embeddings

The Postgres development platform. Supabase gives you a dedicated Postgres database to build your web, mobile, and AI applications.

Persistent Context Across Sessions for Every Agent – Captures everything your agent does during sessions, compresses it with AI, and injects relevant context back into future sessions. Works with Claude Code, OpenClaw, Codex, Gemini, Hermes, Copilot, OpenCode + More

This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.

Open-source LLM knowledge platform: turn raw documents into a queryable RAG, an autonomous reasoning agent, and a self-maintaining Wiki.

A vector index built on TurboQuant, written in Rust with Python bindings

LangChain4j is an idiomatic, open-source Java library for building LLM-powered applications on the JVM. It offers a unified API over popular LLM providers and vector stores, and makes implementing tool calling (including MCP support), agents and RAG easy. It integrates seamlessly with enterprise Java frameworks like Quarkus and Spring Boot.

💡 All-in-one AI framework for semantic search, LLM orchestration and language model workflows

The all-in-one, open-source backend platform for agentic coding. InsForge gives your coding agent database, auth, storage, compute, hosting, and AI gateway to ship full-stack apps end-to-end.

100+ Chinese Word Vectors 上百种预训练中文词向量

Retrieval and Retrieval-augmented LLMs

Private chat with local GPT with document, images, video, etc. 100% private, Apache 2.0. Supports oLLaMa, Mixtral, llama.cpp, and more. Demo: https://gpt.h2o.ai/ https://gpt-docs.h2o.ai/

SeaTunnel is a multimodal, high-performance, distributed, massive data integration tool.

Open Lakehouse Format for Multimodal AI. Convert from Parquet in 2 lines of code for 100x faster random access, vector index, and data versioning. Compatible with Pandas, DuckDB, Polars, Pyarrow, and PyTorch with more integrations coming..

Postgres with GPUs for ML/AI apps.

Memory library for building stateful agents

The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.

Fast and Accurate Code Search for Agents. Uses 99% fewer tokens than grep+read

High-performance data engine for AI and multimodal workloads. Process images, audio, video, and structured data at any scale

Find related notes and excerpts while writing. Your link building copilot displays relevant content in graph + list view. A local embedding model powers semantic search. Zero setup. No API key.

AutoRAG: Now your agent can find anything in your computer. It gets smarter if you are using it frequently.