall.name, parsedArgs.args, context);
         const result = stringifyToolExecutionResult(rawResult);
 
         await sendToolArtifacts(toolCall, result, message);
@@ -1311,35 +1109,47 @@ export async function executeTool(
 
         return result;
     } catch (error) {
-        if (isAbortError(error)) {
+        if (isAbortError(error instanceof Error ? error : String(error))) {
             throw error;
         }
 
-        const result = toolFailureResult("execution_failed", errorMessage(error));
+        const result = toolFailureResult("execution_failed", errorMessage(error instanceof Error ? error : String(error)));
 
         aiLog("error", "tool.failed.returned_to_model", {
             name: toolCall.name,
             duration: aiLogDuration(startedAt),
-            error,
+            error: error instanceof Error ? error : String(error),
         });
 
         return result;
     }
 }
 
-export function toolResourceKeys(toolCall: ToolCallData): string[] {
+export function toolResourceKeys(toolCall: ToolCallData, userId?: number | undefined | null): 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":
@@ -1367,16 +1177,18 @@ export async function runWithToolLocks<T>(keys: string[], task: () => Promise<T>
 }
 
 export async function executeScheduledTool(
+    userId: number | undefined | null,
     toolCall: ToolCallData,
     message: TelegramStreamMessage,
     context: ToolRuntimeContext,
 ): Promise<string> {
-    const keys = toolResourceKeys(toolCall);
+    const keys = toolResourceKeys(toolCall, userId);
-    if (!keys.length) return executeTool(toolCall, message, context);
+    if (!keys.length) return executeTool(userId, toolCall, message, context);
-    return runWithToolLocks(keys, () => executeTool(toolCall, message, context));
+    return runWithToolLocks(keys, () => executeTool(userId, toolCall, message, context));
 }
 
 export async function executeToolBatch(
+    userId: number | undefined | null,
     toolCalls: ToolCallData[],
     message: TelegramStreamMessage,
     context: ToolRuntimeContext,
@@ -1417,7 +1229,7 @@ export async function executeToolBatch(
         message.setStatus(Environment.getUseToolText(statusCalls));
         await message.flush();
 
-        const resultText = await executeScheduledTool(toolCall, message, context);
+        const resultText = await executeScheduledTool(userId, toolCall, message, context);
 
         memory.set(signature, {
             count: (previous?.count ?? 0) + 1,
@@ -1451,6 +1263,33 @@ 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,
@@ -1462,7 +1301,7 @@ export async function executeToolBatch(
         aiLog("error", "tool.batch.failed", {
             count: toolCalls.length,
             duration: aiLogDuration(startedAt),
-            error: e,
+            error: e instanceof Error ? e : String(e),
         });
 
         throw e;
@@ -1479,7 +1318,7 @@ export function appendOllamaToolResults(messages: ChatMessage[], calls: ToolCall
     }
 }
 
-export function stringifyToolExecutionResult(result: unknown): string {
+export function stringifyToolExecutionResult(result: BoundaryValue): string {
     if (typeof result === "string") return result;
     const json = JSON.stringify(toJsonValue(result) ?? String(result));
     return json ?? String(result);
@@ -1487,7 +1326,7 @@ export function stringifyToolExecutionResult(result: unknown): string {
 
 export type ToolExecutionMemory = Map<string, { count: number; result: string }>;
 
-export function stableJsonStringify(value: unknown): string {
+export function stableJsonStringify(value: BoundaryValue): string {
     if (Array.isArray(value)) {
         return `[${value.map(stableJsonStringify).join(",")}]`;
     }
@@ -1602,14 +1441,14 @@ export type NormalizedRouterPlan = {
     m: string; // Missing
 };
 
-export function toolSchemaName(tool: unknown): string | 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;
+    const directName = fn?.name ?? tool.name ?? (typeof tool.type === "string" && tool.type !== "function" ? tool.type : undefined);
     return asOptionalString(directName);
 }
 
-export function toolSchemaNames(tool: unknown): string[] {
+export function toolSchemaNames(tool: BoundaryValue): string[] {
     if (!isRecord(tool)) return [];
 
     if (Array.isArray(tool.functionDeclarations)) {
@@ -1622,13 +1461,17 @@ export function toolSchemaNames(tool: unknown): string[] {
     return name ? [name] : [];
 }
 
-export function allToolSchemaNames(tools: readonly unknown[]): string[] {
+export function allToolSchemaNames(tools: readonly BoundaryValue[]): string[] {
     return [...new Set(tools.flatMap(toolSchemaNames))];
 }
 
-export function getOpenAIResponsesToolsWithImage(config: RuntimeConfigSnapshot): Array<OpenAiResponseTool | LooseRecord> {
+export function getOpenAIResponsesToolsWithImage(
-    return [
+    config: RuntimeConfigSnapshot,
-        ...getOpenAIResponsesTools(),
+    forCreator?: boolean,
+    vectorStoreIds: string[] = [],
+): Array<OpenAiResponseTool | LooseRecord> {
+    const tools: Array<OpenAiResponseTool | LooseRecord> = [
+        ...getOpenAIResponsesTools(forCreator),
         getOpenAICodeInterpreterTool(),
         {
             type: "image_generation",
@@ -1638,8 +1481,17 @@ export function getOpenAIResponsesToolsWithImage(config: RuntimeConfigSnapshot):
             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 {
@@ -1667,7 +1519,7 @@ export type OpenAiCodeInterpreterCall = {
     code: string | null;
     containerId: string;
     status: string;
-    outputs: Array<{type?: "logs" | "image"; logs?: string; url?: string}>;
+    outputs: Array<{ type?: "logs" | "image"; logs?: string; url?: string }>;
 };
 
 export function collectOpenAiResponseCodeInterpreterCalls(response: OpenAiResponseLike): OpenAiCodeInterpreterCall[] {
@@ -1677,7 +1529,7 @@ export function collectOpenAiResponseCodeInterpreterCalls(response: OpenAiRespon
             id: item.id!,
             code: item.code ?? null,
             containerId: item.container_id!,
-            status: item.status ?? "unknown",
+            status: item.status ?? "unrecognized",
             outputs: Array.isArray(item.outputs) ? item.outputs : [],
         }));
 }
@@ -1688,11 +1540,16 @@ export function collectOpenAiResponseImages(response: OpenAiResponseLike): strin
         .map(item => item.result!);
 }
 
-export function writeOpenAiGeneratedImage(sourceMessage: Message, b64: string, label: string): Buffer {
+export function writeOpenAiGeneratedImage(sourceMessage: Message, b64: string, label: string): {
-    const imageBuffer = Buffer.from(b64, "base64");
+    buffer: Buffer;
+    cachePath: string;
+    fileName: string;
+} {
+    const buffer = Buffer.from(b64, "base64");
     const fileName = `${sourceMessage.chat.id}_${sourceMessage.message_id}_${Date.now()}_${label}.png`;
-    fs.writeFileSync(path.join(photoGenDir, fileName), imageBuffer);
+    const cachePath = path.join(photoGenDir(), fileName);
-    return imageBuffer;
+    fs.writeFileSync(cachePath, buffer);
+    return {buffer, cachePath, fileName};
 }
 
 export async function showOpenAiGeneratedImage(
@@ -1703,14 +1560,21 @@ export async function showOpenAiGeneratedImage(
     status: string,
     final: boolean,
 ): Promise<void> {
-    const imageBuffer = writeOpenAiGeneratedImage(sourceMessage, b64, label);
+    const image = writeOpenAiGeneratedImage(sourceMessage, b64, label);
+    const attachment: StoredAttachment = {
+        kind: "image",
+        fileId: image.cachePath,
+        fileName: image.fileName,
+        mimeType: "image/png",
+        cachePath: image.cachePath,
+    };
     if (final && !streamMessage.getText().trim()) {
         streamMessage.replaceText(status);
         streamMessage.clearStatus();
     } else {
         streamMessage.setStatus(status);
     }
-    await streamMessage.showImage(imageBuffer);
+    await streamMessage.showImage(image.buffer, attachment);
 }
 
 export function openAiResponseItemCallId(item: OpenAiResponseOutputItem & { id?: string }): string {

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

@@ -1,219 +1,248 @@
-import {Tool} from "ollama";
+import type {ChatCompletionCreateParamsNonStreaming, ChatCompletionMessageParam} from "openai/resources/chat/completions";
-import {createOllamaClient} from "./ai-runtime-target";
+import {ChatRequest} from "ollama";
-import {aiLog, aiLogDuration, aiLogProviderTarget} from "../logging/ai-logger";
+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 {
-    allToolSchemaNames,
+    buildRankerContext,
-    isRecord,
+    buildRankerTarget,
-    RuntimeConfigSnapshot,
+    buildToolRankerPrompt,
-    toolSchemaNames
+    filterRankedTools,
-} from "./unified-ai-runner.shared";
+    ToolRankerSelection,
-import {z} from "zod";
+} from "./tool-ranker-pipeline.js";
-import {PYTHON_INTERPRETER_TOOL_NAME} from "./tools/python-interpretator";
+import {allToolSchemaNames} from "./unified-ai-runner.shared.js";
+import {sanitizeToolRankerResult} from "./tool-ranker-metadata.js";
+import {resolveToolRankerFallbackSelection} from "./tool-ranker-fallback.js";
 
-export type ToolRankerSelection = {
+export class ToolRanker {
-    tools: Tool[];
-    usedRanker: boolean;
-};
-
-export class OllamaToolRanker {
     constructor(private readonly config: RuntimeConfigSnapshot) {
     }
 
     async selectTools(args: {
+        provider: AiProvider;
         userQuery: string;
-        availableTools: Tool[];
+        availableTools: readonly BoundaryValue[];
         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, round, signal, userQuery} = args;
+        const {availableTools, provider, round, signal, userQuery} = args;
-        const target = this.config.ollamaToolRankerTarget;
+        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);
 
         if (!availableTools.length) {
-            return {tools: [], usedRanker: false};
+            return {toolNames: [], usedRanker: false};
         }
 
-        // Ranker disabled/unconfigured: keep old behavior and expose all allowed tools.
+        const target = configuredTarget ?? (fallbackPolicy === ToolRankerFallbackPolicy.MAIN_MODEL ? mainModelTarget : undefined);
-        if (!target?.model) {
+
-            return {
+        if (!target) {
-                tools: availableTools,
+            return resolveToolRankerFallbackSelection({
-                usedRanker: false,
+                fallbackPolicy,
-            };
+                availableToolNames: availableNames,
+            });
         }
 
         const startedAt = Date.now();
-        const availableNames = new Set(allToolSchemaNames(availableTools));
+        const ranker = buildToolRankerPrompt(buildRankerContext(this.config, provider, target, round, userQuery, availableTools));
-        // const prompt = this.config.rankerToolPrompt?.trim() || DEFAULT_TOOL_RANKER_PROMPT;
 
-        const availableToolNames = availableTools.map(t => "- " + (t.function.name ?? ""));
+        aiLog("debug", "tool_ranker.start", {
-
+            provider,
-        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],
+            availableTools: availableNames,
+            fallbackPolicy,
+            usedMainModelFallback: !configuredTarget && fallbackPolicy === ToolRankerFallbackPolicy.MAIN_MODEL,
         });
 
         try {
-            const ollama = createOllamaClient(target);
+            if (signal.aborted) throw new Error("Aborted");
-            // const response = await ollama.chat({
+            const raw = await runRanker(provider, target, ranker.prompt, userQuery);
-            //     model: target.model,
+            if (signal.aborted) throw new Error("Aborted");
-            //     messages: [
+            const selectedNames = sanitizeToolRankerResult({
-            //         {role: "system", content: prompt},
+                raw,
-            //         {
+                availableToolNames: availableNames,
-            //             role: "user",
+            });
-            //             content: JSON.stringify({
+            const filtered = filterRankedTools(availableTools, selectedNames);
-            //                 q: userQuery,
+            const toolNames = allToolSchemaNames(filtered);
-            //                 tools: toolsForPrompt,
-            //             }),
-            //         },
-            //     ],
-            //     stream: false,
-            //     options: {
-            //         temperature: 0,
-            //         num_ctx: 8192,
-            //     },
-            // });
 
-            const then = performance.now();
+            aiLog("debug", "tool_ranker.done", {
+                provider,
+                round,
+                duration: aiLogDuration(startedAt),
+                selectedNames,
+                selectedCount: toolNames.length,
+                rawPreview: raw.slice(0, 800),
+            });
 
-            const response = await ollama.chat({
+            return {toolNames, usedRanker: true};
-                model: target?.model ?? "",
+        } catch (error) {
-                messages: [
+            if (error instanceof Error && error.message.includes("Aborted")) throw error;
-                    {
+            let failureMessage = error instanceof Error ? error.message : String(error);
-                        role: "system",
+
-                        content: toolRouterPrompt()
+            const canRetryOnMainModel = fallbackPolicy === ToolRankerFallbackPolicy.MAIN_MODEL
-                    },
+                && (
-                    {
+                    target.model !== mainModelTarget.model
-                        role: "user",
+                    || !sameRuntimeEndpoint(target, mainModelTarget)
-                        content: userQuery,
+                );
+
+            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,
+                round,
+                target: aiLogProviderTarget(target),
+                fallbackPolicy,
+                duration: aiLogDuration(startedAt),
+                errorSummary: failureMessage,
+            });
+
+            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,
+                    stream: false as const,
                     think: false,
-                format: routerSchema,
+                    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
+                        num_predict: 256,
                     },
-            });
+                } satisfies ChatRequest & { stream: false };
 
-            const now = performance.now();
+                const response = await ollama.chat(request);
-            const diff = now - then;
+                return response.message?.content?.trim() ?? "";
-            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);
             }
-
+            case AiProvider.MISTRAL: {
-            const selectedNameSet = new Set(selectedNames);
+                const mistral = createMistralClient(target);
-            const tools = availableTools.filter(tool => toolSchemaNames(tool).some(name => selectedNameSet.has(name)));
+                const request: Parameters<typeof mistral.chat.complete>[0] = {
-
+                    model: target.model,
-            aiLog("debug", "ollama.tool_ranker.done", {
+                    messages: [
-                round,
+                        {role: "system", content: prompt},
-                duration: aiLogDuration(startedAt),
+                        {role: "user", content: userQuery},
-                selectedNames,
+                    ],
-                selectedCount: tools.length,
+                    temperature: 0,
-                rawPreview: raw.slice(0, 800),
-            });
-
-            // 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 (String(error).includes("Aborted")) throw error;
-
-            aiLog("warn", "ollama.tool_ranker.failed.fallback_all_allowed", {
-                round,
-                target: aiLogProviderTarget(target),
-                duration: aiLogDuration(startedAt),
-                error,
-            });
-
-            // 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,
                 };
+                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[];
 
-export function latestUserTextFromOllamaMessages(messages: readonly { role?: string; content?: unknown }[]): string {
+                // OpenAI-compatible servers often reject `response_format`, so keep JSON mode
-    for (let i = messages.length - 1; i >= 0; i--) {
+                // only for official OpenAI endpoints.
-        const message = messages[i];
+                const request: ChatCompletionCreateParamsNonStreaming = {
-        if (message?.role !== "user") continue;
+                    model: target.model,
-        if (typeof message.content === "string") return message.content;
+                    messages,
-        if (Array.isArray(message.content)) {
+                };
-            return message.content
+
-                .map(part => isRecord(part) && typeof part.text === "string" ? part.text : "")
+                if (!target.baseUrl) {
-                .filter(Boolean)
+                    // gpt-5 family ranker targets reject temperature=0; use the model default instead.
-                .join("\n");
+                    request.response_format = {type: "json_object"};
+                }
+
+                const response = await openAi.chat.completions.create(request);
+
+                return response.choices[0]?.message?.content?.trim() ?? "";
+            }
         }
     }
-    return "";
 }

src/ai/unified-ai-runner.ts

@@ -5,52 +5,37 @@ 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 {GeminiMessage} from "./gemini-chat-message";
 import {buildAiRegenerateCallbackData} from "./regenerate-callback";
-import {createOllamaClient, getGeminiApiMode} from "./ai-runtime-target";
 import {aiLog, aiLogDuration, aiLogMessageIdentity, aiLogProviderTarget} from "../logging/ai-logger";
 
-import {runOpenAi, runOpenAiCompatibleChat} from "./unified-ai-runner.openai";
-import {runOllama} from "./unified-ai-runner.ollama";
-import {runMistral} from "./unified-ai-runner.mistral";
-import {runGemini} from "./unified-ai-runner.gemini";
 import {
     AI_REQUEST_TIMEOUT_MS,
-    appendTranscriptToChatMessages,
     collectCachedMessageAttachments,
     collectRequestedAttachmentKinds,
-    collectTextMessages,
-    deleteMistralLibrary,
     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";
 
 export type {ToolCallData} from "./unified-ai-runner.shared";
 export {snapshotModel, providerTargets, ollamaModelNames} from "./unified-ai-runner.shared";
@@ -61,9 +46,11 @@ async function executeUnifiedAiRequest(
     downloads: AiDownloadedFile[],
     controller: AbortController,
     streamMessage: TelegramStreamMessage,
-): Promise<{ mistralLibraryId?: string }> {
+): Promise<void> {
     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,
@@ -79,139 +66,48 @@ async function executeUnifiedAiRequest(
         })),
     });
 
-    const {
+    preparedRequest = await prepareUnifiedAiRequestPipeline({
-        chatMessages,
+        options,
-        imageCount
-    } = await collectTextMessages(
-        options.msg,
-        options.text,
-        options.provider,
-        downloads,
         config,
-        options.responseLanguage ?? DEFAULT_AI_RESPONSE_LANGUAGE,
+        downloads,
-    );
+        streamMessage,
-    const firstRoundStatus = initialStatus(downloads, imageCount);
+        controller,
-    const toolContext = toolRuntimeContextFromDownloads(downloads);
+    });
+    if (preparedRequest.finishAfterTranscript) return;
+
     aiLog("debug", "request.messages.collected", {
+        requestId: options.requestId,
         provider: providerName(options.provider),
-        chatMessages: chatMessages.length,
+        chatMessages: preparedRequest.chatMessages.length,
-        imageCount,
+        imageCount: preparedRequest.imageCount,
-        firstRoundStatus,
+        firstRoundStatus: preparedRequest.firstRoundStatus,
-        hasToolInputFiles: !!toolContext.pythonInputFiles?.length,
+        hasToolInputFiles: !!preparedRequest.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 {
-        const preparedMistral = options.provider === AiProvider.MISTRAL
+        await runUnifiedAiResponsePipeline({
-            ? await prepareMistralDocuments(downloads, chatMessages as MistralChatMessage[], streamMessage, config.mistralChatTarget, controller.signal)
+            options,
-            : {documents: []};
+            config,
-        const documents = preparedMistral.documents;
-        mistralLibraryId = preparedMistral.libraryId;
-
-        if (options.provider === AiProvider.OLLAMA) {
-            await prepareOllamaDocumentRag({
             downloads,
-                messages: chatMessages as OllamaChatMessage[],
+            prepared: preparedRequest,
-                userQuery: options.text,
+            streamMessage,
-                message: streamMessage,
+            controller,
-                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, firstRoundStatus, options.msg, config, toolContext,
-                    !!options.think);
-                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(chatMessages as MistralChatMessage[], documents, streamMessage, controller.signal, options.stream ?? true, firstRoundStatus, config, toolContext);
-                break;
-            case AiProvider.GEMINI:
-                if (getGeminiApiMode(config.geminiChatTarget) === "openai") {
-                    await runOpenAiCompatibleChat(options.msg, chatMessages as OpenAIChatMessage[], streamMessage, controller.signal, options.stream ?? true, firstRoundStatus, config, toolContext);
-                } else {
-                    await runGemini(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,
+            mistralLibraryId: preparedRequest?.preparedDocumentRag?.provider === AiProvider.MISTRAL ? preparedRequest.preparedDocumentRag.libraryId : undefined,
         });
-        return {mistralLibraryId};
+        return;
     } catch (e) {
         aiLog("error", "request.execute.failed", {
+            requestId: options.requestId,
             provider: providerName(options.provider),
             duration: aiLogDuration(requestStartedAt),
-            error: e,
+            error: e instanceof Error ? e : String(e),
         });
-        if (mistralLibraryId) {
-            await deleteMistralLibrary(mistralLibraryId, config.mistralChatTarget);
-        }
         throw e;
     }
 }
@@ -222,9 +118,11 @@ export async function runUnifiedAi(options: UnifiedRunOptions): Promise<void> {
     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),
@@ -241,6 +139,7 @@ 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],
         });
@@ -258,6 +157,7 @@ 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;
@@ -265,12 +165,17 @@ 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,
@@ -280,17 +185,42 @@ export async function runUnifiedAi(options: UnifiedRunOptions): Promise<void> {
             : buildAiRegenerateCallbackData(options.provider, !!options.think),
         options.targetMessage,
         options.provider,
-        options.isGuestMsg
+        options.isGuestMsg,
+        imageOutputMode
     );
     cancel.onCancel = () => streamMessage.cancel(cancel.provider);
-    let mistralLibraryId: string | undefined;
     const queueTarget = resolveAiRequestQueueTarget(options, config, requestedAttachmentKinds);
-    aiLog("debug", "run.queue.target", {target: aiLogProviderTarget(queueTarget), cancelId: cancel.id});
+    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);
 
     try {
         const queueMessage = await streamMessage.start(Environment.waitThinkText);
-        setAiCancelMessageId(cancel.id, queueMessage.message_id);
+        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);
         aiLog("info", "run.queue.enter", {
+            requestId,
             cancelId: cancel.id,
             queueMessageId: queueMessage.message_id,
             target: aiLogProviderTarget(queueTarget),
@@ -299,15 +229,16 @@ export async function runUnifiedAi(options: UnifiedRunOptions): Promise<void> {
         await aiProviderRequestQueue.enqueue(queueTarget, {
             signal: controller.signal,
             onPositionChange: async requestsBefore => {
-                aiLog("debug", "run.queue.position", {cancelId: cancel.id, requestsBefore});
+                aiLog("debug", "run.queue.position", {requestId, cancelId: cancel.id, requestsBefore});
                 streamMessage.setStatus(Environment.getAiQueueText(options.provider, requestsBefore));
                 await streamMessage.flush();
             },
-            run: async () => {
+            run: async (): Promise<null> => {
                 const queueWaitFinishedAt = Date.now();
-                aiLog("info", "run.queue.dequeued", {cancelId: cancel.id});
+                aiLog("info", "run.queue.dequeued", {requestId, cancelId: cancel.id});
                 const downloads = attachmentsToDownloadedFiles(cached.attachments);
                 aiLog("debug", "run.downloads.ready", {
+                    requestId,
                     count: downloads.length,
                     downloads: downloads.map(d => ({
                         kind: d.kind,
@@ -318,37 +249,66 @@ export async function runUnifiedAi(options: UnifiedRunOptions): Promise<void> {
                     })),
                 });
                 try {
-                    const result = await executeUnifiedAiRequest(options, config, downloads, controller, streamMessage);
+                    await executeUnifiedAiRequest(options, config, downloads, controller, streamMessage);
-                    mistralLibraryId = result.mistralLibraryId;
+                    aiRequestStatus = "succeeded";
                     aiLog("success", "run.queue.task.done", {
+                        requestId,
                         cancelId: cancel.id,
                         duration: aiLogDuration(queueWaitFinishedAt),
-                        mistralLibraryId,
                     });
                 } finally {
                     cleanupDownloads(downloads);
-                    aiLog("debug", "run.downloads.cleaned", {cancelId: cancel.id, count: downloads.length});
+                    aiLog("debug", "run.downloads.cleaned", {requestId, cancelId: cancel.id, count: downloads.length});
                 }
+                return null;
             },
         });
     } catch (e) {
-        if (controller.signal.aborted || isAbortError(e)) {
+        if (controller.signal.aborted || isAbortError(e instanceof Error ? e : String(e))) {
-            aiLog("warn", "run.aborted", {cancelId: cancel.id, duration: aiLogDuration(startedAt), error: 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)});
             streamMessage.replaceText(streamMessage.getText());
             await streamMessage.finish();
         } else {
-            aiLog("error", "run.failed", {cancelId: cancel.id, duration: aiLogDuration(startedAt), error: e});
+            aiRequestStatus = "failed";
-            await streamMessage.fail(e);
+            aiRequestError = e instanceof Error ? e.message : String(e);
-            logError(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);
         }
     } finally {
         clearTimeout(timeout);
-        finishAiRequest(cancel.id);
+        await AiRequestStore.put({
-        if (mistralLibraryId) {
+            requestId,
-            aiLog("debug", "run.mistral_library.cleanup", {mistralLibraryId});
+            chatId: options.msg.chat.id,
-            await deleteMistralLibrary(mistralLibraryId, config.mistralChatTarget);
+            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);
         aiLog("success", "run.finished", {
+            requestId,
             cancelId: cancel.id,
             provider: providerName(options.provider),
             duration: aiLogDuration(startedAt),

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

@@ -0,0 +1,73 @@
+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

@@ -0,0 +1,61 @@
+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

@@ -0,0 +1,12 @@
+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

@@ -0,0 +1,16 @@
+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

@@ -0,0 +1,26 @@
+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

@@ -0,0 +1,43 @@
+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

@@ -0,0 +1,15 @@
+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

@@ -0,0 +1,6 @@
+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

@@ -0,0 +1,134 @@
+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

@@ -0,0 +1,51 @@
+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

@@ -0,0 +1,189 @@
+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

@@ -0,0 +1,233 @@
+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>;
+}