AI Agents
agentsight
See what your AI agents do — at the system level.
★ 728 starsMIT
View guide →Observability and evaluation for AI apps — see what your agents do.
phoenix is an open-source ai agents project by Arize-ai (Arize-ai/phoenix on GitHub). It has 11,746 GitHub stars and 1,192 forks, is released under the NOASSERTION license, and was last updated on GitHub on 8 October 2026.
Decide what you want the project to do before installing anything.
Grab the source and skim the README for setup requirements.
Install dependencies and add any API keys or settings it needs.
Launch it and follow the example workflow from the docs.
See every call your app makes.
Follow multi-step agent behavior.
Score quality systematically.
Compare runs and prompts.
LangChain, Anthropic SDKs, and more.
Pushed as recently as this week.
Download the source and move into the project folder.
git clone https://github.com/Arize-ai/phoenix.git
cd phoenixIsolate dependencies, then install requirements.
python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txtLaunch using the entry point shown in the README.
python -m phoenix # check README for the exact commandIt is an open-source project at Arize-ai/phoenix with 1192 forks. Check the contributors tab and recent commits to judge how active maintenance is.
GitHub lists no license for this repo, so legally it's all rights reserved — check the README or ask the maintainer before building on it.
Traces of LLM calls, agent runs, latency, and quality signals — plus datasets and experiments for evals.
It integrates with LangChain, Anthropic SDKs, and agent workflows; check the docs for your stack.
Clone the repo and follow the README quickstart — the docs at https://arize.com/docs/phoenix walk through setup.
See what your AI agents do — at the system level.
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Free and open — grab the source, star the repo, and start creating.