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chatgptcryptoanalysis
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import gradio as gr
import requests
import pandas as pd
import plotly.graph_objs as go
from transformers import pipeline

# Load ChatGPT model (adjust to use a model supported in Hugging Face Spaces)
chatgpt = pipeline("text-generation", model="gpt2")  # Change "gpt2" to "chatgpt" if available

# Function to fetch and process data from GPT model
def fetch_and_process_data(prompt):
    response = chatgpt(prompt, max_length=200, do_sample=True)[0]['generated_text']
    return response

# Function to fetch historical price data from CoinGecko
def fetch_historical_data(coin_id, from_timestamp, to_timestamp):
    url = f"https://api.coingecko.com/api/v3/coins/{coin_id}/market_chart/range?vs_currency=usd&from={from_timestamp}&to={to_timestamp}"
    response = requests.get(url)
    if response.status_code == 200:
        data = response.json()
        prices = data['prices']
        return prices
    else:
        return f"Error fetching historical data for {coin_id}"

# Function to convert dates to timestamps
def date_to_timestamp(date_str):
    return int(pd.Timestamp(date_str).timestamp())

# Function to plot historical prices using Plotly
def plot_historical_prices(coin_name, from_date, to_date):
    from_timestamp = date_to_timestamp(from_date)
    to_timestamp = date_to_timestamp(to_date)
    
    prices = fetch_historical_data(coin_name, from_timestamp, to_timestamp)
    
    if isinstance(prices, str):  # In case of error
        return prices
    
    df = pd.DataFrame(prices, columns=['timestamp', 'price'])
    df['date'] = pd.to_datetime(df['timestamp'], unit='ms')
    
    fig = go.Figure()
    fig.add_trace(go.Scatter(x=df['date'], y=df['price'], mode='lines', name=coin_name))
    fig.update_layout(title=f'{coin_name.capitalize()} Prices from {from_date} to {to_date}', xaxis_title='Date', yaxis_title='Price (USD)')
    return fig

# Top 100 Cryptocurrencies (by CoinGecko IDs)
top_100_cryptos = [
    'bitcoin', 'ethereum', 'binancecoin', 'ripple', 'solana', 'cardano', 'dogecoin', 'polygon', 'polkadot', 'tron',
    # Add more top coins as necessary
]

# Function to display both ChatGPT response and price chart
def combined_analysis(prompt, coin_name, from_date, to_date):
    # Fetch ChatGPT response
    chatgpt_response = fetch_and_process_data(prompt)
    
    # Fetch and plot historical price data
    price_chart = plot_historical_prices(coin_name, from_date, to_date)
    
    return chatgpt_response, price_chart

# Create Gradio Interface
interface = gr.Interface(
    fn=combined_analysis,
    inputs=[
        gr.Textbox(label="Enter a prompt for ChatGPT"),
        gr.Dropdown(choices=top_100_cryptos, label="Select Cryptocurrency"),
        gr.Textbox(value="2024-01-01", label="From Date (YYYY-MM-DD)"),
        gr.Textbox(value="2025-12-31", label="To Date (YYYY-MM-DD)")
    ],
    outputs=[
        gr.Textbox(label="ChatGPT Response"),
        gr.Plot(label="Cryptocurrency Price Chart")
    ],
    title="ChatGPT and Cryptocurrency Analysis",
    description="This tool provides real-time cryptocurrency analysis and allows you to interact with ChatGPT for insights."
)

# Launch Gradio app
interface.launch(server_name="0.0.0.0")