Retrieval-Augmented Generation

Teach an LLM about your documents in three steps: ingest them, ask questions, explore the knowledge graph.

1. Ingest Documents

Hierarchical chunking, contextual prefixes, embeddings, and entity extraction — watch the write-path pipeline build a searchable corpus.

Chat with your corpus using four retrieval modes — vector search, small-to-big, entity graph, or all three fused with RRF.

Walk the entity graph interactively — find paths, expand neighborhoods, and jump back into chat from any node.

Думаете, этот паттерн можно сделать лучше? Расскажите как.