updated

app.py

@@ -1,70 +1,120 @@
-import gradio as gr
+# import gradio as gr
+# import joblib
+# from src.preprocess import clean_text
+# import datetime
+
+# # Load model & responses
+# model = joblib.load("models/lms_chatbot.joblib")
+# responses = joblib.load("models/responses.joblib")
+
+# # Keep conversation history
+# history = []
+
+# def chatbot_response(user_input):
+#     if not user_input.strip():
+#         return ""
+
+#     # Add user message
+#     timestamp = datetime.datetime.now().strftime("%H:%M")
+#     history.append({
+#         "sender": "You",
+#         "message": user_input,
+#         "time": timestamp,
+#         "color": "#DCF8C6",
+#         "align": "right"
+#     })
+
+#     # Bot prediction
+#     tag = model.predict([clean_text(user_input)])[0]
+#     bot_reply = responses.get(tag, ["Sorry, I don't understand."])[0]
+
+#     # Add bot message
+#     timestamp = datetime.datetime.now().strftime("%H:%M")
+#     history.append({
+#         "sender": "Bot",
+#         "message": bot_reply,
+#         "time": timestamp,
+#         "color": "#FFFFFF",
+#         "align": "left"
+#     })
+
+#     # Render chat
+#     return render_chat()
+
+# def render_chat():
+#     chat_html = """
+#     <div style="font-family:Helvetica, Arial; background:#F0F0F0; padding:15px; height:400px; overflow-y:auto; border-radius:10px; border:1px solid #ccc;">
+#     """
+#     for msg in history:
+#         chat_html += f"""
+#         <div style="text-align:{msg['align']}; margin:8px 0;">
+#             <div style="display:inline-block; background:{msg['color']}; padding:10px 15px; border-radius:20px; max-width:70%; box-shadow:0 2px 5px rgba(0,0,0,0.2);">
+#                 {msg['message']}<br>
+#                 <span style="font-size:10px; color:gray; float:right;">{msg['time']}</span>
+#             </div>
+#         </div>
+#         """
+#     chat_html += "</div>"
+#     return chat_html
+
+# # Gradio interface
+# demo = gr.Interface(
+#     fn=chatbot_response,
+#     inputs=gr.Textbox(lines=2, placeholder="Type your message here...", label="Your Message"),
+#     outputs=gr.HTML(label="Chat"),
+#     title="🟢 LMS Chatbot",
+#     description="Ask anything about your LMS. Automatic reply with chat bubbles and timestamps!"
+# )
+
+# if __name__ == "__main__":
+#     demo.launch()
+
+
+# app.py
+import streamlit as st
 import joblib
 from src.preprocess import clean_text
 import datetime
 
-# Load model & responses
+# Load trained model & responses
 model = joblib.load("models/lms_chatbot.joblib")
 responses = joblib.load("models/responses.joblib")
 
-# Keep conversation history
-history = []
+# Initialize session state for messages
+if "messages" not in st.session_state:
+    st.session_state.messages = []
 
 def chatbot_response(user_input):
+    """Predict tag and generate response."""
     if not user_input.strip():
         return ""
-
-    # Add user message
-    timestamp = datetime.datetime.now().strftime("%H:%M")
-    history.append({
-        "sender": "You",
-        "message": user_input,
-        "time": timestamp,
-        "color": "#DCF8C6",
-        "align": "right"
-    })
-
-    # Bot prediction
+    
     tag = model.predict([clean_text(user_input)])[0]
     bot_reply = responses.get(tag, ["Sorry, I don't understand."])[0]
+    return bot_reply
+
+# Streamlit UI
+st.set_page_config(page_title="🟢 LMS Chatbot", page_icon="🤖")
+st.title("🟢 LMS Chatbot")
+st.markdown("Ask anything about your LMS and get automated responses!")
+
+# User input
+user_input = st.text_input("Type your message here:", key="input")
+
+if user_input:
+    # Append user message
+    st.session_state.messages.append({"sender": "user", "content": user_input})
+    
+    # Get bot response
+    bot_reply = chatbot_response(user_input)
+    st.session_state.messages.append({"sender": "bot", "content": bot_reply})
+
+# Display chat messages
+for msg in st.session_state.messages:
+    if msg["sender"] == "user":
+        with st.chat_message("user"):
+            st.write(msg["content"])
+    else:
+        with st.chat_message("assistant"):
+            st.write(msg["content"])
 
-    # Add bot message
-    timestamp = datetime.datetime.now().strftime("%H:%M")
-    history.append({
-        "sender": "Bot",
-        "message": bot_reply,
-        "time": timestamp,
-        "color": "#FFFFFF",
-        "align": "left"
-    })
-
-    # Render chat
-    return render_chat()
-
-def render_chat():
-    chat_html = """
-    <div style="font-family:Helvetica, Arial; background:#F0F0F0; padding:15px; height:400px; overflow-y:auto; border-radius:10px; border:1px solid #ccc;">
-    """
-    for msg in history:
-        chat_html += f"""
-        <div style="text-align:{msg['align']}; margin:8px 0;">
-            <div style="display:inline-block; background:{msg['color']}; padding:10px 15px; border-radius:20px; max-width:70%; box-shadow:0 2px 5px rgba(0,0,0,0.2);">
-                {msg['message']}<br>
-                <span style="font-size:10px; color:gray; float:right;">{msg['time']}</span>
-            </div>
-        </div>
-        """
-    chat_html += "</div>"
-    return chat_html
-
-# Gradio interface
-demo = gr.Interface(
-    fn=chatbot_response,
-    inputs=gr.Textbox(lines=2, placeholder="Type your message here...", label="Your Message"),
-    outputs=gr.HTML(label="Chat"),
-    title="🟢 LMS Chatbot",
-    description="Ask anything about your LMS. Automatic reply with chat bubbles and timestamps!"
-)
-
-if __name__ == "__main__":
-    demo.launch()