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autoarena

kolenaIO/autoarena

Automated evaluation of LLMs and RAG systems

GitHub Website

GraphCanon updated 3w · GitHub synced 3w · 29 views this month

108 stars9 forksLast push 1y TypeScript Apache-2.0

Decision brief

autoarena automates evaluations for LLMs and RAG systems through a user-friendly interface where projects are created and judged without manual intervention by the users.

Good fit when

When you need a TypeScript-based tool to rank LLMs and RAG systems via automated head-to-head comparisons, and a web UI is preferable.
If your project relies on PyPI installation and requires a simple setup using environment variables for API credentials.

Avoid when

If your environment lacks the necessary Python packages or you cannot install from PyPI due to restrictions.
When real-time evaluation needs surpass capabilities, such as requiring immediate feedback beyond autoarena's batch-processing approach.

Hosting:: self hosted
Requirements:: Python environment and internet access are needed for PyPI installation via pip.

Observed Jul 16, 2026 · Source: enrich:decision_facts

autoarena alternatives Trust report

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Maintenance and security

Full trust report

Maintenance: Dormant (589d since push); As of 3w
Provenance: Not a fork · Organization account; As of 3w
Security (OSV): No lockfile; As of 1mo

Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.

Install

npm install autoarena

npm

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Same-category neighbours. No typed graph edges are catalogued for this tool yet.

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Evidence and technical details

Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.

Overview

autoarena is a tool to rank LLMs and Retrieval-Augmented Generation (RAG) systems using automated head-to-head evaluations.

Capability facts

Languages: typescript, python
Source: github.language+pyproject.toml · Jul 29, 2026

Compatibility

Sourced claims from the README excerpt - not unsourced marketing copy.

Python runtimePython

Source: README excerpt (regex_v1, Jul 29, 2026)

python -m autoarena

Source link

README

🔥 Getting Started

Install from PyPI:

pip install autoarena

Run as a module and visit localhost:8899 in your browser:

python -m autoarena

With the application running, getting started is simple:

Create a project via the UI.
Add responses from a model by selecting a CSV file with prompt and response columns.
Configure an automated judge via the UI. Note that most judges require credentials, e.g. X_API_KEY in the environment where you're running AutoArena.
Add responses from a second model to kick off an automated judging task using the judges you configured in the previous step to decide which of the models you've uploaded provided a better response to a given prompt.

That's it! After these steps you're fully set up for automated evaluation on AutoArena.

For agents

This page has a .md twin and JSON over the API.

/tools/kolenaio-autoarena.md GET /api/graphcanon/tools/kolenaio-autoarena GET /api/graphcanon/graph?tool=kolenaio-autoarena