MongoDB Atlas Unveils Vector Search for AI and Knowledge Base Integration
Summary
MongoDB Atlas introduces Vector Search, enabling AI and knowledge base integration by storing embeddings and vectors, setting up Galileo for observability, and utilizing MongoDB credentials, vector stores, and Galileo callbacks for hybrid search and AI workloads.
Key Points
- MongoDB Atlas Vector Search allows storing knowledge base inside MongoDB while enabling hybrid search and AI workloads
- Guide covers embedding and storing vectors in Atlas, setting up Galileo, and streaming LangGraph traces to Galileo for observability
- Demonstrates setting up MongoDB credentials, creating vector store, using Galileo callback, and adding callback to agent