stream-chain

You can orchestrate multi-agent workflows by coordinating prompts to form sequential, streaming data pipelines. This approach applies stepwise transformations across code, docs, and analyses, allowing outputs to flow from one stage to the next in real-time.

Building custom multi-agent chains involves creating bespoke prompt sequences where each step consumes the previous output. This enables tailored multi-agent collaboration for complex data processing and stepwise transformations.

Yes, you can use predefined pipelines for common multi-agent tasks to accelerate development and ensure consistency. These battle-tested workflows provide a structured approach to streaming data processing without needing custom configuration.

Multi-agent orchestration supports context propagation between steps and includes optional memory to persist state across runs. This ensures sequential streaming workflows maintain necessary context for complex transformations.

Use sequential streaming workflows when processing complex data that requires stepwise transformations across code, docs, or analyses. It is ideal when outputs must flow from one stage to the next in real-time for continuous data processing.