Update app.py

app.py

@@ -1,7 +1,273 @@
 import gradio as gr
+import yfinance as yf
+import pandas as pd
+import requests
+import json
+from datetime import datetime, timedelta
+import plotly.graph_objects as go
+import plotly.express as px
 
-def greet(name):
-    return "Hello " + name + "!!"
+# Tool 1: Get Stock Price
+def get_stock_price(symbol):
+    """Get real-time stock price and basic info"""
+    try:
+        stock = yf.Ticker(symbol.upper())
+        hist = stock.history(period="1d")
+        info = stock.info
+        
+        if hist.empty:
+            return f"Error: Could not find stock data for {symbol}"
+        
+        current_price = hist['Close'].iloc[-1]
+        prev_close = info.get('previousClose', hist['Close'].iloc[-1])
+        change = current_price - prev_close
+        change_percent = (change / prev_close) * 100
+        
+        result = f"""
+📈 **{symbol.upper()} Stock Price**
+💰 Current Price: ${current_price:.2f}
+📊 Change: ${change:.2f} ({change_percent:+.2f}%)
+📅 Previous Close: ${prev_close:.2f}
+🏢 Company: {info.get('longName', 'N/A')}
+📈 Market Cap: ${info.get('marketCap', 0):,}
+        """
+        return result
+    except Exception as e:
+        return f"Error fetching stock price for {symbol}: {str(e)}"
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()
+# Tool 2: Get Stock Fundamentals
+def get_stock_fundamentals(symbol):
+    """Get fundamental analysis data"""
+    try:
+        stock = yf.Ticker(symbol.upper())
+        info = stock.info
+        
+        # Key fundamental metrics
+        pe_ratio = info.get('trailingPE', 'N/A')
+        forward_pe = info.get('forwardPE', 'N/A')
+        price_to_book = info.get('priceToBook', 'N/A')
+        debt_to_equity = info.get('debtToEquity', 'N/A')
+        roe = info.get('returnOnEquity', 'N/A')
+        profit_margin = info.get('profitMargins', 'N/A')
+        revenue_growth = info.get('revenueGrowth', 'N/A')
+        
+        # Format percentages
+        if isinstance(roe, (int, float)):
+            roe = f"{roe*100:.2f}%"
+        if isinstance(profit_margin, (int, float)):
+            profit_margin = f"{profit_margin*100:.2f}%"
+        if isinstance(revenue_growth, (int, float)):
+            revenue_growth = f"{revenue_growth*100:.2f}%"
+        
+        result = f"""
+🔍 **{symbol.upper()} Fundamental Analysis**
+
+📊 **Valuation Metrics:**
+• P/E Ratio: {pe_ratio}
+• Forward P/E: {forward_pe}
+• Price-to-Book: {price_to_book}
+
+💰 **Financial Health:**
+• Debt-to-Equity: {debt_to_equity}
+• Return on Equity: {roe}
+• Profit Margin: {profit_margin}
+• Revenue Growth: {revenue_growth}
+
+🏢 **Company Info:**
+• Sector: {info.get('sector', 'N/A')}
+• Industry: {info.get('industry', 'N/A')}
+• Employees: {info.get('fullTimeEmployees', 'N/A'):,}
+• Market Cap: ${info.get('marketCap', 0):,}
+        """
+        return result
+    except Exception as e:
+        return f"Error fetching fundamentals for {symbol}: {str(e)}"
+
+# Tool 3: Compare Stocks
+def compare_stocks(symbol1, symbol2, symbol3=""):
+    """Compare 2-3 stocks side by side"""
+    try:
+        symbols = [s.upper().strip() for s in [symbol1, symbol2, symbol3] if s.strip()]
+        
+        if len(symbols) < 2:
+            return "Please provide at least 2 stock symbols"
+        
+        comparison_data = []
+        
+        for symbol in symbols:
+            stock = yf.Ticker(symbol)
+            info = stock.info
+            hist = stock.history(period="1d")
+            
+            if not hist.empty:
+                current_price = hist['Close'].iloc[-1]
+                comparison_data.append({
+                    'Symbol': symbol,
+                    'Company': info.get('longName', 'N/A')[:30],
+                    'Price': f"${current_price:.2f}",
+                    'P/E Ratio': info.get('trailingPE', 'N/A'),
+                    'Market Cap': f"${info.get('marketCap', 0)/1e9:.1f}B",
+                    'Sector': info.get('sector', 'N/A'),
+                    'ROE': f"{info.get('returnOnEquity', 0)*100:.1f}%" if info.get('returnOnEquity') else 'N/A'
+                })
+        
+        if not comparison_data:
+            return "Could not fetch data for any of the provided symbols"
+        
+        # Create comparison table
+        result = "📊 **Stock Comparison**\n\n"
+        result += "| Metric | " + " | ".join([data['Symbol'] for data in comparison_data]) + " |\n"
+        result += "|" + "---|" * (len(comparison_data) + 1) + "\n"
+        
+        metrics = ['Company', 'Price', 'P/E Ratio', 'Market Cap', 'Sector', 'ROE']
+        
+        for metric in metrics:
+            result += f"| **{metric}** | "
+            result += " | ".join([str(data.get(metric, 'N/A')) for data in comparison_data])
+            result += " |\n"
+        
+        return result
+        
+    except Exception as e:
+        return f"Error comparing stocks: {str(e)}"
+
+# Tool 4: AI-Powered Investment Analysis
+def analyze_stock_ai(symbol, analysis_type="comprehensive"):
+    """AI-powered investment insights"""
+    try:
+        stock = yf.Ticker(symbol.upper())
+        info = stock.info
+        hist = stock.history(period="3mo")  # 3 months of data
+        
+        if hist.empty:
+            return f"Could not fetch data for {symbol}"
+        
+        # Calculate technical indicators
+        current_price = hist['Close'].iloc[-1]
+        price_change_3m = ((current_price - hist['Close'].iloc[0]) / hist['Close'].iloc[0]) * 100
+        avg_volume = hist['Volume'].mean()
+        volatility = hist['Close'].pct_change().std() * 100
+        
+        # Get fundamental data
+        pe_ratio = info.get('trailingPE', 0)
+        market_cap = info.get('marketCap', 0)
+        sector = info.get('sector', 'Unknown')
+        
+        # AI Analysis Logic
+        analysis = f"""
+🤖 **AI Investment Analysis for {symbol.upper()}**
+
+📈 **Technical Analysis:**
+• 3-Month Performance: {price_change_3m:+.2f}%
+• Current Price: ${current_price:.2f}
+• Volatility: {volatility:.2f}%
+• Average Volume: {avg_volume:,.0f}
+
+🎯 **Investment Signals:**
+"""
+        
+        # Simple AI-like decision logic
+        signals = []
+        
+        if price_change_3m > 10:
+            signals.append("🟢 Strong upward momentum")
+        elif price_change_3m > 0:
+            signals.append("🟡 Positive trend")
+        else:
+            signals.append("🔴 Declining trend")
+            
+        if pe_ratio and 10 < pe_ratio < 25:
+            signals.append("🟢 Reasonable valuation")
+        elif pe_ratio and pe_ratio > 30:
+            signals.append("🟡 High valuation - growth expected")
+        elif pe_ratio and pe_ratio < 10:
+            signals.append("🟡 Low valuation - value opportunity")
+            
+        if volatility < 20:
+            signals.append("🟢 Low volatility - stable")
+        elif volatility > 40:
+            signals.append("🔴 High volatility - risky")
+            
+        for signal in signals:
+            analysis += f"\n• {signal}"
+            
+        # Risk Assessment
+        risk_level = "Low"
+        if volatility > 30 or (pe_ratio and pe_ratio > 40):
+            risk_level = "High"
+        elif volatility > 20 or (pe_ratio and pe_ratio > 25):
+            risk_level = "Medium"
+            
+        analysis += f"""
+
+⚠️ **Risk Assessment:** {risk_level}
+🏢 **Sector:** {sector}
+💼 **Market Cap:** ${market_cap/1e9:.1f}B
+
+📝 **AI Recommendation:**
+Based on technical and fundamental analysis, this stock shows {signals[0].split()[1]} characteristics. 
+Consider your risk tolerance and portfolio diversification before making investment decisions.
+
+⚠️ *This is AI-generated analysis for educational purposes only. Not financial advice.*
+        """
+        
+        return analysis
+        
+    except Exception as e:
+        return f"Error in AI analysis for {symbol}: {str(e)}"
+
+# Create Gradio Interface
+def create_interface():
+    with gr.Blocks(title="Financial Analyst MCP Tools", theme=gr.themes.Soft()) as demo:
+        gr.Markdown("# 🏦 Financial Analyst - MCP Tools")
+        gr.Markdown("Professional stock analysis tools powered by real-time data and AI insights")
+        
+        with gr.Tabs():
+            # Tool 1: Stock Price
+            with gr.Tab("📈 Stock Price"):
+                gr.Markdown("### Get Real-time Stock Price")
+                with gr.Row():
+                    price_input = gr.Textbox(label="Stock Symbol", placeholder="e.g., AAPL, TSLA, GOOGL")
+                    price_btn = gr.Button("Get Price", variant="primary")
+                price_output = gr.Markdown()
+                price_btn.click(get_stock_price, inputs=price_input, outputs=price_output)
+            
+            # Tool 2: Fundamentals
+            with gr.Tab("🔍 Fundamentals"):
+                gr.Markdown("### Stock Fundamental Analysis")
+                with gr.Row():
+                    fund_input = gr.Textbox(label="Stock Symbol", placeholder="e.g., AAPL, MSFT")
+                    fund_btn = gr.Button("Analyze Fundamentals", variant="primary")
+                fund_output = gr.Markdown()
+                fund_btn.click(get_stock_fundamentals, inputs=fund_input, outputs=fund_output)
+            
+            # Tool 3: Compare Stocks
+            with gr.Tab("⚖️ Compare Stocks"):
+                gr.Markdown("### Side-by-side Stock Comparison")
+                with gr.Row():
+                    with gr.Column():
+                        comp_input1 = gr.Textbox(label="Stock 1", placeholder="e.g., AAPL")
+                        comp_input2 = gr.Textbox(label="Stock 2", placeholder="e.g., MSFT")
+                        comp_input3 = gr.Textbox(label="Stock 3 (Optional)", placeholder="e.g., GOOGL")
+                    comp_btn = gr.Button("Compare Stocks", variant="primary")
+                comp_output = gr.Markdown()
+                comp_btn.click(compare_stocks, inputs=[comp_input1, comp_input2, comp_input3], outputs=comp_output)
+            
+            # Tool 4: AI Analysis
+            with gr.Tab("🤖 AI Analysis"):
+                gr.Markdown("### AI-Powered Investment Insights")
+                with gr.Row():
+                    ai_input = gr.Textbox(label="Stock Symbol", placeholder="e.g., NVDA, AMD")
+                    ai_btn = gr.Button("AI Analysis", variant="primary")
+                ai_output = gr.Markdown()
+                ai_btn.click(analyze_stock_ai, inputs=ai_input, outputs=ai_output)
+        
+        gr.Markdown("---")
+        gr.Markdown("*⚠️ Disclaimer: This tool provides educational information only. Not financial advice. Always consult with financial professionals before making investment decisions.*")
+    
+    return demo
+
+# Launch the app
+if __name__ == "__main__":
+    demo = create_interface()
+    demo.launch()