Semantic Kernel: Multi-agent Orchestration

Orchestration Patterns

Semantic Kernel now supports several orchestration patterns, each designed for different collaboration scenarios. In the Sequence pattern, each agent processes the task in turn, passing its output to the next agent in the sequence. This approach is useful for tasks where a linear flow of information or processing is required.

Use case example: A document passes through a summarization agent, then a translation agent, and finally a quality assurance agent, each building on the previous output.

The Ensemble pattern, on the other hand, allows multiple agents to work on a task concurrently, with their outputs combined or voted on to reach a final decision. This pattern is ideal for scenarios where diverse perspectives or solutions are valuable, such as brainstorming sessions or voting systems.

Use case example: Agents representing different departments discuss a business proposal, with a manager agent moderating the conversation and involving a human when needed.

Magentic Orchestration

Magentic orchestration is based on the MagenticOne pattern invented by AutoGen. It is a flexible, general-purpose multi-agent pattern designed for complex, open-ended tasks that require dynamic collaboration. In this pattern, a dedicated Magentic manager coordinates a team of specialized agents, selecting which agent should act next based on the evolving context, task progress, and agent capabilities.

Conclusion

Multi-agent orchestration in Semantic Kernel opens up new possibilities for building intelligent, collaborative systems. Whether you choose the Sequence, Ensemble, or Magentic pattern, you can define your agents and their capabilities to create custom workflows tailored to your specific needs. Start exploring the orchestration capabilities in Semantic Kernel today and unleash your creativity to develop innovative multi-agent solutions.