AI Agents
babyagi
Yohei Nakajima's autonomous task agent - now a self-building agent framework in Python
★ 22.4k starsMIT
View guide →A frozen snapshot of the original BabyAGI autonomous-agent experiment.
babyagi_archive is an open-source ai agents project by yoheinakajima (yoheinakajima/babyagi_archive on GitHub). It has 110 GitHub stars and 27 forks, is released under the MIT license, and was last updated on GitHub on 30 September 2024.
Write down the task or workflow you want the agent to handle.
Clone the repository and read the README's prerequisites.
Install dependencies and configure keys or endpoints.
Run the sample script and check the output against the docs.
BabyAGI as of September 2024.
The classic create-prioritize-execute cycle.
One of the first famous agent demos.
Simple enough to study in an afternoon.
Free to learn from.
Won't change - stable reference.
Download the source and move into the project folder.
git clone https://github.com/yoheinakajima/babyagi_archive.git
cd babyagi_archiveCreate a virtual environment and install the requirements.
python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txtTreat these as starting points - the README documents the exact commands.
python examples/quickstart.pyNobody actively - it is a preserved snapshot of BabyAGI as of September 2024, kept for historical reference. For maintained code, look at the active frameworks in this collection.
Yes - it is MIT licensed, so you can use, modify, and distribute it freely, including in commercial projects.
In principle, but it is a frozen 2024 snapshot - expect outdated dependencies and legacy API requirements. It is best used for study, not deployment.
No - it is an archived snapshot, not a maintained framework. Learn from it, then build on an actively maintained project from this collection.
The README and the official docs site are the fastest path: run the quickstart example first, then adapt it to your use case.
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