updated

app.py

@@ -1,26 +1,21 @@
-# app.py at the root of your project
+# app.py at the root
 import gradio as gr
-import joblib
-from src.preprocess import clean_text
+from src.predict import chatbot_response
 
-# Load trained model and responses
-model = joblib.load("models/lms_chatbot.joblib")
-responses = joblib.load("models/responses.joblib")
+# Keep conversation history
+history = []
 
-def chatbot_response(user_input):
-    """Predict the tag and return the corresponding response."""
-    clean_input = clean_text(user_input)
-    tag = model.predict([clean_input])[0]
-    return responses.get(tag, ["Sorry, I don't understand."])[0]
+def chat(user_input):
+    global history
+    response = chatbot_response(user_input)
+    history.append(("You", user_input))
+    history.append(("Bot", response))
+    return history, history
 
-# Gradio interface
-demo = gr.Interface(
-    fn=chatbot_response,
-    inputs=gr.Textbox(lines=2, placeholder="Type your message here..."),
-    outputs="text",
-    title="LMS Chatbot",
-    description="Ask anything about LMS and get automated responses."
-)
+# Gradio Chat Interface
+demo = gr.ChatInterface(fn=chat, 
+                        title="LMS Chatbot", 
+                        description="Chat with the LMS Chatbot", 
+                        height=600)
 
-if __name__ == "__main__":
-    demo.launch()
+demo.launch()