Libraries for orchestrating LLM agents, tools, and multi-step control flow. Ranked by community traction, with live GitHub stars and what each is best at.
Microsoft's framework for multi-agent conversation, with a programming model for agents that talk to each other and tools. Best for conversational multi-agent.
Role-playing autonomous agents that collaborate as a 'crew' with defined roles, goals, and task delegation. Best for role-based multi-agent teams.
Data framework for connecting LLMs to private data — indexing, retrieval, and agentic RAG over your documents. Best for RAG.
Graph-based orchestration for stateful, multi-actor agent workflows with explicit control flow and checkpointing. Best for stateful multi-agent workflows.
Programming — not prompting — language models: compile declarative pipelines into optimized prompts/weights. Best for prompt optimization.
Type-safe agent framework from the Pydantic team — structured outputs, dependency injection, and model-agnostic agents. Best for type-safe agents.
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