docs: custom output extraction #817
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rm-openai
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In deep agent workflows, each sub‐agent automatically performs an LLM step to summarize its tool calls before returning to its parent. This leads to: 1. Excessive latency: every nested agent invokes the LLM, compounding delays. 2. Loss of raw tool data: summaries may strip out details the top‐level agent needs. We discovered that `Agent.as_tool(...)` already accepts an (undocumented) `custom_output_extractor` parameter. By providing a callback, a parent agent can override what the sub‐agent returns e.g. hand back raw tool outputs or a custom slice so that only the final agent does summarization. --- This PR adds a “Custom output extraction” section to the Markdown docs under “Agents as tools,” with a minimal code example.
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In deep agent workflows, each sub‐agent automatically performs an LLM step to summarize its tool calls before returning to its parent. This leads to:
We discovered that
Agent.as_tool(...)already accepts an (undocumented)custom_output_extractorparameter. By providing a callback, a parent agent can override what the sub‐agent returns e.g. hand back raw tool outputs or a custom slice so that only the final agent does summarization.This PR adds a “Custom output extraction” section to the Markdown docs under “Agents as tools,” with a minimal code example.