updated

app.py

@@ -1,50 +1,70 @@
-import streamlit as st
+import gradio as gr
 import joblib
 from src.preprocess import clean_text
-import time
+import datetime
 
-# Load trained model & responses
+# Load model & responses
 model = joblib.load("models/lms_chatbot.joblib")
 responses = joblib.load("models/responses.joblib")
 
-# Initialize session state
-if "messages" not in st.session_state:
-    st.session_state.messages = []
+# Keep conversation history
+history = []
 
-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!")
-
-# Function to generate bot response
 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]
-    return bot_reply
-
-# 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})
-    
-    # Typing animation for bot
-    bot_reply = chatbot_response(user_input)
-    display_text = ""
-    st.session_state.messages.append({"sender": "bot", "content": ""})  # placeholder
-
-    bot_index = len(st.session_state.messages) - 1
-    for char in bot_reply:
-        display_text += char
-        st.session_state.messages[bot_index]["content"] = display_text
-        time.sleep(0.03)  # adjust typing speed
-        st.experimental_rerun()  # refresh chat to show animation
-
-# 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()