embeddings

Curated aesthetic embedding collection for Stable Diffusion — style transfer, quality scoring & visual fine-tuning

Taxonomy Completion with Embedding Quantization and an LLM-based Pipeline: A Case Study in Computational Linguistics

Transformers PHP is a toolkit for PHP developers to add machine learning magic to their projects easily.

Kikiola is a high-performance vector database written in Go.

Face similarity search

Production-ready memory framework for AI agents. Dual-agent synthesis, self-evolution, composite scoring, multi-tenant isolation. REST API, Python SDK, CLI.

Lightning-fast RAG for AI agents. ONNX-powered, 4-layer fusion, MCP server. No PyTorch.

Persistent semantic memory server for MCP - Give your AI long-term memory that survives across conversations. Lightweight Python server with SQLite storage and semantic search.

LanceDB C# SDK

High-performance Holographic Memory System (HMS) for Node.js, powered by Rust. This library implements Vector Symbolic Architectures (VSA) using Binary Spatter Code (BSC) to enable semantic search, analogical reasoning, and associative memory at scale.

Elysium Knowledge Repository is an open source initiative to embed all of Humanity's multi-modal knowledge and wisdom.

Code associated with the blog post titled, "Fine-Tuning BGE Embeddings Using Synthetic Data from Amazon Bedrock"

AI-native NoSQL + vector database with built-in semantic search for RAG, AI agents & LLM memory — the async Python client. Self-hosted Pinecone alternative.

This project aims to provide an efficient and scalable API for embedding and storing vectors, leveraging the power of FastAPI, Langchain framework and a vector database such as Chroma.

⚡ Vectro: Lightning-fast embedding quantization. Hit 12M+ vec/s throughput (4.85× faster than FAISS C++) while drastically cutting memory footprint for vector databases and local AI research.

A lock-free, in-memory fuzzy search engine for Kotlin Multiplatform. L2-normalized sparse vector embeddings with O(1) cosine similarity — handles typos, transpositions, and blind continuation. Zero-allocation search via primitive arrays, reactive StateFlow results, and instant cold-start via JSONL import/export.

A Model Context Protocol (MCP) server that provides agentic search capabilities with support for vector search using Qdrant, full-text search using TiDB, or both combined.

OpenViking knowledge base integration for nanobot — RAG augmentation, semantic search, vector embeddings, document indexing. Free models on SiliconFlow.

Local AI server with persistent memory, RAG, and multi-backend inference (MLX / llama.cpp / Ollama). Runs entirely on your machine — zero data sent to external services.