TonicAI/tonic_validate
Metrics to evaluate the quality of responses of your Retrieval Augmented Generation (RAG) applications.
This tool helps evaluate the quality of responses from your AI applications that generate text based on retrieved information, like chatbots or intelligent assistants. You provide questions, the answers your AI gives, and the sources it used, and the tool outputs scores and insights into how accurate and truthful your AI's responses are. This is for anyone who builds or manages AI-powered knowledge systems and wants to ensure their AI provides reliable information.
324 stars. No commits in the last 6 months.
Use this if you need to systematically check if your AI assistant or RAG application is providing accurate, relevant, and non-hallucinated answers based on the information it's given.
Not ideal if you are looking to evaluate AI models that generate creative content or images, or if you don't have clear source documents for your AI's responses.
Stars
324
Forks
31
Language
Python
License
MIT
Category
Last pushed
Jul 10, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/rag/TonicAI/tonic_validate"
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