RAGWire and IntGathering-x-RAG--BlazingDocs
These two tools are competitors, with laxmimerit/RAGWire offering a more comprehensive, production-grade toolkit for multi-format document ingestion into Qdrant with advanced features, while S0lkar/IntGathering-x-RAG--BlazingDocs focuses on batch querying for documents, likely as a simpler RAG implementation.
About RAGWire
laxmimerit/RAGWire
Production-grade RAG toolkit — ingest PDFs, DOCX, XLSX into Qdrant with LLM metadata extraction, hybrid search, and SHA256 deduplication.
Supports multi-format ingestion via MarkItDown (PPTX, XLSX, DOCX, PDFs), markdown-aware recursive chunking, and customizable LLM-based metadata extraction through YAML configuration. Provides pluggable embedding providers (Ollama, OpenAI, HuggingFace, Google, FastEmbed) with Qdrant's dense/sparse/hybrid search, plus directory-level ingestion with file and chunk-level SHA256 deduplication. Designed as modular Python components with environment variable substitution for production deployments.
About IntGathering-x-RAG--BlazingDocs
S0lkar/IntGathering-x-RAG--BlazingDocs
RAG-based tool for document batch querying.
Related comparisons
Scores updated daily from GitHub, PyPI, and npm data. How scores work