Skip to main content

CI status Code coverage Documentation Maintenance
PyPI version PyPI downloads Python versions
Issues Pull requests Commit activity License

↕️ ir_axioms

Axiomatic constraints for information retrieval and retrieval-augmented generation.

ir_axioms is a Python framework for experimenting with axioms in information retrieval in a declarative way. It includes reference implementations of many commonly used traditional retrieval axioms as well as axioms for retrieval-augmented generation. The library is well integrated with the PyTerrier framework and supports Pyserini retrieval indices too. Use-cases of ir_axioms include search-result re-ranking, analyses of (neural) retrieval systems, and analyses of generated RAG answers.

Refer to the ir_axioms documentation for:

TL;DR

To get started without reading the documentation, follow these steps:

  1. Install the package from PyPI:

    pip install ir_axioms>=1.0
    
  2. Install a spaCy model:

    python -m spacy download en_core_web_sm
    
  3. Load and combine axioms:

    from ir_axioms.axiom import TFC1, PROX1, ORIG
    
    axiom = (TFC1() & PROX1()) | ORIG()
    
  4. Define some test data:

    from ir_axioms.model import Query, Document
    
    query = Query(id="q1", text="axiomatic information retrieval")
    documents = [
       Document(id="d1", text="Retrieval axioms formalize constraints for retrieval models.", rank=1),
       Document(id="d2", text="Axiomatic information retrieval: axiomatic constraints guide retrieval.", rank=2),
    ]
    
  5. Compute axiom preferences or re-rank documents:

    axiom.preferences(input=query, outputs=documents)
    axiom.rerank_kwiksort(input=query, ranking=documents)
    

Contribute

If you have found an important feature missing from our tool, please suggest it by creating an issue. We also gratefully accept pull requests! Get started by following our development guides.

License

This repository is released under the MIT license. Files in the data/ directory are exempt from this license. If you use ir_axioms in your research, consider citing us.

Metadata

Release files for ir-axioms 1.2.5

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

Source distribution (sdist)

Source distribution for ir-axioms 1.2.5
File Size Uploaded
ir_axioms-1.2.5.tar.gz 28.7 MB Details

Built distribution (wheel)

Table of built distributions (wheels) for ir-axioms 1.2.5
File Interpreter ABI Platform
ir_axioms-1.2.5-py3-none-any.whl Python 3 none any Details

Total release size: 48.6 MB

Release files / ir_axioms-1.2.5.tar.gz

Download URL ir_axioms-1.2.5.tar.gz
Size 28.7 MB
Tags Source
SHA-256 checksum
How to use checksums
cbb90f78a9de4260619ca6e67c0204e56e0a0155e0d77e80856a2fe4a1af15a5
BLAKE2b-256 checksum
How to use checksums
8133cf2ed9be897d39ba28072226839b5d527155d3dc88453fc71f745782f402
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 Oct 16, 2026.

Transparency log

Release files / ir_axioms-1.2.5-py3-none-any.whl

Download URL ir_axioms-1.2.5-py3-none-any.whl
Size 20.0 MB
Tags Python 3
SHA-256 checksum
How to use checksums
2457e8ebfc33f7e7de11f7a4e2b629c5bc7e6e891b70ebc7e71a8f9f794f49e9
BLAKE2b-256 checksum
How to use checksums
77806f60d8f24af22d05535a349e6a1aab5c0346dcf1957feaa672ca9648e74f
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 Oct 16, 2026.

Transparency log

Release history Release notifications | RSS feed

This release

1.2.5 This release

2 release files

1.2.4

2 release files

1.2.2

2 release files

1.2.1

2 release files

1.2.0

2 release files

1.1.3

2 release files

1.1.2

2 release files

1.1.1

2 release files

1.1

2 release files

1.0.5

2 release files

1.0.4

2 release files

1.0.3

2 release files

0.2.12

2 release files

0.2.8

2 release files

0.2.7

2 release files

0.2.5

2 release files

0.1.3

2 release files

0.1.1

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