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inference-receipts

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-receipts) exists to redirect users to the canonical aiir package. Installing it will automatically install aiir as a dependency.

Metadata

Release files for inference-receipts 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-receipts 0.0.1
File Size Uploaded Provenance
inference_receipts-0.0.1.tar.gz 1.7 kB Without provenance Details

Built distribution (wheel)

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

Total release size: 3.9 kB

Release files / inference_receipts-0.0.1.tar.gz

Download URL inference_receipts-0.0.1.tar.gz
Size 1.7 kB
Tags Source
SHA-256 checksum
How to use checksums
ac89b16883557af25c466f3adaec5416393db6da2f49965d30bdb228fcdd33b8
BLAKE2b-256 checksum
How to use checksums
9f34d380f5392f69f0f92cb980200e2f61e864fcbe12481ff37dfa47bd3b5f88
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.11.0rc1

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

Download URL inference_receipts-0.0.1-py3-none-any.whl
Size 2.2 kB
Tags Python 3
SHA-256 checksum
How to use checksums
1235e0973aca4d419962a979adcaccd1a6527d242e933c2f9ec4f02970309b93
BLAKE2b-256 checksum
How to use checksums
057063217e03f773b491c2fb67837d6f68d0a624049c39369c25cbf48f96cc9b
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.11.0rc1

Security for inference-receipts 0.0.1

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0.0.1 This release

2 release files No provenance

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