Add application file

app.py

@@ -123,23 +123,34 @@ def generate_text(openAI_key,
 
 def generate_answer(question, openAI_key, openAI_base, openAI_API_version):
     topn_chunks = recommender(question)
-    print(len(topn_chunks))
-    print(*topn_chunks, sep = "\n")
+    #     print(len(topn_chunks))
+    #     print(*topn_chunks, sep="\n")
     prompt = ""
     prompt += 'search results:\n\n'
     for c in topn_chunks:
         prompt += c + '\n\n'
 
+
+#         prompt += "Instructions: Compose a comprehensive reply to the query using the search results given. "\
+#               "Cite each reference using [ Page Number] notation (every result has this number at the beginning). "\
+#               "Citation should be done at the end of each sentence. "\
+#               "If the search results mention multiple subjects with the same name, create separate answers for each. "\
+#               "Make sure the answer is correct and don't output false content. "\
+#               "Only answer what is asked. The answer should be in details."\
+#               "\n\nQuery: {question}\nAnswer: "
     prompt += "Instructions: Compose a comprehensive reply to the query using the search results given. "\
               "Cite each reference using [ Page Number] notation (every result has this number at the beginning). "\
-              "Citation should be done at the end of each sentence. If the search results mention multiple subjects "\
-              "with the same name, create separate answers for each. Only include information found in the results and "\
-              "don't add any additional information. Make sure the answer is correct and don't output false content. "\
-              "If the text does not relate to the query, simply state 'Found Nothing'. Ignore outlier "\
-              "search results which has nothing to do with the question. Only answer what is asked. The "\
-              "answer should be short and concise. \n\nQuery: {question}\nAnswer: "
+              "Citation should be done at the end of each sentence. "\
+              "If the search results mention multiple subjects with the same name, create separate answers for each. "\
+              "Only include information found in the results and don't add any additional information."\
+              "Make sure the answer is correct and don't output false content. "\
+              "If the text does not relate to the query, simply state 'Found Nothing'. "\
+              "Ignore outlier search results which has nothing to do with the question."\
+              "Only answer what is asked. The answer should be short and concise."\
+              "\n\nQuery: {question}\nAnswer: "
 
     prompt += f"Query: {question}\nAnswer:"
+    print(prompt)
     answer = generate_text(openAI_key, openAI_base, openAI_API_version, prompt,
                            "chatgpt")
     return answer
@@ -173,6 +184,15 @@ def question_answer(url, file, question, openAI_key, openAI_base,
     return generate_answer(question, openAI_key, openAI_base,
                            openAI_API_version)
 
+
+def chatbot_respond(question, chat_history, url, file, openAI_key, openAI_base,
+            openAI_API_version):
+
+    bot_message = question_answer(url, file, question, openAI_key, openAI_base,
+                                  openAI_API_version)
+    chat_history.append((message, bot_message))
+    return "", chat_history
+
 recommender = SemanticSearch()
 
 title = 'PDF GPT Azure'
@@ -203,7 +223,8 @@ with gr.Blocks() as demo:
             ## REMEMBER to remove the key before public deploy
             ##
             #####################
-            openAI_key = gr.Textbox(label='Enter your Azure OpenAI API key here')
+            openAI_key = gr.Textbox(
+                label='Enter your Azure OpenAI API key here')
             openAI_base = gr.Textbox(label='api_base',
                                      value="https://api.hku.hk")
             openAI_API_version = gr.Textbox(label='API version',
@@ -212,17 +233,18 @@ with gr.Blocks() as demo:
             gr.Markdown("<center><h4>OR<h4></center>")
             file = gr.File(label='Upload your PDF/ Research Paper / Book here',
                            file_types=['.pdf'])
-            
         with gr.Group():
-            question = gr.Textbox(label='Enter your question here')
-            btn = gr.Button(value='Submit', scale=1)
-            answer = gr.Textbox(label='The answer to your question is :')
-
-        btn.click(question_answer,
-                  inputs=[
-                      url, file, question, openAI_key, openAI_base,
-                      openAI_API_version
-                  ],
-                  outputs=[answer])
-#openai.api_key = os.getenv('Your_Key_Here')
+            chatbot = gr.Chatbot()
+            question = gr.Textbox()
+            clear = gr.ClearButton([msg, chatbot])
+
+            msg.submit(
+                chatbot_respond,
+                inputs=[
+                    question, chatbot, url, file, openAI_key, openAI_base,
+                    openAI_API_version
+                ],
+                outputs=[msg, chatbot],
+            )
+
 demo.launch()