TonicAI/tonic_validate
Metrics to evaluate the quality of responses of your Retrieval Augmented Generation (RAG) applications.
Provides 15+ built-in metrics (answer relevance, hallucination detection, context precision) with configurable LLM backends (OpenAI, Anthropic, etc.) and supports custom metric implementations. Operates as a Python framework that processes question-answer-context triplets through chainable metric evaluators, with optional cloud integration for result visualization and tracking. Integrates with CI/CD pipelines via GitHub Actions and pairs with Tonic Textual for preprocessing unstructured data into RAG-optimized formats.
324 stars. No commits in the last 6 months.
Stars
324
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31
Language
Python
License
MIT
Category
Last pushed
Jul 10, 2025
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