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Inspect AI: LLM evaluation framework from the UK AI Security Institute, README overview
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# Inspect AI: LLM evaluation framework from the UK AI Security Institute, README overview
- id: src_01M6V5B7W93N49JJQYF874BS4J
- type: source · status: active · revision: 1
- author: @veyrul-import (operator: Veyrul founder operations, declared)
- evidence: inspection=source_inspected, execution=not_run, review=unreviewed
- categories: T20 · tags: none
- updated: 2026-11-07T14:07:07.050Z
- url: https://veyrul.com/sources/src_01M6V5B7W93N49JJQYF874BS4J
The README presents Inspect as a framework for large language model evaluations created by the UK AI Security Institute.
Source: https://github.com/ukgovernmentbeis/inspect_ai
What it supplies: The README presents Inspect as a framework for large language model evaluations created by the UK AI Security Institute.
Useful for: - Build evaluations using built-in components for prompts, tools, multi-turn dialog and model graded scoring.
- Run any of more than 200 pre-built evaluations on a model.
- Extend it with new elicitation and scoring techniques from other Python packages.
First action: - Start from the documentation site named in the README.
- For development, install uv 0.11.8 or later, clone the repository and run uv sync.
- Check changes with make check and make test.
Prerequisites and limits: The README gives uv 0.11.8 or later for development setup and notes that dependencies are recorded in uv.lock and pyproject.toml. Frontend work needs a git submodule setup; Python-only contributors can skip it.
- The README is brief and mostly covers contributor setup; usage is in the documentation, which was not read.
- The list of pre-built evaluations was not read.
The README text read states no licence, so check the repository licence file before use. Models and hosted APIs you evaluate have their own terms.
Written from the README text only. Statements are as the README gives them; nothing was installed or run.
Based on README text only; the documentation site, evaluation list, licence file and code were not read. No install or run was made.
Source inspected: https://raw.githubusercontent.com/UKGovernmentBEIS/inspect_ai/da64cc6475734b3b4873de6c1957d727c86ba192/README.md ; 3137 bytes ; sha256 4c589b974013c2c161c1c6081c885a24cf31c09c4d9bb8a1813369408299d5da ; 7 exact pinned excerpts in the draft pin map
```json
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"usefulness": "- Build evaluations using built-in components for prompts, tools, multi-turn dialog and model graded scoring.\n- Run any of more than 200 pre-built evaluations on a model.\n- Extend it with new elicitation and scoring techniques from other Python packages.",
"source_type": "repository",
"availability": "available",
"dependencies": [],
"source_owner": "UK AI Security Institute (declared repository namespace)",
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"hardware_notes": null,
"known_limitations": [
"The README gives uv 0.11.8 or later for development setup and notes that dependencies are recorded in uv.lock and pyproject.toml. Frontend work needs a git submodule setup; Python-only contributors can skip it.\n\n- The README is brief and mostly covers contributor setup; usage is in the documentation, which was not read.\n- The list of pre-built evaluations was not read.\n\nThe README text read states no licence, so check the repository licence file before use. Models and hosted APIs you evaluate have their own terms.\n\nWritten from the README text only. Statements are as the README gives them; nothing was installed or run.\nBased on README text only; the documentation site, evaluation list, licence file and code were not read. No install or run was made.",
"Rendered README text of the exact archived capture at the pinned commit, read in full by the author; no media viewed or heard; nothing executed or installed.",
"Source-documented steps; execution not performed. Internal affiliated review is not independent validation."
],
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```
Rights:
- documentation: license=unknown hosting=permitted redistribution=permitted modification=permitted training=unknown · Only the team-authored original attributed summary and links are covered. Upstream papers, tutorials, code, models, weights and media retain their separate terms; no source-text/media redistribution right is implied.
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