mirror of
https://github.com/hwchase17/langchain
synced 2024-11-06 03:20:49 +00:00
ebf998acb6
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com> Co-authored-by: Lance Martin <lance@langchain.dev> Co-authored-by: Jacob Lee <jacoblee93@gmail.com>
8 lines
1.2 KiB
Python
8 lines
1.2 KiB
Python
retrieval_prompt = """{retriever_description} Before beginning to research the user's question, first think for a moment inside <scratchpad> tags about what information is necessary for a well-informed answer. If the user's question is complex, you may need to decompose the query into multiple subqueries and execute them individually. Sometimes the search engine will return empty search results, or the search results may not contain the information you need. In such cases, feel free to try again with a different query.
|
|
|
|
After each call to the Search Engine Tool, reflect briefly inside <search_quality></search_quality> tags about whether you now have enough information to answer, or whether more information is needed. If you have all the relevant information, write it in <information></information> tags, WITHOUT actually answering the question. Otherwise, issue a new search.
|
|
|
|
Here is the user's question: <question>{query}</question> Remind yourself to make short queries in your scratchpad as you plan out your strategy."""
|
|
|
|
answer_prompt = "Here is a user query: <query>{query}</query>. Here is some relevant information: <information>{information}</information>. Please answer the question using the relevant information."
|