feat: 逐步增加docker 支持

.github/workflows/ci.yml

@@ -0,0 +1,99 @@
+name: CI
+
+on:
+  push:
+    branches: [ main, master ]
+  pull_request:
+    branches: [ main, master ]
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: ['3.12']
+
+    steps:
+    - uses: actions/checkout@v4
+
+    - name: Set up Python ${{ matrix.python-version }}
+      uses: actions/setup-python@v5
+      with:
+        python-version: ${{ matrix.python-version }}
+
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        pip install -e .[test]
+        # Install frontend dependencies for potential frontend tests (optional)
+        cd frontend && npm ci && cd ..
+
+    # 统一配置生成，用于后端测试（与前端构建共享相同配置）
+    - name: Create config.yml for CI
+      run: |
+        cat > config.yml << 'EOF'
+        backend_port: 3000
+        frontend_port: 4000
+        max_iterations: 5
+        sub_agent:
+          max_iterations: 3
+          max_tokens: 4096
+          max_agents: 5
+          max_concurrency: 3
+        models:
+          - id: dummy
+            name: Dummy
+            api_url: https://api.example.com
+            api_key: dummy-key
+        default_model: dummy
+        db_type: sqlite
+        db_sqlite_file: ":memory:"
+        workspace_root: ./workspaces
+        EOF
+
+    - name: Run tests with pytest
+      run: |
+        python -m pytest tests/ -v
+
+    - name: Upload coverage to Codecov (optional)
+      uses: codecov/codecov-action@v3
+      if: matrix.python-version == '3.10' && github.event_name == 'push'
+      with:
+        file: ./coverage.xml
+        fail_ci_if_error: false
+  build-frontend:
+    runs-on: ubuntu-latest
+    steps:
+    - uses: actions/checkout@v4
+    - name: Set up Node.js
+      uses: actions/setup-node@v4
+      with:
+        node-version: '20'
+    - name: Install frontend dependencies
+      run: |
+        cd frontend && npm ci
+    # 统一配置生成，用于前端构建（与后端测试共享相同配置）
+    - name: Create config.yml for frontend build
+      run: |
+        cat > config.yml << 'EOF'
+        backend_port: 3000
+        frontend_port: 4000
+        max_iterations: 5
+        sub_agent:
+          max_iterations: 3
+          max_tokens: 4096
+          max_agents: 5
+          max_concurrency: 3
+        models:
+          - id: dummy
+            name: Dummy
+            api_url: https://api.example.com
+            api_key: dummy-key
+        default_model: dummy
+        db_type: sqlite
+        db_sqlite_file: ":memory:"
+        workspace_root: ./workspaces
+        EOF
+    - name: Build frontend
+      run: |
+        cd frontend && npm run build

.gitignore

@@ -28,3 +28,6 @@
 !frontend/src/**/*.css
 !frontend/public/
 !frontend/public/**
+
+# CI / CD
+!.github/workflows/*

README.md

@@ -36,6 +36,11 @@ frontend_port: 4000
 # Max agentic loop iterations (tool call rounds)
 max_iterations: 15
 
+# Sub-agent settings (multi_agent tool)
+sub_agent:
+  max_iterations: 3      # Max tool-call rounds per sub-agent
+  max_concurrency: 3      # ThreadPoolExecutor max workers
+
 # Available models
 # Each model must have its own id, name, api_url, api_key
 models:
@@ -117,6 +122,7 @@ backend/
 │       ├── data.py      # 计算器、文本、JSON 处理
 │       ├── weather.py   # 天气查询（模拟）
 │       ├── file_ops.py  # 文件操作（6 个工具，project_id 自动注入）
+│       ├── agent.py     # 多智能体（子 Agent 并发执行，工具权限隔离）
 │       └── code.py      # Python 代码执行（沙箱）
 └── utils/               # 辅助函数
     ├── helpers.py       # 通用函数（ok/err/build_messages 等）
@@ -207,6 +213,7 @@ frontend/
 | **代码执行** | execute_python | 沙箱环境执行 Python |
 | **文件操作** | file_read, file_write, file_delete, file_list, file_exists, file_mkdir | project_id 自动注入 |
 | **天气** | get_weather | 天气查询（模拟） |
+| **智能体** | multi_agent | 派生子 Agent 并发执行（禁止递归，工具权限与主 Agent 一致） |
 
 ## 文档
 

backend/config.py

@@ -1,41 +1,117 @@
-"""Configuration management"""
+"""Configuration management using dataclasses"""
 import sys
+from dataclasses import dataclass, field
+from typing import List, Dict, Optional
+
 from backend import load_config
 
-_cfg = load_config()
 
-# Model list (for /api/models endpoint)
-MODELS = _cfg.get("models", [])
+@dataclass
+class ModelConfig:
+    """Individual model configuration."""
+    id: str
+    name: str
+    api_url: str
+    api_key: str
 
-# Validate each model has required fields at startup
-_REQUIRED_MODEL_KEYS = {"id", "name", "api_url", "api_key"}
-_model_ids_seen = set()
-for _i, _m in enumerate(MODELS):
-    _missing = _REQUIRED_MODEL_KEYS - set(_m.keys())
-    if _missing:
-        print(f"[config] ERROR: models[{_i}] missing required fields: {_missing}", file=sys.stderr)
-        sys.exit(1)
-    if _m["id"] in _model_ids_seen:
-        print(f"[config] ERROR: duplicate model id '{_m['id']}'", file=sys.stderr)
-        sys.exit(1)
-    _model_ids_seen.add(_m["id"])
 
-# Per-model config lookup: {model_id: {api_url, api_key}}
-MODEL_CONFIG = {m["id"]: {"api_url": m["api_url"], "api_key": m["api_key"]} for m in MODELS}
+@dataclass
+class SubAgentConfig:
+    """Sub-agent (multi_agent tool) settings."""
+    max_iterations: int = 3
+    max_concurrency: int = 3
+    timeout: int = 60
 
-# default_model must exist in models
-DEFAULT_MODEL = _cfg.get("default_model", "")
-if DEFAULT_MODEL and DEFAULT_MODEL not in MODEL_CONFIG:
-    print(f"[config] ERROR: default_model '{DEFAULT_MODEL}' not found in models", file=sys.stderr)
-    sys.exit(1)
-if MODELS and not DEFAULT_MODEL:
-    DEFAULT_MODEL = MODELS[0]["id"]
 
-# Max agentic loop iterations (tool call rounds)
-MAX_ITERATIONS = _cfg.get("max_iterations", 5)
+@dataclass
+class CodeExecutionConfig:
+    """Code execution settings."""
+    default_strictness: str = "standard"
+    extra_allowed_modules: Dict = field(default_factory=dict)
+    backend: str = "subprocess"  # subprocess or docker
+    docker_image: str = "python:3.12-slim"
+    docker_network: str = "none"
+    docker_user: str = "nobody"
+    docker_memory_limit: Optional[str] = None
+    docker_cpu_shares: Optional[int] = None
 
-# Max parallel workers for tool execution (ThreadPoolExecutor)
-TOOL_MAX_WORKERS = _cfg.get("tool_max_workers", 4)
 
-# Max character length for a single tool result content (truncated if exceeded)
-TOOL_RESULT_MAX_LENGTH = _cfg.get("tool_result_max_length", 4096)
+@dataclass
+class AppConfig:
+    """Main application configuration."""
+    models: List[ModelConfig] = field(default_factory=list)
+    default_model: str = ""
+    max_iterations: int = 5
+    tool_max_workers: int = 4
+    sub_agent: SubAgentConfig = field(default_factory=SubAgentConfig)
+    code_execution: CodeExecutionConfig = field(default_factory=CodeExecutionConfig)
+
+    # Per-model config lookup: {model_id: ModelConfig}
+    _model_config_map: Dict[str, ModelConfig] = field(default_factory=dict, repr=False)
+
+    def __post_init__(self):
+        """Build lookup map after initialization."""
+        self._model_config_map = {m.id: m for m in self.models}
+
+    def get_model_config(self, model_id: str) -> Optional[ModelConfig]:
+        """Get model config by ID."""
+        return self._model_config_map.get(model_id)
+
+    def get_model_credentials(self, model_id: str) -> tuple:
+        """Get (api_url, api_key) for a model."""
+        cfg = self.get_model_config(model_id)
+        if not cfg:
+            raise ValueError(f"Unknown model: '{model_id}', not found in config")
+        if not cfg.api_url:
+            raise ValueError(f"Model '{model_id}' has no api_url configured")
+        if not cfg.api_key:
+            raise ValueError(f"Model '{model_id}' has no api_key configured")
+        return cfg.api_url, cfg.api_key
+
+
+def _parse_config(raw: dict) -> AppConfig:
+    """Parse raw YAML config into AppConfig dataclass."""
+    # Parse models
+    models = []
+    for m in raw.get("models", []):
+        models.append(ModelConfig(
+            id=m["id"],
+            name=m["name"],
+            api_url=m["api_url"],
+            api_key=m["api_key"],
+        ))
+
+    # Parse sub_agent
+    sa_raw = raw.get("sub_agent", {})
+    sub_agent = SubAgentConfig(
+        max_iterations=sa_raw.get("max_iterations", 3),
+        max_concurrency=sa_raw.get("max_concurrency", 3),
+        timeout=sa_raw.get("timeout", 60),
+    )
+
+    # Parse code_execution
+    ce_raw = raw.get("code_execution", {})
+    code_execution = CodeExecutionConfig(
+        default_strictness=ce_raw.get("default_strictness", "standard"),
+        extra_allowed_modules=ce_raw.get("extra_allowed_modules", {}),
+        backend=ce_raw.get("backend", "subprocess"),
+        docker_image=ce_raw.get("docker_image", "python:3.12-slim"),
+        docker_network=ce_raw.get("docker_network", "none"),
+        docker_user=ce_raw.get("docker_user", "nobody"),
+        docker_memory_limit=ce_raw.get("docker_memory_limit"),
+        docker_cpu_shares=ce_raw.get("docker_cpu_shares"),
+    )
+
+    return AppConfig(
+        models=models,
+        default_model=raw.get("default_model", ""),
+        max_iterations=raw.get("max_iterations", 5),
+        tool_max_workers=raw.get("tool_max_workers", 4),
+        sub_agent=sub_agent,
+        code_execution=code_execution,
+    )
+
+
+# Load and validate configuration at startup
+_raw_cfg = load_config()
+config = _parse_config(_raw_cfg)

backend/routes/__init__.py

@@ -8,16 +8,16 @@ from backend.routes.stats import bp as stats_bp
 from backend.routes.projects import bp as projects_bp
 from backend.routes.auth import bp as auth_bp, init_auth
 from backend.services.llm_client import LLMClient
-from backend.config import MODEL_CONFIG
+from backend.config import config
 
 
 def register_routes(app: Flask):
     """Register all route blueprints"""
-    # Initialize LLM client with per-model config
-    client = LLMClient(MODEL_CONFIG)
+    # Initialize LLM client with config
+    client = LLMClient(config)
     init_chat_service(client)
 
-    # Register LLM client in service locator so tools (e.g. agent_task) can access it
+    # Register LLM client in service locator so tools (e.g. multi_agent) can access it
     from backend.tools import register_service
     register_service("llm_client", client)
 

backend/routes/conversations.py

@@ -5,7 +5,7 @@ from flask import Blueprint, request, g
 from backend import db
 from backend.models import Conversation, Project
 from backend.utils.helpers import ok, err, to_dict
-from backend.config import DEFAULT_MODEL
+from backend.config import config
 
 bp = Blueprint("conversations", __name__)
 
@@ -40,7 +40,7 @@ def conversation_list():
             user_id=user.id,
             project_id=project_id or None,
             title=d.get("title", ""),
-            model=d.get("model", DEFAULT_MODEL),
+            model=d.get("model", config.default_model),
             system_prompt=d.get("system_prompt", ""),
             temperature=d.get("temperature", 1.0),
             max_tokens=d.get("max_tokens", 65536),

backend/routes/models.py

@@ -1,7 +1,7 @@
 """Model list API routes"""
 from flask import Blueprint
 from backend.utils.helpers import ok
-from backend.config import MODELS
+from backend.config import config
 
 bp = Blueprint("models", __name__)
 
@@ -13,7 +13,10 @@ _SENSITIVE_KEYS = {"api_key", "api_url"}
 def list_models():
     """Get available model list (without sensitive fields like api_key)"""
     safe_models = [
-        {k: v for k, v in m.items() if k not in _SENSITIVE_KEYS}
-        for m in MODELS
+        {
+            "id": m.id,
+            "name": m.name,
+        }
+        for m in config.models
     ]
     return ok(safe_models)

backend/routes/stats.py

@@ -1,29 +1,38 @@
 """Token statistics API routes"""
-from datetime import date, timedelta
+from datetime import date, timedelta, datetime, timezone
 from flask import Blueprint, request, g
-from sqlalchemy import func
-from backend.models import TokenUsage
+from sqlalchemy import func, extract
+from backend.models import TokenUsage, Message, Conversation
 from backend.utils.helpers import ok, err
+from backend import db
 
 bp = Blueprint("stats", __name__)
 
 
+def _utc_today():
+    """Get today's date in UTC to match stored timestamps."""
+    return datetime.now(timezone.utc).date()
+
+
 @bp.route("/api/stats/tokens", methods=["GET"])
 def token_stats():
     """Get token usage statistics"""
     user = g.current_user
     period = request.args.get("period", "daily")
 
-    today = date.today()
+    today = _utc_today()
 
     if period == "daily":
         stats = TokenUsage.query.filter_by(user_id=user.id, date=today).all()
+        # Hourly breakdown from Message table
+        hourly = _build_hourly_stats(user.id, today)
         result = {
             "period": "daily",
             "date": today.isoformat(),
             "prompt_tokens": sum(s.prompt_tokens for s in stats),
             "completion_tokens": sum(s.completion_tokens for s in stats),
             "total_tokens": sum(s.total_tokens for s in stats),
+            "hourly": hourly,
             "by_model": {
                 s.model: {
                     "prompt": s.prompt_tokens,
@@ -92,3 +101,37 @@ def _build_period_result(stats, period, start_date, end_date, days):
         "daily": daily_data,
         "by_model": by_model,
     }
+
+
+def _build_hourly_stats(user_id, day):
+    """Build hourly token breakdown for a given day (UTC) from Message table."""
+    day_start = datetime.combine(day, datetime.min.time()).replace(tzinfo=timezone.utc)
+    day_end = datetime.combine(day, datetime.max.time()).replace(tzinfo=timezone.utc)
+
+    conv_ids = (
+        db.session.query(Conversation.id)
+        .filter(Conversation.user_id == user_id)
+        .subquery()
+    )
+
+    rows = (
+        db.session.query(
+            extract("hour", Message.created_at).label("hour"),
+            func.sum(Message.token_count).label("total"),
+        )
+        .filter(
+            Message.conversation_id.in_(conv_ids),
+            Message.role == "assistant",
+            Message.created_at >= day_start,
+            Message.created_at <= day_end,
+        )
+        .group_by(extract("hour", Message.created_at))
+        .all()
+    )
+
+    hourly = {}
+    for r in rows:
+        h = int(r.hour)
+        hourly[str(h)] = {"total": r.total or 0}
+
+    return hourly

backend/services/chat.py

@@ -14,7 +14,7 @@ from backend.utils.helpers import (
     build_messages,
 )
 from backend.services.llm_client import LLMClient
-from backend.config import MAX_ITERATIONS, TOOL_MAX_WORKERS, TOOL_RESULT_MAX_LENGTH
+from backend.config import config as _cfg
 
 logger = logging.getLogger(__name__)
 
@@ -61,13 +61,20 @@ class ChatService:
         """
         conv_id = conv.id
         conv_model = conv.model
+        conv_max_tokens = conv.max_tokens
+        conv_temperature = conv.temperature
+        conv_thinking_enabled = conv.thinking_enabled
         app = current_app._get_current_object()
         tools = registry.list_all() if tools_enabled else None
         initial_messages = build_messages(conv, project_id)
 
         executor = ToolExecutor(registry=registry)
 
-        context = {"model": conv_model}
+        context = {
+            "model": conv_model,
+            "max_tokens": conv_max_tokens,
+            "temperature": conv_temperature,
+        }
         if project_id:
             context["project_id"] = project_id
         elif conv.project_id:
@@ -82,10 +89,26 @@ class ChatService:
             total_completion_tokens = 0
             total_prompt_tokens = 0
 
-            for iteration in range(MAX_ITERATIONS):
+
+            for iteration in range(_cfg.max_iterations):
+                # Helper to parse stream_result event
+                def parse_stream_result(event_str):
+                    """Parse stream_result SSE event and extract data dict."""
+                    # Format: "event: stream_result\ndata: {...}\n\n"
                     try:
-                    stream_result = self._stream_llm_response(
-                        app, conv_id, messages, tools, tool_choice, step_index
+                        for line in event_str.split('\n'):
+                            if line.startswith('data: '):
+                                return json.loads(line[6:])
+                    except Exception:
+                        pass
+                    return None
+
+                # Collect SSE events and extract final stream_result
+                try:
+                    stream_gen = self._stream_llm_response(
+                        app, messages, tools, tool_choice, step_index,
+                        conv_model, conv_max_tokens, conv_temperature,
+                        conv_thinking_enabled,
                     )
                 except requests.exceptions.HTTPError as e:
                     resp = e.response
@@ -107,22 +130,37 @@ class ChatService:
                     yield _sse_event("error", {"content": f"Internal error: {e}"})
                     return
 
-                if stream_result is None:
-                    return  # Client disconnected
+                result_data = None
+                try:
+                    for event_str in stream_gen:
+                        # Check if this is a stream_result event (final event)
+                        if event_str.startswith("event: stream_result"):
+                            result_data = parse_stream_result(event_str)
+                        else:
+                            # Forward process_step events to client in real-time
+                            yield event_str
+                except Exception as e:
+                    logger.exception("Error during streaming")
+                    yield _sse_event("error", {"content": f"Stream error: {e}"})
+                    return
 
-                full_content, full_thinking, tool_calls_list, \
-                    thinking_step_id, thinking_step_idx, \
-                    text_step_id, text_step_idx, \
-                    completion_tokens, prompt_tokens, \
-                    sse_chunks = stream_result
+                if result_data is None:
+                    return  # Client disconnected or error
+
+                # Extract data from stream_result
+                full_content = result_data["full_content"]
+                full_thinking = result_data["full_thinking"]
+                tool_calls_list = result_data["tool_calls_list"]
+                thinking_step_id = result_data["thinking_step_id"]
+                thinking_step_idx = result_data["thinking_step_idx"]
+                text_step_id = result_data["text_step_id"]
+                text_step_idx = result_data["text_step_idx"]
+                completion_tokens = result_data["completion_tokens"]
+                prompt_tokens = result_data["prompt_tokens"]
 
                 total_prompt_tokens += prompt_tokens
                 total_completion_tokens += completion_tokens
 
-                # Yield accumulated SSE chunks to frontend
-                for chunk in sse_chunks:
-                    yield chunk
-
                 # Save thinking/text steps to all_steps for DB storage
                 if thinking_step_id is not None:
                     all_steps.append({
@@ -185,7 +223,7 @@ class ChatService:
                     # Append assistant message + tool results for the next iteration
                     messages.append({
                         "role": "assistant",
-                        "content": full_content or None,
+                        "content": full_content or "",
                         "tool_calls": tool_calls_list,
                     })
                     messages.extend(tool_results)
@@ -232,12 +270,19 @@ class ChatService:
     # ------------------------------------------------------------------
 
     def _stream_llm_response(
-        self, app, conv_id, messages, tools, tool_choice, step_index
+        self, app, messages, tools, tool_choice, step_index,
+        model, max_tokens, temperature, thinking_enabled,
     ):
-        """Call LLM streaming API and parse the response.
+        """Call LLM streaming API and yield SSE events in real-time.
 
-        Returns a tuple of parsed results, or None if the client disconnected.
-        Raises HTTPError / ConnectionError / Timeout for the caller to handle.
+        This is a generator that yields SSE event strings as they are received.
+        The final yield is a 'stream_result' event containing the accumulated data.
+
+        Yields:
+            str: SSE event strings (process_step events, then stream_result)
+
+        Raises:
+            HTTPError / ConnectionError / Timeout for the caller to handle.
         """
         full_content = ""
         full_thinking = ""
@@ -250,16 +295,13 @@ class ChatService:
         text_step_id = None
         text_step_idx = None
 
-        sse_chunks = []  # Collect SSE events to yield later
-
         with app.app_context():
-            active_conv = db.session.get(Conversation, conv_id)
             resp = self.llm.call(
-                model=active_conv.model,
+                model=model,
                 messages=messages,
-                max_tokens=active_conv.max_tokens,
-                temperature=active_conv.temperature,
-                thinking_enabled=active_conv.thinking_enabled,
+                max_tokens=max_tokens,
+                temperature=temperature,
+                thinking_enabled=thinking_enabled,
                 tools=tools,
                 tool_choice=tool_choice,
                 stream=True,
@@ -269,7 +311,7 @@ class ChatService:
         for line in resp.iter_lines():
             if _client_disconnected():
                 resp.close()
-                return None
+                return  # Client disconnected, stop generator
 
             if not line:
                 continue
@@ -295,37 +337,44 @@ class ChatService:
 
             delta = choices[0].get("delta", {})
 
+            # Yield thinking content in real-time
             reasoning = delta.get("reasoning_content", "")
             if reasoning:
                 full_thinking += reasoning
                 if thinking_step_id is None:
                     thinking_step_id = f"step-{step_index}"
                     thinking_step_idx = step_index
-                sse_chunks.append(_sse_event("process_step", {
+                yield _sse_event("process_step", {
                     "id": thinking_step_id, "index": thinking_step_idx,
                     "type": "thinking", "content": full_thinking,
-                }))
+                })
 
+            # Yield text content in real-time
             text = delta.get("content", "")
             if text:
                 full_content += text
                 if text_step_id is None:
                     text_step_idx = step_index + (1 if thinking_step_id is not None else 0)
                     text_step_id = f"step-{text_step_idx}"
-                sse_chunks.append(_sse_event("process_step", {
+                yield _sse_event("process_step", {
                     "id": text_step_id, "index": text_step_idx,
                     "type": "text", "content": full_content,
-                }))
+                })
 
             tool_calls_list = self._process_tool_calls_delta(delta, tool_calls_list)
 
-        return (
-            full_content, full_thinking, tool_calls_list,
-            thinking_step_id, thinking_step_idx,
-            text_step_id, text_step_idx,
-            token_count, prompt_tokens,
-            sse_chunks,
-        )
+        # Final yield: stream_result event with accumulated data
+        yield _sse_event("stream_result", {
+            "full_content": full_content,
+            "full_thinking": full_thinking,
+            "tool_calls_list": tool_calls_list,
+            "thinking_step_id": thinking_step_id,
+            "thinking_step_idx": thinking_step_idx,
+            "text_step_id": text_step_id,
+            "text_step_idx": text_step_idx,
+            "completion_tokens": token_count,
+            "prompt_tokens": prompt_tokens,
+        })
 
     def _execute_tools_safe(self, app, executor, tool_calls_list, context):
         """Execute tool calls with top-level error wrapping.
@@ -336,17 +385,17 @@ class ChatService:
         try:
             if len(tool_calls_list) > 1:
                 with app.app_context():
-                    tool_results = executor.process_tool_calls_parallel(
-                        tool_calls_list, context, max_workers=TOOL_MAX_WORKERS
+                    return executor.process_tool_calls_parallel(
+                        tool_calls_list, context, max_workers=_cfg.tool_max_workers
                     )
             else:
                 with app.app_context():
-                    tool_results = executor.process_tool_calls(
+                    return executor.process_tool_calls(
                         tool_calls_list, context
                     )
         except Exception as e:
             logger.exception("Error during tool execution")
-            tool_results = [
+            return [
                 {
                     "role": "tool",
                     "tool_call_id": tc["id"],
@@ -359,30 +408,6 @@ class ChatService:
                 for tc in tool_calls_list
             ]
 
-        # Truncate oversized tool result content
-        for tr in tool_results:
-            if len(tr["content"]) > TOOL_RESULT_MAX_LENGTH:
-                try:
-                    result_data = json.loads(tr["content"])
-                    original = result_data
-                except (json.JSONDecodeError, TypeError):
-                    original = None
-
-                tr["content"] = json.dumps(
-                    {"success": False, "error": "Tool result too large, truncated"},
-                    ensure_ascii=False,
-                ) if not original else json.dumps(
-                    {
-                        **original,
-                        "truncated": True,
-                        "_note": f"Content truncated, original length {len(tr['content'])} chars",
-                    },
-                    ensure_ascii=False,
-                    default=str,
-                )[:TOOL_RESULT_MAX_LENGTH]
-
-        return tool_results
-
     def _save_message(
         self, app, conv_id, conv_model, msg_id,
         full_content, all_tool_calls, all_tool_results,

backend/services/llm_client.py

@@ -35,28 +35,22 @@ def _detect_provider(api_url: str) -> str:
 class LLMClient:
     """OpenAI-compatible LLM API client.
 
-    Each model must have its own api_url and api_key configured in MODEL_CONFIG.
+    Each model must have its own api_url and api_key configured in config.models.
     """
 
-    def __init__(self, model_config: dict):
-        """Initialize with per-model config lookup.
+    def __init__(self, cfg):
+        """Initialize with AppConfig.
 
         Args:
-            model_config: {model_id: {"api_url": ..., "api_key": ...}}
+            cfg: AppConfig dataclass instance
         """
-        self.model_config = model_config
+        self.cfg = cfg
 
     def _get_credentials(self, model: str):
         """Get api_url and api_key for a model, with env-var expansion."""
-        cfg = self.model_config.get(model)
-        if not cfg:
-            raise ValueError(f"Unknown model: '{model}', not found in config")
-        api_url = _resolve_env_vars(cfg.get("api_url", ""))
-        api_key = _resolve_env_vars(cfg.get("api_key", ""))
-        if not api_url:
-            raise ValueError(f"Model '{model}' has no api_url configured")
-        if not api_key:
-            raise ValueError(f"Model '{model}' has no api_key configured")
+        api_url, api_key = self.cfg.get_model_credentials(model)
+        api_url = _resolve_env_vars(api_url)
+        api_key = _resolve_env_vars(api_key)
         return api_url, api_key
 
     def _build_body(self, model, messages, max_tokens, temperature, thinking_enabled,

backend/tools/__init__.py

@@ -15,13 +15,13 @@ Usage:
     result = registry.execute("web_search", {"query": "Python"})
 """
 
-from backend.tools.core import ToolDefinition, ToolResult, ToolRegistry, registry
-from backend.tools.factory import tool, register_tool
+from backend.tools.core import registry
+from backend.tools.factory import tool
 from backend.tools.executor import ToolExecutor
 
 
 # ---------------------------------------------------------------------------
-# Service locator – allows tools (e.g. agent_task) to access LLM client
+# Service locator – allows tools (e.g. multi_agent) to access LLM client
 # ---------------------------------------------------------------------------
 _services: dict = {}
 
@@ -47,16 +47,12 @@ def init_tools() -> None:
 
 # Public API exports
 __all__ = [
-    # Core classes
-    "ToolDefinition",
-    "ToolResult",
-    "ToolRegistry",
-    "ToolExecutor",
     # Instances
     "registry",
     # Factory functions
     "tool",
-    "register_tool",
+    # Classes
+    "ToolExecutor",
     # Initialization
     "init_tools",
     # Service locator

backend/tools/builtin/agent.py

@@ -1,130 +1,49 @@
-"""Multi-agent tools for concurrent and batch task execution.
-
-Provides:
-- parallel_execute: Run multiple tool calls concurrently
-- agent_task: Spawn sub-agents with their own LLM conversation loops
-"""
 import json
+import logging
 from concurrent.futures import ThreadPoolExecutor, as_completed
-from typing import List, Dict, Any, Optional
-
+from typing import List, Any, Optional
+from backend.tools import get_service
 from backend.tools.factory import tool
 from backend.tools.core import registry
 from backend.tools.executor import ToolExecutor
+from backend.config import config
+
+logger = logging.getLogger(__name__)
+
+# Sub-agents are forbidden from using multi_agent to prevent infinite recursion
+BLOCKED_TOOLS = {"multi_agent"}
 
 
-# ---------------------------------------------------------------------------
-# parallel_execute – run multiple tool calls concurrently
-# ---------------------------------------------------------------------------
+def _to_executor_calls(tool_calls: list, id_prefix: str = "tc") -> list:
+    """Normalize tool calls into executor-compatible format.
 
-@tool(
-    name="parallel_execute",
-    description=(
-        "Execute multiple tool calls concurrently for better performance. "
-        "Use when you have several independent operations that don't depend on each other "
-        "(e.g. reading multiple files, running multiple searches, fetching several pages). "
-        "Results are returned in the same order as the input."
-    ),
-    parameters={
-        "type": "object",
-        "properties": {
-            "tool_calls": {
-                "type": "array",
-                "items": {
-                    "type": "object",
-                    "properties": {
-                        "name": {
-                            "type": "string",
-                            "description": "Tool name to execute",
-                        },
-                        "arguments": {
-                            "type": "object",
-                            "description": "Arguments for the tool",
-                        },
-                    },
-                    "required": ["name", "arguments"],
-                },
-                "description": "List of tool calls to execute in parallel (max 10)",
-            },
-            "concurrency": {
-                "type": "integer",
-                "description": "Max concurrent executions (1-5, default 3)",
-                "default": 3,
-            },
-        },
-        "required": ["tool_calls"],
-    },
-    category="agent",
-)
-def parallel_execute(arguments: dict) -> dict:
-    """Execute multiple tool calls concurrently.
-
-    Args:
-        arguments: {
-            "tool_calls": [
-                {"name": "file_read", "arguments": {"path": "a.py"}},
-                {"name": "web_search", "arguments": {"query": "python"}}
-            ],
-            "concurrency": 3,
-            "_project_id": "..."  // injected by executor
-        }
-
-    Returns:
-        {"results": [{index, tool_name, success, data/error}]}
+    Accepts two input shapes:
+      - LLM format: {"function": {"name": ..., "arguments": ...}}
+      - Simple format: {"name": ..., "arguments": ...}
     """
-    tool_calls = arguments["tool_calls"]
-    concurrency = min(max(arguments.get("concurrency", 3), 1), 5)
-
-    if len(tool_calls) > 10:
-        return {"success": False, "error": "Maximum 10 tool calls allowed per parallel execution"}
-
-    # Build executor context from injected fields
-    context = {}
-    project_id = arguments.get("_project_id")
-    if project_id:
-        context["project_id"] = project_id
-
-    # Format tool_calls into executor-compatible format
     executor_calls = []
     for i, tc in enumerate(tool_calls):
+        if "function" in tc:
+            func = tc["function"]
             executor_calls.append({
-            "id": f"pe-{i}",
+                "id": tc.get("id", f"{id_prefix}-{i}"),
+                "type": tc.get("type", "function"),
+                "function": {
+                    "name": func["name"],
+                    "arguments": func["arguments"],
+                },
+            })
+        else:
+            executor_calls.append({
+                "id": f"{id_prefix}-{i}",
                 "type": "function",
                 "function": {
                     "name": tc["name"],
                     "arguments": json.dumps(tc["arguments"], ensure_ascii=False),
                 },
             })
+    return executor_calls
 
-    # Use ToolExecutor for proper context injection, caching and dedup
-    executor = ToolExecutor(registry=registry, enable_cache=False)
-    executor_results = executor.process_tool_calls_parallel(
-        executor_calls, context, max_workers=concurrency
-    )
-
-    # Format output
-    results = []
-    for er in executor_results:
-        try:
-            content = json.loads(er["content"]) if isinstance(er["content"], str) else er["content"]
-        except (json.JSONDecodeError, TypeError):
-            content = {"success": False, "error": "Failed to parse result"}
-        results.append({
-            "index": len(results),
-            "tool_name": er["name"],
-            **content,
-        })
-
-    return {
-        "success": True,
-        "results": results,
-        "total": len(results),
-    }
-
-
-# ---------------------------------------------------------------------------
-# agent_task – spawn sub-agents with independent LLM conversation loops
-# ---------------------------------------------------------------------------
 
 def _run_sub_agent(
     task_name: str,
@@ -132,6 +51,7 @@ def _run_sub_agent(
     tool_names: Optional[List[str]],
     model: str,
     max_tokens: int,
+    temperature: float,
     project_id: Optional[str],
     app: Any,
     max_iterations: int = 3,
@@ -141,7 +61,6 @@ def _run_sub_agent(
     Each sub-agent gets its own ToolExecutor instance and runs a simplified
     version of the main agent loop, limited to prevent runaway cost.
     """
-    from backend.tools import get_service
 
     llm_client = get_service("llm_client")
     if not llm_client:
@@ -151,16 +70,21 @@ def _run_sub_agent(
             "error": "LLM client not available",
         }
 
-    # Build tool list – filter to requested tools or use all
+    # Build tool list – filter to requested tools, then remove blocked
     all_tools = registry.list_all()
     if tool_names:
         allowed = set(tool_names)
         tools = [t for t in all_tools if t["function"]["name"] in allowed]
     else:
-        tools = all_tools
+        tools = list(all_tools)
+
+    # Remove blocked tools to prevent recursion
+    tools = [t for t in tools if t["function"]["name"] not in BLOCKED_TOOLS]
 
     executor = ToolExecutor(registry=registry)
-    context = {"project_id": project_id} if project_id else None
+    context = {"model": model}
+    if project_id:
+        context["project_id"] = project_id
 
     # System prompt: instruction + reminder to give a final text answer
     system_msg = (
@@ -170,17 +94,21 @@ def _run_sub_agent(
     )
     messages = [{"role": "system", "content": system_msg}]
 
-    for _ in range(max_iterations):
+    for i in range(max_iterations):
+        is_final = (i == max_iterations - 1)
         try:
             with app.app_context():
                 resp = llm_client.call(
                     model=model,
                     messages=messages,
-                    tools=tools if tools else None,
+                    # On the last iteration, don't pass tools so the LLM is
+                    # forced to produce a final text response instead of calling
+                    # more tools.
+                    tools=None if is_final else (tools if tools else None),
                     stream=False,
-                    max_tokens=min(max_tokens, 4096),
-                    temperature=0.7,
-                    timeout=60,
+                    max_tokens=max_tokens,
+                    temperature=temperature,
+                    timeout=config.sub_agent.timeout,
                 )
 
             if resp.status_code != 200:
@@ -196,20 +124,26 @@ def _run_sub_agent(
             message = choice["message"]
 
             if message.get("tool_calls"):
-                messages.append(message)
-                tc_list = message["tool_calls"]
-                # Convert OpenAI tool_calls to executor format
-                executor_calls = []
-                for tc in tc_list:
-                    executor_calls.append({
-                        "id": tc.get("id", ""),
-                        "type": tc.get("type", "function"),
-                        "function": {
-                            "name": tc["function"]["name"],
-                            "arguments": tc["function"]["arguments"],
-                        },
+                # Only extract needed fields — LLM response may contain extra
+                # fields (e.g. reasoning_content) that the API rejects on re-send
+                messages.append({
+                    "role": "assistant",
+                    "content": message.get("content") or "",
+                    "tool_calls": message["tool_calls"],
                 })
-                tool_results = executor.process_tool_calls(executor_calls, context)
+                tc_list = message["tool_calls"]
+                executor_calls = _to_executor_calls(tc_list)
+                # Execute tools inside app_context – file ops and other DB-
+                # dependent tools require an active Flask context and session.
+                with app.app_context():
+                    if len(executor_calls) > 1:
+                        tool_results = executor.process_tool_calls_parallel(
+                            executor_calls, context
+                        )
+                    else:
+                        tool_results = executor.process_tool_calls(
+                            executor_calls, context
+                        )
                 messages.extend(tool_results)
             else:
                 # Final text response
@@ -226,7 +160,7 @@ def _run_sub_agent(
                 "error": str(e),
             }
 
-    # Exhausted iterations without final response — return last LLM output if any
+    # Exhausted iterations without final response
     return {
         "task_name": task_name,
         "success": True,
@@ -234,49 +168,49 @@ def _run_sub_agent(
     }
 
 
-# @tool(
-#     name="agent_task",
-#     description=(
-#         "Spawn one or more sub-agents to work on tasks concurrently. "
-#         "Each agent runs its own independent conversation with the LLM and can use tools. "
-#         "Useful for parallel research, multi-file analysis, or dividing complex tasks into sub-tasks. "
-#         "Each agent is limited to 3 iterations and 4096 tokens to control cost."
-#     ),
-#     parameters={
-#         "type": "object",
-#         "properties": {
-#             "tasks": {
-#                 "type": "array",
-#                 "items": {
-#                     "type": "object",
-#                     "properties": {
-#                         "name": {
-#                             "type": "string",
-#                             "description": "Short name/identifier for this task",
-#                         },
-#                         "instruction": {
-#                             "type": "string",
-#                             "description": "Detailed instruction for the sub-agent",
-#                         },
-#                         "tools": {
-#                             "type": "array",
-#                             "items": {"type": "string"},
-#                             "description": (
-#                                 "Tool names this agent can use (empty = all tools). "
-#                                 "e.g. ['file_read', 'file_list', 'web_search']"
-#                             ),
-#                         },
-#                     },
-#                     "required": ["name", "instruction"],
-#                 },
-#                 "description": "Tasks for parallel sub-agents (max 5)",
-#             },
-#         },
-#         "required": ["tasks"],
-#     },
-#     category="agent",
-# )
-def agent_task(arguments: dict) -> dict:
+@tool(
+    name="multi_agent",
+    description=(
+        "Spawn multiple sub-agents to work on tasks concurrently. "
+        "Each agent runs its own independent conversation with the LLM and can use tools. "
+        "Useful for parallel research, multi-file analysis, or dividing complex tasks into sub-tasks. "
+        "Resource limits (iterations, tokens, concurrency) are configured in config.yml -> sub_agent."
+    ),
+    parameters={
+        "type": "object",
+        "properties": {
+            "tasks": {
+                "type": "array",
+                "items": {
+                    "type": "object",
+                    "properties": {
+                        "name": {
+                            "type": "string",
+                            "description": "Short name/identifier for this task",
+                        },
+                        "instruction": {
+                            "type": "string",
+                            "description": "Detailed instruction for the sub-agent",
+                        },
+                        "tools": {
+                            "type": "array",
+                            "items": {"type": "string"},
+                            "description": (
+                                "Tool names this agent can use (empty = all tools). "
+                                "e.g. ['file_read', 'file_list', 'web_search']"
+                            ),
+                        },
+                    },
+                    "required": ["name", "instruction"],
+                },
+                "description": "Tasks for parallel sub-agents (max 5)",
+            },
+        },
+        "required": ["tasks"],
+    },
+    category="agent",
+)
+def multi_agent(arguments: dict) -> dict:
     """Spawn sub-agents to work on tasks concurrently.
 
     Args:
@@ -296,7 +230,7 @@ def agent_task(arguments: dict) -> dict:
         }
 
     Returns:
-        {"success": true, "results": [{task_name, success, response/error}]}
+        {"success": true, "results": [{task_name, success, response/error}], "total": int}
     """
     from flask import current_app
 
@@ -309,11 +243,13 @@ def agent_task(arguments: dict) -> dict:
     app = current_app._get_current_object()
 
     # Use injected model/project_id from executor context, fall back to defaults
-    model = arguments.get("_model", "glm-5")
+    model = arguments.get("_model") or config.default_model
     project_id = arguments.get("_project_id")
+    max_tokens = arguments.get("_max_tokens", 65536)
+    temperature = arguments.get("_temperature", 0.7)
 
-    # Execute agents concurrently (max 3 at a time)
-    concurrency = min(len(tasks), 3)
+    # Execute agents concurrently
+    concurrency = min(len(tasks), config.sub_agent.max_concurrency)
     results = [None] * len(tasks)
 
     with ThreadPoolExecutor(max_workers=concurrency) as pool:
@@ -324,9 +260,11 @@ def agent_task(arguments: dict) -> dict:
                 task["instruction"],
                 task.get("tools"),
                 model,
-                4096,
+                max_tokens,
+                temperature,
                 project_id,
                 app,
+                config.sub_agent.max_iterations,
             ): i
             for i, task in enumerate(tasks)
         }

backend/tools/builtin/code.py

@@ -1,55 +1,131 @@
-"""Safe code execution tool with sandboxing"""
+"""Safe code execution tool with sandboxing and strictness levels"""
 import ast
 import subprocess
 import sys
 import tempfile
 import textwrap
-from pathlib import Path
+from typing import Dict, List, Set
 
 from backend.tools.factory import tool
+from backend.config import config
+from backend.tools.docker_executor import DockerExecutor
 
 
-# Blacklist of dangerous modules - all other modules are allowed
-BLOCKED_MODULES = {
-    # System-level access
-    "os", "sys", "subprocess", "shutil", "signal", "ctypes",
-    "multiprocessing", "threading", "_thread",
-    # Network access
-    "socket", "http", "urllib", "requests", "ftplib", "smtplib",
-    "telnetlib", "xmlrpc", "asyncio",
-    # File system / I/O
-    "pathlib", "io", "glob", "tempfile", "shutil", "fnmatch",
-    # Code execution / introspection
-    "importlib", "pkgutil", "code", "codeop", "compileall",
-    "runpy", "pdb", "profile", "cProfile",
-    # Dangerous stdlib
-    "webbrowser", "antigravity", "turtle",
-    # IPC / persistence
-    "pickle", "shelve", "marshal", "sqlite3", "dbm",
-    # Process / shell
-    "commands", "pipes", "pty", "posix", "posixpath",
-}
+# Strictness profiles configuration
+# - lenient: no restrictions at all
+# - standard: allowlist based, only safe modules permitted
+# - strict: minimal allowlist, only pure computation modules
+STRICTNESS_PROFILES: Dict[str, dict] = {
+    "lenient": {
+        "timeout": 30,
+        "description": "No restrictions, all modules and builtins allowed",
+        "allowlist_modules": None,  # None means all allowed
+        "blocked_builtins": set(),
+    },
 
-
-# Blacklist of dangerous builtins
-BLOCKED_BUILTINS = {
-    "eval", "exec", "compile", "open", "input",
-    "__import__", "globals", "locals", "vars",
+    "standard": {
+        "timeout": 10,
+        "description": "Allowlist based, only safe modules and builtins permitted",
+        "allowlist_modules": {
+            # Data types & serialization
+            "json", "csv", "re", "typing",
+            # Data structures
+            "collections", "itertools", "functools", "operator", "heapq", "bisect",
+            "array", "copy", "pprint", "enum",
+            # Math & numbers
+            "math", "cmath", "statistics", "random", "fractions", "decimal", "numbers",
+            # Date & time
+            "datetime", "time", "calendar",
+            # Text processing
+            "string", "textwrap", "unicodedata", "difflib",
+            # Data formats
+            "base64", "binascii", "quopri", "uu", "html", "xml.etree.ElementTree",
+            # Functional & concurrency helpers
+            "dataclasses", "hashlib", "hmac",
+            # Common utilities
+            "abc", "contextlib", "warnings", "logging",
+        },
+        "blocked_builtins": {
+            "eval", "exec", "compile", "__import__",
+            "open", "input", "globals", "locals", "vars",
             "breakpoint", "exit", "quit",
             "memoryview", "bytearray",
+            "getattr", "setattr", "delattr",
+        },
+    },
+
+    "strict": {
+        "timeout": 5,
+        "description": "Minimal allowlist, only pure computation modules",
+        "allowlist_modules": {
+            # Pure data structures
+            "collections", "itertools", "functools", "operator",
+            "array", "copy", "enum",
+            # Pure math
+            "math", "cmath", "numbers", "fractions", "decimal",
+            "random", "statistics",
+            # Pure text
+            "string", "textwrap", "unicodedata",
+            # Type hints
+            "typing",
+            # Utilities (no I/O)
+            "dataclasses", "abc", "contextlib",
+        },
+        "blocked_builtins": {
+            "eval", "exec", "compile", "__import__",
+            "open", "input", "globals", "locals", "vars",
+            "breakpoint", "exit", "quit",
+            "memoryview", "bytearray",
+            "dir", "hasattr", "getattr", "setattr", "delattr",
+            "type", "isinstance", "issubclass",
+        },
+    },
 }
 
 
+def register_extra_modules(strictness: str, modules: Set[str] | List[str]) -> None:
+    """Register additional modules to a strictness level's allowlist.
+
+    Args:
+        strictness: One of "lenient", "standard", "strict".
+        modules: Module names to add to the allowlist.
+    """
+    if strictness not in STRICTNESS_PROFILES:
+        raise ValueError(f"Invalid strictness level: {strictness}. Must be one of: {', '.join(STRICTNESS_PROFILES.keys())}")
+
+    profile = STRICTNESS_PROFILES[strictness]
+    if profile.get("allowlist_modules") is None:
+        return  # lenient mode allows everything, nothing to add
+
+    profile["allowlist_modules"].update(modules)
+
+
+# Apply extra modules from config.yml on module load
+for _level, _mods in config.code_execution.extra_allowed_modules.items():
+    if isinstance(_mods, list) and _mods:
+        register_extra_modules(_level, _mods)
+
+
 @tool(
     name="execute_python",
-    description="Execute Python code in a sandboxed environment. Most standard library modules are allowed, with dangerous modules (os, subprocess, socket, etc.) blocked. Max execution time: 10 seconds.",
+    description="Execute Python code in a sandboxed environment with configurable strictness levels (lenient/standard/strict). "
+                "Default: 'standard' mode - balances security and flexibility with 10s timeout. "
+                "Use 'lenient' for data processing tasks (30s timeout, more modules allowed). "
+                "Use 'strict' for basic calculations only (5s timeout, minimal module access).",
     parameters={
         "type": "object",
         "properties": {
             "code": {
                 "type": "string",
-                "description": "Python code to execute. Dangerous modules (os, subprocess, socket, etc.) are blocked."
-
+                "description": "Python code to execute. Available modules depend on strictness level."
+            },
+            "strictness": {
+                "type": "string",
+                "enum": ["lenient", "standard", "strict"],
+                "description": "Optional. Security strictness level (default: standard). "
+                              "lenient: 30s timeout, most modules allowed; "
+                              "standard: 10s timeout, balanced security; "
+                              "strict: 5s timeout, minimal permissions."
             }
         },
         "required": ["code"]
@@ -61,36 +137,76 @@ def execute_python(arguments: dict) -> dict:
     Execute Python code safely with sandboxing.
 
     Security measures:
-    1. Blocked dangerous imports (blacklist)
-    2. Blocked dangerous builtins
-    3. Timeout limit (10s)
-    4. No file system access
-    5. No network access
+    1. Lenient mode: no restrictions
+    2. Standard/strict mode: allowlist based module restrictions
+    3. Configurable blocked builtins based on strictness level
+    4. Timeout limit (5s/10s/30s based on strictness)
+    5. Subprocess isolation
     """
     code = arguments["code"]
+    strictness = arguments.get("strictness", config.code_execution.default_strictness)
     
-    # Security check: detect dangerous imports
-    dangerous_imports = _check_dangerous_imports(code)
-    if dangerous_imports:
+    # Validate strictness level
+    if strictness not in STRICTNESS_PROFILES:
         return {
             "success": False,
-            "error": f"Blocked imports: {', '.join(dangerous_imports)}. These modules are not allowed for security reasons."
+            "error": f"Invalid strictness level: {strictness}. Must be one of: {', '.join(STRICTNESS_PROFILES.keys())}"
         }
     
-    # Security check: detect dangerous function calls
-    dangerous_calls = _check_dangerous_calls(code)
+    # Get profile configuration
+    profile = STRICTNESS_PROFILES[strictness]
+    allowlist_modules = profile.get("allowlist_modules")
+    blocked_builtins = profile["blocked_builtins"]
+    timeout = profile["timeout"]
+
+    # Parse and validate code syntax first
+    try:
+        tree = ast.parse(code)
+    except SyntaxError as e:
+        return {"success": False, "error": f"Syntax error in code: {e}"}
+
+    # Security check: detect disallowed imports
+    disallowed_imports = _check_disallowed_imports(tree, allowlist_modules)
+    if disallowed_imports:
+        return {
+            "success": False,
+            "error": f"Blocked imports: {', '.join(disallowed_imports)}. These modules are not allowed in '{strictness}' mode."
+        }
+
+    # Security check: detect dangerous function calls (skip if no restrictions)
+    if blocked_builtins:
+        dangerous_calls = _check_dangerous_calls(tree, blocked_builtins)
         if dangerous_calls:
             return {
                 "success": False,
-            "error": f"Blocked functions: {', '.join(dangerous_calls)}"
+                "error": f"Blocked functions: {', '.join(dangerous_calls)}. These functions are not allowed in '{strictness}' mode."
             }
 
-    # Execute in isolated subprocess
+    # Choose execution backend
+    backend = config.code_execution.backend
+    if backend == "docker":
+        # Use Docker executor
+        executor = DockerExecutor(
+            image=config.code_execution.docker_image,
+            network=config.code_execution.docker_network,
+            user=config.code_execution.docker_user,
+            memory_limit=config.code_execution.docker_memory_limit,
+            cpu_shares=config.code_execution.docker_cpu_shares,
+        )
+        result = executor.execute(
+            code=code,
+            timeout=timeout,
+            strictness=strictness,
+        )
+        # Docker executor already returns the same dict structure
+        return result
+    else:
+        # Default subprocess backend
         try:
             result = subprocess.run(
-            [sys.executable, "-c", _build_safe_code(code)],
+                [sys.executable, "-c", _build_safe_code(code, blocked_builtins, allowlist_modules)],
                 capture_output=True,
-            timeout=10,
+                timeout=timeout,
                 cwd=tempfile.gettempdir(),
                 encoding="utf-8",
                 env={  # Clear environment variables
@@ -99,18 +215,25 @@ def execute_python(arguments: dict) -> dict:
             )
 
             if result.returncode == 0:
-            return {"success": True, "output": result.stdout}
+                return {
+                    "success": True,
+                    "output": result.stdout,
+                    "strictness": strictness,
+                    "timeout": timeout
+                }
             else:
                 return {"success": False, "error": result.stderr or "Execution failed"}
 
         except subprocess.TimeoutExpired:
-        return {"success": False, "error": "Execution timeout (10s limit)"}
+            return {"success": False, "error": f"Execution timeout ({timeout}s limit in '{strictness}' mode)"}
         except Exception as e:
             return {"success": False, "error": f"Execution error: {str(e)}"}
 
 
-def _build_safe_code(code: str) -> str:
-    """Build sandboxed code with restricted globals"""
+def _build_safe_code(code: str, blocked_builtins: Set[str],
+                     allowlist_modules: Set[str] | None = None) -> str:
+    """Build sandboxed code with restricted globals and runtime import hook."""
+    allowlist_repr = "None" if allowlist_modules is None else repr(allowlist_modules)
     template = textwrap.dedent('''
         import builtins
 
@@ -118,6 +241,20 @@ def _build_safe_code(code: str) -> str:
         _BLOCKED = %r
         _safe_builtins = {k: getattr(builtins, k) for k in dir(builtins) if k not in _BLOCKED}
 
+        # Runtime import hook for allowlist enforcement
+        _ALLOWLIST = %s
+        if _ALLOWLIST is not None:
+            _original_import = builtins.__import__
+            def _restricted_import(name, *args, **kwargs):
+                top_level = name.split(".")[0]
+                if top_level not in _ALLOWLIST:
+                    raise ImportError(
+                        f"'{top_level}' is not allowed in the current strictness mode"
+                    )
+                return _original_import(name, *args, **kwargs)
+            builtins.__import__ = _restricted_import
+            _safe_builtins["__import__"] = _restricted_import
+
         # Create safe namespace
         _safe_globals = {
             "__builtins__": _safe_builtins,
@@ -128,44 +265,43 @@ def _build_safe_code(code: str) -> str:
         exec(%r, _safe_globals)
     ''').strip()
 
-    return template % (BLOCKED_BUILTINS, code)
+    return template % (blocked_builtins, allowlist_repr, code)
 
 
-def _check_dangerous_imports(code: str) -> list:
-    """Check for blocked (blacklisted) imports"""
-    try:
-        tree = ast.parse(code)
-    except SyntaxError:
+def _check_disallowed_imports(tree: ast.AST, allowlist_modules: Set[str] | None) -> List[str]:
+    """Check for imports not in allowlist. None allowlist means everything is allowed."""
+    if allowlist_modules is None:
         return []
 
-    dangerous = []
+    disallowed = []
     for node in ast.walk(tree):
         if isinstance(node, ast.Import):
             for alias in node.names:
                 module = alias.name.split(".")[0]
-                if module in BLOCKED_MODULES:
-                    dangerous.append(module)
+                if module not in allowlist_modules:
+                    disallowed.append(module)
         elif isinstance(node, ast.ImportFrom):
             if node.module:
                 module = node.module.split(".")[0]
-                if module in BLOCKED_MODULES:
-                    dangerous.append(module)
+                if module not in allowlist_modules:
+                    disallowed.append(module)
 
-    return dangerous
+    return list(dict.fromkeys(disallowed))  # deduplicate while preserving order
 
 
-def _check_dangerous_calls(code: str) -> list:
-    """Check for blocked function calls"""
-    try:
-        tree = ast.parse(code)
-    except SyntaxError:
-        return []
-
+def _check_dangerous_calls(tree: ast.AST, blocked_builtins: Set[str]) -> List[str]:
+    """Check for blocked function calls including attribute access patterns."""
     dangerous = []
     for node in ast.walk(tree):
         if isinstance(node, ast.Call):
             if isinstance(node.func, ast.Name):
-                if node.func.id in BLOCKED_BUILTINS:
+                # Direct call: eval("...")
+                if node.func.id in blocked_builtins:
                     dangerous.append(node.func.id)
+            elif isinstance(node.func, ast.Attribute):
+                # Attribute call: builtins.open(...) or os.system(...)
+                attr_name = node.func.attr
+                if attr_name in blocked_builtins:
+                    dangerous.append(attr_name)
 
-    return dangerous
+    return list(dict.fromkeys(dangerous))

backend/tools/docker_executor.py

@@ -0,0 +1,156 @@
+"""Docker-based code execution with isolation."""
+import subprocess
+import tempfile
+from typing import Optional, Dict, Any
+from pathlib import Path
+
+from backend.config import config
+
+
+class DockerExecutor:
+    """Execute Python code in isolated Docker containers."""
+    
+    def __init__(
+        self,
+        image: str = "python:3.12-slim",
+        network: str = "none",
+        user: str = "nobody",
+        workdir: str = "/workspace",
+        memory_limit: Optional[str] = None,
+        cpu_shares: Optional[int] = None,
+    ):
+        self.image = image
+        self.network = network
+        self.user = user
+        self.workdir = workdir
+        self.memory_limit = memory_limit
+        self.cpu_shares = cpu_shares
+    
+    def execute(
+        self,
+        code: str,
+        timeout: int,
+        strictness: str,
+        extra_env: Optional[Dict[str, str]] = None,
+        mount_src: Optional[str] = None,
+        mount_dst: Optional[str] = None,
+    ) -> Dict[str, Any]:
+        """
+        Execute Python code in a Docker container.
+        
+        Args:
+            code: Python code to execute.
+            timeout: Maximum execution time in seconds.
+            strictness: Strictness level (lenient/standard/strict) for logging.
+            extra_env: Additional environment variables.
+            mount_src: Host path to mount into container (optional).
+            mount_dst: Container mount path (defaults to workdir).
+        
+        Returns:
+            Dictionary with keys:
+                success: bool
+                output: str if success else empty
+                error: str if not success else empty
+                container_id: str for debugging
+        """
+        # Create temporary file with code inside a temporary directory
+        # so we can mount it into container
+        with tempfile.TemporaryDirectory() as tmpdir:
+            code_path = Path(tmpdir) / "code.py"
+            code_path.write_text(code, encoding="utf-8")
+            
+            # Build docker run command
+            cmd = [
+                "docker", "run",
+                "--rm",
+                f"--network={self.network}",
+                f"--user={self.user}",
+                f"--workdir={self.workdir}",
+                f"--env=PYTHONIOENCODING=utf-8",
+            ]
+            
+            # Add memory limit if specified
+            if self.memory_limit:
+                cmd.append(f"--memory={self.memory_limit}")
+            
+            # Add CPU shares if specified
+            if self.cpu_shares:
+                cmd.append(f"--cpu-shares={self.cpu_shares}")
+            
+            # Add timeout via --stop-timeout (seconds before SIGKILL)
+            # Docker's timeout is different; we'll use subprocess timeout instead.
+            # We'll rely on subprocess timeout, but also set --stop-timeout as backup.
+            stop_timeout = timeout + 2  # give 2 seconds grace
+            cmd.append(f"--stop-timeout={stop_timeout}")
+            
+            # Mount the temporary directory as /workspace (read-only)
+            cmd.extend(["-v", f"{tmpdir}:{self.workdir}:ro"])
+            
+            # Additional mount if provided
+            if mount_src and mount_dst:
+                cmd.extend(["-v", f"{mount_src}:{mount_dst}:ro"])
+            
+            # Add environment variables
+            env = extra_env or {}
+            for k, v in env.items():
+                cmd.extend(["-e", f"{k}={v}"])
+            
+            # Finally, image and command to run
+            cmd.append(self.image)
+            cmd.extend(["python", "-c", code])
+            
+            # Execute docker run with timeout
+            try:
+                result = subprocess.run(
+                    cmd,
+                    capture_output=True,
+                    timeout=timeout,
+                    encoding="utf-8",
+                    errors="ignore",
+                )
+                
+                if result.returncode == 0:
+                    return {
+                        "success": True,
+                        "output": result.stdout,
+                        "error": "",
+                        "container_id": "",  # not available with --rm
+                        "strictness": strictness,
+                        "timeout": timeout,
+                    }
+                else:
+                    return {
+                        "success": False,
+                        "output": "",
+                        "error": result.stderr or f"Container exited with code {result.returncode}",
+                        "container_id": "",
+                        "strictness": strictness,
+                        "timeout": timeout,
+                    }
+            except subprocess.TimeoutExpired:
+                return {
+                    "success": False,
+                    "output": "",
+                    "error": f"Execution timeout ({timeout}s limit in '{strictness}' mode)",
+                    "container_id": "",
+                    "strictness": strictness,
+                    "timeout": timeout,
+                }
+            except Exception as e:
+                return {
+                    "success": False,
+                    "output": "",
+                    "error": f"Docker execution error: {str(e)}",
+                    "container_id": "",
+                    "strictness": strictness,
+                    "timeout": timeout,
+                }
+
+
+# Singleton instance
+_default_executor = DockerExecutor()
+
+
+def execute_in_docker(code: str, timeout: int, strictness: str, **kwargs) -> Dict[str, Any]:
+    """Convenience function using default executor."""
+    return _default_executor.execute(code, timeout, strictness, **kwargs)

backend/tools/executor.py

@@ -51,30 +51,89 @@ class ToolExecutor:
                 return record["result"]
         return None
 
-    def clear_history(self) -> None:
-        """Clear call history (call this at start of new conversation turn)"""
-        self._call_history.clear()
-
     @staticmethod
     def _inject_context(name: str, args: dict, context: Optional[dict]) -> None:
         """Inject context fields into tool arguments in-place.
 
         - file_* tools: inject project_id
-        - agent_task: inject model and project_id (prefixed with _ to avoid collisions)
-        - parallel_execute: inject project_id (prefixed with _ to avoid collisions)
+        - agent tools (multi_agent): inject _model and _project_id
         """
         if not context:
             return
         if name.startswith("file_") and "project_id" in context:
             args["project_id"] = context["project_id"]
-        if name == "agent_task":
+        if name == "multi_agent":
             if "model" in context:
                 args["_model"] = context["model"]
             if "project_id" in context:
                 args["_project_id"] = context["project_id"]
-        if name == "parallel_execute":
-            if "project_id" in context:
-                args["_project_id"] = context["project_id"]
+            if "max_tokens" in context:
+                args["_max_tokens"] = context["max_tokens"]
+            if "temperature" in context:
+                args["_temperature"] = context["temperature"]
+
+    def _prepare_call(
+        self,
+        call: dict,
+        context: Optional[dict],
+        seen_calls: set,
+    ) -> tuple:
+        """Parse, inject context, check dedup/cache for a single tool call.
+
+        Returns a tagged tuple:
+          ("error",   call_id, name, error_msg)
+          ("cached",  call_id, name, result_dict)  -- dedup or cache hit
+          ("execute", call_id, name, args, cache_key)
+        """
+        name = call["function"]["name"]
+        args_str = call["function"]["arguments"]
+        call_id = call["id"]
+
+        # Parse JSON arguments
+        try:
+            args = json.loads(args_str) if isinstance(args_str, str) else args_str
+        except json.JSONDecodeError:
+            return ("error", call_id, name, "Invalid JSON arguments")
+
+        # Inject context
+        self._inject_context(name, args, context)
+
+        # Dedup within same batch
+        call_key = f"{name}:{json.dumps(args, sort_keys=True)}"
+        if call_key in seen_calls:
+            return ("cached", call_id, name,
+                    {"success": True, "data": None, "cached": True, "duplicate": True})
+        seen_calls.add(call_key)
+
+        # History dedup
+        history_result = self._check_duplicate_in_history(name, args)
+        if history_result is not None:
+            return ("cached", call_id, name, {**history_result, "cached": True})
+
+        # Cache check
+        cache_key = self._make_cache_key(name, args)
+        cached_result = self._get_cached(cache_key)
+        if cached_result is not None:
+            return ("cached", call_id, name, {**cached_result, "cached": True})
+
+        return ("execute", call_id, name, args, cache_key)
+
+    def _execute_and_record(
+        self,
+        name: str,
+        args: dict,
+        cache_key: str,
+    ) -> dict:
+        """Execute a tool, cache result, record history, and return raw result dict."""
+        result = self._execute_tool(name, args)
+        if result.get("success"):
+            self._set_cache(cache_key, result)
+        self._call_history.append({
+            "name": name,
+            "args_str": json.dumps(args, sort_keys=True, ensure_ascii=False),
+            "result": result,
+        })
+        return result
 
     def process_tool_calls_parallel(
         self,
@@ -85,10 +144,6 @@ class ToolExecutor:
         """
         Process tool calls concurrently and return message list (ordered by input).
 
-        Identical logic to process_tool_calls but uses ThreadPoolExecutor so that
-        independent tool calls (e.g. reading 3 files, running 2 searches) execute
-        in parallel instead of sequentially.
-
         Args:
             tool_calls: Tool call list returned by LLM
             context: Optional context info (user_id, project_id, etc.)
@@ -102,80 +157,31 @@ class ToolExecutor:
 
         max_workers = min(max(max_workers, 1), 6)
 
-        # Phase 1: prepare each call (parse args, inject context, check dedup/cache)
-        # This phase is fast and sequential – it must be done before parallelism
-        # to avoid race conditions on seen_calls / _call_history / _cache.
-        prepared: List[Optional[tuple]] = [None] * len(tool_calls)
-        seen_calls: set = set()
+        # Phase 1: prepare (sequential – avoids race conditions on shared state)
+        prepared = [self._prepare_call(call, context, set()) for call in tool_calls]
 
-        for i, call in enumerate(tool_calls):
-            name = call["function"]["name"]
-            args_str = call["function"]["arguments"]
-            call_id = call["id"]
-
-            # Parse JSON arguments
-            try:
-                args = json.loads(args_str) if isinstance(args_str, str) else args_str
-            except json.JSONDecodeError:
-                prepared[i] = self._create_error_result(call_id, name, "Invalid JSON arguments")
-                continue
-
-            # Inject context into tool arguments
-            self._inject_context(name, args, context)
-
-            # Dedup within same batch
-            call_key = f"{name}:{json.dumps(args, sort_keys=True)}"
-            if call_key in seen_calls:
-                prepared[i] = self._create_tool_result(
-                    call_id, name,
-                    {"success": True, "data": None, "cached": True, "duplicate": True}
-                )
-                continue
-            seen_calls.add(call_key)
-
-            # History dedup
-            history_result = self._check_duplicate_in_history(name, args)
-            if history_result is not None:
-                prepared[i] = self._create_tool_result(call_id, name, {**history_result, "cached": True})
-                continue
-
-            # Cache check
-            cache_key = self._make_cache_key(name, args)
-            cached_result = self._get_cached(cache_key)
-            if cached_result is not None:
-                prepared[i] = self._create_tool_result(call_id, name, {**cached_result, "cached": True})
-                continue
-
-            # Mark as needing actual execution
-            prepared[i] = ("execute", call_id, name, args, cache_key)
-
-        # Separate pre-resolved results from tasks needing execution
+        # Phase 2: separate pre-resolved from tasks needing execution
         results: List[dict] = [None] * len(tool_calls)
-        exec_tasks: Dict[int, tuple] = {}  # index -> (call_id, name, args, cache_key)
+        exec_tasks: Dict[int, tuple] = {}
 
         for i, item in enumerate(prepared):
-            if isinstance(item, dict):
-                results[i] = item
-            elif isinstance(item, tuple) and item[0] == "execute":
+            tag = item[0]
+            if tag == "error":
+                _, call_id, name, error_msg = item
+                results[i] = self._create_error_result(call_id, name, error_msg)
+            elif tag == "cached":
+                _, call_id, name, result_dict = item
+                results[i] = self._create_tool_result(call_id, name, result_dict)
+            else:  # "execute"
                 _, call_id, name, args, cache_key = item
                 exec_tasks[i] = (call_id, name, args, cache_key)
 
-        # Phase 2: execute remaining calls in parallel
+        # Phase 3: execute remaining calls in parallel
         if exec_tasks:
             def _run(idx: int, call_id: str, name: str, args: dict, cache_key: str) -> tuple:
                 t0 = time.time()
-                result = self._execute_tool(name, args)
+                result = self._execute_and_record(name, args, cache_key)
                 elapsed = time.time() - t0
-
-                if result.get("success"):
-                    self._set_cache(cache_key, result)
-
-                self._call_history.append({
-                    "name": name,
-                    "args_str": json.dumps(args, sort_keys=True, ensure_ascii=False),
-                    "result": result,
-                })
-
                 return idx, self._create_tool_result(call_id, name, result, execution_time=elapsed)
 
             with ThreadPoolExecutor(max_workers=max_workers) as pool:
@@ -205,64 +211,21 @@ class ToolExecutor:
             Tool response message list, can be appended to messages
         """
         results = []
-        seen_calls = set()  # Track calls within this batch
+        seen_calls: set = set()
 
         for call in tool_calls:
-            name = call["function"]["name"]
-            args_str = call["function"]["arguments"]
-            call_id = call["id"]
-
-            try:
-                args = json.loads(args_str) if isinstance(args_str, str) else args_str
-            except json.JSONDecodeError:
-                results.append(self._create_error_result(
-                    call_id, name, "Invalid JSON arguments"
-                ))
-                continue
-
-            # Inject context into tool arguments
-            self._inject_context(name, args, context)
-
-            # Check for duplicate within same batch
-            call_key = f"{name}:{json.dumps(args, sort_keys=True)}"
-            if call_key in seen_calls:
-                # Skip duplicate, but still return a result
-                results.append(self._create_tool_result(
-                    call_id, name,
-                    {"success": True, "data": None, "cached": True, "duplicate": True}
-                ))
-                continue
-            seen_calls.add(call_key)
-
-            # Check history for previous call in this session
-            history_result = self._check_duplicate_in_history(name, args)
-            if history_result is not None:
-                result = {**history_result, "cached": True}
-                results.append(self._create_tool_result(call_id, name, result))
-                continue
-
-            # Check cache
-            cache_key = self._make_cache_key(name, args)
-            cached_result = self._get_cached(cache_key)
-            if cached_result is not None:
-                result = {**cached_result, "cached": True}
-                results.append(self._create_tool_result(call_id, name, result))
-                continue
-
-            # Execute tool with retry
-            result = self._execute_tool(name, args)
-            
-            # Cache the result (only cache successful results)
-            if result.get("success"):
-                self._set_cache(cache_key, result)
-            
-            # Add to history
-            self._call_history.append({
-                "name": name,
-                "args_str": json.dumps(args, sort_keys=True, ensure_ascii=False),
-                "result": result
-            })
+            prepared = self._prepare_call(call, context, seen_calls)
+            tag = prepared[0]
 
+            if tag == "error":
+                _, call_id, name, error_msg = prepared
+                results.append(self._create_error_result(call_id, name, error_msg))
+            elif tag == "cached":
+                _, call_id, name, result_dict = prepared
+                results.append(self._create_tool_result(call_id, name, result_dict))
+            else:  # "execute"
+                _, call_id, name, args, cache_key = prepared
+                result = self._execute_and_record(name, args, cache_key)
                 results.append(self._create_tool_result(call_id, name, result))
 
         return results

backend/tools/factory.py

@@ -34,30 +34,3 @@ def tool(
         return func
     return decorator
 
-
-def register_tool(
-    name: str,
-    handler: Callable,
-    description: str,
-    parameters: dict,
-    category: str = "general"
-) -> None:
-    """
-    Register a tool directly (without decorator)
-
-    Usage:
-        register_tool(
-            name="my_tool",
-            handler=my_function,
-            description="Description",
-            parameters={...}
-        )
-    """
-    tool_def = ToolDefinition(
-        name=name,
-        description=description,
-        parameters=parameters,
-        handler=handler,
-        category=category
-    )
-    registry.register(tool_def)

backend/utils/__init__.py

@@ -1,11 +1,11 @@
 """Backend utilities"""
-from backend.utils.helpers import ok, err, to_dict, get_or_create_default_user, record_token_usage, build_messages
+from backend.utils.helpers import ok, err, to_dict, message_to_dict, record_token_usage, build_messages
 
 __all__ = [
     "ok",
     "err",
     "to_dict",
-    "get_or_create_default_user",
+    "message_to_dict",
     "record_token_usage",
     "build_messages",
 ]

backend/utils/helpers.py

@@ -1,6 +1,6 @@
 """Common helper functions"""
 import json
-from datetime import date, datetime
+from datetime import date, datetime, timezone
 from typing import Any
 from flask import jsonify
 from backend import db
@@ -97,7 +97,7 @@ def message_to_dict(msg: Message) -> dict:
 
 def record_token_usage(user_id, model, prompt_tokens, completion_tokens):
     """Record token usage"""
-    today = date.today()
+    today = datetime.now(timezone.utc).date()
     usage = TokenUsage.query.filter_by(
         user_id=user_id, date=today, model=model
     ).first()
@@ -133,6 +133,13 @@ def build_messages(conv, project_id=None):
     # Query messages directly to avoid detached instance warning
     messages = Message.query.filter_by(conversation_id=conv.id).order_by(Message.created_at.asc()).all()
     for m in messages:
+        # Skip tool messages — they are ephemeral intermediate results, not
+        # meant to be replayed as conversation history (would violate the API
+        # protocol that requires tool messages to follow an assistant message
+        # with matching tool_calls).
+        if m.role == "tool":
+            continue
+
         # Build full content from JSON structure
         full_content = m.content
         try:

docs/Design.md

@@ -66,6 +66,7 @@ backend/
 │       ├── data.py      # 计算器、文本、JSON
 │       ├── weather.py   # 天气查询
 │       ├── file_ops.py  # 文件操作（project_id 自动注入）
+│       ├── agent.py     # 多智能体（子 Agent 并发执行，工具权限隔离）
 │       └── code.py      # 代码执行
 │
 ├── utils/               # 辅助函数
@@ -266,8 +267,8 @@ classDiagram
         -ToolRegistry registry
         -dict _cache
         -list _call_history
-        +process_tool_calls(calls, context) list
-        +clear_history() void
+        +process_tool_calls(list, dict) list
+        +process_tool_calls_parallel(list, dict, int) list
     }
 
     ChatService --> LLMClient : 使用
@@ -295,18 +296,17 @@ classDiagram
         +register(ToolDefinition) void
         +get(str name) ToolDefinition?
         +list_all() list~dict~
-        +list_by_category(str) list~dict~
         +execute(str name, dict args) dict
-        +remove(str name) bool
-        +has(str name) bool
     }
 
     class ToolExecutor {
         -ToolRegistry registry
+        -bool enable_cache
+        -int cache_ttl
         -dict _cache
         -list _call_history
         +process_tool_calls(list, dict) list
-        +clear_history() void
+        +process_tool_calls_parallel(list, dict, int) list
     }
 
     class ToolResult {
@@ -394,18 +394,19 @@ def validate_path_in_project(path: str, project_dir: Path) -> Path:
 工具执行器自动为文件工具注入 `project_id`：
 
 ```python
-# backend/tools/executor.py
+# backend/tools/executor.py — _inject_context()
 
-def process_tool_calls(self, tool_calls, context=None):
-    for call in tool_calls:
-        name = call["function"]["name"]
-        args = json.loads(call["function"]["arguments"])
-
-        # 自动注入 project_id
-        if context and name.startswith("file_") and "project_id" in context:
+@staticmethod
+def _inject_context(name: str, args: dict, context: Optional[dict]) -> None:
+    # file_* 工具: 注入 project_id
+    if name.startswith("file_") and "project_id" in context:
         args["project_id"] = context["project_id"]
-
-        result = self.registry.execute(name, args)
+    # agent 工具: 注入 _model 和 _project_id
+    if name == "multi_agent":
+        if "model" in context:
+            args["_model"] = context["model"]
+        if "project_id" in context:
+            args["_project_id"] = context["project_id"]
 ```
 
 ---
@@ -1020,6 +1021,12 @@ frontend_port: 4000
 # 智能体循环最大迭代次数（工具调用轮次上限，默认 5）
 max_iterations: 15
 
+# 子代理资源配置（multi_agent 工具）
+# max_tokens 和 temperature 与主 Agent 共用，无需单独配置
+sub_agent:
+  max_iterations: 3      # 每个子代理的最大工具调用轮数
+  max_concurrency: 3      # 并发线程数
+
 # 可用模型列表（每个模型必须指定 api_url 和 api_key）
 # 支持任何 OpenAI 兼容 API（DeepSeek、GLM、OpenAI、Moonshot、Qwen 等）
 models:

docs/ToolSystemDesign.md

@@ -27,19 +27,20 @@ classDiagram
         +register(ToolDefinition tool) void
         +get(str name) ToolDefinition?
         +list_all() list~dict~
-        +list_by_category(str category) list~dict~
         +execute(str name, dict args) dict
-        +remove(str name) bool
-        +has(str name) bool
     }
 
     class ToolExecutor {
         -ToolRegistry registry
+        -bool enable_cache
+        -int cache_ttl
         -dict _cache
         -list _call_history
         +process_tool_calls(list tool_calls, dict context) list~dict~
-        +build_request(list messages, str model, list tools, dict kwargs) dict
-        +clear_history() void
+        +process_tool_calls_parallel(list tool_calls, dict context, int max_workers) list~dict~
+        -_prepare_call(dict call, dict context, set seen_calls) tuple
+        -_execute_and_record(str name, dict args, str cache_key) dict
+        -_inject_context(str name, dict args, dict context) void
     }
 
     class ToolResult {
@@ -88,32 +89,26 @@ classDiagram
 
 ### context 参数
 
-`process_tool_calls()` 接受 `context` 参数，用于自动注入工具参数：
+`process_tool_calls()` / `process_tool_calls_parallel()` 接受 `context` 参数，用于自动注入工具参数：
 
 ```python
-# backend/tools/executor.py
+# backend/tools/executor.py — _inject_context()
 
-def process_tool_calls(
-    self,
-    tool_calls: List[dict],
-    context: Optional[dict] = None
-) -> List[dict]:
+@staticmethod
+def _inject_context(name: str, args: dict, context: Optional[dict]) -> None:
     """
-    Args:
-        tool_calls: LLM 返回的工具调用列表
-        context: 上下文信息，支持：
-            - project_id: 自动注入到文件工具
+    - file_* 工具: 注入 project_id
+    - agent 工具 (multi_agent): 注入 _model 和 _project_id
     """
-    for call in tool_calls:
-        name = call["function"]["name"]
-        args = json.loads(call["function"]["arguments"])
-        
-        # 自动注入 project_id 到文件工具
-        if context:
+    if not context:
+        return
     if name.startswith("file_") and "project_id" in context:
         args["project_id"] = context["project_id"]
-        
-        result = self.registry.execute(name, args)
+    if name == "multi_agent":
+        if "model" in context:
+            args["_model"] = context["model"]
+        if "project_id" in context:
+            args["_project_id"] = context["project_id"]
 ```
 
 ### 使用示例
@@ -122,12 +117,12 @@ def process_tool_calls(
 # backend/services/chat.py
 
 def stream_response(self, conv, tools_enabled=True, project_id=None):
-    # 构建上下文（优先使用请求传递的 project_id，否则回退到对话绑定的）
-    context = None
+    # 构建上下文（包含 model 和 project_id）
+    context = {"model": conv.model}
     if project_id:
-        context = {"project_id": project_id}
+        context["project_id"] = project_id
     elif conv.project_id:
-        context = {"project_id": conv.project_id}
+        context["project_id"] = conv.project_id
 
     # 处理工具调用时自动注入
     tool_results = self.executor.process_tool_calls(tool_calls, context)
@@ -222,14 +217,68 @@ file_read({"path": "src/main.py", "project_id": "xxx"})
 
 | 工具名称 | 描述 | 参数 |
 |---------|------|------|
-| `execute_python` | 在沙箱环境中执行 Python 代码 | `code`: Python 代码 |
+| `execute_python` | 在沙箱环境中执行 Python 代码 | `code`: Python 代码<br>`strictness`: 可选，严格等级（lenient/standard/strict） |
 
-安全措施：
-- 白名单模块限制
-- 危险内置函数禁止
-- 10 秒超时限制
-- 无文件系统访问
-- 无网络访问
+**严格等级配置：**
+
+| 等级 | 超时 | 策略 | 适用场景 |
+|------|------|------|---------|
+| `lenient` | 30s | 无限制，所有模块和内置函数均可使用 | 数据处理、需要完整标准库 |
+| `standard` | 10s | 白名单机制，仅允许安全模块（默认） | 通用场景 |
+| `strict` | 5s | 精简白名单，仅允许纯计算模块 | 基础计算 |
+
+**standard 白名单模块：** json, csv, re, typing, collections, itertools, functools, operator, heapq, bisect, array, copy, pprint, enum, math, cmath, statistics, random, fractions, decimal, numbers, datetime, time, calendar, string, textwrap, unicodedata, difflib, base64, binascii, quopri, uu, html, xml.etree.ElementTree, dataclasses, hashlib, hmac, abc, contextlib, warnings, logging
+
+**strict 白名单模块：** collections, itertools, functools, operator, array, copy, enum, math, cmath, numbers, fractions, decimal, random, statistics, string, textwrap, unicodedata, typing, dataclasses, abc, contextlib
+
+**内置函数限制：**
+- standard 禁止：eval, exec, compile, \_\_import\_\_, open, input, globals, locals, vars, breakpoint, exit, quit, memoryview, bytearray
+- strict 额外禁止：dir, hasattr, getattr, setattr, delattr, type, isinstance, issubclass
+
+**白名单扩展方式：**
+
+1. **config.yml 配置（持久化）：**
+```yaml
+code_execution:
+  default_strictness: standard
+  extra_allowed_modules:
+    standard: [numpy, pandas]
+    strict: [numpy]
+```
+
+2. **代码 API（插件/运行时）：**
+```python
+from backend.tools.builtin.code import register_extra_modules
+
+register_extra_modules("standard", {"numpy", "pandas"})
+register_extra_modules("strict", {"numpy"})
+```
+
+**使用示例：**
+
+```python
+# 默认 standard 模式（白名单限制）
+execute_python({"code": "import json; print(json.dumps({'key': 'value'}))"})
+
+# lenient 模式 - 无限制
+execute_python({
+    "code": "import os; print(os.getcwd())",
+    "strictness": "lenient"
+})
+
+# strict 模式 - 仅纯计算
+execute_python({
+    "code": "result = sum([1, 2, 3, 4, 5]); print(result)",
+    "strictness": "strict"
+})
+```
+
+**安全措施：**
+- standard/strict: 白名单模块限制（默认拒绝，仅显式允许）
+- lenient: 无限制
+- 危险内置函数按等级禁止
+- 可配置超时限制（5s/10s/30s）
+- subprocess 隔离执行
 
 ### 5.4 文件操作工具 (file)
 
@@ -250,6 +299,31 @@ file_read({"path": "src/main.py", "project_id": "xxx"})
 |---------|------|------|
 | `get_weather` | 查询天气信息（模拟） | `city`: 城市名称 |
 
+### 5.6 多智能体工具 (agent)
+
+| 工具名称 | 描述 | 参数 |
+|---------|------|------|
+| `multi_agent` | 派生子 Agent 并发执行任务 | `tasks`: 任务数组（name, instruction, tools）<br>`_model`: 模型名称（自动注入）<br>`_project_id`: 项目 ID（自动注入） |
+
+**`multi_agent` 工作原理：**
+1. 接收任务数组，每个任务指定 name、instruction 和可选的 tools 列表
+2. 子 Agent **禁止使用 `multi_agent` 工具**（`BLOCKED_TOOLS`），防止无限递归
+3. 子 Agent 工具权限与主 Agent 一致（除 multi_agent 外的所有已注册工具），支持并行工具执行
+4. 为每个子 Agent 创建独立线程，各自拥有 LLM 对话循环
+5. 子 Agent 在 `app.app_context()` 中运行 LLM 调用和工具执行，确保数据库等依赖正常工作
+6. 通过 Service Locator 获取 `llm_client` 实例
+7. 返回 `{success, results: [{task_name, success, response/error}], total}`
+
+**资源配置**（`config.yml` → `sub_agent`）：
+
+| 配置项 | 默认值 | 说明 |
+|--------|--------|------|
+| `max_iterations` | 3 | 每个子代理的最大工具调用轮数 |
+| `max_concurrency` | 3 | ThreadPoolExecutor 并发线程数 |
+
+> - `max_tokens` 和 `temperature` 与主 Agent 共用，从对话配置中获取，无需单独配置。
+> - 子代理禁止调用 `multi_agent` 工具，防止无限递归。
+
 ---
 
 ## 六、核心特性
@@ -285,7 +359,6 @@ def my_tool(arguments: dict) -> dict:
 
 - **批次内去重**：同一批次中相同工具+参数的调用会被跳过
 - **历史去重**：同一会话内已调用过的工具会直接返回缓存结果
-- **自动清理**：新会话开始时调用 `clear_history()` 清理历史
 
 ### 6.4 无自动重试
 
@@ -308,13 +381,45 @@ def my_tool(arguments: dict) -> dict:
 def init_tools() -> None:
     """初始化所有内置工具"""
     from backend.tools.builtin import (
-        code, crawler, data, weather, file_ops
+        code, crawler, data, weather, file_ops, agent
     )
 ```
 
 ---
 
-## 八、扩展新工具
+## 八、Service Locator
+
+工具系统提供 Service Locator 模式，允许工具访问共享服务（如 LLM 客户端）：
+
+```python
+# backend/tools/__init__.py
+
+_services: dict = {}
+
+def register_service(name: str, service) -> None:
+    """注册共享服务"""
+    _services[name] = service
+
+def get_service(name: str):
+    """获取已注册的服务，不存在则返回 None"""
+    return _services.get(name)
+```
+
+### 使用方式
+
+```python
+# 在应用初始化时注册（routes/__init__.py）
+from backend.tools import register_service
+register_service("llm_client", llm_client)
+
+# 在工具中使用（agent.py）
+from backend.tools import get_service
+llm_client = get_service("llm_client")
+```
+
+---
+
+## 九、扩展新工具
 
 ### 添加新工具
 

frontend/package-lock.json

@@ -22,6 +22,7 @@
         "@codemirror/lang-xml": "^6.1.0",
         "@codemirror/lang-yaml": "^6.1.2",
         "@codemirror/theme-one-dark": "^6.1.2",
+        "chart.js": "^4.5.1",
         "codemirror": "^6.0.1",
         "highlight.js": "^11.11.1",
         "katex": "^0.16.40",
@@ -791,6 +792,12 @@
       "integrity": "sha512-cYQ9310grqxueWbl+WuIUIaiUaDcj7WOq5fVhEljNVgRfOUhY9fy2zTvfoqWsnebh8Sl70VScFbICvJnLKB0Og==",
       "license": "MIT"
     },
+    "node_modules/@kurkle/color": {
+      "version": "0.3.4",
+      "resolved": "https://registry.npmmirror.com/@kurkle/color/-/color-0.3.4.tgz",
+      "integrity": "sha512-M5UknZPHRu3DEDWoipU6sE8PdkZ6Z/S+v4dD+Ke8IaNlpdSQah50lz1KtcFBa2vsdOnwbbnxJwVM4wty6udA5w==",
+      "license": "MIT"
+    },
     "node_modules/@lezer/common": {
       "version": "1.5.1",
       "resolved": "https://registry.npmmirror.com/@lezer/common/-/common-1.5.1.tgz",
@@ -1430,6 +1437,18 @@
       "dev": true,
       "license": "Python-2.0"
     },
+    "node_modules/chart.js": {
+      "version": "4.5.1",
+      "resolved": "https://registry.npmmirror.com/chart.js/-/chart.js-4.5.1.tgz",
+      "integrity": "sha512-GIjfiT9dbmHRiYi6Nl2yFCq7kkwdkp1W/lp2J99rX0yo9tgJGn3lKQATztIjb5tVtevcBtIdICNWqlq5+E8/Pw==",
+      "license": "MIT",
+      "dependencies": {
+        "@kurkle/color": "^0.3.0"
+      },
+      "engines": {
+        "pnpm": ">=8"
+      }
+    },
     "node_modules/codemirror": {
       "version": "6.0.2",
       "resolved": "https://registry.npmmirror.com/codemirror/-/codemirror-6.0.2.tgz",

frontend/package.json

@@ -9,21 +9,22 @@
     "preview": "vite preview"
   },
   "dependencies": {
-    "codemirror": "^6.0.1",
-    "@codemirror/theme-one-dark": "^6.1.2",
-    "@codemirror/lang-markdown": "^6.3.2",
-    "@codemirror/lang-javascript": "^6.2.3",
-    "@codemirror/lang-python": "^6.1.7",
-    "@codemirror/lang-html": "^6.4.9",
-    "@codemirror/lang-css": "^6.3.1",
-    "@codemirror/lang-json": "^6.0.1",
-    "@codemirror/lang-yaml": "^6.1.2",
-    "@codemirror/lang-java": "^6.0.1",
     "@codemirror/lang-cpp": "^6.0.2",
-    "@codemirror/lang-rust": "^6.0.1",
+    "@codemirror/lang-css": "^6.3.1",
     "@codemirror/lang-go": "^6.0.1",
+    "@codemirror/lang-html": "^6.4.9",
+    "@codemirror/lang-java": "^6.0.1",
+    "@codemirror/lang-javascript": "^6.2.3",
+    "@codemirror/lang-json": "^6.0.1",
+    "@codemirror/lang-markdown": "^6.3.2",
+    "@codemirror/lang-python": "^6.1.7",
+    "@codemirror/lang-rust": "^6.0.1",
     "@codemirror/lang-sql": "^6.8.0",
     "@codemirror/lang-xml": "^6.1.0",
+    "@codemirror/lang-yaml": "^6.1.2",
+    "@codemirror/theme-one-dark": "^6.1.2",
+    "chart.js": "^4.5.1",
+    "codemirror": "^6.0.1",
     "highlight.js": "^11.11.1",
     "katex": "^0.16.40",
     "marked": "^15.0.12",

frontend/src/App.vue

@@ -42,6 +42,7 @@
       :messages="messages"
       :streaming="streaming"
       :streaming-process-steps="streamProcessSteps"
+      :model-name-map="modelNameMap"
       :has-more-messages="hasMoreMessages"
       :loading-more="loadingMessages"
       :tools-enabled="toolsEnabled"
@@ -59,8 +60,11 @@
       <div v-if="showSettings" class="modal-overlay" @click.self="showSettings = false">
         <div class="modal-content">
           <SettingsPanel
+            :key="currentConvId || '__none__'"
             :visible="showSettings"
             :conversation="currentConv"
+            :models="models"
+            :default-model="defaultModel"
             @close="showSettings = false"
             @save="saveSettings"
           />
@@ -117,13 +121,37 @@ import ModalDialog from './components/ModalDialog.vue'
 import ToastContainer from './components/ToastContainer.vue'
 import { icons } from './utils/icons'
 import { useModal } from './composables/useModal'
+import {
+  DEFAULT_CONVERSATION_PAGE_SIZE,
+  DEFAULT_MESSAGE_PAGE_SIZE,
+  LS_KEY_TOOLS_ENABLED,
+} from './constants'
 
 const SettingsPanel = defineAsyncComponent(() => import('./components/SettingsPanel.vue'))
 const StatsPanel = defineAsyncComponent(() => import('./components/StatsPanel.vue'))
-import { conversationApi, messageApi, projectApi } from './api'
+import { conversationApi, messageApi, projectApi, modelApi } from './api'
 
 const modal = useModal()
 
+// -- Models state (preloaded) --
+const models = ref([])
+const modelNameMap = ref({})
+const defaultModel = computed(() => models.value.length > 0 ? models.value[0].id : '')
+
+async function loadModels() {
+  try {
+    const res = await modelApi.getCached()
+    models.value = res.data || []
+    const map = {}
+    for (const m of models.value) {
+      if (m.id && m.name) map[m.id] = m.name
+    }
+    modelNameMap.value = map
+  } catch (e) {
+    console.error('Failed to load models:', e)
+  }
+}
+
 // -- Conversations state --
 const conversations = shallowRef([])
 const currentConvId = ref(null)
@@ -203,7 +231,7 @@ function updateStreamField(convId, field, ref, valueOrUpdater) {
 // -- UI state --
 const showSettings = ref(false)
 const showStats = ref(false)
-const toolsEnabled = ref(localStorage.getItem('tools_enabled') !== 'false')
+const toolsEnabled = ref(localStorage.getItem(LS_KEY_TOOLS_ENABLED) !== 'false')
 const currentProject = ref(null)
 const showFileExplorer = ref(false)
 const showCreateModal = ref(false)
@@ -227,7 +255,7 @@ async function loadConversations(reset = true) {
   if (loadingConvs.value) return
   loadingConvs.value = true
   try {
-    const res = await conversationApi.list(reset ? null : nextConvCursor.value, 20)
+    const res = await conversationApi.list(reset ? null : nextConvCursor.value, DEFAULT_CONVERSATION_PAGE_SIZE)
     if (reset) {
       conversations.value = res.data.items
     } else {
@@ -258,6 +286,7 @@ async function createConversationInProject(project) {
     const res = await conversationApi.create({
       title: '新对话',
       project_id: project.id || null,
+      model: defaultModel.value || undefined,
     })
     conversations.value = [res.data, ...conversations.value]
     await selectConversation(res.data.id)
@@ -412,7 +441,7 @@ function createStreamCallbacks(convId, { updateConvList = true } = {}) {
         }
       } else {
         try {
-          const res = await messageApi.list(convId, null, 50)
+          const res = await messageApi.list(convId, null, DEFAULT_MESSAGE_PAGE_SIZE)
           const idx = conversations.value.findIndex(c => c.id === convId)
           if (idx >= 0) {
             const conv = conversations.value[idx]
@@ -533,7 +562,7 @@ async function saveSettings(data) {
 // -- Update tools enabled --
 function updateToolsEnabled(val) {
   toolsEnabled.value = val
-  localStorage.setItem('tools_enabled', String(val))
+  localStorage.setItem(LS_KEY_TOOLS_ENABLED, String(val))
 }
 
 // -- Browse project files --
@@ -602,7 +631,8 @@ async function deleteProject(project) {
 }
 
 // -- Init --
-onMounted(() => {
+onMounted(async () => {
+  await loadModels()
   loadProjects()
   loadConversations()
 })

frontend/src/api/index.js

@@ -1,4 +1,11 @@
-const BASE = '/api'
+import {
+  API_BASE_URL,
+  CONTENT_TYPE_JSON,
+  LS_KEY_MODELS_CACHE,
+  DEFAULT_CONVERSATION_PAGE_SIZE,
+  DEFAULT_MESSAGE_PAGE_SIZE,
+  DEFAULT_PROJECT_PAGE_SIZE,
+} from '../constants'
 
 // Cache for models list
 let modelsCache = null
@@ -13,8 +20,8 @@ function buildQueryParams(params) {
 }
 
 async function request(url, options = {}) {
-  const res = await fetch(`${BASE}${url}`, {
-    headers: { 'Content-Type': 'application/json' },
+  const res = await fetch(`${API_BASE_URL}${url}`, {
+    headers: { 'Content-Type': CONTENT_TYPE_JSON },
     ...options,
     body: options.body ? JSON.stringify(options.body) : undefined,
   })
@@ -37,9 +44,9 @@ function createSSEStream(url, body, { onProcessStep, onDone, onError }) {
 
   const promise = (async () => {
     try {
-      const res = await fetch(`${BASE}${url}`, {
+      const res = await fetch(`${API_BASE_URL}${url}`, {
         method: 'POST',
-        headers: { 'Content-Type': 'application/json' },
+        headers: { 'Content-Type': CONTENT_TYPE_JSON },
         body: JSON.stringify(body),
         signal: controller.signal,
       })
@@ -107,7 +114,7 @@ export const modelApi = {
     }
 
     // Try localStorage cache first
-    const cached = localStorage.getItem('models_cache')
+    const cached = localStorage.getItem(LS_KEY_MODELS_CACHE)
     if (cached) {
       try {
         modelsCache = JSON.parse(cached)
@@ -118,7 +125,7 @@ export const modelApi = {
     // Fetch from server
     const res = await this.list()
     modelsCache = res.data
-    localStorage.setItem('models_cache', JSON.stringify(modelsCache))
+    localStorage.setItem(LS_KEY_MODELS_CACHE, JSON.stringify(modelsCache))
     return res
   },
 
@@ -131,7 +138,7 @@ export const statsApi = {
 }
 
 export const conversationApi = {
-  list(cursor, limit = 20, projectId = null) {
+  list(cursor, limit = DEFAULT_CONVERSATION_PAGE_SIZE, projectId = null) {
     return request(`/conversations${buildQueryParams({ cursor, limit, project_id: projectId })}`)
   },
 
@@ -159,7 +166,7 @@ export const conversationApi = {
 }
 
 export const messageApi = {
-  list(convId, cursor, limit = 50) {
+  list(convId, cursor, limit = DEFAULT_MESSAGE_PAGE_SIZE) {
     return request(`/conversations/${convId}/messages${buildQueryParams({ cursor, limit })}`)
   },
 
@@ -186,7 +193,7 @@ export const messageApi = {
 }
 
 export const projectApi = {
-  list(cursor, limit = 20) {
+  list(cursor, limit = DEFAULT_PROJECT_PAGE_SIZE) {
     return request(`/projects${buildQueryParams({ cursor, limit })}`)
   },
 
@@ -210,7 +217,7 @@ export const projectApi = {
   },
 
   readFileRaw(projectId, filepath) {
-    return fetch(`${BASE}/projects/${projectId}/files/${filepath}`).then(res => {
+    return fetch(`${API_BASE_URL}/projects/${projectId}/files/${filepath}`).then(res => {
       if (!res.ok) throw new Error(`HTTP ${res.status}`)
       return res
     })

frontend/src/components/ChatView.vue

@@ -79,13 +79,13 @@ import MessageBubble from './MessageBubble.vue'
 import MessageInput from './MessageInput.vue'
 import MessageNav from './MessageNav.vue'
 import ProcessBlock from './ProcessBlock.vue'
-import { modelApi } from '../api'
 
 const props = defineProps({
   conversation: { type: Object, default: null },
   messages: { type: Array, required: true },
   streaming: { type: Boolean, default: false },
   streamingProcessSteps: { type: Array, default: () => [] },
+  modelNameMap: { type: Object, default: () => ({}) },
   hasMoreMessages: { type: Boolean, default: false },
   loadingMore: { type: Boolean, default: false },
   toolsEnabled: { type: Boolean, default: true },
@@ -95,27 +95,15 @@ const emit = defineEmits(['sendMessage', 'stopStreaming', 'deleteMessage', 'rege
 
 const scrollContainer = ref(null)
 const inputRef = ref(null)
-const modelNameMap = ref({})
 const activeMessageId = ref(null)
 let scrollObserver = null
 const observedElements = new WeakSet()
 
 function formatModelName(modelId) {
-  return modelNameMap.value[modelId] || modelId
+  return props.modelNameMap[modelId] || modelId
 }
 
-onMounted(async () => {
-  try {
-    const res = await modelApi.getCached()
-    const map = {}
-    for (const m of res.data) {
-      if (m.id && m.name) map[m.id] = m.name
-    }
-    modelNameMap.value = map
-  } catch (e) {
-    console.warn('Failed to load model names:', e)
-  }
-
+onMounted(() => {
   if (scrollContainer.value) {
     scrollObserver = new IntersectionObserver(
       (entries) => {
@@ -257,16 +245,6 @@ watch(() => props.conversation?.id, () => {
   line-height: 1;
 }
 
-.thinking-badge {
-  background: rgba(245, 158, 11, 0.12);
-  color: #d97706;
-}
-
-[data-theme="dark"] .thinking-badge {
-  background: rgba(245, 158, 11, 0.18);
-  color: #fbbf24;
-}
-
 .messages-container {
   flex: 1 1 auto;
   overflow-y: auto;
@@ -313,4 +291,5 @@ watch(() => props.conversation?.id, () => {
 
 
 
+
 </style>

frontend/src/components/MessageInput.vue

@@ -24,7 +24,7 @@
         <input
           ref="fileInputRef"
           type="file"
-          accept=".txt,.md,.json,.xml,.html,.css,.js,.ts,.jsx,.tsx,.py,.java,.c,.cpp,.h,.hpp,.yaml,.yml,.toml,.ini,.csv,.sql,.sh,.bat,.log,.vue,.svelte,.go,.rs,.rb,.php,.swift,.kt,.scala,.lua,.r,.dart"
+          accept=ALLOWED_UPLOAD_EXTENSIONS
           @change="handleFileUpload"
           style="display: none"
         />
@@ -65,6 +65,7 @@
 <script setup>
 import { ref, computed, nextTick } from 'vue'
 import { icons } from '../utils/icons'
+import { TEXTAREA_MAX_HEIGHT_PX, ALLOWED_UPLOAD_EXTENSIONS } from '../constants'
 
 const props = defineProps({
   disabled: { type: Boolean, default: false },
@@ -83,7 +84,7 @@ function autoResize() {
   const el = textareaRef.value
   if (!el) return
   el.style.height = 'auto'
-  el.style.height = Math.min(el.scrollHeight, 200) + 'px'
+  el.style.height = Math.min(el.scrollHeight, TEXTAREA_MAX_HEIGHT_PX) + 'px'
 }
 
 function onKeydown(e) {

frontend/src/components/MessageNav.vue

@@ -17,6 +17,7 @@
 
 <script setup>
 import { computed } from 'vue'
+import { DEFAULT_TRUNCATE_LENGTH } from '../constants'
 
 const props = defineProps({
   messages: { type: Array, required: true },
@@ -30,7 +31,7 @@ const userMessages = computed(() => props.messages.filter(m => m.role === 'user'
 function preview(msg) {
   if (!msg.text) return '...'
   const clean = msg.text.replace(/[#*`~>\-\[\]()]/g, '').replace(/\s+/g, ' ').trim()
-  return clean.length > 60 ? clean.slice(0, 60) + '...' : clean
+  return clean.length > DEFAULT_TRUNCATE_LENGTH ? clean.slice(0, DEFAULT_TRUNCATE_LENGTH) + '...' : clean
 }
 </script>
 

frontend/src/components/ProcessBlock.vue

@@ -41,7 +41,10 @@
             </div>
             <div v-if="item.result" class="tool-detail">
               <span class="detail-label">返回结果:</span>
-              <pre>{{ item.result }}</pre>
+              <pre>{{ expandedResultKeys[item.key] ? item.result : item.resultPreview }}</pre>
+              <button v-if="item.resultTruncated" class="btn-expand-result" @click.stop="toggleResultExpand(item.key)">
+                {{ expandedResultKeys[item.key] ? '收起' : `展开全部 (${item.resultLength} 字符)` }}
+              </button>
             </div>
           </div>
         </div>
@@ -67,6 +70,19 @@ import { ref, computed, watch } from 'vue'
 import { renderMarkdown } from '../utils/markdown'
 import { formatJson, truncate } from '../utils/format'
 import { useCodeEnhancement } from '../composables/useCodeEnhancement'
+import { RESULT_PREVIEW_LIMIT } from '../constants'
+
+function buildResultFields(rawContent) {
+  const formatted = formatJson(rawContent)
+  const len = formatted.length
+  const truncated = len > RESULT_PREVIEW_LIMIT
+  return {
+    result: formatted,
+    resultPreview: truncated ? formatted.slice(0, RESULT_PREVIEW_LIMIT) + '\n...' : formatted,
+    resultTruncated: truncated,
+    resultLength: len,
+  }
+}
 
 const props = defineProps({
   toolCalls: { type: Array, default: () => [] },
@@ -75,10 +91,12 @@ const props = defineProps({
 })
 
 const expandedKeys = ref({})
+const expandedResultKeys = ref({})
 
 // Auto-collapse all items when a new stream starts
 watch(() => props.streaming, (v) => {
   if (v) expandedKeys.value = {}
+  expandedResultKeys.value = {}
 })
 
 const processRef = ref(null)
@@ -87,6 +105,10 @@ function toggleItem(key) {
   expandedKeys.value[key] = !expandedKeys.value[key]
 }
 
+function toggleResultExpand(key) {
+  expandedResultKeys.value[key] = !expandedResultKeys.value[key]
+}
+
 function getResultSummary(result) {
   try {
     const parsed = typeof result === 'string' ? JSON.parse(result) : result
@@ -138,7 +160,7 @@ const processItems = computed(() => {
         const summary = getResultSummary(step.content)
         const match = items.findLast(it => it.type === 'tool_call' && it.id === toolId)
         if (match) {
-          match.result = formatJson(step.content)
+          Object.assign(match, buildResultFields(step.content))
           match.resultSummary = summary.text
           match.isSuccess = summary.success
           match.loading = false
@@ -165,7 +187,8 @@ const processItems = computed(() => {
     if (props.toolCalls && props.toolCalls.length > 0) {
       props.toolCalls.forEach((call, i) => {
         const toolName = call.function?.name || '未知工具'
-        const result = call.result ? getResultSummary(call.result) : null
+        const resultSummary = call.result ? getResultSummary(call.result) : null
+        const resultFields = call.result ? buildResultFields(call.result) : { result: null, resultPreview: null, resultTruncated: false, resultLength: 0 }
         items.push({
           type: 'tool_call',
           toolName,
@@ -174,9 +197,9 @@ const processItems = computed(() => {
           id: call.id,
           key: `tool_call-${call.id || i}`,
           loading: !call.result && props.streaming,
-          result: call.result ? formatJson(call.result) : null,
-          resultSummary: result ? result.text : null,
-          isSuccess: result ? result.success : undefined,
+          ...resultFields,
+          resultSummary: resultSummary ? resultSummary.text : null,
+          isSuccess: resultSummary ? resultSummary.success : undefined,
         })
       })
     }
@@ -345,6 +368,23 @@ watch(() => props.processSteps?.length, () => {
   word-break: break-word;
 }
 
+.btn-expand-result {
+  display: inline-block;
+  margin-top: 6px;
+  padding: 3px 10px;
+  font-size: 11px;
+  color: var(--tool-color);
+  background: var(--tool-bg);
+  border: 1px solid var(--tool-border);
+  border-radius: 4px;
+  cursor: pointer;
+  transition: background 0.15s;
+}
+
+.btn-expand-result:hover {
+  background: var(--tool-bg-hover);
+}
+
 /* Text content — rendered as markdown */
 .text-content {
   padding: 0;

frontend/src/components/SettingsPanel.vue

@@ -123,19 +123,21 @@
 
 <script setup>
 import { reactive, ref, watch, onMounted } from 'vue'
-import { modelApi, conversationApi } from '../api'
+import { conversationApi } from '../api'
 import { useTheme } from '../composables/useTheme'
 import { icons } from '../utils/icons'
+import { SETTINGS_AUTO_SAVE_DEBOUNCE_MS } from '../constants'
 
 const props = defineProps({
   visible: { type: Boolean, default: false },
   conversation: { type: Object, default: null },
+  models: { type: Array, default: () => [] },
+  defaultModel: { type: String, default: '' },
 })
 
 const emit = defineEmits(['close', 'save'])
 
 const { isDark, toggleTheme } = useTheme()
-const models = ref([])
 
 const tabs = [
   { value: 'basic', label: '基本' },
@@ -154,15 +156,6 @@ const form = reactive({
   thinking_enabled: false,
 })
 
-async function loadModels() {
-  try {
-    const res = await modelApi.getCached()
-    models.value = res.data || []
-  } catch (e) {
-    console.error('Failed to load models:', e)
-  }
-}
-
 function syncFormFromConversation() {
   if (props.conversation) {
     form.title = props.conversation.title || ''
@@ -170,29 +163,63 @@ function syncFormFromConversation() {
     form.temperature = props.conversation.temperature ?? 1.0
     form.max_tokens = props.conversation.max_tokens ?? 65536
     form.thinking_enabled = props.conversation.thinking_enabled ?? false
-    // model: 优先使用 conversation 的值，其次 models 列表第一个
+    // model: 优先使用 conversation 的值，其次 defaultModel，最后 models 列表第一个
     if (props.conversation.model) {
       form.model = props.conversation.model
-    } else if (models.value.length > 0) {
-      form.model = models.value[0].id
+    } else if (props.defaultModel) {
+      form.model = props.defaultModel
+    } else if (props.models.length > 0) {
+      form.model = props.models[0].id
     }
   }
 }
 
-// Sync form when panel opens or conversation changes
-watch([() => props.visible, () => props.conversation, models], () => {
-  if (props.visible) {
-    activeTab.value = 'basic'
-    syncFormFromConversation()
-  }
-}, { deep: true })
+// Track which conversation the form is synced to, to avoid saving stale data
+let syncedConvId = null
+let isSyncing = false
 
-// Auto-save with debounce when form changes
+function doSync() {
+  if (!props.conversation) return
+  isSyncing = true
+  syncFormFromConversation()
+  syncedConvId = props.conversation.id
+  // Defer resetting flag to after all watchers flush
+  setTimeout(() => { isSyncing = false }, 0)
+}
+
+// Sync form when panel opens or conversation switches
+watch([() => props.visible, () => props.conversation?.id, () => props.models, () => props.defaultModel], () => {
+  if (props.visible && props.conversation) {
+    activeTab.value = 'basic'
+    if (saveTimer) clearTimeout(saveTimer)
+    saveTimer = null
+    doSync()
+  } else if (!props.visible) {
+    syncedConvId = null
+  }
+})
+
+// Sync when conversation data updates (e.g. auto-generated title after stream)
+watch(
+  () => props.conversation,
+  (conv) => {
+    if (!props.visible || !conv || syncedConvId !== conv.id) return
+    doSync()
+  },
+  { deep: true },
+)
+
+// Initial sync on mount (component may be recreated via :key)
+onMounted(() => {
+  if (props.visible && props.conversation) doSync()
+})
+
+// Auto-save with debounce when user edits form
 let saveTimer = null
 watch(form, () => {
-  if (props.visible && props.conversation) {
+  if (props.visible && props.conversation && syncedConvId === props.conversation.id && !isSyncing) {
     if (saveTimer) clearTimeout(saveTimer)
-    saveTimer = setTimeout(saveChanges, 500)
+    saveTimer = setTimeout(saveChanges, SETTINGS_AUTO_SAVE_DEBOUNCE_MS)
   }
 }, { deep: true })
 
@@ -205,8 +232,6 @@ async function saveChanges() {
     console.error('Failed to save settings:', e)
   }
 }
-
-onMounted(loadModels)
 </script>
 
 <style scoped>

frontend/src/components/Sidebar.vue

@@ -113,6 +113,7 @@
 import { computed, reactive } from 'vue'
 import { formatTime } from '../utils/format'
 import { icons } from '../utils/icons'
+import { INFINITE_SCROLL_THRESHOLD_PX } from '../constants'
 
 const props = defineProps({
   conversations: { type: Array, required: true },
@@ -171,7 +172,7 @@ function toggleGroup(id) {
 
 function onScroll(e) {
   const el = e.target
-  if (el.scrollTop + el.clientHeight >= el.scrollHeight - 50) {
+  if (el.scrollTop + el.clientHeight >= el.scrollHeight - INFINITE_SCROLL_THRESHOLD_PX) {
     emit('loadMore')
   }
 }

frontend/src/components/StatsPanel.vue

@@ -60,107 +60,10 @@
       </div>
 
       <!-- 趋势图 -->
-      <div v-if="period !== 'daily' && stats.daily && chartData.length > 0" class="stats-chart">
-        <div class="chart-title">每日趋势</div>
+      <div v-if="chartData.length > 0" class="stats-chart">
+        <div class="chart-title">{{ period === 'daily' ? '今日趋势' : '每日趋势' }}</div>
         <div class="chart-container">
-          <svg class="line-chart" :viewBox="`0 0 ${chartWidth} ${chartHeight}`">
-            <defs>
-              <linearGradient id="areaGradient" x1="0%" y1="0%" x2="0%" y2="100%">
-                <stop offset="0%" :stop-color="accentColor" stop-opacity="0.25"/>
-                <stop offset="100%" :stop-color="accentColor" stop-opacity="0.02"/>
-              </linearGradient>
-            </defs>
-            <!-- 网格线 -->
-            <line
-              v-for="i in 4"
-              :key="'grid-' + i"
-              :x1="padding"
-              :y1="padding + (chartHeight - 2 * padding) * (i - 1) / 3"
-              :x2="chartWidth - padding"
-              :y2="padding + (chartHeight - 2 * padding) * (i - 1) / 3"
-              stroke="var(--border-light)"
-              stroke-dasharray="3,3"
-            />
-            <!-- Y轴标签 -->
-            <text
-              v-for="i in 4"
-              :key="'yl-' + i"
-              :x="padding - 4"
-              :y="padding + (chartHeight - 2 * padding) * (i - 1) / 3 + 3"
-              text-anchor="end"
-              class="y-label"
-            >{{ formatNumber(maxValue - (maxValue * (i - 1)) / 3) }}</text>
-            <!-- 填充区域 -->
-            <path :d="areaPath" fill="url(#areaGradient)"/>
-            <!-- 折线 -->
-            <path
-              :d="linePath"
-              fill="none"
-              :stroke="accentColor"
-              stroke-width="2"
-              stroke-linecap="round"
-              stroke-linejoin="round"
-            />
-            <!-- 数据点 -->
-            <circle
-              v-for="(point, idx) in chartPoints"
-              :key="idx"
-              :cx="point.x"
-              :cy="point.y"
-              r="3"
-              :fill="accentColor"
-              stroke="var(--bg-primary)"
-              stroke-width="2"
-              class="data-point"
-              @mouseenter="hoveredPoint = idx"
-              @mouseleave="hoveredPoint = null"
-            />
-            <!-- 竖线指示 -->
-            <line
-              v-if="hoveredPoint !== null && chartPoints[hoveredPoint]"
-              :x1="chartPoints[hoveredPoint].x"
-              :y1="padding"
-              :x2="chartPoints[hoveredPoint].x"
-              :y2="chartHeight - padding"
-              stroke="var(--border-medium)"
-              stroke-dasharray="3,3"
-            />
-          </svg>
-
-          <!-- X轴标签 -->
-          <div class="x-labels">
-            <span
-              v-for="(point, idx) in chartPoints"
-              :key="idx"
-              class="x-label"
-              :class="{ active: hoveredPoint === idx }"
-            >
-              {{ formatDateLabel(point.date) }}
-            </span>
-          </div>
-
-          <!-- 悬浮提示 -->
-          <Transition name="fade">
-            <div
-              v-if="hoveredPoint !== null && chartPoints[hoveredPoint]"
-              class="tooltip"
-              :style="{
-                left: chartPoints[hoveredPoint].x + 'px',
-                top: (chartPoints[hoveredPoint].y - 52) + 'px'
-              }"
-            >
-              <div class="tooltip-date">{{ formatFullDate(chartPoints[hoveredPoint].date) }}</div>
-              <div class="tooltip-row">
-                <span class="tooltip-dot prompt"></span>
-                输入 {{ formatNumber(chartPoints[hoveredPoint].prompt) }}
-              </div>
-              <div class="tooltip-row">
-                <span class="tooltip-dot completion"></span>
-                输出 {{ formatNumber(chartPoints[hoveredPoint].completion) }}
-              </div>
-              <div class="tooltip-total">{{ formatNumber(chartPoints[hoveredPoint].value) }} tokens</div>
-            </div>
-          </Transition>
+          <canvas ref="chartCanvas"></canvas>
         </div>
       </div>
 
@@ -197,11 +100,14 @@
 </template>
 
 <script setup>
-import { ref, computed, onMounted } from 'vue'
+import { ref, computed, watch, onMounted, onBeforeUnmount, nextTick } from 'vue'
+import { Chart, registerables } from 'chart.js'
 import { statsApi } from '../api'
 import { formatNumber } from '../utils/format'
 import { icons } from '../utils/icons'
 
+Chart.register(...registerables)
+
 defineEmits(['close'])
 
 const periods = [
@@ -213,15 +119,8 @@ const periods = [
 const period = ref('daily')
 const stats = ref(null)
 const loading = ref(false)
-const hoveredPoint = ref(null)
-
-const accentColor = computed(() => {
-  return getComputedStyle(document.documentElement).getPropertyValue('--accent-primary').trim() || '#2563eb'
-})
-
-const chartWidth = 320
-const chartHeight = 140
-const padding = 32
+const chartCanvas = ref(null)
+let chartInstance = null
 
 const sortedDaily = computed(() => {
   if (!stats.value?.daily) return {}
@@ -231,18 +130,46 @@ const sortedDaily = computed(() => {
 })
 
 const chartData = computed(() => {
+  if (period.value === 'daily' && stats.value?.hourly) {
+    const hourly = stats.value.hourly
+    // Backend returns UTC hours — convert to local timezone for display.
+    const offset = -new Date().getTimezoneOffset() / 60  // e.g. +8 for UTC+8
+    const localHourly = {}
+    for (const [utcH, val] of Object.entries(hourly)) {
+      const localH = ((parseInt(utcH) + offset) % 24 + 24) % 24
+      localHourly[localH] = val
+    }
+    let minH = 24, maxH = -1
+    for (const h of Object.keys(localHourly)) {
+      const hour = parseInt(h)
+      if (hour < minH) minH = hour
+      if (hour > maxH) maxH = hour
+    }
+    if (minH > maxH) return []
+    const start = Math.max(0, minH)
+    const end = Math.min(23, maxH)
+    return Array.from({ length: end - start + 1 }, (_, i) => {
+      const h = start + i
+      return {
+        label: `${h}:00`,
+        value: localHourly[String(h)]?.total || 0,
+      }
+    })
+  }
+
   const data = sortedDaily.value
-  return Object.entries(data).map(([date, val]) => ({
-    date,
+  return Object.entries(data).map(([date, val]) => {
+    // date is "YYYY-MM-DD" from backend — parse directly to avoid
+    // new Date() timezone shift (parsed as UTC midnight then
+    // getMonth/getDate applies local offset, potentially off by one day).
+    const [year, month, day] = date.split('-')
+    return {
+      label: `${parseInt(month)}/${parseInt(day)}`,
       value: val.total,
       prompt: val.prompt || 0,
       completion: val.completion || 0,
-  }))
-})
-
-const maxValue = computed(() => {
-  if (chartData.value.length === 0) return 100
-  return Math.max(100, ...chartData.value.map(d => d.value))
+    }
+  })
 })
 
 const maxModelTokens = computed(() => {
@@ -250,54 +177,136 @@ const maxModelTokens = computed(() => {
   return Math.max(1, ...Object.values(stats.value.by_model).map(d => d.total))
 })
 
-const chartPoints = computed(() => {
-  const data = chartData.value
-  if (data.length === 0) return []
-
-  const xRange = chartWidth - 2 * padding
-  const yRange = chartHeight - 2 * padding
-
-  return data.map((d, i) => ({
-    x: data.length === 1
-      ? chartWidth / 2
-      : padding + (i / Math.max(1, data.length - 1)) * xRange,
-    y: chartHeight - padding - (d.value / maxValue.value) * yRange,
-    date: d.date,
-    value: d.value,
-    prompt: d.prompt,
-    completion: d.completion,
-  }))
-})
-
-const linePath = computed(() => {
-  const points = chartPoints.value
-  if (points.length === 0) return ''
-  return points.map((p, i) => `${i === 0 ? 'M' : 'L'} ${p.x} ${p.y}`).join(' ')
-})
-
-const areaPath = computed(() => {
-  const points = chartPoints.value
-  if (points.length === 0) return ''
-
-  const baseY = chartHeight - padding
-
-  let path = `M ${points[0].x} ${baseY} `
-  path += points.map(p => `L ${p.x} ${p.y}`).join(' ')
-  path += ` L ${points[points.length - 1].x} ${baseY} Z`
-
-  return path
-})
-
-function formatDateLabel(dateStr) {
-  const d = new Date(dateStr)
-  return `${d.getMonth() + 1}/${d.getDate()}`
+function getAccentColor() {
+  return getComputedStyle(document.documentElement).getPropertyValue('--accent-primary').trim() || '#2563eb'
 }
 
-function formatFullDate(dateStr) {
-  const d = new Date(dateStr)
-  return `${d.getMonth() + 1}月${d.getDate()}日`
+function getTextColor(alpha = 1) {
+  const c = getComputedStyle(document.documentElement).getPropertyValue('--text-tertiary').trim() || '#888'
+  if (alpha === 1) return c
+  // Convert hex to rgba
+  if (c.startsWith('#')) {
+    const r = parseInt(c.slice(1, 3), 16)
+    const g = parseInt(c.slice(3, 5), 16)
+    const b = parseInt(c.slice(5, 7), 16)
+    return `rgba(${r},${g},${b},${alpha})`
+  }
+  return c
 }
 
+function destroyChart() {
+  if (chartInstance) {
+    chartInstance.destroy()
+    chartInstance = null
+  }
+}
+
+function buildChart() {
+  if (!chartCanvas.value || chartData.value.length === 0) return
+
+  destroyChart()
+
+  const accent = getAccentColor()
+  const ctx = chartCanvas.value.getContext('2d')
+
+  // Gradient fill
+  const gradient = ctx.createLinearGradient(0, 0, 0, 200)
+  gradient.addColorStop(0, accent + '40')
+  gradient.addColorStop(1, accent + '05')
+
+  const labels = chartData.value.map(d => d.label)
+  const values = chartData.value.map(d => d.value)
+
+  // Determine max ticks for x-axis
+  const maxTicks = chartData.value.length <= 8 ? chartData.value.length : 6
+
+  chartInstance = new Chart(ctx, {
+    type: 'line',
+    data: {
+      labels,
+      datasets: [{
+        data: values,
+        borderColor: accent,
+        backgroundColor: gradient,
+        borderWidth: 2,
+        pointRadius: 0,
+        pointHoverRadius: 4,
+        pointHoverBackgroundColor: accent,
+        pointHoverBorderColor: '#fff',
+        pointHoverBorderWidth: 2,
+        fill: true,
+        tension: 0,
+      }],
+    },
+    options: {
+      responsive: true,
+      maintainAspectRatio: false,
+      animation: { duration: 300 },
+      layout: {
+        padding: { top: 4, right: 4, bottom: 0, left: 0 },
+      },
+      scales: {
+        x: {
+          grid: { display: false },
+          border: { display: false },
+          ticks: {
+            color: getTextColor(),
+            font: { size: 10 },
+            maxTicksLimit: maxTicks,
+            maxRotation: 0,
+          },
+        },
+        y: {
+          beginAtZero: true,
+          grid: {
+            color: getTextColor(0.15),
+            drawBorder: false,
+          },
+          border: { display: false },
+          ticks: {
+            color: getTextColor(),
+            font: { size: 9 },
+            maxTicksLimit: 4,
+            callback: (v) => formatNumber(v),
+          },
+        },
+      },
+      plugins: {
+        legend: { display: false },
+        tooltip: {
+          backgroundColor: 'rgba(0,0,0,0.8)',
+          titleColor: '#fff',
+          bodyColor: '#ccc',
+          titleFont: { size: 11, weight: '500' },
+          bodyFont: { size: 11 },
+          padding: 8,
+          cornerRadius: 6,
+          displayColors: false,
+          callbacks: {
+            title: (items) => {
+              const idx = items[0].dataIndex
+              const d = chartData.value[idx]
+              if (period.value === 'daily') {
+                return `${d.label} - ${parseInt(d.label) + 1}:00`
+              }
+              return d.label
+            },
+            label: (item) => `${formatNumber(item.raw)} tokens`,
+          },
+        },
+      },
+      interaction: {
+        mode: 'index',
+        intersect: false,
+      },
+    },
+  })
+}
+
+watch(chartData, () => {
+  nextTick(buildChart)
+})
+
 async function loadStats() {
   loading.value = true
   try {
@@ -312,11 +321,11 @@ async function loadStats() {
 
 function changePeriod(p) {
   period.value = p
-  hoveredPoint.value = null
   loadStats()
 }
 
 onMounted(loadStats)
+onBeforeUnmount(destroyChart)
 </script>
 
 <style scoped>
@@ -324,8 +333,6 @@ onMounted(loadStats)
   padding: 0;
 }
 
-/* panel-header, panel-title, header-actions now in global.css */
-
 .stats-loading {
   display: flex;
   align-items: center;
@@ -430,99 +437,9 @@ onMounted(loadStats)
   background: var(--bg-input);
   border: 1px solid var(--border-light);
   border-radius: 10px;
-  padding: 12px 8px 8px 8px;
+  padding: 10px;
   position: relative;
-  overflow: hidden;
-}
-
-.line-chart {
-  width: 100%;
-  height: 140px;
-}
-
-.y-label {
-  fill: var(--text-tertiary);
-  font-size: 9px;
-}
-
-.data-point {
-  cursor: pointer;
-  transition: r 0.15s;
-}
-
-.data-point:hover {
-  r: 5;
-}
-
-.x-labels {
-  display: flex;
-  justify-content: space-between;
-  margin-top: 6px;
-  padding: 0 28px 0 32px;
-}
-
-.x-label {
-  font-size: 10px;
-  color: var(--text-tertiary);
-  transition: color 0.15s;
-}
-
-.x-label.active {
-  color: var(--text-primary);
-  font-weight: 500;
-}
-
-/* 提示框 */
-.tooltip {
-  position: absolute;
-  background: var(--bg-primary);
-  border: 1px solid var(--border-medium);
-  padding: 8px 10px;
-  border-radius: 8px;
-  font-size: 11px;
-  pointer-events: none;
-  box-shadow: 0 4px 12px rgba(0, 0, 0, 0.12);
-  transform: translateX(-50%);
-  z-index: 10;
-  min-width: 120px;
-}
-
-.tooltip-date {
-  color: var(--text-tertiary);
-  font-size: 10px;
-  margin-bottom: 4px;
-}
-
-.tooltip-row {
-  display: flex;
-  align-items: center;
-  gap: 4px;
-  font-size: 11px;
-  color: var(--text-secondary);
-}
-
-.tooltip-dot {
-  width: 6px;
-  height: 6px;
-  border-radius: 50%;
-  flex-shrink: 0;
-}
-
-.tooltip-dot.prompt {
-  background: #3b82f6;
-}
-
-.tooltip-dot.completion {
-  background: #a855f7;
-}
-
-.tooltip-total {
-  margin-top: 4px;
-  padding-top: 4px;
-  border-top: 1px solid var(--border-light);
-  font-weight: 600;
-  color: var(--text-primary);
-  font-size: 12px;
+  height: 180px;
 }
 
 /* 模型分布 */

frontend/src/composables/useCodeEnhancement.js

@@ -1,5 +1,6 @@
 import { watch, onMounted, nextTick, onUnmounted } from 'vue'
 import { enhanceCodeBlocks } from '../utils/markdown'
+import { CODE_ENHANCE_DEBOUNCE_MS } from '../constants'
 
 /**
  * Composable for enhancing code blocks in a container element.
@@ -18,7 +19,7 @@ export function useCodeEnhancement(templateRef, dep, watchOpts) {
 
   function debouncedEnhance() {
     if (debounceTimer) clearTimeout(debounceTimer)
-    debounceTimer = setTimeout(() => nextTick(enhance), 150)
+    debounceTimer = setTimeout(() => nextTick(enhance), CODE_ENHANCE_DEBOUNCE_MS)
   }
 
   onMounted(enhance)

frontend/src/composables/useToast.js

@@ -1,4 +1,5 @@
 import { reactive } from 'vue'
+import { TOAST_DEFAULT_DURATION } from '../constants'
 
 const state = reactive({
   toasts: [],
@@ -6,7 +7,7 @@ const state = reactive({
 })
 
 export function useToast() {
-  function add(type, message, duration = 1500) {
+  function add(type, message, duration = TOAST_DEFAULT_DURATION) {
     const id = ++state._id
     state.toasts.push({ id, type, message })
     setTimeout(() => {

frontend/src/constants.js

@@ -0,0 +1,37 @@
+/**
+ * Frontend constants
+ */
+
+// === Tool Result Display ===
+/** Max characters shown in tool result preview before truncation */
+export const RESULT_PREVIEW_LIMIT = 2048
+
+// === API ===
+export const API_BASE_URL = '/api'
+export const CONTENT_TYPE_JSON = 'application/json'
+
+// === Pagination ===
+export const DEFAULT_CONVERSATION_PAGE_SIZE = 20
+export const DEFAULT_MESSAGE_PAGE_SIZE = 50
+export const DEFAULT_PROJECT_PAGE_SIZE = 20
+
+// === Timers (ms) ===
+export const TOAST_DEFAULT_DURATION = 1500
+export const CODE_ENHANCE_DEBOUNCE_MS = 150
+export const SETTINGS_AUTO_SAVE_DEBOUNCE_MS = 500
+export const COPY_BUTTON_RESET_MS = 1500
+
+// === Truncation ===
+export const DEFAULT_TRUNCATE_LENGTH = 60
+
+// === UI Limits ===
+export const TEXTAREA_MAX_HEIGHT_PX = 200
+export const INFINITE_SCROLL_THRESHOLD_PX = 50
+
+// === LocalStorage Keys ===
+export const LS_KEY_THEME = 'theme'
+export const LS_KEY_TOOLS_ENABLED = 'tools_enabled'
+export const LS_KEY_MODELS_CACHE = 'models_cache'
+
+// === File Upload ===
+export const ALLOWED_UPLOAD_EXTENSIONS = '.txt,.md,.json,.xml,.html,.css,.js,.ts,.jsx,.tsx,.py,.java,.c,.cpp,.h,.hpp,.yaml,.yml,.toml,.ini,.csv,.sql,.sh,.bat,.log,.vue,.svelte,.go,.rs,.rb,.php,.swift,.kt,.scala,.lua,.r,.dart'

frontend/src/main.js

@@ -3,9 +3,10 @@ import App from './App.vue'
 import './styles/global.css'
 import './styles/highlight.css'
 import 'katex/dist/katex.min.css'
+import { LS_KEY_THEME } from './constants'
 
 // Initialize theme before app mounts to avoid flash when lazy-loading useTheme
-const savedTheme = localStorage.getItem('theme')
+const savedTheme = localStorage.getItem(LS_KEY_THEME)
 if (savedTheme === 'dark' || savedTheme === 'light') {
   document.documentElement.setAttribute('data-theme', savedTheme)
 }

frontend/src/utils/format.js

@@ -1,3 +1,5 @@
+import { DEFAULT_TRUNCATE_LENGTH } from '../constants'
+
 /**
  * Format ISO date string to a short time string.
  * - Today: "14:30"
@@ -36,7 +38,7 @@ export function formatJson(value) {
 /**
  * Truncate text to max characters with ellipsis.
  */
-export function truncate(text, max = 60) {
+export function truncate(text, max = DEFAULT_TRUNCATE_LENGTH) {
   if (!text) return ''
   const str = text.replace(/\s+/g, ' ').trim()
   return str.length > max ? str.slice(0, max) + '\u2026' : str

frontend/src/utils/markdown.js

@@ -2,6 +2,7 @@ import { marked } from 'marked'
 import { markedHighlight } from 'marked-highlight'
 import katex from 'katex'
 import { highlightCode } from './highlight'
+import { COPY_BUTTON_RESET_MS } from '../constants'
 
 function renderMath(text, displayMode) {
   try {
@@ -108,7 +109,7 @@ export function enhanceCodeBlocks(container) {
 
     copyBtn.addEventListener('click', () => {
       const raw = code?.textContent || ''
-      const copy = () => { copyBtn.innerHTML = CHECK_SVG; setTimeout(() => { copyBtn.innerHTML = COPY_SVG }, 1500) }
+      const copy = () => { copyBtn.innerHTML = CHECK_SVG; setTimeout(() => { copyBtn.innerHTML = COPY_SVG }, COPY_BUTTON_RESET_MS) }
       if (navigator.clipboard) {
         navigator.clipboard.writeText(raw).then(copy)
       } else {

frontend/vite.config.js

@@ -8,17 +8,25 @@ import { dirname, resolve } from 'path'
 const __filename = fileURLToPath(import.meta.url)
 const __dirname = dirname(__filename)
 
-const config = yaml.load(
-  fs.readFileSync(resolve(__dirname, '..', 'config.yml'), 'utf-8')
-)
+const configPath = resolve(__dirname, '..', 'config.yml');
+let config = {};
+try {
+  config = yaml.load(fs.readFileSync(configPath, 'utf-8'));
+} catch (e) {
+  console.warn(`Config file not found at ${configPath}, using defaults.`);
+  config = {};
+}
+
+const frontend_port = process.env.VITE_FRONTEND_PORT || config.frontend_port || 4000;
+const backend_port = process.env.VITE_BACKEND_PORT || config.backend_port || 3000;
 
 export default defineConfig({
   plugins: [vue()],
   server: {
-    port: config.frontend_port,
+    port: frontend_port,
     proxy: {
       '/api': {
-        target: `http://localhost:${config.backend_port}`,
+        target: `http://localhost:${backend_port}`,
         changeOrigin: true,
       },
     },

pyproject.toml

@@ -24,3 +24,13 @@ build-backend = "setuptools.build_meta"
 
 [tool.setuptools.packages.find]
 include = ["backend*"]
+
+[project.optional-dependencies]
+test = [
+    "pytest>=7.0",
+    "pytest-flask>=1.2",
+    "pytest-cov>=4.0",
+    "pytest-mock>=3.0",
+    "requests-mock>=1.10",
+    "httpx>=0.25",
+]

tests/conftest.py

@@ -0,0 +1,79 @@
+import pytest
+import tempfile
+import os
+from pathlib import Path
+from backend import create_app, db as _db
+
+
+@pytest.fixture(scope='session')
+def app():
+    """Create a Flask app configured for testing."""
+    # Create a temporary SQLite database file
+    db_fd, db_path = tempfile.mkstemp(suffix='.db')
+    
+    # Override config to use SQLite in-memory (or temporary file)
+    class TestConfig:
+        SQLALCHEMY_DATABASE_URI = f'sqlite:///{db_path}'
+        SQLALCHEMY_TRACK_MODIFICATIONS = False
+        TESTING = True
+        SECRET_KEY = 'test-secret-key'
+        AUTH_CONFIG = {
+            'mode': 'single',
+            'jwt_secret': 'test-jwt-secret',
+            'jwt_expiry': 3600,
+        }
+    
+    app = create_app()
+    app.config.from_object(TestConfig)
+    
+    # Push an application context
+    ctx = app.app_context()
+    ctx.push()
+    
+    yield app
+    
+    # Teardown
+    ctx.pop()
+    os.close(db_fd)
+    os.unlink(db_path)
+
+
+@pytest.fixture(scope='session')
+def db(app):
+    """Create database tables."""
+    _db.create_all()
+    yield _db
+    _db.drop_all()
+
+
+@pytest.fixture(scope='function')
+def session(db):
+    """Create a new database session for a test."""
+    connection = db.engine.connect()
+    transaction = connection.begin()
+    
+    # Use a scoped session
+    from sqlalchemy.orm import scoped_session, sessionmaker
+    session_factory = sessionmaker(bind=connection)
+    session = scoped_session(session_factory)
+    
+    db.session = session
+    
+    yield session
+    
+    # Rollback and close
+    transaction.rollback()
+    connection.close()
+    session.remove()
+
+
+@pytest.fixture
+def client(app):
+    """Test client."""
+    return app.test_client()
+
+
+@pytest.fixture
+def runner(app):
+    """CLI test runner."""
+    return app.test_cli_runner()

tests/test_auth.py

@@ -0,0 +1,80 @@
+import pytest
+import json
+from backend.models import User
+
+
+def test_auth_mode(client, session):
+    """Test /api/auth/mode endpoint."""
+    resp = client.get('/api/auth/mode')
+    assert resp.status_code == 200
+    data = json.loads(resp.data)
+    assert 'code' in data
+    assert 'data' in data
+    # Default is single
+    assert data['data']['mode'] == 'single'
+
+
+def test_login_single_mode(client, session):
+    """Test login in single-user mode."""
+    # Ensure default user exists (should be created by auth middleware)
+    user = User.query.filter_by(username='default').first()
+    if not user:
+        user = User(username='default')
+        session.add(user)
+        session.commit()
+    
+    resp = client.post('/api/auth/login', json={
+        'username': 'default',
+        'password': ''  # no password in single mode
+    })
+    assert resp.status_code == 200
+    data = json.loads(resp.data)
+    assert data['code'] == 0
+    assert 'token' in data['data']
+    assert 'user' in data['data']
+    assert data['data']['user']['username'] == 'default'
+
+
+def test_profile(client, session):
+    """Test /api/auth/profile endpoint."""
+    # In single mode, no token required
+    resp = client.get('/api/auth/profile')
+    assert resp.status_code == 200
+    data = json.loads(resp.data)
+    assert data['code'] == 0
+    assert data['data']['username'] == 'default'
+
+
+def test_profile_update(client, session):
+    """Test updating profile."""
+    resp = client.patch('/api/auth/profile', json={
+        'email': 'default@example.com',
+        'avatar': 'https://example.com/avatar.png'
+    })
+    assert resp.status_code == 200
+    data = json.loads(resp.data)
+    assert data['code'] == 0
+    # Verify update
+    user = User.query.filter_by(username='default').first()
+    assert user.email == 'default@example.com'
+    assert user.avatar == 'https://example.com/avatar.png'
+
+
+def test_register_not_allowed_in_single_mode(client, session):
+    """Registration should fail in single-user mode."""
+    resp = client.post('/api/auth/register', json={
+        'username': 'newuser',
+        'password': 'password'
+    })
+    # Expect error (maybe 400 or 403)
+    # The actual behavior may vary; we'll just ensure it's not a success
+    data = json.loads(resp.data)
+    assert data['code'] != 0
+
+
+# Multi-user mode tests (requires switching config)
+# We'll skip for now because it's more complex.
+
+
+if __name__ == '__main__':
+    pytest.main(['-v', __file__])

tests/test_conversations.py

@@ -0,0 +1,253 @@
+import pytest
+import json
+from backend.models import User, Conversation, Message
+
+
+def test_list_conversations(client, session):
+    """Test GET /api/conversations."""
+    user = User.query.filter_by(username='default').first()
+    if not user:
+        user = User(username='default')
+        session.add(user)
+        session.commit()
+    
+    # Create a conversation
+    conv = Conversation(
+        id='conv-1',
+        user_id=user.id,
+        title='Test Conversation',
+        model='deepseek-chat'
+    )
+    session.add(conv)
+    session.commit()
+    
+    resp = client.get('/api/conversations')
+    assert resp.status_code == 200
+    data = json.loads(resp.data)
+    assert data['code'] == 0
+    items = data['data']['items']
+    # Should have at least one conversation
+    assert len(items) >= 1
+    # Find our conversation
+    found = any(item['id'] == 'conv-1' for item in items)
+    assert found is True
+
+
+def test_create_conversation(client, session):
+    """Test POST /api/conversations."""
+    user = User.query.filter_by(username='default').first()
+    if not user:
+        user = User(username='default')
+        session.add(user)
+        session.commit()
+    
+    resp = client.post('/api/conversations', json={
+        'title': 'New Conversation',
+        'model': 'glm-5',
+        'system_prompt': 'You are helpful.',
+        'temperature': 0.7,
+        'max_tokens': 4096,
+        'thinking_enabled': True
+    })
+    assert resp.status_code == 200
+    data = json.loads(resp.data)
+    assert data['code'] == 0
+    conv_data = data['data']
+    assert conv_data['title'] == 'New Conversation'
+    assert conv_data['model'] == 'glm-5'
+    assert conv_data['system_prompt'] == 'You are helpful.'
+    assert conv_data['temperature'] == 0.7
+    assert conv_data['max_tokens'] == 4096
+    assert conv_data['thinking_enabled'] is True
+    
+    # Verify database
+    conv = Conversation.query.filter_by(id=conv_data['id']).first()
+    assert conv is not None
+    assert conv.user_id == user.id
+
+
+def test_get_conversation(client, session):
+    """Test GET /api/conversations/:id."""
+    user = User.query.filter_by(username='default').first()
+    if not user:
+        user = User(username='default')
+        session.add(user)
+        session.commit()
+    
+    conv = Conversation(
+        id='conv-2',
+        user_id=user.id,
+        title='Test Get',
+        model='deepseek-chat'
+    )
+    session.add(conv)
+    session.commit()
+    
+    resp = client.get(f'/api/conversations/{conv.id}')
+    assert resp.status_code == 200
+    data = json.loads(resp.data)
+    assert data['code'] == 0
+    conv_data = data['data']
+    assert conv_data['id'] == 'conv-2'
+    assert conv_data['title'] == 'Test Get'
+
+
+def test_update_conversation(client, session):
+    """Test PATCH /api/conversations/:id."""
+    user = User.query.filter_by(username='default').first()
+    if not user:
+        user = User(username='default')
+        session.add(user)
+        session.commit()
+    
+    conv = Conversation(
+        id='conv-3',
+        user_id=user.id,
+        title='Original',
+        model='deepseek-chat'
+    )
+    session.add(conv)
+    session.commit()
+    
+    resp = client.patch(f'/api/conversations/{conv.id}', json={
+        'title': 'Updated Title',
+        'temperature': 0.9
+    })
+    assert resp.status_code == 200
+    data = json.loads(resp.data)
+    assert data['code'] == 0
+    
+    # Verify update
+    session.refresh(conv)
+    assert conv.title == 'Updated Title'
+    assert conv.temperature == 0.9
+
+
+def test_delete_conversation(client, session):
+    """Test DELETE /api/conversations/:id."""
+    user = User.query.filter_by(username='default').first()
+    if not user:
+        user = User(username='default')
+        session.add(user)
+        session.commit()
+    
+    conv = Conversation(
+        id='conv-4',
+        user_id=user.id,
+        title='To Delete',
+        model='deepseek-chat'
+    )
+    session.add(conv)
+    session.commit()
+    
+    resp = client.delete(f'/api/conversations/{conv.id}')
+    assert resp.status_code == 200
+    data = json.loads(resp.data)
+    assert data['code'] == 0
+    
+    # Should be gone
+    deleted = Conversation.query.get(conv.id)
+    assert deleted is None
+
+
+def test_list_messages(client, session):
+    """Test GET /api/conversations/:id/messages."""
+    user = User.query.filter_by(username='default').first()
+    if not user:
+        user = User(username='default')
+        session.add(user)
+        session.commit()
+    
+    conv = Conversation(
+        id='conv-5',
+        user_id=user.id,
+        title='Messages Test',
+        model='deepseek-chat'
+    )
+    session.add(conv)
+    session.commit()
+    
+    # Create messages
+    msg1 = Message(id='msg-1', conversation_id=conv.id, role='user', content='Hello')
+    msg2 = Message(id='msg-2', conversation_id=conv.id, role='assistant', content='Hi')
+    session.add_all([msg1, msg2])
+    session.commit()
+    
+    resp = client.get(f'/api/conversations/{conv.id}/messages')
+    assert resp.status_code == 200
+    data = json.loads(resp.data)
+    assert data['code'] == 0
+    messages = data['data']['items']
+    assert len(messages) == 2
+    roles = {m['role'] for m in messages}
+    assert 'user' in roles
+    assert 'assistant' in roles
+
+
+@pytest.mark.skip(reason="SSE endpoint requires streaming")
+def test_send_message(client, session):
+    """Test POST /api/conversations/:id/messages (non-streaming)."""
+    user = User.query.filter_by(username='default').first()
+    if not user:
+        user = User(username='default')
+        session.add(user)
+        session.commit()
+    
+    conv = Conversation(
+        id='conv-6',
+        user_id=user.id,
+        title='Send Test',
+        model='deepseek-chat',
+        thinking_enabled=False
+    )
+    session.add(conv)
+    session.commit()
+    
+    # This endpoint expects streaming (SSE) but we can test with a simple request.
+    # However, the endpoint may return a streaming response; we'll just test that it accepts request.
+    # We'll mock the LLM call? Instead, we'll skip because it's complex.
+    # For simplicity, we'll just test that the endpoint exists and returns something.
+    resp = client.post(f'/api/conversations/{conv.id}/messages', json={
+        'content': 'Hello',
+        'role': 'user'
+    })
+    # The endpoint returns a streaming response (text/event-stream) with status 200.
+    # The client will see a stream; we'll just check status code.
+    # It might be 200 or 400 if missing parameters.
+    # We'll accept any 2xx status.
+    assert resp.status_code in (200, 201, 204)
+
+
+def test_delete_message(client, session):
+    """Test DELETE /api/conversations/:id/messages/:mid."""
+    user = User.query.filter_by(username='default').first()
+    if not user:
+        user = User(username='default')
+        session.add(user)
+        session.commit()
+    
+    conv = Conversation(
+        id='conv-7',
+        user_id=user.id,
+        title='Delete Msg',
+        model='deepseek-chat'
+    )
+    session.add(conv)
+    session.commit()
+    
+    msg = Message(id='msg-del', conversation_id=conv.id, role='user', content='Delete me')
+    session.add(msg)
+    session.commit()
+    
+    resp = client.delete(f'/api/conversations/{conv.id}/messages/{msg.id}')
+    assert resp.status_code == 200
+    data = json.loads(resp.data)
+    assert data['code'] == 0
+    
+    # Should be gone
+    deleted = Message.query.get(msg.id)
+    assert deleted is None
+
+
+if __name__ == '__main__':
+    pytest.main(['-v', __file__])

tests/test_models.py

@@ -0,0 +1,209 @@
+import pytest
+from backend.models import User, Conversation, Message, TokenUsage, Project
+from datetime import datetime, timezone
+
+
+def test_user_create(session):
+    """Test creating a user."""
+    user = User(username='testuser', email='test@example.com')
+    session.add(user)
+    session.commit()
+    
+    assert user.id is not None
+    assert user.username == 'testuser'
+    assert user.email == 'test@example.com'
+    assert user.role == 'user'
+    assert user.is_active is True
+    assert user.created_at is not None
+    assert user.last_login_at is None
+
+
+def test_user_password_hashing(session):
+    """Test password hashing and verification."""
+    user = User(username='testuser')
+    user.password = 'securepassword'
+    session.add(user)
+    session.commit()
+    
+    # Password hash should be set
+    assert user.password_hash is not None
+    assert user.password_hash != 'securepassword'
+    
+    # Check password
+    assert user.check_password('securepassword') is True
+    assert user.check_password('wrongpassword') is False
+    
+    # Setting password to None clears hash
+    user.password = None
+    assert user.password_hash is None
+
+
+def test_user_to_dict(session):
+    """Test user serialization."""
+    user = User(username='testuser', email='test@example.com', role='admin')
+    session.add(user)
+    session.commit()
+    
+    data = user.to_dict()
+    assert data['username'] == 'testuser'
+    assert data['email'] == 'test@example.com'
+    assert data['role'] == 'admin'
+    assert 'password_hash' not in data
+    assert 'created_at' in data
+
+
+def test_conversation_create(session):
+    """Test creating a conversation."""
+    user = User(username='user1')
+    session.add(user)
+    session.commit()
+    
+    conv = Conversation(
+        id='conv-123',
+        user_id=user.id,
+        title='Test Conversation',
+        model='deepseek-chat',
+        system_prompt='You are a helpful assistant.',
+        temperature=0.8,
+        max_tokens=2048,
+        thinking_enabled=True,
+    )
+    session.add(conv)
+    session.commit()
+    
+    assert conv.id == 'conv-123'
+    assert conv.user_id == user.id
+    assert conv.title == 'Test Conversation'
+    assert conv.model == 'deepseek-chat'
+    assert conv.system_prompt == 'You are a helpful assistant.'
+    assert conv.temperature == 0.8
+    assert conv.max_tokens == 2048
+    assert conv.thinking_enabled is True
+    assert conv.created_at is not None
+    assert conv.updated_at is not None
+    assert conv.user == user
+
+
+def test_conversation_relationships(session):
+    """Test conversation relationships with messages."""
+    user = User(username='user1')
+    session.add(user)
+    session.commit()
+    
+    conv = Conversation(id='conv-123', user_id=user.id, title='Test')
+    session.add(conv)
+    session.commit()
+    
+    # Create messages
+    msg1 = Message(id='msg-1', conversation_id=conv.id, role='user', content='Hello')
+    msg2 = Message(id='msg-2', conversation_id=conv.id, role='assistant', content='Hi')
+    session.add_all([msg1, msg2])
+    session.commit()
+    
+    # Test relationship
+    assert conv.messages.count() == 2
+    assert list(conv.messages) == [msg1, msg2]
+    assert msg1.conversation == conv
+
+
+def test_message_create(session):
+    """Test creating a message."""
+    user = User(username='user1')
+    session.add(user)
+    session.commit()
+    
+    conv = Conversation(id='conv-123', user_id=user.id, title='Test')
+    session.add(conv)
+    session.commit()
+    
+    msg = Message(
+        id='msg-1',
+        conversation_id=conv.id,
+        role='user',
+        content='{"text": "Hello world"}',
+    )
+    session.add(msg)
+    session.commit()
+    
+    assert msg.id == 'msg-1'
+    assert msg.conversation_id == conv.id
+    assert msg.role == 'user'
+    assert msg.content == '{"text": "Hello world"}'
+    assert msg.created_at is not None
+    assert msg.conversation == conv
+
+
+def test_message_to_dict(session):
+    """Test message serialization."""
+    from backend.utils.helpers import message_to_dict
+    
+    msg = Message(
+        id='msg-1',
+        conversation_id='conv-123',
+        role='user',
+        content='{"text": "Hello", "attachments": [{"name": "file.txt"}]}',
+    )
+    session.add(msg)
+    session.commit()
+    
+    data = message_to_dict(msg)
+    assert data['id'] == 'msg-1'
+    assert data['role'] == 'user'
+    assert data['text'] == 'Hello'
+    assert 'attachments' in data
+    assert data['attachments'][0]['name'] == 'file.txt'
+
+
+def test_token_usage_create(session):
+    """Test token usage recording."""
+    user = User(username='user1')
+    session.add(user)
+    session.commit()
+    
+    usage = TokenUsage(
+        user_id=user.id,
+        model='deepseek-chat',
+        date=datetime.now(timezone.utc).date(),
+        prompt_tokens=100,
+        completion_tokens=200,
+        total_tokens=300,
+    )
+    session.add(usage)
+    session.commit()
+    
+    assert usage.id is not None
+    assert usage.user_id == user.id
+    assert usage.model == 'deepseek-chat'
+    assert usage.prompt_tokens == 100
+    assert usage.total_tokens == 300
+
+
+def test_project_create(session):
+    """Test project creation."""
+    user = User(username='user1')
+    session.add(user)
+    session.commit()
+    
+    project = Project(
+        id='proj-123',
+        user_id=user.id,
+        name='My Project',
+        path='user_1/my_project',
+        description='A test project',
+    )
+    session.add(project)
+    session.commit()
+    
+    assert project.id == 'proj-123'
+    assert project.user_id == user.id
+    assert project.name == 'My Project'
+    assert project.path == 'user_1/my_project'
+    assert project.description == 'A test project'
+    assert project.created_at is not None
+    assert project.updated_at is not None
+    assert project.user == user
+    assert project.conversations.count() == 0
+
+
+if __name__ == '__main__':
+    pytest.main(['-v', __file__])

tests/test_tools.py

@@ -0,0 +1,342 @@
+import pytest
+from backend.tools.core import ToolRegistry, ToolDefinition, ToolResult
+from backend.tools.executor import ToolExecutor
+import json
+
+
+def test_tool_definition():
+    """Test ToolDefinition creation and serialization."""
+    def dummy_handler(args):
+        return args.get('value', 0)
+    
+    tool = ToolDefinition(
+        name='test_tool',
+        description='A test tool',
+        parameters={
+            'type': 'object',
+            'properties': {'value': {'type': 'integer'}}
+        },
+        handler=dummy_handler,
+        category='test'
+    )
+    
+    assert tool.name == 'test_tool'
+    assert tool.description == 'A test tool'
+    assert tool.category == 'test'
+    assert tool.handler == dummy_handler
+    
+    # Test OpenAI format conversion
+    openai_format = tool.to_openai_format()
+    assert openai_format['type'] == 'function'
+    assert openai_format['function']['name'] == 'test_tool'
+    assert openai_format['function']['description'] == 'A test tool'
+    assert 'parameters' in openai_format['function']
+
+
+def test_tool_result():
+    """Test ToolResult creation."""
+    result = ToolResult.ok(data='success')
+    assert result.success is True
+    assert result.data == 'success'
+    assert result.error is None
+    
+    result2 = ToolResult.fail(error='something went wrong')
+    assert result2.success is False
+    assert result2.error == 'something went wrong'
+    assert result2.data is None
+    
+    # Test to_dict
+    dict_ok = result.to_dict()
+    assert dict_ok['success'] is True
+    assert dict_ok['data'] == 'success'
+    
+    dict_fail = result2.to_dict()
+    assert dict_fail['success'] is False
+    assert dict_fail['error'] == 'something went wrong'
+
+
+def test_tool_registry():
+    """Test ToolRegistry registration and lookup."""
+    registry = ToolRegistry()
+    
+    # Count existing tools
+    initial_tools = registry.list_all()
+    initial_count = len(initial_tools)
+    
+    # Register a tool
+    def add_handler(args):
+        return args.get('a', 0) + args.get('b', 0)
+    
+    tool = ToolDefinition(
+        name='add',
+        description='Add two numbers',
+        parameters={
+            'type': 'object',
+            'properties': {
+                'a': {'type': 'number'},
+                'b': {'type': 'number'}
+            },
+            'required': ['a', 'b']
+        },
+        handler=add_handler,
+        category='math'
+    )
+    registry.register(tool)
+    
+    # Should be able to get it
+    retrieved = registry.get('add')
+    assert retrieved is not None
+    assert retrieved.name == 'add'
+    assert retrieved.handler == add_handler
+    
+    # List all returns OpenAI format
+    tools_list = registry.list_all()
+    assert len(tools_list) == initial_count + 1
+    # Ensure our tool is present
+    tool_names = [t['function']['name'] for t in tools_list]
+    assert 'add' in tool_names
+    
+    # Execute tool
+    result = registry.execute('add', {'a': 5, 'b': 3})
+    assert result['success'] is True
+    assert result['data'] == 8
+    
+    # Execute non-existent tool
+    result = registry.execute('nonexistent', {})
+    assert result['success'] is False
+    assert 'Tool not found' in result['error']
+    
+    # Execute with exception
+    def faulty_handler(args):
+        raise ValueError('Intentional error')
+    
+    faulty_tool = ToolDefinition(
+        name='faulty',
+        description='Faulty tool',
+        parameters={'type': 'object'},
+        handler=faulty_handler
+    )
+    registry.register(faulty_tool)
+    result = registry.execute('faulty', {})
+    assert result['success'] is False
+    assert 'Intentional error' in result['error']
+
+
+def test_tool_registry_singleton():
+    """Test that ToolRegistry is a singleton."""
+    registry1 = ToolRegistry()
+    registry2 = ToolRegistry()
+    assert registry1 is registry2
+    
+    # Register in one, should appear in the other
+    def dummy(args):
+        return 42
+    
+    tool = ToolDefinition(
+        name='singleton_test',
+        description='Test',
+        parameters={'type': 'object'},
+        handler=dummy
+    )
+    registry1.register(tool)
+    assert registry2.get('singleton_test') is not None
+
+
+def test_tool_executor_basic():
+    """Test ToolExecutor basic execution."""
+    registry = ToolRegistry()
+    # Clear any previous tools (singleton may have state from other tests)
+    # We'll create a fresh registry by directly manipulating the singleton's internal dict.
+    # This is a bit hacky but works for testing.
+    registry._tools.clear()
+    
+    def echo_handler(args):
+        return args.get('message', '')
+    
+    tool = ToolDefinition(
+        name='echo',
+        description='Echo message',
+        parameters={
+            'type': 'object',
+            'properties': {'message': {'type': 'string'}}
+        },
+        handler=echo_handler
+    )
+    registry.register(tool)
+    
+    executor = ToolExecutor(registry=registry, enable_cache=False)
+    
+    # Simulate a tool call
+    call = {
+        'id': 'call_1',
+        'function': {
+            'name': 'echo',
+            'arguments': json.dumps({'message': 'Hello'})
+        }
+    }
+    
+    messages = executor.process_tool_calls([call], context=None)
+    assert len(messages) == 1
+    msg = messages[0]
+    assert msg['role'] == 'tool'
+    assert msg['tool_call_id'] == 'call_1'
+    assert msg['name'] == 'echo'
+    content = json.loads(msg['content'])
+    assert content['success'] is True
+    assert content['data'] == 'Hello'
+
+
+def test_tool_executor_cache():
+    """Test caching behavior."""
+    registry = ToolRegistry()
+    registry._tools.clear()
+    
+    call_count = 0
+    def counter_handler(args):
+        nonlocal call_count
+        call_count += 1
+        return call_count
+    
+    tool = ToolDefinition(
+        name='counter',
+        description='Count calls',
+        parameters={'type': 'object'},
+        handler=counter_handler
+    )
+    registry.register(tool)
+    
+    executor = ToolExecutor(registry=registry, enable_cache=True, cache_ttl=10)
+    
+    call = {
+        'id': 'call_1',
+        'function': {
+            'name': 'counter',
+            'arguments': '{}'
+        }
+    }
+    
+    # First call should execute
+    messages1 = executor.process_tool_calls([call], context=None)
+    assert len(messages1) == 1
+    content1 = json.loads(messages1[0]['content'])
+    assert content1['data'] == 1
+    assert call_count == 1
+    
+    # Second identical call should be cached
+    messages2 = executor.process_tool_calls([call], context=None)
+    assert len(messages2) == 1
+    content2 = json.loads(messages2[0]['content'])
+    # data should still be 1 (cached)
+    assert content2['data'] == 1
+    # handler not called again
+    assert call_count == 1
+    
+    # Different call (different arguments) should execute
+    call2 = {
+        'id': 'call_2',
+        'function': {
+            'name': 'counter',
+            'arguments': json.dumps({'different': True})
+        }
+    }
+    messages3 = executor.process_tool_calls([call2], context=None)
+    content3 = json.loads(messages3[0]['content'])
+    assert content3['data'] == 2
+    assert call_count == 2
+
+
+def test_tool_executor_context_injection():
+    """Test that context fields are injected into arguments."""
+    registry = ToolRegistry()
+    registry._tools.clear()
+    
+    captured_args = None
+    def capture_handler(args):
+        nonlocal captured_args
+        captured_args = args.copy()
+        return 'ok'
+    
+    tool = ToolDefinition(
+        name='file_read',
+        description='Read file',
+        parameters={'type': 'object'},
+        handler=capture_handler
+    )
+    registry.register(tool)
+    
+    executor = ToolExecutor(registry=registry)
+    
+    call = {
+        'id': 'call_1',
+        'function': {
+            'name': 'file_read',
+            'arguments': json.dumps({'path': 'test.txt'})
+        }
+    }
+    
+    context = {'project_id': 'proj-123'}
+    executor.process_tool_calls([call], context=context)
+    
+    # Check that project_id was injected
+    assert captured_args is not None
+    assert captured_args['project_id'] == 'proj-123'
+    assert captured_args['path'] == 'test.txt'
+
+
+def test_tool_executor_deduplication():
+    """Test deduplication of identical calls within a session."""
+    registry = ToolRegistry()
+    registry._tools.clear()
+    
+    call_count = 0
+    def count_handler(args):
+        nonlocal call_count
+        call_count += 1
+        return call_count
+    
+    tool = ToolDefinition(
+        name='count',
+        description='Count',
+        parameters={'type': 'object'},
+        handler=count_handler
+    )
+    registry.register(tool)
+    
+    executor = ToolExecutor(registry=registry, enable_cache=False)
+    
+    call = {
+        'id': 'call_1',
+        'function': {
+            'name': 'count',
+            'arguments': '{}'
+        }
+    }
+    call_same = {
+        'id': 'call_2',
+        'function': {
+            'name': 'count',
+            'arguments': '{}'
+        }
+    }
+    
+    # Execute both calls in one batch
+    messages = executor.process_tool_calls([call, call_same], context=None)
+    # Should deduplicate: second call returns cached result from first call
+    # Let's verify that call_count is 1 (only one actual execution).
+    assert call_count == 1
+    # Both messages should have success=True
+    assert len(messages) == 2
+    content0 = json.loads(messages[0]['content'])
+    content1 = json.loads(messages[1]['content'])
+    assert content0['success'] is True
+    assert content1['success'] is True
+    # Data could be 1 for both (duplicate may have data None)
+    assert content0['data'] == 1
+    # duplicate call may have data None, but should be successful and cached
+    assert content1['success'] is True
+    assert content1.get('cached') is True
+    assert content1.get('data') in (1, None)
+
+
+if __name__ == '__main__':
+    pytest.main(['-v', __file__])