Update app.py

- Remove save document button
- Modification of the prompt

app.py

@@ -67,28 +67,6 @@ def construct_index(doc):
   return index
 
 
-def upload_doc(file):
-    # Open the PDF file in binary mode
-    with open(file.name, 'rb') as f:
-        # Initialize a PDF file reader object
-        pdf_reader = PdfReader(f)
-
-        # Initialize an empty string for storing the extracted text
-        text = ''
-
-        # Loop through the number of pages
-        for page in pdf_reader.pages:
-            # Add the text from each page to the text string
-            text += page.extract_text()
-        
-        index = construct_index([Document(text)])
-  
-        # Save index to Azure blob storage
-        file_name = os.path.basename(file.name)
-        index.storage_context.persist(f'gpt/storage_demo/{file_name}', fs=fs)
-
-        return ''
-
 def extract_text(file):
     # Open the PDF file in binary mode
     with open(file.name, 'rb') as f:
@@ -133,7 +111,7 @@ def ask_ai_upload(doc, question):
   
   # Define the query & the querying method
   query_engine = index.as_query_engine(optimizer=SentenceEmbeddingOptimizer(percentile_cutoff=0.8), similarity_top_k=7) 
-  query = 'Answer the question truthfully based on the text provided. Include verbatim quote and after the quote write a step by step explanation. Use bullet points. Provide an answer as detailed and precise as possible. The task is:' + str(question)  
+  query = 'Answer the question truthfully based on the text provided. Use bullet points. After each quote, write a step by step explanation. Provide an answer as detailed and precise as possible. The task is:' + str(question)
   response = query_engine.query(query)
 
   return response.response
@@ -158,7 +136,7 @@ def ask_ai_choose(doc, question):
   
   # Define the query & the querying method
   query_engine = index.as_query_engine(optimizer=SentenceEmbeddingOptimizer(percentile_cutoff=0.8), similarity_top_k=7) 
-  query = 'Answer the question truthfully based on the text provided. Include verbatim quote and after the quote write a step by step explanation. Use bullet points. Provide an answer as detailed and precise as possible. The task is:' + str(question)
+  query = 'Answer the question truthfully based on the text provided. Use bullet points. After each quote, write a step by step explanation. Provide an answer as detailed and precise as possible. The task is:' + str(question)
   response = query_engine.query(query)
 
   return response.response
@@ -191,14 +169,12 @@ with gr.Blocks(theme=theme) as demo:
 
     with gr.Tab("Upload a document & ask a question 📥"):
       upload_file = gr.inputs.File(label="Upload your PDF document")
-      upload_button = gr.Button("Save the document in Ardian Knowledge Library")
       output = gr.Textbox(label='Output', visible=False)
       chatbot = gr.Chatbot()
       question = gr.Textbox(label='Question', info="Please write your question here.")
       clear = gr.Button("Clear")
 
       question.submit(respond_document_upload, [question, chatbot, upload_file], [question, chatbot])
-      upload_button.click(upload_doc, inputs=upload_file, outputs=output)
       clear.click(lambda: None, None, chatbot, queue=False)
         
     with gr.Tab("Choose a document & ask a question 📚"):