Tag: #embedding
8 packages • ⭐ 10,742 total stars
A Low-Code MCP Framework for Building Complex and Innovative RAG Pipelines
The AI-native database built for LLM applications, providing incredibly fast hybrid search of dense vector, sparse vector, tensor (multi-vector), and full-text.
Redis Vector Library (RedisVL) -- the AI-native Python client for Redis.
Java AI application development framework (supports LLM-tool,skill; RAG; MCP; Agent-ReAct,Team-Agent). Compatible with java8 ~ java25. It can also be embedded in SpringBoot, jFinal, Vert.x, Quarkus, a
Brain-inspired knowledge graph: spreading activation, Hebbian learning, memory consolidation.
Docling simplifies document processing, parsing diverse formats — including advanced PDF understanding — and providing seamless integrations with the gen AI ecosystem
The highest-scoring AI memory system ever benchmarked that isn't reliant on LLM reranking. And it's free & burns less tokens.
🚀 Build memory and retrieval infrastructure for ReasonKit, enhancing data management and access for your applications with ease and efficiency.