Update app.py

app.py

@@ -13,14 +13,28 @@ basic_model_url = "https://huggingface.co/anshupatel4298/bert-chatbot-model/reso
 local_model_path = "basic_chatbot_model.h5"
 bert_model_name = "anshupatel4298/bert-chatbot-model/bert_model"
 
-# Download the Basic Model from the URL
+# Define the model architecture
+def create_model():
+    model = tf.keras.Sequential([
+        tf.keras.layers.Dense(128, activation='relu', input_shape=(100,)),  # Adjust input shape accordingly
+        tf.keras.layers.Dropout(0.5),
+        tf.keras.layers.Dense(64, activation='relu'),
+        tf.keras.layers.Dropout(0.5),
+        tf.keras.layers.Dense(10, activation='softmax')  # Adjust the number of classes accordingly
+    ])
+    return model
+
+# Create the model
+basic_model = create_model()
+
+# Download the Basic Model weights from the URL if not already downloaded
 if not os.path.exists(local_model_path):
     response = requests.get(basic_model_url)
     with open(local_model_path, 'wb') as f:
         f.write(response.content)
 
-# Load Basic Model from the local file
-basic_model = tf.keras.models.load_model(local_model_path)
+# Load the weights into the model
+basic_model.load_weights(local_model_path)
 
 # Load BERT Model and Tokenizer
 bert_model = TFBertForSequenceClassification.from_pretrained(bert_model_name)
@@ -51,3 +65,4 @@ if st.button("Send"):
             response = tf.argmax(outputs.logits, axis=-1).numpy()[0]
 
         st.write(f"Bot: {response}")
+