Update app.py

app.py

@@ -1,53 +1,8 @@
-from flask import Flask, request, jsonify
+# Use a pipeline as a high-level helper
 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)
+messages = [
+    {"role": "user", "content": "Who are you?"},
+]
+pipe = pipeline("text-generation", model="JackCloudman/Phi-4-jackterated", trust_remote_code=True)
+pipe(messages)