Skip to main content

AnyBench

AnyBench turns the Git history of repositories you supply into coding problems, verifies them in Docker, runs coding models, and creates an HTML report. You do not need to know the repository's language or write benchmark cases yourself.

First run

Install Python 3.11+, Git, and Docker, then start the Docker daemon. Install AnyBench:

python -m pip install any-bench

Run it with one or more local repository paths or Git URLs:

anybench start /path/to/repository
anybench start /path/to/repo-a https://github.com/org/repo-b.git

On the first run, the wizard asks for a builder model, at least one candidate model, and an optional judge. Enter each model's API type, base URL, model ID, and credential. It checks the prerequisites and shows the maximum workload before any paid model calls. Confirm once to begin. The report path appears when the run finishes.

The builder drafts problems from up to 50 recent commits per repository. AnyBench prepares a Docker test environment, then retains only problems whose test fails before the historical fix and passes after it. Every verified problem is run once per candidate by default. Unverified problems are listed with reasons; they are never counted as solved or unsolved.

To set a smaller or larger workload:

anybench start /path/to/repo --commits 20 --max-problems 10

Interrupted sessions can resume without repeating recorded paid calls:

anybench start --resume .anybench/runs/SESSION_NAME

If a model call was interrupted with unknown billing state, AnyBench stops and asks for a new session rather than silently paying for it again.

Models and API keys

The wizard recommends an environment variable name for each credential, such as OPENAI_API_KEY. Set it in your shell before starting. You can also enter a key at a hidden prompt for the current run or save a literal api_key in the private .anybench/config.json file. Saved configs use 0600 permissions and .anybench/ is Git-ignored. Literal keys are excluded from run manifests, reports, and generated model files. To edit repositories or add, edit, and remove models later, run:

anybench configure

The supported endpoint protocols are OpenAI-compatible Chat Completions, OpenAI-compatible Responses, and Anthropic-compatible Messages. The judge is optional; verified local tests provide the main score.

How setup works

Docker is required for isolated verification and candidate execution. The builder proposes dependency setup for the repository's language and test tooling. AnyBench builds the image and allows one automated repair attempt. Image builds may download public dependencies; verification and benchmark containers have no network access. If the repository needs a private registry, external service, or another unsupported setup, the report explains why its problems were not verified. The generated Docker recipes and run files are under .anybench/runs/.

For custom images, headless harnesses, detailed metrics, and the individual build, validate, run, evaluate, and report commands, see the advanced guide.

Release files for any-bench 0.4.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for any-bench 0.4.0
File Size Uploaded
any_bench-0.4.0.tar.gz 106.5 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for any-bench 0.4.0
File Interpreter ABI Platform
any_bench-0.4.0-py3-none-any.whl Python 3 none any Details

Total release size: 200.9 kB

Release files / any_bench-0.4.0.tar.gz

Download URL any_bench-0.4.0.tar.gz
Size 106.5 kB
Tags Source
SHA-256 checksum
How to use checksums
618fc339e81ae9b4e48b497f2e0b3aab83c6aef99f9be07cc6697d23b930569a
BLAKE2b-256 checksum
How to use checksums
9e6f6b138bf0b2936b82b2e4de8634a7bcc9fe46a5912d64981e531204becf16
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.14

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Sep 25, 2026.

Transparency log

Release files / any_bench-0.4.0-py3-none-any.whl

Download URL any_bench-0.4.0-py3-none-any.whl
Size 94.4 kB
Tags Python 3
SHA-256 checksum
How to use checksums
d9108ed23f0290b24ba640a14424a03b06b3218d844310d1ab016ff0fa8d75c7
BLAKE2b-256 checksum
How to use checksums
d75837895f6e1caebd718b99fedf335dc7c0f21fc81105f9fb0fa4a2c01c4d6d
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.14

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Sep 25, 2026.

Transparency log

Release history Release notifications | RSS feed

0.4.1

2 release files

This release

0.4.0 This release

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page