Metadata-Version: 2.4
Name: guardrails-ai-qa-relevance-llm-eval
Version: 0.0.2
Summary: Makes a second request to the LLM, asking it if its original response was relevant to the prompt.
Author-email: Guardrails AI <contact@guardrailsai.com>
License-Expression: MIT
Project-URL: Homepage, https://guardrailsai.com
Project-URL: Repository, https://github.com/guardrails-ai/guardrails-hub/tree/main/qa_relevance_llm_eval/py
Project-URL: Documentation, https://guardrails-ai.github.io/guardrails-hub/autoapi/guardrails_ai/qa_relevance_llm_eval/index.html
Requires-Python: <4,>=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: guardrails-ai>=0.4.0
Provides-Extra: dev
Requires-Dist: ruff; extra == "dev"
Requires-Dist: pytest; extra == "dev"
Requires-Dist: coverage>=7.6.12; extra == "dev"
Requires-Dist: pyright[nodejs]>=1.1.396; extra == "dev"
Dynamic: license-file

# guardrails-ai-qa-relevance-llm-eval

Makes a second request to the LLM, asking it if its original response was relevant to the prompt.

## Installation

```bash
pip install guardrails-ai-qa-relevance-llm-eval
```

This validator ships local models. After installing, run the post-install step to download them:

```bash
python -m guardrails_ai.qa_relevance_llm_eval.post_install
```

## Usage

```python
from guardrails import Guard
from guardrails_ai.qa_relevance_llm_eval import QARelevanceLLMEval

guard = Guard().use(QARelevanceLLMEval)
```

## License

MIT — © Guardrails AI.
