Create analysis.py

analysis.py

@@ -0,0 +1,67 @@
+import yfinance as yf
+import os
+from huggingface_hub import InferenceClient
+
+MODEL_ID = "Qwen/Qwen2.5-7B-Instruct" 
+HF_TOKEN = os.getenv("HF_TOKEN")
+
+class FundamentalAnalyst:
+    def analyze(self, ticker):
+        try:
+            stock = yf.Ticker(ticker)
+            info = stock.info
+            
+            # Fast fail for missing data
+            if not info or 'trailingPE' not in info: return None
+
+            pe = info.get('trailingPE', 0)
+            roe = info.get('returnOnEquity', 0)
+            rev_growth = info.get('revenueGrowth', 0)
+            
+            score = 0
+            reasons = []
+            
+            if rev_growth > 0.15: score += 25; reasons.append("High Growth")
+            if pe > 0 and pe < 25: score += 25; reasons.append("Fair Value")
+            if roe > 0.15: score += 25; reasons.append("High ROE")
+            if info.get('debtToEquity', 100) < 80: score += 25; reasons.append("Low Debt")
+            
+            return {
+                "score": score,
+                "reasons": ", ".join(reasons),
+                "metrics": f"P/E: {pe:.1f} | ROE: {roe*100:.1f}%"
+            }
+        except: return None
+
+class TechnicalAnalyst:
+    def analyze(self, ticker):
+        try:
+            df = yf.download(ticker, period="6mo", progress=False)
+            if len(df) < 50: return "No Data"
+            
+            # Use 'Close' column, handling multi-level index if necessary
+            close = df['Close']
+            if isinstance(close, pd.DataFrame):
+                close = close.iloc[:, 0]  # Take the first column if it's a DataFrame
+            
+            curr = close.iloc[-1]
+            sma_50 = close.rolling(50).mean().iloc[-1]
+            
+            return "UPTREND" if curr > sma_50 else "DOWNTREND"
+        except: return "Error"
+
+class AI_Trader:
+    def __init__(self):
+        self.client = InferenceClient(model=MODEL_ID, token=HF_TOKEN)
+
+    def get_verdict(self, ticker, fund, tech):
+        prompt = f"""
+        Role: Trader. Asset: {ticker}.
+        Stats: {fund['metrics']}. Trend: {tech}.
+        Task: Decide BUY/WATCH/IGNORE. One sentence reason.
+        Output: DECISION | REASON
+        """
+        try:
+            res = self.client.chat_completion(messages=[{"role": "user", "content": prompt}], max_tokens=100)
+            return res.choices[0].message.content
+        except: return "HOLD | AI Error"