Update app.py

app.py

@@ -231,13 +231,11 @@ questions = [
     "what is the dependent variable in this study?",
 ]
 
-def mask_key(key):
-    return '*' * len(key)
-    
+
 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."""
+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([Page No.]) 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: 1200; }""") as demo:
 
@@ -248,7 +246,6 @@ with gr.Blocks(css="""#chatbot { font-size: 14px; min-height: 1200; }""") as dem
         
         with gr.Group():
             gr.Markdown(f'<p style="text-align:center">Get your Open AI API key <a href="https://platform.openai.com/account/api-keys">here</a></p>')
-            openAI_key = gr.Textbox(label='Enter your OpenAI API key here', preprocess=mask_key)
             url = gr.Textbox(label='Enter PDF URL here   (Example: https://arxiv.org/pdf/1706.06722.pdf )')
             gr.Markdown("<center><h4>OR<h4></center>")
             file = gr.File(label='Upload your PDF/ Research Paper / Book here', file_types=['.pdf'])
@@ -272,9 +269,10 @@ with gr.Blocks(css="""#chatbot { font-size: 14px; min-height: 1200; }""") as dem
             btn.style(full_width=True)
 
         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=50, elem_id="chatbot")
-            
+
+        with gr.Accordion("API Key"):
+            openAI_key = gr.Textbox(label='Enter your OpenAI API key here', password=True)
 
     # Bind the click event of the button to the question_answer function
     btn.click(
@@ -285,3 +283,4 @@ with gr.Blocks(css="""#chatbot { font-size: 14px; min-height: 1200; }""") as dem
 
 demo.launch()
 
+