stream-chain

Multi-agent workflow coordination chains outputs from one step to the next, creating cohesive and auditable pipelines. You can orchestrate custom chains or predefined pipelines to pass iterative prompts and memory across sequential steps.

Automating code analysis and deployment pipelines uses predefined pipelines to execute standard software engineering tasks. This approach applies multi-agent coordination and memory integration to maintain persistence across iterative workflow steps.

Custom chain execution supports data processing tasks by maintaining memory of previous results across sequential prompts. You can invoke the flow with a sequence of prompts to pass iterative outputs through the chain.

Multi-agent workflow coordination includes configurable timeouts, verbose logging, and error handling for custom chain execution. These features ensure pipeline stability during iterative prompts and multi-agent collaboration.

Custom chains offer flexible execution by running a sequence of prompts, while predefined pipelines suit standard tasks. Both modes support memory integration and swarm coordination for multi-agent collaboration in software development.

Sequential chain execution is not ideal for software engineering tasks requiring parallel processing or independent agent actions without memory dependencies. It is designed for iterative prompts where outputs must pass sequentially across steps.