stream-chain

To automate a multi-agent workflow, you design custom prompt chains or predefined pipelines that pass outputs from one step as context to subsequent steps. This sequential data transformation preserves context across multiple agents for structured execution.

A prompt chain is a sequence of custom prompts or predefined pipelines that coordinates multi-agent tasks by passing the output of one step as context to the next. This mechanism enables stepwise execution for complex processes like code analysis and testing.

Yes, multi-agent orchestration supports automating code review by sequentially analyzing code, identifying issues, suggesting fixes, and generating test cases. This structured workflow ensures repeatable stepwise execution across development and QA tasks.

You set up a pipeline by specifying prompts in sequence to analyze the codebase, identify issues, and suggest improvements. This orchestrates multi-step workflows by streaming data transformations across multiple agents while preserving context.

Yes, multi-agent workflow orchestration preserves context between sequential steps by passing outputs from one step directly as context to subsequent steps. This ensures that data transformation and multi-agent coordination maintain continuity throughout the pipeline.

Use predefined pipelines for standard, repeatable automation workflows like code migration or QA, and use custom prompt chains when you need flexible, multi-step workflows tailored to specific data transformation or analysis tasks.