Spaces:
Runtime error
Runtime error
| from langchain.prompts.prompt import PromptTemplate | |
| from langchain.llms import OpenAI | |
| from langchain.chains import ChatVectorDBChain | |
| _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 conversation containing all the messages exchanged between these people. | |
| 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 this online conversation between these people. | |
| You are given the following extracted parts of a long document and a question. | |
| Provide a conversational answer that solely comes from this online conversation between these people and your interpretation. | |
| Your responses should be informative, interesting, and engaging. You should respond thoroughly. | |
| Question: {question} | |
| ========= | |
| {context} | |
| ========= | |
| Answer:""" | |
| QA_PROMPT = PromptTemplate(template=template, input_variables=["question", "context"]) | |
| def get_chain(vectorstore): | |
| llm = OpenAI(temperature=0) | |
| qa_chain = ChatVectorDBChain.from_llm( | |
| llm, | |
| vectorstore, | |
| qa_prompt=QA_PROMPT, | |
| condense_question_prompt=CONDENSE_QUESTION_PROMPT, | |
| ) | |
| return qa_chain | |