Overview
AgentFlow is an open-source project focused on improving the effectiveness of agentic systems in multi-step planning and tool usage. It offers components and patterns for building, evaluating, and refining agent strategies, helping researchers and engineers coordinate LLM reasoning, tool invocation, and environment interactions in complex tasks.
Key features
- Emphasizes planning and tool-augmented mechanisms for agentic systems, supporting complex multi-step decision flows.
- Provides evaluation and debugging utilities for observing agent behavior, decision traces, and tool interactions.
- Modular design enables easy integration with existing LLMs and toolchains and supports extensible custom strategies.
Use cases
- Building agents that require multi-step planning and tool interaction, such as automated research assistants, workflow automation, and task orchestration.
- Researching and comparing different agent strategies and decision-making mechanisms.
- Educational and prototyping platform for validating tool-augmented and multi-agent collaboration approaches.
Technical aspects
- Primarily Python-based, with a clear module structure and example code for quick onboarding and extension.
- Built around composable strategy and tool interfaces compatible with mainstream LLMs and external tool invocation patterns.
- MIT licensed and community-driven, suitable for both research and engineering adoption.