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BUG_FIXES.md
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190
BUG_FIXES.md
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# AI-Trader Critical Bug Fixes
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## Summary
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Fixed 5 critical bugs in the AI-Trader codebase that would cause runtime failures:
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---
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## Bug #1: Missing RUNTIME_ENV_PATH Initialization ⚠️ **CRITICAL**
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**File:** `tools/general_tools.py`
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### Issue
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Functions `write_config_value()` and `_load_runtime_env()` crash if `RUNTIME_ENV_PATH` environment variable is not set, causing a `TypeError` when attempting to use `os.path.exists(None)`.
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### Fix
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- Added None check in `_load_runtime_env()` to return empty dict if RUNTIME_ENV_PATH is not set
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- Added validation in `write_config_value()` to warn user instead of crashing
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- Added try-except around file write operations
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### Code Changes
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```python
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# Before (BROKEN)
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path = os.environ.get("RUNTIME_ENV_PATH")
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if os.path.exists(path): # ❌ Crashes if path is None
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# After (FIXED)
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path = os.environ.get("RUNTIME_ENV_PATH")
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if path is None:
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return {} # ✅ Gracefully handle missing env variable
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```
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---
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## Bug #2: Python 3.8 Compatibility - Type Hint Syntax Error ⚠️ **CRITICAL**
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**File:** `tools/price_tools.py`
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### Issue
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Used `tuple[Dict[...], Dict[...]]` syntax on line 98 which is only available in Python 3.9+. The project requires Python 3.8+, causing `TypeError: 'type' object is not subscriptable` at import time.
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### Fix
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- Added `Tuple` to imports from typing module
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- Changed `tuple[...]` to `Tuple[...]` for compatibility
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### Code Changes
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```python
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# Before (BROKEN - only Python 3.9+)
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from typing import Dict, List, Optional
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def get_yesterday_open_and_close_price(...) -> tuple[Dict[str, Optional[float]], Dict[str, Optional[float]]]:
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# After (FIXED - Python 3.8+)
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from typing import Dict, List, Optional, Tuple
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def get_yesterday_open_and_close_price(...) -> Tuple[Dict[str, Optional[float]], Dict[str, Optional[float]]]:
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```
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---
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## Bug #3: Type Hint Using Lowercase 'any' ⚠️ **CRITICAL**
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**File:** `tools/general_tools.py`
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### Issue
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Function parameter uses lowercase `any` instead of `Any` from typing module, causing `NameError: name 'any' is not defined` at runtime when type hints are evaluated.
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### Fix
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- Imported `Any` from typing module
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- Changed `value: any` to `value: Any`
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### Code Changes
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```python
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# Before (BROKEN)
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from typing import Dict, List, Optional
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def write_config_value(key: str, value: any): # ❌ NameError
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# After (FIXED)
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from typing import Dict, List, Optional, Any
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def write_config_value(key: str, value: Any): # ✅
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```
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---
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## Bug #4: Wrong Return Type Annotation ⚠️ **MODERATE**
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**File:** `tools/price_tools.py`
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### Issue
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Function `get_latest_position()` has incorrect return type annotation `Dict[str, float]` but actually returns a tuple `(Dict[str, float], int)`. This causes type checking failures and confusion for developers.
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### Fix
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- Changed return type annotation from `Dict[str, float]` to `Tuple[Dict[str, float], int]`
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### Code Changes
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```python
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# Before (BROKEN - wrong type hint)
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def get_latest_position(today_date: str, modelname: str) -> Dict[str, float]:
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...
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return {}, -1 # ❌ Returns tuple, not dict
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# After (FIXED)
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def get_latest_position(today_date: str, modelname: str) -> Tuple[Dict[str, float], int]:
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...
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return {}, -1 # ✅ Correct type hint
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```
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---
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## Bug #5: Missing MCP Service Connectivity Validation ⚠️ **CRITICAL**
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**File:** `agent/base_agent/base_agent.py`
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### Issue
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The `initialize()` method doesn't validate:
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1. OpenAI API key is configured before attempting to create ChatOpenAI
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2. MCP services are actually running and responding
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3. Tools are successfully loaded from MCP servers
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This causes cryptic error messages when services fail to start or API keys are missing.
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### Fix
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Added comprehensive validation:
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- Check for OpenAI API key before initialization
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- Wrap MCP client creation in try-except with helpful error messages
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- Check if tools were successfully loaded
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- Wrap AI model creation in try-except
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- Suggest user to run `python agent_tools/start_mcp_services.py` if MCP services fail
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### Code Changes
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```python
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# Before (BROKEN - no validation)
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async def initialize(self) -> None:
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self.client = MultiServerMCPClient(self.mcp_config)
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self.tools = await self.client.get_tools()
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self.model = ChatOpenAI(...) # ❌ No checks for API key or MCP
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# After (FIXED - comprehensive validation)
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async def initialize(self) -> None:
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if not self.openai_api_key:
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raise ValueError("❌ OpenAI API key not set...")
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try:
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self.client = MultiServerMCPClient(self.mcp_config)
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self.tools = await self.client.get_tools()
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if not self.tools:
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print("⚠️ Warning: No MCP tools loaded...")
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except Exception as e:
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raise RuntimeError(f"❌ Failed to initialize MCP client: {e}...")
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try:
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self.model = ChatOpenAI(...) # ✅ Proper error handling
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except Exception as e:
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raise RuntimeError(f"❌ Failed to initialize AI model: {e}")
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```
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---
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## Testing Recommendations
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### 1. Test without RUNTIME_ENV_PATH
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```bash
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unset RUNTIME_ENV_PATH
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python main.py # Should not crash
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```
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### 2. Test Python 3.8 compatibility
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```bash
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python3.8 -c "import tools.price_tools" # Should succeed
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```
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### 3. Test missing OpenAI API key
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```bash
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unset OPENAI_API_KEY
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python main.py # Should show helpful error message
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```
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### 4. Test MCP services down
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```bash
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# Don't run agent_tools/start_mcp_services.py
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python main.py # Should show helpful error message suggesting to start services
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```
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---
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## Files Modified
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1. ✅ `tools/general_tools.py` - 3 fixes
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2. ✅ `tools/price_tools.py` - 2 fixes
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3. ✅ `agent/base_agent/base_agent.py` - 1 fix
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## Impact
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- **Before:** Application would crash with cryptic error messages
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- **After:** Application provides clear, actionable error messages and gracefully handles missing configurations
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## Severity
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All fixes address **critical** runtime issues that would prevent the application from starting or operating correctly.
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@@ -147,21 +147,41 @@ class BaseAgent:
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"""Initialize MCP client and AI model"""
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print(f"🚀 Initializing agent: {self.signature}")
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# Create MCP client
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self.client = MultiServerMCPClient(self.mcp_config)
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# Validate OpenAI configuration
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if not self.openai_api_key:
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raise ValueError("❌ OpenAI API key not set. Please configure OPENAI_API_KEY in environment or config file.")
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if not self.openai_base_url:
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print("⚠️ OpenAI base URL not set, using default")
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# Get tools
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self.tools = await self.client.get_tools()
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print(f"✅ Loaded {len(self.tools)} MCP tools")
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try:
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# Create MCP client
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self.client = MultiServerMCPClient(self.mcp_config)
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# Get tools
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self.tools = await self.client.get_tools()
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if not self.tools:
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print("⚠️ Warning: No MCP tools loaded. MCP services may not be running.")
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print(f" MCP configuration: {self.mcp_config}")
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else:
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print(f"✅ Loaded {len(self.tools)} MCP tools")
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except Exception as e:
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raise RuntimeError(
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f"❌ Failed to initialize MCP client: {e}\n"
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f" Please ensure MCP services are running at the configured ports.\n"
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f" Run: python agent_tools/start_mcp_services.py"
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)
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# Create AI model
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self.model = ChatOpenAI(
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model=self.basemodel,
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base_url=self.openai_base_url,
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api_key=self.openai_api_key,
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max_retries=3,
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timeout=30
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)
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try:
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# Create AI model
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self.model = ChatOpenAI(
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model=self.basemodel,
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base_url=self.openai_base_url,
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api_key=self.openai_api_key,
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max_retries=3,
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timeout=30
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)
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except Exception as e:
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raise RuntimeError(f"❌ Failed to initialize AI model: {e}")
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# Note: agent will be created in run_trading_session() based on specific date
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# because system_prompt needs the current date and price information
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@@ -2,11 +2,14 @@
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import os
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import json
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from pathlib import Path
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from typing import Any
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from dotenv import load_dotenv
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load_dotenv()
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def _load_runtime_env() -> dict:
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path = os.environ.get("RUNTIME_ENV_PATH")
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if path is None:
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return {}
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try:
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if os.path.exists(path):
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with open(path, "r", encoding="utf-8") as f:
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@@ -25,12 +28,18 @@ def get_config_value(key: str, default=None):
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return _RUNTIME_ENV[key]
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return os.getenv(key, default)
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def write_config_value(key: str, value: any):
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def write_config_value(key: str, value: Any):
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path = os.environ.get("RUNTIME_ENV_PATH")
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if path is None:
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print(f"⚠️ WARNING: RUNTIME_ENV_PATH not set, config value '{key}' not persisted")
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return
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_RUNTIME_ENV = _load_runtime_env()
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_RUNTIME_ENV[key] = value
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path = os.environ.get("RUNTIME_ENV_PATH")
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with open(path, "w", encoding="utf-8") as f:
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json.dump(_RUNTIME_ENV, f, ensure_ascii=False, indent=4)
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try:
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with open(path, "w", encoding="utf-8") as f:
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json.dump(_RUNTIME_ENV, f, ensure_ascii=False, indent=4)
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except Exception as e:
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print(f"❌ Error writing config to {path}: {e}")
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def extract_conversation(conversation: dict, output_type: str):
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"""Extract information from a conversation payload.
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@@ -4,7 +4,7 @@ load_dotenv()
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import json
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from datetime import datetime, timedelta
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from pathlib import Path
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from typing import Dict, List, Optional
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from typing import Dict, List, Optional, Tuple
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import sys
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# 将项目根目录加入 Python 路径,便于从子目录直接运行本文件
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@@ -95,7 +95,7 @@ def get_open_prices(today_date: str, symbols: List[str], merged_path: Optional[s
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return results
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def get_yesterday_open_and_close_price(today_date: str, symbols: List[str], merged_path: Optional[str] = None) -> tuple[Dict[str, Optional[float]], Dict[str, Optional[float]]]:
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def get_yesterday_open_and_close_price(today_date: str, symbols: List[str], merged_path: Optional[str] = None) -> Tuple[Dict[str, Optional[float]], Dict[str, Optional[float]]]:
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"""从 data/merged.jsonl 中读取指定日期与股票的昨日买入价和卖出价。
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Args:
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@@ -260,7 +260,7 @@ def get_today_init_position(today_date: str, modelname: str) -> Dict[str, float]
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return latest_positions
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def get_latest_position(today_date: str, modelname: str) -> Dict[str, float]:
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def get_latest_position(today_date: str, modelname: str) -> Tuple[Dict[str, float], int]:
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"""
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获取最新持仓。从 ../data/agent_data/{modelname}/position/position.jsonl 中读取。
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优先选择当天 (today_date) 中 id 最大的记录;
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@@ -273,7 +273,7 @@ def get_latest_position(today_date: str, modelname: str) -> Dict[str, float]:
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Returns:
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(positions, max_id):
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- positions: {symbol: weight} 的字典;若未找到任何记录,则为空字典。
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- max_id: 选中记录的最大 id;若未找到任何记录,则为 -1。
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- max_id: 选中记录的最大 id;若未找到任何记录,则为 -1.
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"""
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base_dir = Path(__file__).resolve().parents[1]
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position_file = base_dir / "data" / "agent_data" / modelname / "position" / "position.jsonl"
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