A framework for building multi-agent systems around an intuitive role-playing paradigm: you define agents with roles and goals, and assemble them into a crew. It is one of the easiest agent frameworks to get working with local models.
A graph-based framework from the LangChain team for building stateful, controllable agent workflows. You define agents as graphs with explicit state, branching, and human-in-the-loop steps, which suits production systems that need audit trails and recovery points. Works with local models.
An open-source framework for stateful agents with long-term memory, formerly known as MemGPT. It gives agents transparent, persistent memory so they can remember facts across sessions, which general-purpose frameworks do not ship by default.
A Python agent framework from the Pydantic team, built around type safety and structured, validated outputs. It is model-agnostic, works with local models, and brings a clean, familiar developer experience to building agents.