Add OpenAI compatible chat backend

.env.example

@@ -46,6 +46,15 @@ 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=
 
@@ -94,6 +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
@@ -124,6 +137,7 @@ MCP_SERVERS=
 # 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

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

@@ -7,6 +7,7 @@ Bot for Telegram with a lot of commands and AI (Ollama/Mistral/OpenAI) written i
 ```bash
 cp .env.example .env
 # Edit .env: add BOT_TOKEN, CREATOR_ID and configure optional AI models (MISTRAL_API_KEY, OPENAI_API_KEY, OLLAMA_ADDRESS)
+# For OpenAI-compatible servers (llama.cpp, etc.), set OPENAI_BACKEND=compatible and OPENAI_BASE_URL.
 # Optional: set DATABASE_URL to postgres://... for PostgreSQL or :memory: for ephemeral SQLite.
 # Optional: set DATA_PATH if you want to override the default local storage directory.
 ```
@@ -39,6 +40,13 @@ If you want to disable all built-in local tools and use only MCP tools, set:
 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`:
 
 ```bash

bun.lock

@@ -14,8 +14,8 @@
         "emoji-regex": "^10.6.0",
         "fluent-ffmpeg": "^2.1.3",
         "ollama": "^0.6.3",
-        "openai": "^6.37.0",
-        "pg": "^8.20.0",
+        "openai": "^6.38.0",
+        "pg": "^8.21.0",
         "qrcode": "^1.5.4",
         "sharp": "^0.34.5",
         "systeminformation": "^5.31.6",
@@ -27,12 +27,12 @@
         "@eslint/js": "^9.39.4",
         "@types/bun": "^1.3.14",
         "@types/fluent-ffmpeg": "^2.1.28",
-        "@types/node": "^25.8.0",
+        "@types/node": "^25.9.1",
         "@types/pg": "^8.20.0",
         "@types/qrcode": "^1.5.6",
         "eslint": "^9.39.4",
         "typescript": "^6.0.3",
-        "typescript-eslint": "^8.59.3",
+        "typescript-eslint": "^8.59.4",
       },
     },
   },
@@ -179,7 +179,7 @@
 
     "@types/json-schema": ["@types/json-schema@7.0.15", "", {}, "sha512-5+fP8P8MFNC+AyZCDxrB2pkZFPGzqQWUzpSeuuVLvm8VMcorNYavBqoFcxK8bQz4Qsbn4oUEEem4wDLfcysGHA=="],
 
-    "@types/node": ["@types/node@25.9.0", "", { "dependencies": { "undici-types": ">=7.24.0 <7.24.7" } }, "sha512-AOQwYUNolgy3VosiRqXrACUXTN8nJUtPl7FJXMqZVyxiiCLhQuG3jXKvCS1ALr+Y2OmZhzzLVlYPEqJaiqkaJQ=="],
+    "@types/node": ["@types/node@25.9.1", "", { "dependencies": { "undici-types": ">=7.24.0 <7.24.7" } }, "sha512-xfrlY7UD5rMJk3ZVJP8BNzS28J36YJg+xp+LPXV1TdWxr8uMH5A860QNxYDGQe/ylDSgjxE52Q9VnO7p75tJxg=="],
 
     "@types/pg": ["@types/pg@8.20.0", "", { "dependencies": { "@types/node": "*", "pg-protocol": "*", "pg-types": "^2.2.0" } }, "sha512-bEPFOaMAHTEP1EzpvHTbmwR8UsFyHSKsRisLIHVMXnpNefSbGA1bD6CVy+qKjGSqmZqNqBDV2azOBo8TgkcVow=="],
 

package-lock.json

@@ -30,7 +30,7 @@
         "@eslint/js": "^9.39.4",
         "@types/bun": "^1.3.14",
         "@types/fluent-ffmpeg": "^2.1.28",
-        "@types/node": "^25.9.0",
+        "@types/node": "^25.9.1",
         "@types/pg": "^8.20.0",
         "@types/qrcode": "^1.5.6",
         "eslint": "^9.39.4",
@@ -1246,9 +1246,9 @@
       "license": "MIT"
     },
     "node_modules/@types/node": {
-      "version": "25.9.0",
-      "resolved": "https://registry.npmjs.org/@types/node/-/node-25.9.0.tgz",
-      "integrity": "sha512-AOQwYUNolgy3VosiRqXrACUXTN8nJUtPl7FJXMqZVyxiiCLhQuG3jXKvCS1ALr+Y2OmZhzzLVlYPEqJaiqkaJQ==",
+      "version": "25.9.1",
+      "resolved": "https://registry.npmjs.org/@types/node/-/node-25.9.1.tgz",
+      "integrity": "sha512-xfrlY7UD5rMJk3ZVJP8BNzS28J36YJg+xp+LPXV1TdWxr8uMH5A860QNxYDGQe/ylDSgjxE52Q9VnO7p75tJxg==",
       "license": "MIT",
       "dependencies": {
         "undici-types": ">=7.24.0 <7.24.7"

package.json

@@ -35,7 +35,7 @@
     "@eslint/js": "^9.39.4",
     "@types/bun": "^1.3.14",
     "@types/fluent-ffmpeg": "^2.1.28",
-    "@types/node": "^25.9.0",
+    "@types/node": "^25.9.1",
     "@types/pg": "^8.20.0",
     "@types/qrcode": "^1.5.6",
     "eslint": "^9.39.4",

src/ai/ai-runtime-target.ts

@@ -6,7 +6,7 @@ import {AiModelCapabilities} from "../model/ai-model-capabilities.js";
 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;
@@ -24,6 +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"],
@@ -155,6 +156,25 @@ export function resolveAiRuntimeTarget(
     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 {
     return left.provider === right.provider
         && (left.baseUrl ?? "") === (right.baseUrl ?? "")

src/ai/conversation-pipeline.ts

@@ -16,6 +16,7 @@ import type {AttachmentKind, AiRuntimeTarget, RuntimeConfigSnapshot} from "./uni
 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;
@@ -267,11 +268,13 @@ function buildSystemInstruction(
     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");
 }
@@ -310,11 +313,12 @@ export async function buildConversationSnapshot(
         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),
+        systemInstruction: buildSystemInstruction(config, responseLanguage, includePythonToolPrompt, runtimeTarget.systemPromptAdditions, memoryInstruction),
     };
 }
 

src/ai/document-rag-pipeline.ts

@@ -42,6 +42,10 @@ export async function prepareDocumentRag(
     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);

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

@@ -2,6 +2,7 @@ import type {
     ResponseInputMessageContentList,
     ResponseOutputMessage,
 } from "openai/resources/responses/responses";
+import type {ChatCompletionMessageParam} from "openai/resources/chat/completions";
 
 type OpenAIInputChatMessage = {
     type: "message";
@@ -17,3 +18,5 @@ type OpenAIOutputChatMessage = {
 } & 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

@@ -14,6 +14,12 @@ function normalizeToolArguments(value: unknown): string {
     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 : [];
 
@@ -32,6 +38,86 @@ export function extractOpenAiTextDelta(input: unknown): string {
     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") {

src/ai/provider-model-runtime.ts

@@ -196,7 +196,8 @@ 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")) {

src/ai/tool-mappers.ts

@@ -3,6 +3,7 @@ import {AiProvider} from "../model/ai-provider.js";
 import {getTools} from "./tools/registry.js";
 import {WEB_SEARCH_TOOL_NAME} from "./tools/web-search.js";
 import {PYTHON_INTERPRETER_TOOL_NAME} from "./tools/python-interpretator.js";
+import {toolSchemaNames} from "./tool-schema-utils.js";
 
 export type AiProviderName = "ollama" | "openai" | "mistral";
 
@@ -26,6 +27,11 @@ export function getOpenAITools(forCreator?: boolean): AiTool[] {
     }));
 }
 
+export function getOpenAICompatibleTools(forCreator?: boolean): AiTool[] {
+    // The compatible chat.completions backend only accepts plain function tools.
+    return getOpenAITools(forCreator);
+}
+
 export type OpenAiResponseTool = {
     type: "function";
     name: string;
@@ -79,3 +85,20 @@ export function getProviderTools(provider: AiProvider, forCreator?: boolean): Ai
             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-ranker-metadata.ts

@@ -102,6 +102,100 @@ export const TOOL_RANKER_TOOL_INFOS = {
             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.",
@@ -443,6 +537,16 @@ function buildPriorityLines(tools: readonly ToolRankerToolInfo[]): string[] {
     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");

src/ai/tools/create-note.ts

@@ -1,11 +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 {asNonEmptyString} from "./utils";
+import {NOTES_HEADER, notesDir, notesRootFile} from "../../index.js";
+import {asNonEmptyString} from "./utils.js";
 import fs from "node:fs";
-import {toolsLogger} from "./tool-logger";
-import {AiJsonObject} from "../tool-types";
+import {toolsLogger} from "./tool-logger.js";
+import {AiJsonObject} from "../tool-types.js";
 
 const logger = toolsLogger.child("create-note");
 

src/ai/tools/datetime.ts

@@ -1,5 +1,5 @@
 import {AiTool} from "../tool-types";
-import {asNonEmptyString} from "./utils";
+import {asNonEmptyString} from "./utils.js";
 import {AiJsonObject} from "../tool-types";
 
 export const getCurrentDateTimeTool = {

src/ai/tools/files.ts

@@ -3,8 +3,8 @@ import fs from "node:fs";
 import path from "node:path";
 import {z} from "zod";
 
-import {Environment} from "../../common/environment";
-import {AiJsonObject, AiJsonValue, AiTool} from "../tool-types";
+import {Environment} from "../../common/environment.js";
+import {AiJsonObject, AiJsonValue, AiTool} from "../tool-types.js";
 import {
     MAX_COPY_ENTRIES,
     MAX_COPY_TOTAL_BYTES,
@@ -23,8 +23,8 @@ import {
     MAX_PATCH_SEARCH_BYTES,
     MAX_STREAM_WRITE_IDLE_MS,
     MAX_STREAM_WRITE_SESSIONS,
-} from "./limits";
-import {asBoolean, asNonEmptyString, asPositiveInt, asString} from "./utils";
+} from "./limits.js";
+import {asBoolean, asNonEmptyString, asPositiveInt, asString} from "./utils.js";
 
 // =============================================================================
 // Public types and schemas

src/ai/tools/market-rates.ts

@@ -1,7 +1,7 @@
-import {AiTool} from "../tool-types";
+import {AiTool} from "../tool-types.js";
 import axios from "axios";
-import {toolsLogger} from "./tool-logger";
-import {AiJsonObject} from "../tool-types";
+import {toolsLogger} from "./tool-logger.js";
+import {AiJsonObject} from "../tool-types.js";
 
 const logger = toolsLogger.child("market-rates");
 

src/ai/tools/notes.ts

@@ -1,11 +1,11 @@
-import {AiTool} from "../tool-types";
+import {AiTool} from "../tool-types.js";
 import path from "node:path";
 import {readdir, readFile, stat, unlink, writeFile} from "node:fs/promises";
-import {notesDir, notesRootFile} from "../../index";
-import {asNonEmptyString} from "./utils";
-import {toolsLogger} from "./tool-logger";
+import {notesDir, notesRootFile} from "../../index.js";
+import {asNonEmptyString} from "./utils.js";
+import {toolsLogger} from "./tool-logger.js";
 import {z} from "zod";
-import {AiJsonObject} from "../tool-types";
+import {AiJsonObject} from "../tool-types.js";
 
 const logger = toolsLogger.child("notes");
 

src/ai/tools/registry.ts

@@ -1,17 +1,17 @@
-import {Environment} from "../../common/environment";
-import {AiTool} from "../tool-types";
-import {WEB_SEARCH_TOOL_NAME, webSearch, webSearchTool, webSearchToolPrompt} from "./web-search";
-import {getCurrentDateTime, getCurrentDateTimeTool} from "./datetime";
-import {shellExecute, shellExecuteTool} from "./shell";
-import {ToolHandler} from "./types";
-import {getWeather, getWeatherTool} from "./weather";
+import {Environment} from "../../common/environment.js";
+import {AiTool} from "../tool-types.js";
+import {WEB_SEARCH_TOOL_NAME, webSearch, webSearchTool, webSearchToolPrompt} from "./web-search.js";
+import {getCurrentDateTime, getCurrentDateTimeTool} from "./datetime.js";
+import {shellExecute, shellExecuteTool} from "./shell.js";
+import {ToolHandler} from "./types.js";
+import {getWeather, getWeatherTool} from "./weather.js";
 import {
     GET_FINANCIAL_MARKET_DATA_TOOL_NAME,
     getFinancialMarketData,
     getFinancialMarketDataToolPrompt,
     getMarketRates
-} from "./market-rates";
-import {pythonInterpreterTool, runPythonInterpreter} from "./python-interpretator";
+} from "./market-rates.js";
+import {pythonInterpreterTool, runPythonInterpreter} from "./python-interpretator.js";
 import {
     beginFileWrite,
     beginFileWriteTool,
@@ -44,12 +44,14 @@ import {
     updateFileTool,
     writeFileChunk,
     writeFileChunkTool
-} from "./files";
+} from "./files.js";
+import {executeMemoryTool, memoryToolPrompt, memoryTools, type MemoryToolName} from "./user-memory.js";
 import {getMcpToolHandlers, getMcpToolPrompts, getMcpTools} from "../mcp/mcp-registry.js";
 
 export const defaultTools: AiTool[] = [
     getCurrentDateTimeTool,
     getFinancialMarketData,
+    ...memoryTools,
 ];
 
 export const fileTools = [
@@ -73,35 +75,62 @@ export const fileTools = [
     deletePathTool,
 ] satisfies AiTool[];
 
+function parseToolNameSet(raw: string | undefined): Set<string> | undefined {
+    if (!raw?.trim()) return undefined;
+
+    const names = raw
+        .split(",")
+        .map(item => item.trim().toLowerCase())
+        .filter(Boolean);
+
+    return names.length ? new Set(names) : undefined;
+}
+
+function isLocalToolEnabled(toolName: string): boolean {
+    if (Environment.DISABLE_LOCAL_TOOLS) return false;
+
+    const allowlist = parseToolNameSet(Environment.LOCAL_TOOL_ALLOWLIST);
+    if (allowlist && !allowlist.has(toolName.toLowerCase())) return false;
+
+    const denylist = parseToolNameSet(Environment.LOCAL_TOOL_DENYLIST);
+    if (denylist && denylist.has(toolName.toLowerCase())) return false;
+
+    return true;
+}
+
+function filterEnabledTools(tools: AiTool[]): AiTool[] {
+    return tools.filter(tool => isLocalToolEnabled(tool.function.name));
+}
+
 export const getTools = (forCreator?: boolean) => {
-    const tools: AiTool[] = Environment.DISABLE_LOCAL_TOOLS ? [] : [
-        ...defaultTools,
-    ];
+    const tools: AiTool[] = [];
 
     if (Environment.DISABLE_LOCAL_TOOLS) {
         tools.push(...getMcpTools());
         return tools;
     }
 
+    tools.push(...filterEnabledTools(defaultTools));
+
     if (Environment.BRAVE_SEARCH_API_KEY) {
-        tools.push(webSearchTool);
+        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(...fileTools);
+        tools.push(...filterEnabledTools(fileTools));
     }
 
     if (forCreator) {
         if (Environment.ENABLE_PYTHON_INTERPRETER) {
-            tools.push(pythonInterpreterTool);
+            tools.push(...filterEnabledTools([pythonInterpreterTool]));
         }
 
         if (Environment.ENABLE_UNSAFE_EVAL) {
-            tools.push(shellExecuteTool);
+            tools.push(...filterEnabledTools([shellExecuteTool]));
         }
     }
 
@@ -132,7 +161,7 @@ export const fileToolHandlers = {
 };
 
 export const getToolHandlers = () => {
-    let handlers: Record<string, ToolHandler> = {
+    const handlers: Record<string, ToolHandler> = {
         ...getMcpToolHandlers(),
     };
 
@@ -140,21 +169,43 @@ export const getToolHandlers = () => {
         return handlers;
     }
 
-    handlers = {
-        ...handlers,
-        get_datetime: getCurrentDateTime,
-        get_financial_market_data: getMarketRates,
+    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"};
+            }
 
-        ...fileToolHandlers,
+            return executeMemoryTool(tool.function.name as MemoryToolName, {
+                userId,
+                content: typeof args?.content === "string" ? args.content : undefined,
+            }, context);
+        };
+    }
 
-        python_interpreter: runPythonInterpreter,
+    if (isLocalToolEnabled("read_file")) handlers.read_file = readFile;
+    if (isLocalToolEnabled("list_directory")) handlers.list_directory = listDirectory;
+    if (isLocalToolEnabled("search_files")) handlers.search_files = searchFiles;
+    if (isLocalToolEnabled("create_file")) handlers.create_file = createFile;
+    if (isLocalToolEnabled("begin_file_write")) handlers.begin_file_write = beginFileWrite;
+    if (isLocalToolEnabled("write_file_chunk")) handlers.write_file_chunk = writeFileChunk;
+    if (isLocalToolEnabled("finish_file_write")) handlers.finish_file_write = finishFileWrite;
+    if (isLocalToolEnabled("cancel_file_write")) handlers.cancel_file_write = cancelFileWrite;
+    if (isLocalToolEnabled("send_file_as_attachment")) handlers.send_file_as_attachment = sendFileAsAttachment;
+    if (isLocalToolEnabled("create_directory")) handlers.create_directory = createDirectory;
+    if (isLocalToolEnabled("copy_path")) handlers.copy_path = copyPath;
+    if (isLocalToolEnabled("update_file")) handlers.update_file = updateFile;
+    if (isLocalToolEnabled("edit_file_patch")) handlers.edit_file_patch = editFilePatch;
+    if (isLocalToolEnabled("rename_path")) handlers.rename_path = renamePath;
+    if (isLocalToolEnabled("delete_path")) handlers.delete_path = deletePath;
 
-        shell_execute: shellExecute,
-
-        web_search: webSearch,
-
-        get_weather: getWeather,
-    };
+    if (isLocalToolEnabled("python_interpreter")) handlers.python_interpreter = (args, _context) => runPythonInterpreter(args);
+    if (isLocalToolEnabled("shell_execute")) handlers.shell_execute = shellExecute;
+    if (isLocalToolEnabled("web_search")) handlers.web_search = webSearch;
+    if (isLocalToolEnabled("get_weather")) handlers.get_weather = getWeather;
 
     return handlers;
 };
@@ -165,14 +216,28 @@ export function getToolPrompts(toolNames: string[]): string[] {
     }
 
     const prompts: string[] = [];
+    const memoryToolNames = new Set(memoryTools.map(tool => tool.function.name));
+    let memoryPromptAdded = false;
 
     for (const toolName of toolNames) {
+        if (!isLocalToolEnabled(toolName)) {
+            continue;
+        }
+
         if (!prompts.includes(fileToolsToolPrompt) &&
             fileTools.map(t => t.function.name).includes(toolName)) {
             prompts.push(fileToolsToolPrompt);
             continue;
         }
 
+        if (memoryToolNames.has(toolName)) {
+            if (!memoryPromptAdded) {
+                prompts.push(memoryToolPrompt);
+                memoryPromptAdded = true;
+            }
+            continue;
+        }
+
         switch (toolName) {
             case GET_FINANCIAL_MARKET_DATA_TOOL_NAME:
                 prompts.push(getFinancialMarketDataToolPrompt);

src/ai/tools/runtime.ts

@@ -1,14 +1,19 @@
-import {getToolHandlers} from "./registry";
-import {normalizeToolArguments} from "./utils";
-import {PYTHON_INTERPRETER_TOOL_NAME, PythonInterpreterInputFile, runPythonInterpreter} from "./python-interpretator";
-import {toolsLogger} from "./tool-logger";
-import {AiJsonObject, AiJsonValue} from "../tool-types";
+import {getToolHandlers} from "./registry.js";
+import {normalizeToolArguments} from "./utils.js";
+import {PYTHON_INTERPRETER_TOOL_NAME, PythonInterpreterInputFile, runPythonInterpreter} from "./python-interpretator.js";
+import {toolsLogger} from "./tool-logger.js";
+import {AiJsonObject, AiJsonValue} from "../tool-types.js";
+import type {MemoryRuntimeContext} from "./user-memory.js";
+import type {AiRuntimeTarget} from "../ai-runtime-target.js";
+import type {AiProvider} from "../../model/ai-provider.js";
 
 const logger = toolsLogger.child("runtime");
 
 export type ToolRuntimeContext = {
     pythonInputFiles?: PythonInterpreterInputFile[];
-};
+    provider?: AiProvider;
+    runtimeTarget?: AiRuntimeTarget;
+} & MemoryRuntimeContext;
 
 function stringifyToolResult(result: AiJsonValue): string {
     if (typeof result === "string") return result;
@@ -48,7 +53,7 @@ export async function executeToolCall(
         }
 
         const arguments1 = normalizeToolArguments(args, userId);
-        const result = await handler(arguments1);
+        const result = await handler(arguments1, context);
         const s = stringifyToolResult(result);
         logger.debug("execute.done", {name, chars: s.length, duration: logger.duration(startedAt)});
         return s;

src/ai/tools/search-notes.ts

@@ -1,10 +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 {asNonEmptyString} from "./utils";
-import {toolsLogger} from "./tool-logger";
-import {AiJsonObject, AiJsonValue} from "../tool-types";
+import {notesDir, notesRootFile} from "../../index.js";
+import {asNonEmptyString} from "./utils.js";
+import {toolsLogger} from "./tool-logger.js";
+import {AiJsonObject, AiJsonValue} from "../tool-types.js";
 
 const logger = toolsLogger.child("search-notes");
 

src/ai/tools/shell.ts

@@ -1,6 +1,6 @@
 import {AiTool} from "../tool-types";
-import {runCommand} from "../../util/utils";
-import {asNonEmptyString} from "./utils";
+import {runCommand} from "../../util/utils.js";
+import {asNonEmptyString} from "./utils.js";
 import {AiJsonObject} from "../tool-types";
 
 export const shellExecuteTool = {

src/ai/tools/types.ts

@@ -1,3 +1,4 @@
 import {AiJsonObject, AiJsonValue} from "../tool-types";
+import type {ToolRuntimeContext} from "./runtime.js";
 
-export type ToolHandler = (args?: AiJsonObject) => Promise<AiJsonValue | string | null | undefined> | AiJsonValue | string | null | undefined;
+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

@@ -1,5 +1,5 @@
 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";
 

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 {logError} from "../../util/utils";
-import {AiJsonObject, AiTool} from "../tool-types";
-import {asNonEmptyString} from "./utils";
+import {Environment} from "../../common/environment.js";
+import {logError} from "../../util/utils.js";
+import {AiJsonObject, AiTool} from "../tool-types.js";
+import {asNonEmptyString} from "./utils.js";
 
 export const getWeatherTool = {
     type: "function",

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 {logError} from "../../util/utils";
-import {AiJsonObject, AiJsonValue, AiTool} from "../tool-types";
-import {asBoolean, asNonEmptyString} from "./utils";
+import {Environment} from "../../common/environment.js";
+import {logError} from "../../util/utils.js";
+import {AiJsonObject, AiJsonValue, AiTool} from "../tool-types.js";
+import {asBoolean, asNonEmptyString} from "./utils.js";
 
 type BraveSearchProfile = {
     name?: string;

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

@@ -19,6 +19,7 @@ import {
 } 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";
@@ -80,6 +81,21 @@ async function runProviderModelCall(params: {
 
     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[],

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

@@ -7,6 +7,8 @@ import {aiLog, aiLogDuration, aiLogProviderTarget, aiLogToolCall} from "../loggi
 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,
@@ -66,7 +68,7 @@ export async function runMistral(
                 streamMessage,
                 signal,
             });
-            const filteredTools = rankResult.filteredTools;
+            const filteredTools = ensureToolsSelected(availableTools, rankResult.filteredTools, MEMORY_TOOL_NAMES);
             const requestTools = filteredTools.length ? filteredTools : undefined;
 
             streamMessage.setStatus(roundStatus(round, firstRoundStatus) ?? "");
@@ -113,7 +115,11 @@ export async function runMistral(
                     userId: msg.from?.id,
                     toolCalls: calls,
                     streamMessage,
-                    toolContext,
+                    toolContext: {
+                        ...toolContext,
+                        provider: AiProvider.MISTRAL,
+                        runtimeTarget: config.mistralChatTarget,
+                    },
                     toolMemory,
                     adapter,
                     appendTargets: [messages, requestMessages],
@@ -183,7 +189,11 @@ export async function runMistral(
                 userId: msg.from?.id,
                 toolCalls: calls,
                 streamMessage,
-                toolContext,
+                toolContext: {
+                    ...toolContext,
+                    provider: AiProvider.MISTRAL,
+                    runtimeTarget: config.mistralChatTarget,
+                },
                 toolMemory,
                 adapter,
                 appendTargets: [messages, requestMessages],

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

@@ -15,6 +15,8 @@ import {createOllamaClient} from "./ai-runtime-target";
 import {aiLog, aiLogDuration, aiLogMessageIdentity, aiLogProviderTarget, aiLogToolCall} from "../logging/ai-logger";
 import {getProviderAdapter} from "./provider-adapters";
 import {runToolRankStage} from "./tool-rank-stage";
+import {ensureToolsSelected} from "./tool-mappers.js";
+import {MEMORY_TOOL_NAMES} from "./tools/user-memory.js";
 
 import {
     allToolSchemaNames,
@@ -203,7 +205,7 @@ export async function runOllama(
                     signal,
                 });
 
-                const filteredTools = [...new Set(rankResult.filteredTools as Tool[])];
+                const filteredTools = [...new Set(ensureToolsSelected(availableOllamaTools, rankResult.filteredTools as Tool[], MEMORY_TOOL_NAMES) as Tool[])];
                 activeToolNames = filteredTools.map(t => t.function.name ?? "");
                 if (filteredTools.length > 0) {
                     request.tools = [...filteredTools];
@@ -297,7 +299,11 @@ export async function runOllama(
                     userId: msg.from?.id,
                     toolCalls: calls,
                     streamMessage,
-                    toolContext,
+                    toolContext: {
+                        ...toolContext,
+                        provider: AiProvider.OLLAMA,
+                        runtimeTarget: target,
+                    },
                     toolMemory,
                     adapter,
                     appendTargets: [messages],
@@ -429,7 +435,11 @@ export async function runOllama(
                 userId: msg.from?.id,
                 toolCalls: calls,
                 streamMessage,
-                toolContext,
+                toolContext: {
+                    ...toolContext,
+                    provider: AiProvider.OLLAMA,
+                    runtimeTarget: target,
+                },
                 toolMemory,
                 adapter,
                 appendTargets: [messages],

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

@@ -12,6 +12,7 @@ import type {
 } from "openai/resources/responses/responses";
 import {createOpenAiClient} from "./ai-runtime-target";
 import {aiLog, aiLogDuration, aiLogMessageIdentity, aiLogProviderTarget, aiLogToolCall} from "../logging/ai-logger";
+import {buildUserMemoryPrompt} from "./tools/user-memory.js";
 
 import {
     AsyncIterableStream,
@@ -29,23 +30,21 @@ import {
     showOpenAiGeneratedImage,
     ToolCallData,
     ToolExecutionMemory,
-    errorMessage,
     allToolSchemaNames
 } 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 {bot} from "../index";
-import fs from "node:fs";
-import path from "node:path";
+import {ensureToolsSelected} from "./tool-mappers.js";
+import {MEMORY_TOOL_NAMES} from "./tools/user-memory.js";
 import {logError} from "../util/utils";
-import {SendFileAttachmentResult, SendFileAttachmentResultSchema} from "./tools/files";
 import {DEFAULT_AI_RESPONSE_LANGUAGE} from "../common/user-ai-settings";
 import {AiDownloadedFile} from "./telegram-attachments";
 import {AiProvider} from "../model/ai-provider";
 import {getProviderAdapter} from "./provider-adapters";
 import {runToolRankStage} from "./tool-rank-stage";
+import {tryToUploadFiles} from "./openai-upload-files.js";
 
 export async function runOpenAi(
     msg: Message,
@@ -75,6 +74,7 @@ export async function runOpenAi(
         DEFAULT_AI_RESPONSE_LANGUAGE,
         false,
         config.openAiChatTarget.systemPromptAdditions,
+        await buildUserMemoryPrompt(msg.from?.id),
     );
 
     aiLog("info", "openai.run.start", {
@@ -115,9 +115,13 @@ export async function runOpenAi(
                             tools.unshift(fileSearchTool);
                         }
                     }
-                    return tools.length ? tools : undefined;
+                    const withMemory = ensureToolsSelected(availableTools, tools, MEMORY_TOOL_NAMES);
+                    return withMemory.length ? withMemory : undefined;
                 })()
-                : (filteredTools.length ? filteredTools : undefined);
+                : (() => {
+                    const withMemory = ensureToolsSelected(availableTools, filteredTools, MEMORY_TOOL_NAMES);
+                    return withMemory.length ? withMemory : undefined;
+                })();
 
             if (!stream) {
                 const request: ResponseCreateParamsNonStreaming = {
@@ -187,7 +191,11 @@ export async function runOpenAi(
                     userId: msg.from?.id,
                     toolCalls,
                     streamMessage,
-                    toolContext,
+                    toolContext: {
+                        ...toolContext,
+                        provider: AiProvider.OPENAI,
+                        runtimeTarget: config.openAiChatTarget,
+                    },
                     toolMemory,
                     adapter,
                     appendTargets: [toolOutputs],
@@ -397,7 +405,11 @@ export async function runOpenAi(
                 userId: msg.from?.id,
                 toolCalls,
                 streamMessage,
-                toolContext,
+                toolContext: {
+                    ...toolContext,
+                    provider: AiProvider.OPENAI,
+                    runtimeTarget: config.openAiChatTarget,
+                },
                 toolMemory,
                 adapter,
                 appendTargets: [toolOutputs],
@@ -504,72 +516,6 @@ async function cleanupOpenAiDocumentRag(openAi: OpenAI, vectorStoreId: string, f
     }
 }
 
-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
-        };
-    }
-}
-
 // function openAiResponseContentToText(content: string | readonly { text?: string; refusal?: string }[]): string {
 //     if (typeof content === "string") return content;
 //     if (!Array.isArray(content)) return "";

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

@@ -4,7 +4,7 @@ import path from "node:path";
 import type {BoundaryValue} from "../common/boundary-types";
 import {AiProvider} from "../model/ai-provider.js";
 import {ToolRankerFallbackPolicy} from "../common/policies.js";
-import {Environment} from "../common/environment.js";
+import {Environment, type OpenAiBackend} from "../common/environment.js";
 import {delay, logError, replyToMessage} from "../util/utils.js";
 import {MessageStore} from "../common/message-store.js";
 import type {OpenAiResponseTool} from "./tool-mappers.js";
@@ -274,6 +274,7 @@ export type RuntimeConfigSnapshot = {
     openAiChatTarget: AiRuntimeTarget;
     openAiImageTarget: AiRuntimeTarget;
     openAiToolRankerTarget?: AiRuntimeTarget;
+    openAiBackend: OpenAiBackend;
 };
 
 export function snapshotRuntimeConfig(): RuntimeConfigSnapshot {
@@ -307,9 +308,14 @@ export function snapshotRuntimeConfig(): RuntimeConfigSnapshot {
         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"}));
@@ -382,11 +388,13 @@ export function buildSystemInstruction(
     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");
 }
@@ -1117,19 +1125,31 @@ export async function executeTool(
     }
 }
 
-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":
@@ -1162,7 +1182,7 @@ export async function executeScheduledTool(
     message: TelegramStreamMessage,
     context: ToolRuntimeContext,
 ): Promise<string> {
-    const keys = toolResourceKeys(toolCall);
+    const keys = toolResourceKeys(toolCall, userId);
     if (!keys.length) return executeTool(userId, toolCall, message, context);
     return runWithToolLocks(keys, () => executeTool(userId, toolCall, message, context));
 }

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

@@ -1,4 +1,4 @@
-import {ChatCompletionMessageParam} from "openai/resources/chat/completions";
+import type {ChatCompletionCreateParamsNonStreaming, ChatCompletionMessageParam} from "openai/resources/chat/completions";
 import {ChatRequest} from "ollama";
 import {BoundaryValue} from "../common/boundary-types.js";
 import {ToolRankerFallbackPolicy} from "../common/policies.js";
@@ -107,7 +107,7 @@ export class ToolRanker {
                         target: aiLogProviderTarget(target),
                         fallbackTarget: aiLogProviderTarget(mainModelTarget),
                         duration: aiLogDuration(startedAt),
-                        error: failureMessage,
+                        errorSummary: failureMessage,
                     });
 
                     const fallbackRanker = buildToolRankerPrompt(
@@ -142,7 +142,7 @@ export class ToolRanker {
                         target: aiLogProviderTarget(target),
                         fallbackTarget: aiLogProviderTarget(mainModelTarget),
                         duration: aiLogDuration(startedAt),
-                        error: fallbackErrorMessage,
+                        errorSummary: fallbackErrorMessage,
                     });
 
                     failureMessage = fallbackErrorMessage;
@@ -155,7 +155,7 @@ export class ToolRanker {
                 target: aiLogProviderTarget(target),
                 fallbackPolicy,
                 duration: aiLogDuration(startedAt),
-                error: failureMessage,
+                errorSummary: failureMessage,
             });
 
             return resolveToolRankerFallbackSelection({
@@ -227,12 +227,19 @@ export class ToolRanker {
                     {role: "user", content: userQuery},
                 ] satisfies ChatCompletionMessageParam[];
 
-                // gpt-5 family ranker targets reject temperature=0; use the model default instead.
-                const response = await openAi.chat.completions.create({
+                // OpenAI-compatible servers often reject `response_format`, so keep JSON mode
+                // only for official OpenAI endpoints.
+                const request: ChatCompletionCreateParamsNonStreaming = {
                     model: target.model,
                     messages,
-                    response_format: {type: "json_object"},
-                });
+                };
+
+                if (!target.baseUrl) {
+                    // gpt-5 family ranker targets reject temperature=0; use the model default instead.
+                    request.response_format = {type: "json_object"};
+                }
+
+                const response = await openAi.chat.completions.create(request);
 
                 return response.choices[0]?.message?.content?.trim() ?? "";
             }

src/common/environment.ts

@@ -14,6 +14,13 @@ import type {ToolCallData} from "../ai/unified-ai-runner.js";
 import {PYTHON_INTERPRETER_TOOL_NAME} from "../ai/tools/python-interpretator.js";
 import {Localization, type LocalizationParams} from "./localization.js";
 
+export const OpenAiBackendModes = {
+    OFFICIAL: "official",
+    COMPATIBLE: "compatible",
+} as const;
+
+export type OpenAiBackend = typeof OpenAiBackendModes[keyof typeof OpenAiBackendModes];
+
 function parseBooleanLike(value: string): boolean {
     const normalized = value.trim().toLowerCase();
     return ["true", "t", "y", "1"].includes(normalized);
@@ -215,6 +222,8 @@ const RuntimeEnvSchema = z.object({
 
     ENABLE_PYTHON_INTERPRETER: optionalBooleanSchema,
     DISABLE_LOCAL_TOOLS: optionalBooleanSchema,
+    LOCAL_TOOL_ALLOWLIST: optionalStringSchema,
+    LOCAL_TOOL_DENYLIST: optionalStringSchema,
     MCP_SERVERS: optionalStringSchema,
 
     OLLAMA_API_KEY: optionalStringSchema,
@@ -243,6 +252,10 @@ const RuntimeEnvSchema = z.object({
 
     OPENAI_BASE_URL: optionalStringSchema,
     OPENAI_API_KEY: optionalStringSchema,
+    OPENAI_BACKEND: enumWithDefaultSchema(
+        OpenAiBackendModes,
+        OpenAiBackendModes.OFFICIAL,
+    ),
     OPENAI_MODEL: stringWithDefaultSchema("gpt-4.1-nano"),
     OPENAI_IMAGE_MODEL: stringWithDefaultSchema("gpt-image-1-mini"),
     OPENAI_TRANSCRIPTION_MODEL: stringWithDefaultSchema("gpt-4o-mini-transcribe"),
@@ -311,6 +324,8 @@ export class Environment {
 
     static ENABLE_PYTHON_INTERPRETER: boolean = false;
     static DISABLE_LOCAL_TOOLS: boolean = false;
+    static LOCAL_TOOL_ALLOWLIST?: string;
+    static LOCAL_TOOL_DENYLIST?: string;
     static MCP_SERVERS?: string;
 
     static OLLAMA_API_KEY?: string;
@@ -339,6 +354,7 @@ export class Environment {
 
     static OPENAI_BASE_URL?: string;
     static OPENAI_API_KEY?: string;
+    static OPENAI_BACKEND: OpenAiBackend = OpenAiBackendModes.OFFICIAL;
     static OPENAI_MODEL: string = "";
     static OPENAI_IMAGE_MODEL: string = "";
     static OPENAI_TRANSCRIPTION_MODEL: string = "";
@@ -1847,6 +1863,8 @@ export class Environment {
 
         Environment.ENABLE_PYTHON_INTERPRETER = env.ENABLE_PYTHON_INTERPRETER ?? false;
         Environment.DISABLE_LOCAL_TOOLS = env.DISABLE_LOCAL_TOOLS ?? false;
+        Environment.LOCAL_TOOL_ALLOWLIST = env.LOCAL_TOOL_ALLOWLIST;
+        Environment.LOCAL_TOOL_DENYLIST = env.LOCAL_TOOL_DENYLIST;
         Environment.MCP_SERVERS = env.MCP_SERVERS;
 
         Environment.OLLAMA_API_KEY = env.OLLAMA_API_KEY;
@@ -1875,6 +1893,7 @@ export class Environment {
 
         Environment.OPENAI_BASE_URL = env.OPENAI_BASE_URL;
         Environment.OPENAI_API_KEY = env.OPENAI_API_KEY;
+        Environment.OPENAI_BACKEND = env.OPENAI_BACKEND;
         Environment.OPENAI_MODEL = env.OPENAI_MODEL;
         Environment.OPENAI_IMAGE_MODEL = env.OPENAI_IMAGE_MODEL;
         Environment.OPENAI_TRANSCRIPTION_MODEL = env.OPENAI_TRANSCRIPTION_MODEL;
@@ -2075,6 +2094,10 @@ export class Environment {
         this.OPENAI_API_KEY = newAIApiKey;
     }
 
+    static setOpenAIBackend(newBackend: OpenAiBackend): void {
+        this.OPENAI_BACKEND = newBackend;
+    }
+
     static setOpenAIModel(newModel: string): void {
         this.OPENAI_MODEL = newModel;
     }

src/db/database-manager.ts

@@ -2055,7 +2055,24 @@ export class DatabaseManager {
     }
 
     private static async migrateLegacyNormalizedTables(): Promise<void> {
-        const messages = await DatabaseManager.getAllMessages();
+        // Do not call getAllMessages() here: it awaits DatabaseManager.ready, which
+        // is the promise currently waiting on ensureSchema(). That creates a
+        // self-deadlock during startup migrations.
+        const messages = await DatabaseManager.query<MessageDbRow>(`
+            SELECT
+                "id",
+                "chatId",
+                "replyToMessageId",
+                "fromId",
+                "text",
+                "quoteText",
+                "date",
+                "deletedByBotAt",
+                "attachments",
+                "pipelineAudit"
+            FROM "messages"
+            ORDER BY "chatId", "id"
+        `);
         const attachments = messages.flatMap(message => DatabaseManager.attachmentRowsFromMessageRow(message));
         const artifacts = messages.flatMap(message => DatabaseManager.artifactRowsFromMessageRow(message));
         const requestAudits = messages.flatMap(message => DatabaseManager.requestAuditRowsFromMessageRow(message));

src/index.ts

@@ -194,6 +194,7 @@ export const filesDir = path.join(Environment.DATA_PATH, "files");
 export const NOTES_HEADER = "## Notes\n";
 export const notesDir = path.join(Environment.DATA_PATH, "notes");
 export const notesRootFile = path.join(notesDir, "index.md");
+export const memoryDir = path.join(Environment.DATA_PATH, "memory");
 
 const logger = appLogger.child("main");
 
@@ -262,7 +263,7 @@ async function main() {
     });
 
     await measureStartupStep("environment.load", () => Environment.load());
-    const dirsToCheck = [cacheDir, photoDir, photoGenDir, documentDir, audioDir, videoDir, videoNotesDir, videoTempDir, notesDir, filesDir];
+    const dirsToCheck = [cacheDir, photoDir, photoGenDir, documentDir, audioDir, videoDir, videoNotesDir, videoTempDir, notesDir, memoryDir, filesDir];
     await measureStartupStep("prepare_directories", () => {
         const created: string[] = [];
         for (const dir of dirsToCheck) {

test/openai-backend.test.mjs

@@ -0,0 +1,14 @@
+import test from "node:test";
+import assert from "node:assert/strict";
+
+const {Environment} = await import("../dist/common/environment.js");
+
+test("openai backend defaults to official", () => {
+    assert.equal(Environment.OPENAI_BACKEND, "official");
+});
+
+test("openai backend setter updates runtime config", () => {
+    Environment.setOpenAIBackend("compatible");
+    assert.equal(Environment.OPENAI_BACKEND, "compatible");
+    Environment.setOpenAIBackend("official");
+});

test/openai-compatible-integration.test.mjs

@@ -0,0 +1,43 @@
+import test from "node:test";
+import assert from "node:assert/strict";
+import {OpenAI} from "openai";
+
+const {extractOpenAiChatToolCalls} = await import("../dist/ai/provider-adapter-contract.js");
+
+const baseURL = process.env.OPENAI_COMPATIBLE_TEST_BASE_URL;
+const model = process.env.OPENAI_COMPATIBLE_TEST_MODEL;
+const apiKey = process.env.OPENAI_COMPATIBLE_TEST_API_KEY ?? process.env.OPENAI_API_KEY ?? "test";
+
+test("openai-compatible chat.completions tool loop works on a real server", {skip: !baseURL || !model}, async () => {
+    const client = new OpenAI({baseURL, apiKey});
+
+    const response = await client.chat.completions.create({
+        model,
+        temperature: 0,
+        messages: [
+            {role: "system", content: "You must call the ping tool exactly once. Do not answer in plain text."},
+            {role: "user", content: "ping"},
+        ],
+        tools: [{
+            type: "function",
+            function: {
+                name: "ping",
+                description: "Return a ping token.",
+                parameters: {
+                    type: "object",
+                    properties: {},
+                    additionalProperties: false,
+                },
+            },
+        }],
+        tool_choice: {
+            type: "function",
+            function: {name: "ping"},
+        },
+    });
+
+    const calls = extractOpenAiChatToolCalls(response);
+
+    assert.equal(calls.length, 1);
+    assert.equal(calls[0].name, "ping");
+});

test/provider-adapter-contract.test.mjs

@@ -5,6 +5,11 @@ const {
     extractOpenAiToolCalls,
     extractOpenAiStreamingToolCalls,
     extractOpenAiTextDelta,
+    extractOpenAiChatToolCalls,
+    extractOpenAiChatStreamingToolCalls,
+    extractOpenAiChatTextDelta,
+    mergeToolCallChunks,
+    normalizeStreamingTextDelta,
     extractMistralToolCalls,
     extractMistralTextDelta,
     extractOllamaToolCalls,
@@ -42,6 +47,62 @@ test("openai contract extracts text delta and function calls", () => {
     assert.equal(streamed[0].name, "search_files");
 });
 
+test("openai chat contract extracts text delta and tool calls", () => {
+    assert.equal(extractOpenAiChatTextDelta({choices: [{delta: {content: "hello chat"}}]}), "hello chat");
+    assert.equal(normalizeStreamingTextDelta("hel", "hello"), "lo");
+    assert.equal(normalizeStreamingTextDelta("hel", "lo"), "lo");
+
+    const calls = extractOpenAiChatToolCalls({
+        choices: [{
+            message: {
+                tool_calls: [{
+                    id: "chat-1",
+                    function: {
+                        name: "read_user_info",
+                        arguments: "{\"userId\":123}",
+                    },
+                }],
+            },
+        }],
+    });
+
+    assert.equal(calls.length, 1);
+    assert.equal(calls[0].id, "chat-1");
+    assert.equal(calls[0].name, "read_user_info");
+
+    const streamed = extractOpenAiChatStreamingToolCalls({
+        choices: [{
+            delta: {
+                tool_calls: [{
+                    index: 0,
+                    id: "chat-2",
+                    function: {
+                        name: "write_note",
+                        arguments: "{\"text\":",
+                    },
+                }],
+            },
+        }],
+    });
+
+    assert.equal(streamed.length, 1);
+    assert.equal(streamed[0].id, "chat-2");
+    assert.equal(streamed[0].name, "write_note");
+    assert.equal(streamed[0].argumentsText, "{\"text\":");
+
+    const merged = mergeToolCallChunks([
+        {id: "chat-2", name: "", argumentsText: "{\"text\":"},
+    ], [{
+        id: "chat-2",
+        name: "write_note",
+        argumentsText: "\"hello\"}",
+    }]);
+
+    assert.equal(merged.length, 1);
+    assert.equal(merged[0].name, "write_note");
+    assert.equal(merged[0].argumentsText, "{\"text\":\"hello\"}");
+});
+
 test("mistral contract extracts content and tool calls", () => {
     assert.equal(extractMistralTextDelta({
         content: [{text: "hello"}, {text: " world"}],

test/tool-ranker.test.mjs

@@ -86,6 +86,19 @@ test("prompt includes search files routing example for usage search", () => {
     assert.ok(prompt.includes(JSON.stringify({toolNames: ["search_files"]})));
 });
 
+test("prompt includes memory routing examples for remember requests", () => {
+    const prompt = promptFor("no_tool", "read_user_info", "add_user_info", "remove_user_info", "replace_user_info", "delete_user_info");
+
+    assert.ok(prompt.includes("что ты помнишь обо мне?"));
+    assert.ok(prompt.includes("запомни, что меня зовут Иван"));
+    assert.ok(prompt.includes("забудь, что я люблю кофе"));
+    assert.ok(prompt.includes("забудь всё обо мне и запиши только это"));
+    assert.ok(prompt.includes("удали всю память обо мне"));
+    assert.ok(prompt.includes("inspect remembered user info -> read_user_info"));
+    assert.ok(prompt.includes("remember a new user fact -> add_user_info"));
+    assert.ok(prompt.includes(JSON.stringify({toolNames: ["add_user_info"]})));
+});
+
 test("prompt includes edit file patch routing example for targeted edits", () => {
     const prompt = promptFor("no_tool", "edit_file_patch");
 

test/user-memory.test.mjs

@@ -0,0 +1,197 @@
+import test from "node:test";
+import assert from "node:assert/strict";
+import fs from "node:fs";
+import os from "node:os";
+import path from "node:path";
+
+const {Environment} = await import("../dist/common/environment.js");
+const {
+    buildUserMemoryPrompt,
+    compressMemoryWithFallback,
+    deleteUserMemory,
+    getMemoryFilePath,
+    readUserMemory,
+    updateUserMemory,
+} = await import("../dist/ai/tools/user-memory.js");
+const {AiProvider} = await import("../dist/model/ai-provider.js");
+
+function makeTempDataPath() {
+    return fs.mkdtempSync(path.join(os.tmpdir(), "tg-chat-bot-memory-"));
+}
+
+function withEnv(vars, fn) {
+    const snapshot = new Map();
+    for (const [key, value] of Object.entries(vars)) {
+        snapshot.set(key, process.env[key]);
+        if (value === undefined) {
+            delete process.env[key];
+        } else {
+            process.env[key] = value;
+        }
+    }
+
+    return Promise.resolve(fn()).finally(() => {
+        for (const [key, value] of snapshot.entries()) {
+            if (value === undefined) {
+                delete process.env[key];
+            } else {
+                process.env[key] = value;
+            }
+        }
+    });
+}
+
+test("memory storage supports append replace and remove", async () => {
+    const oldDataPath = Environment.DATA_PATH;
+    Environment.DATA_PATH = makeTempDataPath();
+
+    try {
+        const userId = 475823381;
+
+        let result = await updateUserMemory({
+            userId,
+            scope: "user",
+            action: "replace",
+            content: "# Profile\nLikes tea",
+        });
+        assert.equal(result.success, true);
+
+        result = await updateUserMemory({
+            userId,
+            scope: "user",
+            action: "add",
+            content: "Prefers concise answers",
+        });
+        assert.equal(result.success, true);
+        assert.match(result.content, /Likes tea/);
+        assert.match(result.content, /Prefers concise answers/);
+
+        result = await updateUserMemory({
+            userId,
+            scope: "user",
+            action: "remove",
+            content: "Prefers concise answers",
+        });
+        assert.equal(result.success, true);
+        assert.doesNotMatch(result.content, /Prefers concise answers/);
+
+        const readback = await readUserMemory(userId, "user");
+        assert.equal(readback.success, true);
+        assert.equal(readback.filePath, getMemoryFilePath(userId, "user"));
+        assert.match(readback.content, /Likes tea/);
+    } finally {
+        Environment.DATA_PATH = oldDataPath;
+    }
+});
+
+test("memory delete removes the file", async () => {
+    const oldDataPath = Environment.DATA_PATH;
+    Environment.DATA_PATH = makeTempDataPath();
+
+    try {
+        const userId = 999;
+        await updateUserMemory({userId, scope: "user", action: "replace", content: "hello"});
+        const deleted = await deleteUserMemory(userId, "user");
+        assert.equal(deleted.success, true);
+        const readback = await readUserMemory(userId, "user");
+        assert.equal(readback.success, true);
+        assert.equal(readback.content, "");
+    } finally {
+        Environment.DATA_PATH = oldDataPath;
+    }
+});
+
+test("memory prompt combines system and user files", async () => {
+    const oldDataPath = Environment.DATA_PATH;
+    Environment.DATA_PATH = makeTempDataPath();
+
+    try {
+        const userId = 1234;
+
+        await updateUserMemory({
+            userId,
+            scope: "system",
+            action: "replace",
+            content: "Ты зовешься Евлампий.",
+        });
+        await updateUserMemory({
+            userId,
+            scope: "user",
+            action: "replace",
+            content: "Пользователь любит короткие ответы.",
+        });
+
+        const prompt = await buildUserMemoryPrompt(userId);
+        assert(prompt);
+        assert.equal(prompt?.includes("## Assistant memory (system.md)"), true);
+        assert.equal(prompt?.includes("This is information about the assistant and its behavior."), true);
+        assert.equal(prompt?.includes("## User memory (user.md)"), true);
+        assert.equal(prompt?.includes("This is information about the user."), true);
+        assert(prompt.indexOf("## Assistant memory (system.md)") < prompt.indexOf("## User memory (user.md)"));
+    } finally {
+        Environment.DATA_PATH = oldDataPath;
+    }
+});
+
+test("memory compression falls back to current target when explicit target fails", async () => {
+    await withEnv({
+        OLLAMA_MEMORY_COMPRESS_MODEL: "memory-compress-model",
+        OLLAMA_CHAT_MODEL: "chat-model",
+    }, async () => {
+        const calls = [];
+        const result = await compressMemoryWithFallback(
+            {
+                provider: AiProvider.OLLAMA,
+                currentTarget: {
+                    provider: AiProvider.OLLAMA,
+                    purpose: "chat",
+                    model: "chat-model",
+                },
+                scope: "system",
+                currentText: "x".repeat(1200),
+                limit: 1000,
+            },
+            async ({target}) => {
+                calls.push(target.model);
+                if (target.model === "memory-compress-model") {
+                    throw new Error("boom");
+                }
+                return "short summary";
+            },
+        );
+
+        assert.deepEqual(calls, ["memory-compress-model", "chat-model"]);
+        assert.equal(result.content, "short summary");
+        assert.equal(result.compressed, true);
+    });
+});
+
+test("memory compression uses current target when no separate target exists", async () => {
+    await withEnv({
+        OLLAMA_MEMORY_COMPRESS_MODEL: undefined,
+        OLLAMA_CHAT_MODEL: "chat-model",
+    }, async () => {
+        const calls = [];
+        const result = await compressMemoryWithFallback(
+            {
+                provider: AiProvider.OLLAMA,
+                currentTarget: {
+                    provider: AiProvider.OLLAMA,
+                    purpose: "chat",
+                    model: "chat-model",
+                },
+                scope: "user",
+                currentText: "x".repeat(1200),
+                limit: 1000,
+            },
+            async ({target}) => {
+                calls.push(target.model);
+                return "summary";
+            },
+        );
+
+        assert.deepEqual(calls, ["chat-model"]);
+        assert.equal(result.content, "summary");
+        assert.equal(result.compressed, true);
+    });
+});