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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) | |