pip install dspy langchain langchain-community yfinance

import dspy
from langchain_community.tools.yahoo_finance_news import YahooFinanceNewsTool
from dspy.adapters.types.tool import Tool
import json
import yfinance as yf

# Configure DSPy
lm = dspy.LM(model='openai/gpt-4o-mini')
dspy.configure(lm=lm, allow_tool_async_sync_conversion=True)

# Convert LangChain Yahoo Finance tool to DSPy
yahoo_finance_tool = YahooFinanceNewsTool()
finance_news_tool = Tool.from_langchain(yahoo_finance_tool)

def get_stock_price(ticker: str) -> str:
    """Get current stock price and basic info."""
    try:
        stock = yf.Ticker(ticker)
        info = stock.info
        hist = stock.history(period="1d")
        
        if hist.empty:
            return f"Could not retrieve data for {ticker}"
        
        current_price = hist['Close'].iloc[-1]
        prev_close = info.get('previousClose', current_price)
        change_pct = ((current_price - prev_close) / prev_close * 100) if prev_close else 0
        
        result = {
            "ticker": ticker,
            "price": round(current_price, 2),
            "change_percent": round(change_pct, 2),
            "company": info.get('longName', ticker)
        }
        
        return json.dumps(result)
    except Exception as e:
        return f"Error: {str(e)}"

def compare_stocks(tickers: str) -> str:
    """Compare multiple stocks (comma-separated)."""
    try:
        ticker_list = [t.strip().upper() for t in tickers.split(',')]
        comparison = []
        
        for ticker in ticker_list:
            stock = yf.Ticker(ticker)
            info = stock.info
            hist = stock.history(period="1d")
            
            if not hist.empty:
                current_price = hist['Close'].iloc[-1]
                prev_close = info.get('previousClose', current_price)
                change_pct = ((current_price - prev_close) / prev_close * 100) if prev_close else 0
                
                comparison.append({
                    "ticker": ticker,
                    "price": round(current_price, 2),
                    "change_percent": round(change_pct, 2)
                })
        
        return json.dumps(comparison)
    except Exception as e:
        return f"Error: {str(e)}"

class FinancialAnalysisAgent(dspy.Module):
    """ReAct agent for financial analysis using Yahoo Finance data."""
    
    def __init__(self):
        super().__init__()
        
        # Combine all tools
        self.tools = [
            finance_news_tool,  # LangChain Yahoo Finance News
            get_stock_price,
            compare_stocks
        ]
        
        # Initialize ReAct
        self.react = dspy.ReAct(
            signature="financial_query -> analysis_response",
            tools=self.tools,
            max_iters=6
        )
    
    def forward(self, financial_query: str):
        return self.react(financial_query=financial_query)

def run_financial_demo():
    """Demo of the financial analysis agent."""
    
    # Initialize agent
    agent = FinancialAnalysisAgent()
    
    # Example queries
    queries = [
        "What's the latest news about Apple (AAPL) and how might it affect the stock price?",
        "Compare AAPL, GOOGL, and MSFT performance",
        "Find recent Tesla news and analyze sentiment"
    ]
    
    for query in queries:
        print(f"Query: {query}")
        response = agent(financial_query=query)
        print(f"Analysis: {response.analysis_response}")
        print("-" * 50)

# Run the demo
if __name__ == "__main__":
    run_financial_demo()

Analysis: Given the current price of Apple (AAPL) at $196.58 and the slight increase of 0.48%, it appears that the stock is performing steadily in the market. However, the inability to access the latest news means that any significant developments that could influence investor sentiment and stock price are unknown. Investors should keep an eye on upcoming announcements or market trends that could impact Apple's performance, especially in comparison to other tech stocks like Microsoft (MSFT), which is also showing a positive trend.