Merge dazzling-leakey into main: GraphRecursionError fix and stock data validation

Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>

backend/app/services/trading_service.py

@@ -205,7 +205,16 @@ class TradingService:
                     "investment_debate_state": final_state.get("investment_debate_state"),
                     "risk_debate_state": final_state.get("risk_debate_state"),
                 }
-                
+
+                # Log report completeness for debugging
+                for key, value in reports.items():
+                    if isinstance(value, dict):
+                        sub_filled = [k for k, v in value.items() if v and k not in ("count", "latest_speaker")]
+                        logger.info(f"📊 Report '{key}': filled fields = {sub_filled}")
+                    else:
+                        status_icon = "✅" if value else "❌"
+                        logger.info(f"📊 Report '{key}': {status_icon} {'populated' if value else 'EMPTY'}")
+
                 # Load price data
                 from backend.app.services.price_service import PriceService
                 price_data = None

frontend/app/analysis/results/page.tsx

@@ -54,6 +54,22 @@ export default function AnalysisResultsPage() {
   const [saveError, setSaveError] = useState<string | null>(null);
   const [savedToCloud, setSavedToCloud] = useState(false);
 
+  // Debug: log received analysis data structure
+  useEffect(() => {
+    if (analysisResult) {
+      console.log("[Results] analysisResult.reports keys:", Object.keys(analysisResult.reports || {}));
+      const ids = analysisResult.reports?.investment_debate_state;
+      const rds = analysisResult.reports?.risk_debate_state;
+      if (ids) console.log("[Results] investment_debate_state keys:", Object.keys(ids));
+      if (rds) console.log("[Results] risk_debate_state keys:", Object.keys(rds));
+      // Log which reports are populated
+      ANALYST_KEYS.forEach(a => {
+        const val = getNestedValue(analysisResult.reports, a.reportKey);
+        console.log(`[Results] ${a.key} (${a.reportKey}):`, val ? "populated" : "EMPTY/MISSING");
+      });
+    }
+  }, [analysisResult]);
+
   // Build analysts array with translations
   const ANALYSTS = useMemo(() => ANALYST_KEYS.map(analyst => ({
     key: analyst.key,

tradingagents/agents/utils/core_stock_tools.py

@@ -1,5 +1,6 @@
 from langchain_core.tools import tool
 from typing import Annotated
+from datetime import datetime, timedelta
 from tradingagents.dataflows.interface import route_to_vendor
 
 
@@ -19,4 +20,14 @@ def get_stock_data(
     Returns:
         str: 一個格式化的數據框，包含指定股票代碼在指定日期範圍內的股價數據。
     """
+    # 強制至少 365 天的資料範圍，確保分析品質一致
+    try:
+        start_dt = datetime.strptime(start_date, "%Y-%m-%d")
+        end_dt = datetime.strptime(end_date, "%Y-%m-%d")
+        if (end_dt - start_dt).days < 365:
+            start_dt = end_dt - timedelta(days=365)
+            start_date = start_dt.strftime("%Y-%m-%d")
+            print(f"[get_stock_data] 日期範圍不足 1 年，已自動調整 start_date 為 {start_date}")
+    except ValueError:
+        pass  # 日期格式錯誤時使用原始值
     return route_to_vendor("get_stock_data", symbol, start_date, end_date)

tradingagents/agents/utils/prompts.py

@@ -87,7 +87,7 @@ You are a senior technical analyst responsible for providing precise market tech
 4. **Trading Recommendations**: Provide entry/exit positions, risk control parameters
 
 【Technical Operations】
-• Use get_stock_data to obtain historical price data
+• Use get_stock_data to obtain historical price data — always request at least 1 year of data (start_date = trade_date minus 365 days)
 • Use get_indicators to calculate technical indicators (set look_back_days to 50 or 200 for moving averages)
 • Integrate data to provide professional insights
 
@@ -118,7 +118,7 @@ Please provide a professional, precise, and actionable technical analysis report
 4. **操作建議**：提供進出場位置、風險控制參數
 
 【技術操作】
-• 使用 get_stock_data 取得歷史價格資料
+• 使用 get_stock_data 取得歷史價格資料 — 務必取得至少 1 年的資料（start_date = 交易日期減 365 天）
 • 使用 get_indicators 計算技術指標（均線請設定 look_back_days 為 50 或 200）
 • 整合數據後提出專業見解
 

tradingagents/default_config.py

@@ -16,7 +16,7 @@ DEFAULT_CONFIG = {
     # 辯論與討論設定
     "max_debate_rounds": 1,
     "max_risk_discuss_rounds": 1,
-    "max_recur_limit": 100,
+    "max_recur_limit": 200,
     # 資料供應商設定
     # 類別層級設定 (該類別所有工具的預設值)
     # 可用供應商:

tradingagents/graph/propagation.py

@@ -18,7 +18,7 @@ class Propagator:
     這個類別負責建立圖執行的初始狀態，並提供圖呼叫所需的參數。
     """
 
-    def __init__(self, max_recur_limit=100):
+    def __init__(self, max_recur_limit=200):
         """
         使用設定參數進行初始化。
 
@@ -68,14 +68,26 @@ class Propagator:
             "company_name": actual_company_name,  # 真實公司全名
             "trade_date": str(trade_date),  # 交易日期
             "investment_debate_state": InvestDebateState(
-                {"history": "", "current_response": "", "count": 0}
+                {
+                    "bull_history": "",
+                    "bear_history": "",
+                    "history": "",
+                    "current_response": "",
+                    "judge_decision": "",
+                    "count": 0,
+                }
             ),  # 投資辯論的初始狀態
             "risk_debate_state": RiskDebateState(
                 {
+                    "risky_history": "",
+                    "safe_history": "",
+                    "neutral_history": "",
                     "history": "",
+                    "latest_speaker": "",
                     "current_risky_response": "",
                     "current_safe_response": "",
                     "current_neutral_response": "",
+                    "judge_decision": "",
                     "count": 0,
                 }
             ),  # 風險辯論的初始狀態

tradingagents/graph/trading_graph.py

@@ -146,8 +146,11 @@ class TradingAgentsXGraph:
         # Extract language from config (default: zh-TW for backward compatibility)
         self.language = self.config.get("language", "zh-TW")
 
-        # 初始化組件
-        self.conditional_logic = ConditionalLogic()
+        # 初始化組件（從 config 傳入辯論回合數）
+        self.conditional_logic = ConditionalLogic(
+            max_debate_rounds=self.config.get("max_debate_rounds", 1),
+            max_risk_discuss_rounds=self.config.get("max_risk_discuss_rounds", 1),
+        )
         self.graph_setup = GraphSetup(
             self.quick_thinking_llm,
             self.deep_thinking_llm,
@@ -161,7 +164,9 @@ class TradingAgentsXGraph:
             self.language,  # Pass language for agent reports
         )
 
-        self.propagator = Propagator()
+        self.propagator = Propagator(
+            max_recur_limit=self.config.get("max_recur_limit", 200),
+        )
         self.reflector = Reflector(self.quick_thinking_llm)
         self.signal_processor = SignalProcessor(self.quick_thinking_llm)