Embeddings GitHub Repositories (2026) · Open Source Tools

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

ID-based RAG FastAPI: Integration with Langchain and PostgreSQL/pgvector

Compute Sentence Embeddings Fast!

Pretrained text classifiers you can run and retrain on CPU

Local code search combining BM25, vector similarity, and cross-encoder reranking. Parses 60+ languages with tree-sitter, runs entirely offline, and returns structured results with file paths, line ranges, and symbol metadata. Built in Rust.

Agentic Voice Notes for iPhone and macOS - Rust, Dioxus, LanceDB + RIG + SQLite

Local persistent memory store for LLM applications including claude desktop, github copilot, codex, antigravity, etc.

The EMBL-EBI Ontology Lookup Service (OLS)

Local AI-powered document search and editing with first-in-class hybrid retrieval, LLM answers, WebUI, REST API and MCP support for AI clients.

llama.cpp (GGUF LLMs) and llava.cpp (GGUF VLMs) for ROS 2

Rust library for generating vector embeddings and reranking locally!

SQL as a Function for Rust — an embedded SQL database with a typed ORM and pluggable LMDB/RocksDB storage.

RushDB is a self-describing, graph-native database that helps AI agents reason over data with confidence: progressively introspect what's queryable—without guesswork.

Long-term memory for any AI agent. One Rust binary, offline, 98.2% recall@5 on LongMemEval-S. Self-host free or use Uteke Cloud.

Agent skills for Qdrant vector search: scaling, performance optimization, search quality, monitoring, deployment, model migration, version upgrades, and SDK usage across Python, TypeScript, Rust, Go, .NET, Java

Local-first code intelligence for AI assistants. Turns your codebase into a knowledge graph your AI can query, navigate, and remember. 25 MCP tools.

LLPhant - A comprehensive PHP Generative AI Framework using OpenAI GPT 4. Inspired by Langchain

Ollama SDK for .NET

Pure Rust PDF library for AI/RAG: structure-aware chunking, no ML, no C deps.

Established strong JEV based natural language to SQL performance and well-covered semantic operators for PostgreSQL(PG) with optimized cost and latency. Reusable evidence, with native execution, parallel plans and explainable embeddings in development preview.