Merge branch 'main' of https://github.com/HKUDS/AI-Trader

agent/base_agent/base_agent.py

@@ -147,21 +147,41 @@ class BaseAgent:
         """Initialize MCP client and AI model"""
         print(f"🚀 Initializing agent: {self.signature}")
         
-        # Create MCP client
-        self.client = MultiServerMCPClient(self.mcp_config)
+        # Validate OpenAI configuration
+        if not self.openai_api_key:
+            raise ValueError("❌ OpenAI API key not set. Please configure OPENAI_API_KEY in environment or config file.")
+        if not self.openai_base_url:
+            print("⚠️  OpenAI base URL not set, using default")
         
-        # Get tools
-        self.tools = await self.client.get_tools()
-        print(f"✅ Loaded {len(self.tools)} MCP tools")
+        try:
+            # Create MCP client
+            self.client = MultiServerMCPClient(self.mcp_config)
+            
+            # Get tools
+            self.tools = await self.client.get_tools()
+            if not self.tools:
+                print("⚠️  Warning: No MCP tools loaded. MCP services may not be running.")
+                print(f"   MCP configuration: {self.mcp_config}")
+            else:
+                print(f"✅ Loaded {len(self.tools)} MCP tools")
+        except Exception as e:
+            raise RuntimeError(
+                f"❌ Failed to initialize MCP client: {e}\n"
+                f"   Please ensure MCP services are running at the configured ports.\n"
+                f"   Run: python agent_tools/start_mcp_services.py"
+            )
         
-        # Create AI model
-        self.model = ChatOpenAI(
-            model=self.basemodel,
-            base_url=self.openai_base_url,
-            api_key=self.openai_api_key,
-            max_retries=3,
-            timeout=30
-        )
+        try:
+            # Create AI model
+            self.model = ChatOpenAI(
+                model=self.basemodel,
+                base_url=self.openai_base_url,
+                api_key=self.openai_api_key,
+                max_retries=3,
+                timeout=30
+            )
+        except Exception as e:
+            raise RuntimeError(f"❌ Failed to initialize AI model: {e}")
         
         # Note: agent will be created in run_trading_session() based on specific date
         # because system_prompt needs the current date and price information

tools/general_tools.py

@@ -2,11 +2,14 @@
 import os
 import json
 from pathlib import Path
+from typing import Any
 from dotenv import load_dotenv
 load_dotenv()
 
 def _load_runtime_env() -> dict:
     path = os.environ.get("RUNTIME_ENV_PATH")
+    if path is None:
+        return {}
     try:
         if os.path.exists(path):
             with open(path, "r", encoding="utf-8") as f:
@@ -25,12 +28,18 @@ def get_config_value(key: str, default=None):
         return _RUNTIME_ENV[key]
     return os.getenv(key, default)
 
-def write_config_value(key: str, value: any):
+def write_config_value(key: str, value: Any):
+    path = os.environ.get("RUNTIME_ENV_PATH")
+    if path is None:
+        print(f"⚠️  WARNING: RUNTIME_ENV_PATH not set, config value '{key}' not persisted")
+        return
     _RUNTIME_ENV = _load_runtime_env()
     _RUNTIME_ENV[key] = value
-    path = os.environ.get("RUNTIME_ENV_PATH")
-    with open(path, "w", encoding="utf-8") as f:
-        json.dump(_RUNTIME_ENV, f, ensure_ascii=False, indent=4)
+    try:
+        with open(path, "w", encoding="utf-8") as f:
+            json.dump(_RUNTIME_ENV, f, ensure_ascii=False, indent=4)
+    except Exception as e:
+        print(f"❌ Error writing config to {path}: {e}")
 
 def extract_conversation(conversation: dict, output_type: str):
     """Extract information from a conversation payload.

tools/price_tools.py

@@ -4,7 +4,7 @@ load_dotenv()
 import json
 from datetime import datetime, timedelta
 from pathlib import Path
-from typing import Dict, List, Optional
+from typing import Dict, List, Optional, Tuple
 import sys
 
 # 将项目根目录加入 Python 路径，便于从子目录直接运行本文件
@@ -95,7 +95,7 @@ def get_open_prices(today_date: str, symbols: List[str], merged_path: Optional[s
 
     return results
 
-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]]]:
+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]]]:
     """从 data/merged.jsonl 中读取指定日期与股票的昨日买入价和卖出价。
 
     Args:
@@ -260,7 +260,7 @@ def get_today_init_position(today_date: str, modelname: str) -> Dict[str, float]
     
     return latest_positions
 
-def get_latest_position(today_date: str, modelname: str) -> Dict[str, float]:
+def get_latest_position(today_date: str, modelname: str) -> Tuple[Dict[str, float], int]:
     """
     获取最新持仓。从 ../data/agent_data/{modelname}/position/position.jsonl 中读取。
     优先选择当天 (today_date) 中 id 最大的记录；
@@ -273,7 +273,7 @@ def get_latest_position(today_date: str, modelname: str) -> Dict[str, float]:
     Returns:
         (positions, max_id):
           - positions: {symbol: weight} 的字典；若未找到任何记录，则为空字典。
-          - max_id: 选中记录的最大 id；若未找到任何记录，则为 -1。
+          - max_id: 选中记录的最大 id；若未找到任何记录，则为 -1.
     """
     base_dir = Path(__file__).resolve().parents[1]
     position_file = base_dir / "data" / "agent_data" / modelname / "position" / "position.jsonl"