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Open-source BGE series embedding models and retrieval tools from BAAI, providing state-of-the-art text embeddings and rerankers for Chinese and English, widely used in RAG systems and agent retrieval pipelines.
Open-source BGE series embedding models and retrieval tools from BAAI, providing state-of-the-art text embeddings and rerankers for Chinese and English, widely used in RAG systems and agent retrieval pipelines.
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.
LightRAG is a simple and fast Retrieval-Augmented Generation framework using graph-enhanced retrieval, published at EMNLP 2025.
KAG is a logical form-guided reasoning and retrieval framework based on OpenSPG engine and LLMs for building logical reasoning and factual Q&A solutions for professional domain knowledge bases, effectively overcoming the limitations of traditional RAG vector similarity models.
A production-ready Agentic RAG system with RESTful API, featuring multimodal document ingestion, hybrid search, knowledge graph construction, and agent-driven retrieval-augmented generation workflows.