8 Best CodeAct Alternatives in 2026 (Open Source)
CodeAct — Official Repo for ICML 2024 paper "Executable Code Actions Elicit Better LLM Agents" by Xingyao Wang, Yangyi Chen, Lifan Yuan, Yizhe Zhang, Yunzhu Li, Hao Peng, Heng Ji. vs ReAct/text-based agents: executable Python code as unified action space with containerized execution, achieving 20% higher success rate than JSON/text actions
Short answer
- Closest match to CodeAct: smolagents.
- Most actively developed: E2B (230 commits in the last 90 days).
- Fastest growing: smolagents (+531 GitHub stars in the last 30 days).
- No commit in 6+ months: TaskWeaver, Code Interpreter API, GPT-Code and AgentRun and 1 more.
These 8 open-source tools do the same job. They are ordered by how closely they match CodeAct, with live GitHub data so you can see which projects are actively maintained.
By package downloads E2B is the most used here (12.9M in the last 30 days), even though smolagents has the most GitHub stars. See all agent tools by downloads.
| Tool | GitHub stars | Stars / 30d | Last commit | Downloads / 30d |
|---|---|---|---|---|
| CodeAct(original) | 1.7k | +11 | 2024-05-23 | — |
| smolagents | 29.7k | +531 | 2026-09-30 | — |
| TaskWeaver | 6.2k | +6 | 2026-03-23 | — |
| Code Interpreter API | 3.8k | -2 | 2024-11-07 | 192 |
| GPT-Code | 3.5k | -6 | 2023-07-29 | — |
| AgentRun | 380 | +2 | 2024-11-10 | — |
| E2B | 14.1k | +420 | 2026-10-02 | 12.9M |
| e2b | 2.4k | +25 | 2026-09-30 | — |
| Lumos | 477 | 0 | 2024-03-19 | — |
1. smolagents
🤗 smolagents: a barebones library for agents that think in code.
What sets it apart: vs LangChain: code-first agent design uses 30% fewer tokens by writing Python instead of JSON tool calls; vs CrewAI: lighter ~1000 lines core with HuggingFace Hub integration for sharing agents/tools
Best for: Building code-writing AI agents with sandboxed execution; HuggingFace ecosystem users wanting agent capabilities; Multi-modal agent applications
2. TaskWeaver
The first "code-first" agent framework for seamlessly planning and executing data analytics tasks.
What sets it apart: Unlike text-only agent frameworks like AutoGen, TaskWeaver preserves full code execution state and in-memory data across turns, enabling seamless multi-step data analytics that manipulate DataFrames and complex structures directly
Best for: Data scientists needing automated multi-step analytics pipelines with code generation; Teams building AI agents that must handle complex data structures like DataFrames natively
3. Code Interpreter API
👾 Open source implementation of the ChatGPT Code Interpreter
What sets it apart: vs raw LangChain code execution: sandboxed Code Interpreter replica with file I/O and conversation memory — the closest open-source implementation of ChatGPT's Code Interpreter feature
Best for: Developers wanting open-source ChatGPT Code Interpreter functionality; Data analysis automation with file input/output; Building code execution agents with sandboxed safety
4. GPT-Code
An open source implementation of OpenAI's ChatGPT Code interpreter
What sets it apart: vs ChatGPT Code Interpreter / Open Interpreter: self-hosted open-source web UI for AI code generation and execution — own your data and conversations without ChatGPT Plus subscription
Best for: Self-hosted Code Interpreter alternative; Data analysis and visualization with AI assistance; Document processing and automation scripting
5. AgentRun
The easiest, and fastest way to run AI-generated Python code safely
What sets it apart: Single-line safe Python code execution from LLMs in Docker containers with automatic dependency management, safety checks, and resource limiting
Best for: safe-llm-code-execution; sandboxed-python-runtime; giving-code-execution-to-llm-agents
6. E2B
Open-source, secure environment with real-world tools for enterprise-grade agents.
What sets it apart: Purpose-built sandboxed execution for AI-generated code with sub-second startup — vs generic containers which require more setup and have slower cold starts
Best for: Running untrusted AI-generated code safely; Building code execution features into AI applications
7. e2b
Python & JS/TS SDK for running AI-generated code/code interpreting in your AI app
What sets it apart: Purpose-built cloud infrastructure for AI-generated code execution — secure sandboxes designed specifically for LLM output, not repurposed containers
Best for: AI apps needing safe code execution from LLM outputs; Building AI coding assistants with runnable code; Data analysis agents that generate and run Python
8. Lumos
Code and data for "Lumos: Learning Agents with Unified Data, Modular Design, and Open-Source LLMs"
What sets it apart: vs GPT-4 agents: unified modular framework achieving competitive performance with 7B-13B models — planning + grounding + execution separation enables task-agnostic agent architecture from Allen AI
Best for: Multi-step reasoning: web navigation, QA, math problem-solving; Research into efficient agent architectures with small models; Building agents competitive with GPT-4 at lower cost
FAQ
- What are the best alternatives to CodeAct?
- The closest open-source alternatives to CodeAct are smolagents, TaskWeaver and Code Interpreter API, followed by GPT-Code, AgentRun and E2B. They are ranked by how closely they match what CodeAct does.
- Which CodeAct alternative is the most popular?
- smolagents has the most GitHub stars among CodeAct alternatives, with 29,662 stars.
- Which CodeAct alternative is the most actively maintained?
- By recent activity, E2B (230 commits in the last 90 days) is the most actively developed alternative.
Maintain CodeAct or one of these alternatives?
Each tool page has a maintainer box: a README badge with your live rank and stars, or a homepage feature for $49 / 7 days.
CodeAct · smolagents · TaskWeaver · Code Interpreter API · GPT-Code · AgentRun