Show HN: RAG-corpus-profiler – A linter for RAG datasets (dedup, PII, quality) (github.com)

The newly announced RAG Corpus Profiler is a linter specifically designed for enhancing the data quality of Retrieval-Augmented Generation (RAG) datasets. This pre-flight audit tool addresses critical issues such as semantic duplicates, personally identifiable information (PII) leaks, and low-information noise that can derail RAG implementations. By auditing various formats, including JSON and DOCX, the profiler visualizes data health and estimates costs before ingesting large datasets into vector databases like Pinecone and Weaviate. Significant for the AI/ML community, this tool automates crucial checks and integrates smoothly into CI/CD pipelines, offering an exit code mechanism to prevent bad data from progressing to production. Its features include a semantic deduplication engine using all-MiniLM-L6-v2, a PII scanning capability to prevent GDPR violations, and an ROI calculator to reduce embedding costs by 15-30%. Moreover, the gap analysis function can highlight blind spots in the knowledge base, guiding engineers and product managers in ensuring comprehensive coverage for user queries. By addressing these foundational data quality issues, RAG Corpus Profiler helps streamline the development of robust AI applications, enhancing their performance and reliability.