Update app.py

app.py

@@ -10,10 +10,7 @@ from langchain.chains import RetrievalQA # for conversing with chatGPT
 from langchain.chat_models import ChatOpenAI # the LLM model we'll use (ChatGPT)
 from langchain import PromptTemplate
 
-
-
-
-def load_doc(pdf_doc, open_ai_key):
+def load_pdf_and_generate_embeddings(pdf_doc, open_ai_key):
     if openai_key is not None:
         os.environ['OPENAI_API_KEY'] = open_ai_key
         #Load the pdf file
@@ -38,16 +35,18 @@ def load_doc(pdf_doc, open_ai_key):
         PROMPT = PromptTemplate(template=prompt_template, input_variables=["context", "question"])
         chain_type_kwargs = {"prompt": PROMPT}
         pdf_qa = RetrievalQA.from_chain_type(llm=ChatOpenAI(temperature=0, model_name="gpt-4"),chain_type="stuff", retriever=vectordb.as_retriever(), chain_type_kwargs=chain_type_kwargs, return_source_documents=False)
-        
-        
+                
         return "Ready"
     else:
         return "Please provide an OpenAI API key"
+        
 
-
+ 
+    
 def answer_query(query):
     question = query
-    return pdf_qa.run(question)
+    response = "Field Name: field; Question sent to gpt-4: ", question, "Response from gpt-4:",pdf_qa.run(question)
+    return response
 
 css="""
 #col-container {max-width: 700px; margin-left: auto; margin-right: auto;}
@@ -73,8 +72,8 @@ with gr.Blocks(css=css,theme=gr.themes.Monochrome()) as demo:
         with gr.Row():
             status = gr.Textbox(label="Status", placeholder="", interactive=False)
             load_pdf = gr.Button("Load PDF")
-        with gr.Row():
-            document_type = gr.Dropdown(['Deed of Trust', 'TRANSMITTAL SUMMARY'], label="PDF being loaded is")
+        
+            
             
         with gr.Row():
             input = gr.Textbox(label="Type in your question")
@@ -82,10 +81,14 @@ with gr.Blocks(css=css,theme=gr.themes.Monochrome()) as demo:
             submit_query = gr.Button("Submit")
         
  
-    load_pdf.click(load_doc, inputs=[pdf_doc, openai_key], outputs=status)
+    load_pdf.click(load_pdf_and_generate_embeddings, inputs=[pdf_doc, openai_key], outputs=status)
+    
         
     submit_query.click(answer_query,input,output)
 
 
-#forcing a save in order to re-build the container.
 demo.launch()
+
+
+
+