Update app.py

app.py

@@ -2,19 +2,12 @@ import gradio as gr
 import pandas as pd
 from sentence_transformers import SentenceTransformer, util
 
-# Load FAQ data from a CSV file containing questions and answers
-try:
-    faq_df = pd.read_csv("lic_faq.csv", encoding="utf-8")
-except UnicodeDecodeError:
-    faq_df = pd.read_csv("lic_faq.csv", encoding="ISO-8859-1")
-
-# Initialize the SentenceTransformer model for semantic text similarity
+# Load FAQ
+faq_df = pd.read_csv("lic_faq.csv")
 model = SentenceTransformer('all-MiniLM-L6-v2')
-
-# Convert FAQ questions into embeddings for similarity comparison
 faq_embeddings = model.encode(faq_df['question'].tolist(), convert_to_tensor=True)
 
-# Define policy suggestions to recommend based on keywords in the user query
+# Policy recommendations
 policy_suggestions = {
     "term": "💡 You might consider LIC Tech Term Plan for pure protection at low cost.",
     "money back": "💡 LIC Money Back Policy is great for periodic returns along with insurance.",
@@ -23,11 +16,10 @@ policy_suggestions = {
     "pension": "💡 LIC Jeevan Akshay and PM Vaya Vandana Yojana are best for pension seekers."
 }
 
-# Chatbot function to process user queries and generate responses
 def chatbot(history, query):
     query_lower = query.lower().strip()
 
-    # Handle common greetings with a friendly response
+    # Handle greetings
     if query_lower in ["hi", "hello", "hey", "good morning", "good evening"]:
         response = "👋 Hello! I’m your LIC Assistant. Ask me anything about policies, claims, onboarding, or commission."
     else:
@@ -41,230 +33,31 @@ def chatbot(history, query):
         else:
             response = faq_df.iloc[best_idx]['answer']
 
-            for keyword, suggestion in policy_suggestions.items():
-                if keyword in query_lower:
-                    response += f"\n\n{suggestion}"
-                    break
+        for keyword, suggestion in policy_suggestions.items():
+            if keyword in query_lower:
+                response += f"\n\n{suggestion}"
+                break
 
     history.append((query, response))
     return history, history
 
-# Custom CSS for a normal chatbot visual design with adjusted bubbles
-custom_css = """
-/* General container styling */
-.gradio-container {
-    font-family: 'Arial', sans-serif;
-    background: linear-gradient(135deg, #f5f7fa 0%, #c3cfe2 100%);
-    min-height: 100vh;
-    padding: 0;
-    margin: 0;
-    font-size: 14px;
-}
-
-/* Header styling */
-h1 {
-    color: #2c3e50 !important;
-    font-size: 24px !important;
-    text-align: center;
-    margin: 15px 0;
-    text-shadow: none;
-}
-
-p {
-    color: #34495e !important;
-    font-size: 14px !important;
-    text-align: center;
-    margin-bottom: 15px;
-}
-
-/* Chatbot container */
-.chatbot {
-    border-radius: 8px !important;
-    box-shadow: 0 2px 10px rgba(0,0,0,0.1) !important;
-    background: #ffffff !important;
-    padding: 10px !important;
-    max-width: 800px !important;
-    margin: 0 auto !important;
-    height: 70vh !important;
-    overflow-y: auto !important;
-    display: block;
-    box-sizing: border-box !important; /* Ensure consistent sizing */
-}
-
-/* Chat bubbles: Normal design without border */
-.chatbot .bubble {
-    border: none !important; /* Explicitly remove border */
-    border-radius: 8px !important;
-    padding: 6px 10px !important; /* Reduced padding */
-    margin: 5px 0 !important;
-    max-width: 70% !important;
-    font-size: 14px !important;
-    min-height: 20px !important; /* Reduced minimum height */
-    min-width: 50px !important; /* Reduced minimum width */
-    word-wrap: break-word !important;
-    line-height: 1.4 !important;
-    color: #2c3e50 !important;
-    box-sizing: border-box !important; /* Include padding in size */
-}
-
-/* User bubble: Right-aligned, light blue */
-.chatbot .bubble:nth-child(odd) {
-    background: #3498db !important;
-    color: #ffffff !important;
-    margin-left: auto !important;
-    align-self: flex-end !important;
-}
-
-/* Bot bubble: Left-aligned, light gray */
-.chatbot .bubble:nth-child(even) {
-    background: #ecf0f1 !important;
-    margin-right: auto !important;
-    align-self: flex-start !important;
-}
-
-/* Input area */
-.gradio-row:last-child {
-    width: 100% !important;
-    max-width: 800px !important;
-    margin: 10px auto !important;
-    padding: 10px !important;
-    display: flex !important;
-    align-items: center !important;
-    background: transparent !important;
-    box-sizing: border-box !important;
-}
-
-/* Textbox styling */
-input[type="text"] {
-    border: 1px solid #bdc3c7 !important;
-    border-radius: 4px !important;
-    padding: 8px 12px !important;
-    font-size: 14px !important;
-    box-shadow: 0 1px 3px rgba(0,0,0,0.1) !important;
-    flex-grow: 1 !important;
-    margin-right: 10px !important;
-    color: #2c3e50 !important;
-    box-sizing: border-box !important;
-}
-
-input[type="text"]::placeholder {
-    color: #7f8c8d !important;
-    font-size: 14px !important;
-}
-
-input[type="text"]:focus {
-    border-color: #3498db !important;
-    outline: none !important;
-}
-
-/* Send button */
-button {
-    border-radius: 4px !important;
-    background: #3498db !important;
-    color: white !important;
-    padding: 8px 20px !important;
-    font-size: 14px !important;
-    border: none !important;
-    min-width: 80px !important;
-    transition: background 0.3s ease !important;
-    text-align: center !important;
-    box-sizing: border-box !important;
-}
-
-button:hover {
-    background: #2980b9 !important;
-}
-
-/* Clear button */
-button[aria-label="Clear Chat"] {
-    background: #bdc3c7 !important;
-    padding: 6px 15px !important;
-    font-size: 14px !important;
-    min-width: 90px !important;
-    margin-top: 10px !important;
-    align-self: center !important;
-    color: #ffffff !important;
-    box-sizing: border-box !important;
-}
-
-button[aria-label="Clear Chat"]:hover {
-    background: #95a5a6 !important;
-}
-
-/* Scrollbar styling */
-.chatbot::-webkit-scrollbar {
-    width: 6px;
-}
-
-.chatbot::-webkit-scrollbar-track {
-    background: #f5f7fa;
-}
-
-.chatbot::-webkit-scrollbar-thumb {
-    background: #3498db;
-    border-radius: 3px;
-}
-
-.chatbot::-webkit-scrollbar-thumb:hover {
-    background: #2980b9;
-}
-
-/* Mobile-specific adjustments */
-@media (max-width: 768px) {
-    .chatbot {
-        max-width: 100% !important;
-        height: 65vh !important;
-        margin: 0 !important;
-    }
-    .gradio-row:last-child {
-        max-width: 100% !important;
-        padding: 5px !important;
-    }
-    input[type="text"] {
-        padding: 6px 10px !important;
-    }
-    button {
-        padding: 6px 15px !important;
-    }
-}
-"""
-
-with gr.Blocks(title="LIC Agent Chatbot", css=custom_css) as demo:
+with gr.Blocks(title="LIC Agent Chatbot") as demo:
     gr.Markdown(
-        "<h1>🧑‍💼 LIC Agent Assistant</h1>"
-        "<p>Ask me anything about policies, claims, commissions, onboarding, and KYC.</p>"
+        "<h1 style='text-align:center;color:#0D47A1;'>🧑‍💼 LIC Agent Assistant</h1>"
+        "<p style='text-align:center;'>Ask me anything about policies, claims, commissions, onboarding, and KYC.</p>"
     )
 
-    chatbot_ui = gr.Chatbot(
-        label="LIC Assistant",
-        height=600,
-        bubble_full_width=False,
-        avatar_images=("🧑", "🤖"),
-        show_copy_button=True
-    )
+    chatbot_ui = gr.Chatbot(label="LIC Assistant", height=450, bubble_full_width=False, avatar_images=("🧑", "🤖"))
 
     with gr.Row():
-        msg = gr.Textbox(
-            placeholder="Type your question here...",
-            show_label=False,
-            scale=8,
-            elem_classes="chat-input"
-        )
+        msg = gr.Textbox(placeholder="Ask your question here...", show_label=False, scale=8)
         send = gr.Button("Send", variant="primary", scale=2)
 
-    clear = gr.Button("Clear Chat", variant="secondary")
+    clear = gr.Button("Clear Chat")
 
     state = gr.State([])
 
-    # Send message on Enter key and clear textbox
-    def send_message(history, query):
-        if query:
-            history, _ = chatbot(history, query)
-            return history, ""
-        return history, query
-
-    send.click(fn=send_message, inputs=[state, msg], outputs=[chatbot_ui, msg])
-    msg.submit(fn=send_message, inputs=[state, msg], outputs=[chatbot_ui, msg])
+    send.click(fn=chatbot, inputs=[state, msg], outputs=[chatbot_ui, state])
     clear.click(lambda: ([], []), None, [chatbot_ui, state], queue=False)
 
-demo.launch()
+demo.launch()