app.py

import gradio as gr
import pandas as pd
from datetime import datetime, timedelta
import requests
import json
import os

def verify_api_key():
    api_key = os.environ.get('MISTRAL_API_KEY')
    if not api_key:
        return "ERROR: Mistral API key not found in environment variables"
    return "API key found"

def fetch_nifty_data():
    try:
        end_date = datetime.now()
        start_date = end_date - timedelta(days=15)
        
        url = f"https://query1.finance.yahoo.com/v8/finance/chart/%5ENSEI?period1={int(start_date.timestamp())}&period2={int(end_date.timestamp())}&interval=1d"
        
        headers = {
            'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36'
        }
        
        response = requests.get(url, headers=headers)
        data = response.json()
        
        timestamps = data['chart']['result'][0]['timestamp']
        quote = data['chart']['result'][0]['indicators']['quote'][0]
        
        df = pd.DataFrame({
            'Date': [datetime.fromtimestamp(ts).strftime('%Y-%m-%d') for ts in timestamps],
            'Open': quote['open'],
            'High': quote['high'],
            'Low': quote['low'],
            'Close': quote['close'],
            'Volume': quote['volume']
        })
        
        numeric_columns = ['Open', 'High', 'Low', 'Close']
        df[numeric_columns] = df[numeric_columns].round(2)
        
        return df
    except Exception as e:
        print(f"Error fetching data: {str(e)}")
        return pd.DataFrame()

def get_mistral_analysis(df):
    try:
        api_key = os.environ.get('MISTRAL_API_KEY')
        if not api_key:
            return "Error: Mistral API key not found. Please add it to the environment variables."

        # Get last 10 days of data
        last_10_days = df.tail(10)
        
        # Calculate current price (last close)
        current_price = last_10_days.iloc[-1]['Close']
        
        # Format data for prompt
        data_str = f"""Based on the following NIFTY 50 price data for the last 10 days, provide only support levels, resistance levels, target price, and trading setup. Format exactly as shown below:

Support Levels:
- S1: [price] (brief reason)
- S2: [price] (brief reason)
- S3: [price] (brief reason)

Resistance Levels:
- R1: [price] (brief reason)
- R2: [price] (brief reason)
- R3: [price] (brief reason)

Today's Target Price:
- Target ([direction]): [price] (brief reason)

Trading Setup:
- Direction: [Bullish/Bearish]
- Entry Price Range: [range]
- Stop Loss: [price]
- Risk/Reward Ratio: [ratio]

Current price: {current_price}

Data:
"""
        for _, row in last_10_days.iterrows():
            data_str += f"{row['Date']}: O:{row['Open']} H:{row['High']} L:{row['Low']} C:{row['Close']}\n"

        url = "https://api.mistral.ai/v1/chat/completions"
        
        headers = {
            "Content-Type": "application/json",
            "Authorization": f"Bearer {api_key}"
        }
        
        data = {
            "model": "mistral-small",
            "messages": [
                {"role": "system", "content": "You are a price action trader. Provide only the requested levels and setup information in the exact format specified. Do not add any additional analysis or explanation."},
                {"role": "user", "content": data_str}
            ],
            "temperature": 0.7,
            "max_tokens": 500
        }
        
        response = requests.post(url, headers=headers, json=data)
        
        if response.status_code == 200:
            return response.json()['choices'][0]['message']['content']
        else:
            return f"Error {response.status_code}: {response.text}"
            
    except Exception as e:
        return f"Error getting analysis: {str(e)}"

def show_nifty_data_and_analysis():
    api_status = verify_api_key()
    if api_status.startswith("ERROR"):
        return pd.DataFrame(), api_status
    
    df = fetch_nifty_data()
    analysis = get_mistral_analysis(df) if not df.empty else "Unable to fetch data"
    return df, analysis

# Create Gradio interface
with gr.Blocks() as demo:
    with gr.Column():
        gr.Markdown("# NIFTY 50 Levels and Setup")
        
        # Add refresh button
        refresh_btn = gr.Button("Refresh Data", variant="primary")
        
        # Add outputs
        with gr.Row():
            with gr.Column(scale=1):
                gr.Markdown("### Market Data")
                output_table = gr.Dataframe(
                    headers=["Date", "Open", "High", "Low", "Close", "Volume"],
                    wrap=True
                )
            
            with gr.Column(scale=1):
                gr.Markdown("### Trading Levels")
                analysis_output = gr.Textbox(
                    label="Levels and Setup",
                    lines=15,
                    elem_classes="analysis"
                )
    
    # Set up refresh button click event
    refresh_btn.click(
        fn=show_nifty_data_and_analysis,
        outputs=[output_table, analysis_output],
    )
    
    # Initial load of data
    demo.load(
        fn=show_nifty_data_and_analysis,
        outputs=[output_table, analysis_output],
    )

# Launch the app
demo.launch()