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FastAgent
by HKUDS
Lightweight, fast Python agents for tool use and simple orchestration
Python
Updated Feb 10, 2026
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How It Works
Implements lightweight LLM agents focused on speed and simplicity for task automation and tool use. This approach combines ReAct Pattern (Reason + Act) with an opinionated agent orchestration pattern Hierarchical Multi-Agent Pattern that prioritizes fast turn-taking, tool invocation, and short-lived context windows to reduce latency and cost. Designed as a small Python SDK for building agents that execute tools, delegate subtasks, and run conversational workflows with minimal boilerplate.
Key Benefits
As agents delegate tasks and interact more frequently, lightweight orchestration reduces surface area where failures and mistrust accumulate. FastAgent makes it easier to prototype agent teams and study their behavior under realistic latency and tool-use constraints, which is crucial for measuring agent reliability and delegation safety. Until now many agent frameworks prioritized features over speed; this repo fills the gap for exploring agent failure modes and rapid A/B evaluation of agent strategies Defense in Depth Pattern.
Target Use Cases
Developers prototyping multi-agent workflows who need low-latency, tool-enabled agents to experiment with delegation and failure modes Agentic RAG Pattern.
Use Cases
- Prototyping tool-enabled agents that invoke external tools with low latency
- Testing agent delegation patterns and short-lived conversational workflows
- Exploring agent failure modes and rapid A/B comparisons of agent strategies
Topics
agent-orchestrationagentscomputer-use-agentmcptool-use
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Keywords
multi-agent orchestrationagent delegationagent reliability