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app.py

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+import gradio as gr
+import os
+from openai import OpenAI
+from stock_utils import get_stock_data
+
+# Initialize OpenAI client using Hugging Face secret
+client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
+
+def analyze_stock(ticker):
+    try:
+        # Get stock data using yfinance
+        data = get_stock_data(ticker)
+        if "error" in data:
+            return f"Data fetch error: {data['error']}"
+
+        # Construct prompt
+        prompt = (
+            "You are a financial analyst. Analyze the following stock data and provide:\n"
+            "1. A BUY / HOLD / SELL recommendation\n"
+            "2. Reason for the recommendation\n"
+            "3. Summary in bullet points\n\n"
+            f"Stock Data:\n{data}"
+        )
+
+        # Call OpenAI chat model
+        response = client.chat.completions.create(
+            model="gpt-4o",
+            messages=[{"role": "user", "content": prompt}]
+        )
+
+        raw_text = response.choices[0].message.content.strip()
+
+        # Clean markdown artifacts (if model wraps in ``` or quotes)
+        if raw_text.startswith("```") and raw_text.endswith("```"):
+            raw_text = raw_text[3:-3].strip()
+        elif raw_text.startswith("'''") and raw_text.endswith("'''"):
+            raw_text = raw_text[3:-3].strip()
+        elif raw_text.startswith('"') and raw_text.endswith('"'):
+            raw_text = raw_text[1:-1].strip()
+
+        return raw_text
+
+    except Exception as e:
+        return f"❌ Unexpected error: {str(e)}"
+
+# Gradio app UI
+demo = gr.Interface(
+    fn=analyze_stock,
+    inputs=gr.Textbox(label="Enter Stock Ticker (e.g., AAPL)"),
+    outputs=gr.Textbox(label="Agent Recommendation"),
+    title="📈 AI Stock Advisor Agent",
+    description="Enter a stock ticker to get GPT-4o-powered insights and a recommendation"
+)
+
+demo.launch()

requirements.txt

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+gradio
+openai>=1.2.0
+yfinance
+pandas

stock_utils.py

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+import yfinance as yf
+
+def get_stock_data(ticker):
+    try:
+        stock = yf.Ticker(ticker)
+        hist = stock.history(period="5d")
+        info = stock.info
+
+        data = {
+            "ticker": ticker,
+            "company_name": info.get("longName", "N/A"),
+            "current_price": info.get("currentPrice", "N/A"),
+            "pe_ratio": info.get("trailingPE", "N/A"),
+            "market_cap": info.get("marketCap", "N/A"),
+            "day_low": info.get("dayLow", "N/A"),
+            "day_high": info.get("dayHigh", "N/A"),
+            "volume": info.get("volume", "N/A"),
+            "52_week_high": info.get("fiftyTwoWeekHigh", "N/A"),
+            "52_week_low": info.get("fiftyTwoWeekLow", "N/A"),
+            "recent_close_prices": hist['Close'].tail(3).to_list()
+        }
+
+        return data
+    except Exception as e:
+        return {"error": str(e)}