2 docs tagged with "embeddings"

Retrieval-Augmented Generation chatbot backed by MongoDB Atlas Vector Search. Ingest your own documents, embed them with OpenAI, and answer questions with $vectorSearch — your documents and their embeddings live in one database, no separate vector store. The Atlas-native companion to the pgvector AI RAG Chatbot.

Retrieval-Augmented Generation chatbot backed by Postgres + pgvector. Ingest your own documents, store OpenAI embeddings alongside them, and answer questions using only your data — no third-party vector DB, no proprietary cloud, nothing leaves your infrastructure. Includes seed, ingest, chat, history, and delete endpoints.