Update app.py

app.py

@@ -1,3 +1,53 @@
-# Load model directly
-from transformers import AutoModel
-model = AutoModel.from_pretrained("Omartificial-Intelligence-Space/Arabic-QWQ-32B-Preview")
+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)