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The self-ask-with-search agent allows the LLM to use "intermediate" searches to obtain an answer to a query.
Example from prompt template:
Question: Who lived longer, Muhammad Ali or Alan Turing?
Are follow up questions needed here: Yes.
Follow up: How old was Muhammad Ali when he died?
Intermediate answer: Muhammad Ali was 74 years old when he died.
Follow up: How old was Alan Turing when he died?
Intermediate answer: Alan Turing was 41 years old when he died.
So the final answer is: Muhammad Ali
This is really powerful and in my experience, produces better results than the chat-conversational-react-description agent for searching, barring some minor technical issues. However, it only has the ability to use a single tool: Intermediate Answer.
I'm curious to understand the reasoning for this limitation, is this just missing implementation for using multiple tools, or is there a fundamental reason this type of agent can only use one tool?
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The
self-ask-with-search
agent allows the LLM to use "intermediate" searches to obtain an answer to a query.Example from prompt template:
This is really powerful and in my experience, produces better results than the
chat-conversational-react-description
agent for searching, barring some minor technical issues. However, it only has the ability to use a single tool: Intermediate Answer.I'm curious to understand the reasoning for this limitation, is this just missing implementation for using multiple tools, or is there a fundamental reason this type of agent can only use one tool?
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