ParallelDeepResearch(
self,
*,
processor: ProcessorLiteral = 'pro-fast',
output_schema: Optional[UnionHigh-level Runnable for Parallel deep-research tasks.
Defaults to the pro-fast processor -- the -fast variant of
pro ("Exploratory web research") at 2-5x the speed for similar
accuracy. Drop the -fast suffix (processor="pro", 2-10 min)
or step up to processor="ultra" (5-25 min) for the most thorough
multi-source investigative reports. For shorter, enrichment-style
structured tasks, use :class:ParallelEnrichment or pass
processor="core-fast" here.
Always returns the full basis (citations + reasoning + confidence)
on the result; lower friction than wiring up
:class:ParallelTaskRunTool manually when all you want is "do deep
research on this question."
Example:
research = ParallelDeepResearch() # processor="pro-fast"
result = research.invoke("Latest developments in renewable energy")
print(result["output"]["content"])
for fact in result["output"].get("basis", []):
print(fact["field"], "->", fact["citations"])
# For the most thorough report:
research = ParallelDeepResearch(processor="ultra")