ragctl and rag-doctor
The CLI tool for managing and optimizing RAG pipelines and the agentic diagnostic tool for pinpointing RAG failures are complements, as the former provides general pipeline control and testing, while the latter offers specific, detailed root cause analysis when those pipelines encounter issues, allowing for more precise debugging within a managed workflow.
About ragctl
datallmhub/ragctl
A powerful CLI tool to manage, test, and optimize RAG pipelines. Streamline your Retrieval-Augmented Generation workflows from terminal.
This tool helps AI engineers and developers prepare various documents like PDFs, Word files, and images for use in Retrieval-Augmented Generation (RAG) applications. It takes raw documents, extracts text using advanced OCR, intelligently breaks them into meaningful chunks, and exports them in formats like JSON or directly into a vector store. This streamlines the crucial data preparation step for building robust RAG systems.
About rag-doctor
balavenkatesh3322/rag-doctor
🩺 Agentic RAG pipeline failure diagnosis tool. Tells you why your RAG failed — chunk fragmentation, retrieval miss, position bias, hallucination, or query mismatch — with a root cause ID and concrete fix. CLI + Python SDK + Ollama support.
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