Update app.py

app.py

@@ -236,7 +236,7 @@ recommender = SemanticSearch()
 title = 'PDF GPT Turbo'
 description = """ PDF GPT Turbo allows you to chat with your PDF file using Universal Sentence Encoder and Open AI. It gives hallucination free response than other tools as the embeddings are better than OpenAI. The returned response can even cite the page number in square brackets([]) where the information is located, adding credibility to the responses and helping to locate pertinent information quickly."""
 
-with gr.Blocks(css="""#chatbot { font-size: 14px; min-height: 800; }""") as demo:
+with gr.Blocks(css="""#chatbot { font-size: 14px; min-height: 1200; }""") as demo:
 
     gr.Markdown(f'<center><h1>{title}</h1></center>')
     gr.Markdown(description)
@@ -270,7 +270,7 @@ with gr.Blocks(css="""#chatbot { font-size: 14px; min-height: 800; }""") as demo
 
         with gr.Group():
             #chatbot = gr.Chatbot(placeholder="Chat History", label="Chat History", lines=20, elem_id="chatbot")
-            chatbot = gr.Chatbot(placeholder="Chat History", label="Chat History", lines=35, elem_id="chatbot")
+            chatbot = gr.Chatbot(placeholder="Chat History", label="Chat History", lines=50, elem_id="chatbot")
 
     # Bind the click event of the button to the question_answer function
     btn.click(