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| import streamlit as st | |
| import pandas as pd | |
| import time | |
| import json | |
| import websocket | |
| from transformers import pipeline | |
| # Initialize a Hugging Face model for text generation | |
| # You can replace with your preferred model on Hugging Face | |
| model = pipeline('text-generation', model='gpt2') # Example GPT model, replace with your custom model | |
| # WebSocket to get real-time data (using Binance WebSocket as an example for BTC/USDT) | |
| def on_message(ws, message): | |
| data = json.loads(message) | |
| price = float(data['k']['c']) # Close price from WebSocket data | |
| signal = get_signal_from_model(price) # Get the signal from the model | |
| update_signal(signal, price) # Update the signal in the Streamlit interface | |
| def on_error(ws, error): | |
| print("Error:", error) | |
| def on_close(ws, close_status_code, close_msg): | |
| print("Closed") | |
| def on_open(ws): | |
| print("Connection established") | |
| # Function to get signal from the model | |
| def get_signal_from_model(price): | |
| # In this example, we are generating a signal based on a price input | |
| # You can replace this with your own model logic or more advanced signal generation | |
| input_text = f"Generate trading signal based on the current price: {price}" | |
| prediction = model(input_text, max_length=50, num_return_sequences=1) | |
| return prediction[0]['generated_text'] | |
| # Streamlit setup | |
| st.title('Crypto Trading Signals with Hugging Face & Streamlit') | |
| # Placeholder to display the signal | |
| signal_placeholder = st.empty() | |
| # Placeholder to display the current price | |
| price_placeholder = st.empty() | |
| # Function to update the signal on Streamlit interface | |
| def update_signal(signal, price): | |
| signal_placeholder.write(f"Signal: {signal}") | |
| price_placeholder.write(f"Current Price: ${price}") | |
| # Embedding TradingView SuperChart in Streamlit | |
| st.markdown(""" | |
| <iframe src="https://www.tradingview.com/chart/?symbol=BINANCE%3ABTCUSDT" | |
| width="100%" height="500px"></iframe> | |
| """, unsafe_allow_html=True) | |
| # WebSocket connection URL for Binance (you can change the symbol here) | |
| ws_url = "wss://stream.binance.com:9443/ws/btcusdt@kline_1s" | |
| # WebSocketApp to fetch real-time data every second | |
| ws = websocket.WebSocketApp(ws_url, | |
| on_message=on_message, | |
| on_error=on_error, | |
| on_close=on_close) | |
| ws.on_open = on_open | |
| # Start WebSocket in a separate thread to allow real-time signal updates | |
| import threading | |
| def start_socket(): | |
| ws.run_forever() | |
| thread = threading.Thread(target=start_socket) | |
| thread.start() | |
| # Run the Streamlit app with real-time updates every 10 seconds | |
| while True: | |
| time.sleep(10) # Update every 10 seconds, adjust as needed for your strategy | |