Update app.py

app.py

@@ -36,26 +36,21 @@ 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")
+pdf_input = [gr.inputs.File(label="PDF File"),gr.inputs.Textbox(label="Question:"), gr.inputs.Dropdown(choices=["minilm-uncased-squad2","roberta-base-squad2"],label="Model")]
 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], outputs=outputs, examples=[['What are the strategic initiatives?',
-                                'samples/walmart-10k.pdf'],
-                               ['What efforts are being made in regards to digital experiences?',
-                                'samples/walmart-10k.pdf'],
-                               ["How much does the company grow?",
-                                'samples/walmart-10k.pdf'],
-                               ['What are the strategic initiatives?',
-                                'samples/pfizer-10k.pdf'],
-                               ['What efforts are being made in regards to digital experiences?',
-                                'samples/pfizer-10k.pdf'],
-                               ["How much does the company grow?",
-                                'samples/pfizer-10k.pdf'], ])
+interface = gr.Interface(fn=pdf_to_text, inputs=[pdf_input, query_input], outputs=outputs)
 
 # Run the interface
 interface.launch(debug = True)