Knowledge RAG

A turnkey solution for building retrieval-augmented generation (RAG) systems that can chat with your documents. AnythingLLM provides an intuitive interface for uploading documents and asking questions, while Qdrant serves as the high-performance vector database that stores document embeddings for semantic search. LiteLLM acts as a universal gateway that can connect to both local models (via Ollama) and cloud APIs, giving you flexibility in model selection. This combo solves the fundamental challenge of making your private documents queryable through natural language, enabling you to build knowledge bases that can answer complex questions by understanding context and relationships across your entire document collection.