The Excellence
Directory Platform Template

A Pythonic vector database offering comprehensive CRUD operations with robust scalability through sharding and replication. Built on DocArray for vector search and Jina for efficient index serving, deployable from local to cloud environments.

State-of-the-art Python framework for sentence, text, and image embeddings using siamese BERT networks, providing access to 15,000+ pre-trained models for semantic search, similarity comparison, and clustering.

Open Source RAG Framework designed to be 'Conventional but Configurable', streamlining the creation of RAG applications with efficient data management, embeddings generation, and vector storage.

Python toolkit for efficient RAG research providing 36 pre-processed benchmark datasets and 23 state-of-the-art RAG algorithms in a unified, modular framework for reproduction and development.

Programming framework for RAG and AI applications with cutting-edge optimization capabilities, featuring the lowest framework overhead and automatic improvement based on example data.

Python implementation of Nearest Neighbor Descent for k-neighbor-graph construction and ANN search. Targets 80%-100% accuracy with fast performance and supports wide variety of distance metrics. This is an OSS library.

All-in-one open-source AI framework for semantic search, LLM orchestration and language model workflows. Combines vector indexes (sparse/dense), graph networks and relational databases. This is an OSS framework.

Lightweight Python package for storing and retrieving text using chunking, embeddings, and vector search. Powers AI features in Kagi Search with low latency and small memory footprint. This is an OSS library.

Milvus Lite is a lightweight, pip-installable variant of the Milvus vector database that runs as a library in notebooks or laptops, ideal for learning, experimentation, and rapid prototyping of AI and vector search applications.