xingyaoww/code-act

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1705 stars · 148 forks observed · 2026-10-03

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

CodeAct is a research framework and agent system that uses executable Python code as a unified action space for LLM agents, enabling multi-turn interaction with a code interpreter. It includes the CodeActInstruct instruction-tuning dataset and fine-tuned CodeActAgent models (e.g., Mistral-7b based) that can be served via Ollama, llama.cpp, or Kubernetes.

Use cases

• build llm agents that execute python code as actions
• fine-tune an open-source llm for agent tasks
• run a self-hosted chat agent with code execution
• evaluate llm agents on tool-use benchmarks
• deploy an llm agent stack on kubernetes
• run a code-executing agent locally on a laptop

When to choose

• you want agents that act via executable code rather than JSON or text tool calls
• you need an open-source, fine-tunable agent model with a Python interpreter sandbox
• you want to reproduce or extend the CodeAct research (M3ToolEval, CodeActInstruct)

When to avoid

• you need a production-hardened agent framework with broad integrations
• you cannot safely sandbox arbitrary code execution
• you only need simple prompt-based tool calling without code execution

Facets

framework · maturity active

agent-framework llm-inference llm-training rag artificial-intelligence large-language-models machine-learning python self-hosted code-act llm-agent executable-code-actions instruction-tuning python-interpreter research-paper icml-2024 ai-agents docker kubernetes

Member repositories

For agents

markdown · JSON · MCP: product_card(name="xingyaoww/code-act")