Update app.py

app.py

@@ -38,8 +38,8 @@ template_html = env.get_template('template_html.j2')
 #cross_encoder = CrossEncoder('cross-encoder/ms-marco-MiniLM-L-6-v2') 
 #cross_encoder = CrossEncoder('BAAI/bge-reranker-base')
 # Examples
-examples = ['What is the 4 digit classification heading for Gold jewellery?',
-            'What is the 6 digit classification heading for Mobile phone?',
+examples = ['what is social media and what are rules related to it for expenditure monitoring ,
+            'how many reports to be submitted by Expenditure observer with annexure names ?',
             ]
 
 
@@ -103,7 +103,7 @@ def bot(history, cross_encoder):
 
 with gr.Blocks(theme='Insuz/SimpleIndigo') as demo:
     gr.HTML(value="""<div style="display: flex; align-items: center; justify-content: space-between;">
-    <h1 style="color: #008000">ADWITIYA - <span style="color: #008000">Expenditure Observer AI Assistant</span></h1>
+    <h1 style="color: #008000">NIRVACHANA - <span style="color: #008000">Expenditure Observer AI Assistant</span></h1>
     <img src='logo.png' alt="Chatbot" width="50" height="50" />
     </div>""",elem_id='heading')
     gr.HTML(value="""<p style="font-family: sans-serif; font-size: 16px;">A free chat bot assistant for Expenditure Observers on Compendium on Election Expenditure Monitoring using Open source LLMs. <br> The bot can answer questions in natural language, taking relevant extracts from the ECI document which can be accessed <a href="https://www.eci.gov.in/eci-backend/public/api/download?url=LMAhAK6sOPBp%2FNFF0iRfXbEB1EVSLT41NNLRjYNJJP1KivrUxbfqkDatmHy12e%2Fzk1vx4ptJpQsKYHA87guoLjnPUWtHeZgKtEqs%2FyzfTTYIC0newOHHOjl1rl0u3mJBSIq%2Fi7zDsrcP74v%2FKr8UNw%3D%3D" style="color: #008000; text-decoration: none;">here</a>.</p>""",elem_id='Sub-heading')
@@ -128,7 +128,7 @@ with gr.Blocks(theme='Insuz/SimpleIndigo') as demo:
                 )
         txt_btn = gr.Button(value="Submit text", scale=1)
 
-    cross_encoder = gr.Radio(choices=['MiniLM-L6v2','BGE reranker'], value='MiniLM-L6v2')
+    cross_encoder = gr.Radio(choices=['MiniLM-L6v2','BGE reranker'], value='BGE reranker',label="Embeddings", info="Choose MiniLM for Speed, BGE reranker for accuracy")
 
     prompt_html = gr.HTML()
     # Turn off interactivity while generating if you click