Discussion in r/LocalLLaMA about finding a self-hosted, local RAG (Retrieval Augmented Generation) solution for large language models, allowing users to experiment with different prompts, models, and retrieval rankings. Various tools and resources are suggested, such as Open-WebUI, kotaemon, and tldw.
A mini python based tool designed to convert various types of files and GitHub repositories into LLM-ready Markdown documents with metadata, table of contents, and consistent heading styles. Supports multiple file types, handles zip files, and has GitHub integration.
A post discussing new techniques developed for parsing and searching PDFs, focusing on turning them into a hierarchical structure for RAG search. The approach involves dynamically generating chunks for searches, sending headers and sub-headers to the Language Model along with relevant chunks.
