Update app.py

app.py

@@ -36,16 +36,25 @@ def pdf_to_text(pdf_file, query):
   qa = VectorDBQA.from_chain_type(llm=OpenAI(), chain_type="stuff", vectorstore=vectorstore)
   return qa.run(query)
 
-
+examples = [
+    [os.path.abspath("NASDAQ_AAPL_2020.pdf"), "how much are the outstanding shares ?"],
+    [os.path.abspath("NASDAQ_AAPL_2020.pdf"), "what is competitors strategy ?"],
+    [os.path.abspath("NASDAQ_AAPL_2020.pdf"), "who is the chief executive officer ?"],
+    [os.path.abspath("NASDAQ_MSFT_2020.pdf"), "How much is the guided revenue for next quarter?"]
+]
       
 
 
 # Define the Gradio interface
-pdf_input = [gr.inputs.File(label="PDF File")]
-query_input = gr.inputs.Textbox(label="Query")
-outputs = gr.outputs.Textbox(label="Chatbot Response")
+#pdf_input = [gr.inputs.File(label="PDF File")]
+#query_input = gr.inputs.Textbox(label="Query")
+#outputs = gr.outputs.Textbox(label="Chatbot Response")
 
-interface = gr.Interface(fn=pdf_to_text, inputs=[pdf_input, query_input])
+interface = gr.Interface(fn=pdf_to_text, 
+                         inputs= [gr.inputs.File(label="input pdf file"), gr.inputs.Textbox(label="Question:")],
+                         outputs =gr.outputs.Textbox(label="Chatbot Response"),
+                         examples = examples,
+                        title="Q/A")
 
 # Run the interface
-interface.launch(debug = True)
+interface.launch(enable_queue = True)