app.py

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

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:
        # Get last 10 days of data
        last_10_days = df.tail(10)
        
        # Format data for prompt
        data_str = "this is the last 10 days data for nifty index, Open\tHigh\tLow\tClose\n"
        for _, row in last_10_days.iterrows():
            data_str += f"{row['Open']}\t{row['High']}\t{row['Low']}\t{row['Close']}\n"
        
        data_str += "so i need you to give me the setup for today by priceaction levels"
        
        # Mistral API endpoint
        url = "https://api.mistral.ai/v1/chat/completions"
        
        headers = {
            "Content-Type": "application/json",
            "Authorization": f"Bearer {os.environ.get('MISTRAL_API_KEY')}"
        }
        
        data = {
            "model": "mistral-tiny",
            "messages": [{"role": "user", "content": data_str}]
        }
        
        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():
    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:
    gr.Markdown("# NIFTY 50 Analysis with Mistral AI")
    gr.Markdown("Displays the last 15 days of trading data and AI analysis for NIFTY 50 index")
    
    # Add refresh button
    refresh_btn = gr.Button("Refresh Data and Analysis")
    
    # Add outputs
    with gr.Row():
        with gr.Column():
            gr.Markdown("### Historical Data")
            output_table = gr.Dataframe()
        
        with gr.Column():
            gr.Markdown("### Mistral AI Analysis")
            analysis_output = gr.Textbox(label="Price Action Analysis", lines=10)
    
    # 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],
    )

demo.launch()