Create app.py

app.py

@@ -0,0 +1,42 @@
+import os
+import requests
+from transformers import pipeline
+from flask import Flask, render_template, request, jsonify
+
+app = Flask(__name__)
+
+# Define model URL and local path
+MODEL_URL = "https://huggingface.co/unsloth/Qwen3-4B-128K-GGUF/resolve/main/Qwen3-4B-128K-UD-IQ1_M.gguf"
+MODEL_PATH = "Qwen3-4B-128K-UD-IQ1_M.gguf"
+
+# Function to download the model
+def download_model():
+    if not os.path.exists(MODEL_PATH):
+        print("Downloading the model...")
+        response = requests.get(MODEL_URL, stream=True)
+        with open(MODEL_PATH, 'wb') as model_file:
+            for chunk in response.iter_content(chunk_size=128):
+                model_file.write(chunk)
+        print("Model downloaded successfully.")
+
+# Load the model with Hugging Face Transformers pipeline
+def load_model():
+    download_model()
+    model = pipeline("text-generation", model=MODEL_PATH)
+    return model
+
+# Global model object
+model = load_model()
+
+@app.route('/')
+def index():
+    return render_template('index.html')
+
+@app.route('/generate', methods=['POST'])
+def generate():
+    user_input = request.form['message']
+    response = model(user_input, max_length=100)
+    return jsonify({"response": response[0]['generated_text']})
+
+if __name__ == '__main__':
+    app.run(debug=True)