Qdrant Memories
NormalDescription
A memory example and toolkit based on the Qdrant vector database, demonstrating how to store conversations, documents, and events for semantic recall by agents.
A memory example and toolkit based on the Qdrant vector database, demonstrating how to store conversations, documents, and events for semantic recall by agents.
A high-performance graph database built on GraphBLAS, optimized for LLM and GraphRAG scenarios with real-time knowledge graph construction and querying for graph-structured AI agent retrieval.
An open-source embedded retrieval library for multimodal AI with zero server configuration, using the Lance columnar format for efficient vector search and filtering, ideal for agent memory and RAG applications.
Open-source vector similarity search extension for PostgreSQL, enabling native vector storage and ANN retrieval in relational databases, a foundational component for building agent memory and RAG systems.
Data processing, indexing, and retrieval service examples from the LlamaIndex ecosystem, helping developers integrate external knowledge into agent workflows.