app.py

from flask import Flask, request, jsonify
from transformers import pipeline

# Initialize Flask app
app = Flask(__name__)

# Load the Arabic-QwQ model (using Hugging Face pipeline for simplicity)
model_pipeline = pipeline(
    "text-generation",
    model="Omartificial-Intelligence-Space/Arabic-QWQ-32B-Preview"
)

@app.route('/')
def index():
    """Root endpoint, can serve an HTML form if desired."""
    return """
    <h1>Arabic-QwQ Model Demo</h1>
    <form action="/predict" method="post">
      <label>Enter your prompt:</label><br>
      <input type="text" name="prompt" required><br><br>
      <input type="submit" value="Submit">
    </form>
    """

@app.route('/predict', methods=["POST"])
def predict():
    """
    Route for processing user input with the model.
    - Accepts user input via POST request.
    - Runs inference with Arabic-QwQ model.
    - Returns response.
    """
    try:
        # Extract user input
        user_input = request.form.get("prompt")
        
        # Perform model inference
        output = model_pipeline(user_input, max_length=50, num_return_sequences=1)

        # Return inference results
        return jsonify({
            "input": user_input,
            "response": output[0]['generated_text'] if output else "No response generated"
        })
    
    except Exception as e:
        # Handle errors gracefully
        return jsonify({"error": str(e)}), 500


# Run the app
if __name__ == "__main__":
    app.run(debug=True)