2

app.py

@@ -81,45 +81,45 @@ def period_to_start_end(period_str: str):
         start = now - dt.timedelta(weeks=13)
     return start, now
 
-# --- 取得股票價格與技術指標 ---
-def get_stock_prices(ticker: str, period: str = "3mo") -> Union[Dict, str]:
+@tool
+def get_stock_prices(ticker: str) -> Union[Dict, str]:
+    """Fetches historical stock price data and technical indicator for a given ticker."""
     try:
-        start_date, end_date = period_to_start_end(period)
         data = yf.download(
             ticker,
-            start=start_date,
-            end=end_date,
+            start=dt.datetime.now() - dt.timedelta(weeks=13),
+            end=dt.datetime.now(),
             interval='1d'
         )
 
         if data.empty:
-            return f"無法取得 {ticker} 的歷史資料"
+            return {"error": f"No stock data found for {ticker}"}
+
+        # 如果 columns 有多層，才做重命名
+        if data.columns.nlevels > 1:
+            data.columns = [col[0] for col in data.columns]
 
-        # reset_index() 之後，立刻把欄位名稱都轉成字串
         data.reset_index(inplace=True)
-        data.columns = [str(col) for col in data.columns]
+        data["Date"] = data["Date"].astype(str)
 
-        # 如果你另外有 df = data.copy() 想做技術指標，也要確保欄位一致
         df = data.copy()
 
-        # 計算技術指標
-        from ta.momentum import RSIIndicator, StochasticOscillator
-        from ta.trend import MACD
-        from ta.volume import volume_weighted_average_price
-
         indicators = {}
-
         n = min(12, len(df))
+
+        # RSI
         rsi_series = RSIIndicator(df['Close'], window=14).rsi().iloc[-n:]
         indicators["RSI"] = {
             str(date.date()): int(value) for date, value in rsi_series.dropna().items()
         }
 
+        # Stochastic
         sto_series = StochasticOscillator(df['High'], df['Low'], df['Close'], window=14).stoch().iloc[-n:]
         indicators["Stochastic_Oscillator"] = {
             str(date.date()): int(value) for date, value in sto_series.dropna().items()
         }
 
+        # MACD
         macd = MACD(df['Close'])
         macd_series = macd.macd().iloc[-n:]
         indicators["MACD"] = {
@@ -130,6 +130,7 @@ def get_stock_prices(ticker: str, period: str = "3mo") -> Union[Dict, str]:
             str(date.date()): int(value) for date, value in macd_signal_series.items()
         }
 
+        # VWAP
         vwap_series = volume_weighted_average_price(
             high=df['High'],
             low=df['Low'],
@@ -141,34 +142,37 @@ def get_stock_prices(ticker: str, period: str = "3mo") -> Union[Dict, str]:
         }
 
         return {
-            'stock_price': data.to_dict(orient='records'),
-            'indicators': indicators
+            "stock_price": data.to_dict(orient="records"),
+            "indicators": indicators
         }
     except Exception as e:
         return f"Error fetching price data: {str(e)}"
 
-# --- 取得財務新聞 ---
+@tool
 def get_financial_news(ticker: str) -> Union[Dict, str]:
+    """Fetches the latest financial news related to a given ticker."""
     try:
         stock = yf.Ticker(ticker)
-        news = stock.news
+        news = stock.news  # 從 Yahoo Finance 獲取新聞
         if not news:
             return {"news": "No recent news found."}
-        latest_news = [
-            {
+
+        # 只取最新5則新聞
+        latest_news = []
+        for item in news[:5]:
+            latest_news.append({
                 "title": item.get('title'),
                 "publisher": item.get('publisher'),
                 "link": item.get('link'),
                 "published_date": item.get('providerPublishTime')
-            }
-            for item in news[:5]
-        ]
+            })
         return {"news": latest_news}
     except Exception as e:
         return f"Error fetching news: {str(e)}"
 
-# --- 取得財務指標 ---
+@tool
 def get_financial_metrics(ticker: str) -> Union[Dict, str]:
+    """Fetches key financial ratios for a given ticker."""
     try:
         stock = yf.Ticker(ticker)
         info = stock.info