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refactor: implement structured output handling in final answer synthesis

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This commit enhances the final answer synthesis process in the AgentExecutor class by introducing support for structured outputs when a response model is specified. The synthesis method now utilizes the response model to produce outputs that conform to the expected schema, while still falling back to concatenation in case of synthesis failures. This change ensures that intermediate steps yield free-text results, but the final output can be structured, improving the overall coherence and usability of the synthesized answers.
This commit is contained in:
lorenzejay
2026-02-08 16:19:16 -08:00
parent ff57956d05
commit 735a2204fd
1 changed files with 22 additions and 6 deletions
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28
lib/crewai/src/crewai/experimental/agent_executor.py
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@@ -1986,6 +1986,12 @@ provide clear results that can be used by subsequent steps."""
Makes one LLM call to produce a clean, unified response from
the accumulated step results, rather than dumping raw step outputs.
If a response_model is set (from task.response_model or kickoff(response_format)),
the synthesis call uses it to produce structured output matching the
expected schema. This is the ONLY place response_model is applied in
the Plan-and-Execute path — intermediate steps produce free-text results.
Falls back to concatenation if the synthesis LLM call fails.
"""
step_results: list[str] = [
@@ -2012,6 +2018,7 @@ provide clear results that can be used by subsequent steps."""
# Build synthesis prompt
role = self.agent.role if self.agent else "Assistant"
system_prompt = (
f"You are {role}. You have completed a multi-step task. "
"Synthesize the results from all steps into a single, coherent "
@@ -2031,17 +2038,26 @@ provide clear results that can be used by subsequent steps."""
{"role": "system", "content": system_prompt},
{"role": "user", "content": user_prompt},
],
response_model=self.response_model,
from_task=self.task,
from_agent=self.agent,
)
if synthesis:
final_text = str(synthesis)
self.state.current_answer = AgentFinish(
thought="Synthesized final answer from all completed steps",
output=final_text,
text=final_text,
)
# If response_model produced a BaseModel, store it directly
if isinstance(synthesis, BaseModel):
self.state.current_answer = AgentFinish(
thought="Synthesized structured final answer from all completed steps",
output=synthesis,
text=synthesis.model_dump_json(),
)
else:
final_text = str(synthesis)
self.state.current_answer = AgentFinish(
thought="Synthesized final answer from all completed steps",
output=final_text,
text=final_text,
)
return
except Exception as e: