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| from flask import Flask, request, jsonify, render_template | |
| from huggingface_hub import InferenceClient | |
| import os | |
| # Initialize the Flask app | |
| app = Flask(__name__) | |
| # Initialize the Hugging Face Inference Client | |
| client = InferenceClient("Futuresony/future_ai_12_10_2024.gguf") | |
| def home(): | |
| # Render the HTML template | |
| return render_template("index.html") | |
| def fetch_message(): | |
| data = request.json | |
| message = data.get("text", "") | |
| if not message: | |
| return jsonify({"error": "No input provided."}), 400 | |
| # Define model parameters | |
| model_params = { | |
| "temperature": 0.7, # Controls randomness | |
| "top_p": 0.9, # Nucleus sampling | |
| "max_length": 300, # Limit response length | |
| "do_sample": True # Enable sampling | |
| } | |
| # Process the message using the Hugging Face model | |
| try: | |
| response = client.text_generation( | |
| message, | |
| **model_params # Pass parameters | |
| ) | |
| return jsonify({"response": response}) | |
| except Exception as e: | |
| return jsonify({"error": str(e)}), 500 | |
| if __name__ == "__main__": | |
| # Use PORT environment variable or default to 7860 | |
| port = int(os.getenv("PORT", 7860)) | |
| app.run(host="0.0.0.0", port=port) | |