updated to use gpt-turbo-3.5 instead of davinci

query_data.py

@@ -2,34 +2,56 @@ from langchain.prompts.prompt import PromptTemplate
 from langchain.llms import OpenAI
 from langchain.chains import ChatVectorDBChain
 from langchain.chat_models import ChatOpenAI
+from langchain.prompts.chat import (
+    ChatPromptTemplate,
+    SystemMessagePromptTemplate,
+    AIMessagePromptTemplate,
+    HumanMessagePromptTemplate,
+)
+
+from langchain.schema import (
+    AIMessage,
+    HumanMessage,
+    SystemMessage
+)
+
+system_template = """Use the following pieces of context to answer the users question. 
+If you don't know the answer, just say that you don't know, don't try to make up an answer.
+----------------
+{context}"""
+
+messages = [
+    SystemMessagePromptTemplate.from_template(system_template),
+    HumanMessagePromptTemplate.from_template("{question}")
+]
+prompt = ChatPromptTemplate.from_messages(messages)
 
 _template = """Given the following conversation and a follow up question, rephrase the follow up question to be a standalone question.
 You can assume the question about the syllabus of the H2 Economics, H2 History and H2 Geography A-Level Examinations in Singapore.
-
 Chat History:
 {chat_history}
 Follow Up Input: {question}
 Standalone question:"""
 CONDENSE_QUESTION_PROMPT = PromptTemplate.from_template(_template)
 
-template = """You are an AI assistant for answering questions about history, geography or economics for the H2 A-Levels.
-You are given the following extracted parts of a long document and a question. Provide a conversational answer.
-If you don't know the answer, just say "Hmm, I'm not sure." Don't try to make up an answer.
-If the question is not about history, geography or economics, politely inform them that you are tuned to only answer questions about it.
-Question: {question}
-=========
-{context}
-=========
-Answer in Markdown:"""
-QA_PROMPT = PromptTemplate(template=template, input_variables=["question", "context"])
-
+#template = """You are an AI assistant for answering questions about history, geography or economics for the H2 A-Levels.
+#You are given the following extracted parts of a long document and a question. Provide a conversational answer.
+#If you don't know the answer, just say "Hmm, I'm not sure." Don't try to make up an answer.
+#If the question is not about history, geography or economics, politely inform them that you are tuned to only answer questions about it.
+#Question: {question}
+#=========
+#{context}
+#=========
+#Answer in Markdown:"""
+#QA_PROMPT = PromptTemplate(template=template, input_variables=["question", "context"])
+prompt = ChatPromptTemplate.from_messages(messages)
 
 def get_chain(vectorstore):
-    llm = OpenAI(temperature=0)
+    llm = ChatOpenAI(temperature=0)
     qa_chain = ChatVectorDBChain.from_llm(
         llm,
         vectorstore,
-        qa_prompt=QA_PROMPT,
-        condense_question_prompt=CONDENSE_QUESTION_PROMPT,
+        qa_prompt=prompt,
+        condense_question_prompt = CONDENSE_QUESTION_PROMPT
     )
     return qa_chain