使用autoevals对可重用的评估器提示和指标对模型输出进行评分
Apply reusable evaluators to model outputs when you need lightweight scoring, rationale capture, or quick eval loops in code.
Prerequisites
Python or Node.js, access to an OpenAI-compatible model endpoint or Braintrust proxy
Installation
Use the upstream install or setup path that matches your environment:
- npm install autoevals
- pip install autoevals
- npx braintrust run example.eval.js
- To install the development dependencies, run make develop, and run source env.sh to activate the environment. Make a .env file from the .env.example file and set the environment variables. Run direnv allow to load the...
Requirements and caveats from upstream:
- Python 3.9 or higher
- Compatible with both OpenAI Python SDK v0.x and v1.x
- ### Python
Basic usage or getting-started notes:
- project but are implemented so you can flexibly run them on individual examples, tweak the prompts, and debug
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- Source: https://github.com/1991513ccie-png/skills
- Extracted from upstream docs: https://raw.githubusercontent.com/braintrustdata/autoevals/HEAD/README.md
Documentation
- https://github.com/1991513ccie-png/skills
