Skip to main content

inference-receipt

This package has been consolidated into aiir.

Install the real package

pip install aiir

What is AIIR?

AI Integrity Receipts — lightweight cryptographic commitment records generated during AI inference that bind model identity, sampling configuration, and output tokens into a tamper-evident hash chain.

  • Zero external dependencies (Python stdlib only)
  • Receipt generation in < 100 µs
  • SHA-256 hash chains with O(1) amortized cost
  • Works with any model format (GGUF, ONNX, cloud APIs)
  • MCP server for Claude / Copilot / ChatGPT integration

Links


This package (inference-receipt) exists to redirect users to the canonical aiir package. Installing it will automatically install aiir as a dependency.

Metadata

Release files for inference-receipt 0.0.1

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

Source distribution (sdist)

Source distribution for inference-receipt 0.0.1
File Size Uploaded Provenance
inference_receipt-0.0.1.tar.gz 1.7 kB Without provenance Details

Built distribution (wheel)

Table of built distributions (wheels) for inference-receipt 0.0.1
File Interpreter ABI Platform
inference_receipt-0.0.1-py3-none-any.whl Python 3 none any Details

Total release size: 3.9 kB

Release files / inference_receipt-0.0.1.tar.gz

Download URL inference_receipt-0.0.1.tar.gz
Size 1.7 kB
Tags Source
SHA-256 checksum
How to use checksums
f3664eddb713a97d487604548d55edb88e42ea24e3944307bd023a3e4be84049
BLAKE2b-256 checksum
How to use checksums
2e6c41ca84f48d5f92e560b325e945a91d53515f4263aae9ad4b2c541f13c936
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.11.0rc1

Release files / inference_receipt-0.0.1-py3-none-any.whl

Download URL inference_receipt-0.0.1-py3-none-any.whl
Size 2.2 kB
Tags Python 3
SHA-256 checksum
How to use checksums
58002ac93646aca9ec14083de0d2f3c1025ecbd3baa32ad3cc15bf3ccbbb6074
BLAKE2b-256 checksum
How to use checksums
e2a35429cfe983a8a6c320fb450574355bba0e022c5aca2f6dd2dd4d05ec1e1a
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.11.0rc1

Security for inference-receipt 0.0.1

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.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Release history Release notifications | RSS feed

This release

0.0.1 This release

2 release files No provenance

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