Update app.py

app.py

@@ -8,6 +8,7 @@ from gpt_index import (
     GPTSimpleVectorIndex, 
     LLMPredictor, 
     QuestionAnswerPrompt,
+    RefinePrompt,
     PromptHelper
 )
 
@@ -42,17 +43,19 @@ with gr.Blocks() as demo:
 
     def ask_gpt(message, messages_history):
         messages_history += [{"role": "user", "content": message}]
-        query_str = "Who is the mayor of Atlanta?"
+        query_str = ''
         QA_PROMPT_TMPL = (
-            "You are an AI specialized in Atlanta.\n"
-            "If a query does not involve Atlanta, say you can't answer the query and make the answer related to Atlanta.\n"
-            "If the query is ambiguous, assume it is related to Atlanta.\n"
-            "If you cannot relate the query to Atlanta, do not answer it.\n"
+            "You are an conversational AI specialized in Atlanta.\n"
+            "If a query does not relate to Atlanta, say you can't answer the query.\n"# and make the answer related to Atlanta.\n"
             "We have provided context information below. \n"
             "---------------------\n"
             "{context_str}"
             "\n---------------------\n"
-            "Given this information, please answer the query: {query_str}\n"
+            "Given this information, please give a detailed and conversational answer to the query: {query_str} and cite the url source associated with this answer.\n"
+            "Use information from previous queries in your response when appropriate.\n"
+            "Format the answer to the query like this: Answer: .\n"
+            "\nSource: followed by the source in bold.\n"
+            "Put the Answer and Source on different lines of the response and the Source is the url source associated with the answer.\n"
         )
         QA_PROMPT = QuestionAnswerPrompt(QA_PROMPT_TMPL)
         
@@ -60,7 +63,7 @@ with gr.Blocks() as demo:
         # Takes in the input from the user to deliver responses
         index = GPTSimpleVectorIndex.load_from_disk('index_demo.json')
         message = ' '.join([message['content'] for message in messages_history])
-        response = index.query(message, response_mode="compact", text_qa_template = QA_PROMPT)
+        response = index.query(message, text_qa_template = QA_PROMPT)
         return response.response, messages_history
         #return response['choices'][0]['message']['content'], messages_history