embeddings

Vectrain is a high-performance, modular, plug-and-play RAG pipeline that ingests data, generates vector embeddings, and stores them in vector databases for semantic search, recommendations, and analytics.

PostgreSQL TurboQuant Index for PGVector

Persistent semantic memory for AI agents on Raspberry Pi 5 — local Qdrant + MCP, no cloud, ~3s per query

PegasusX: The Future of Multimodal Embeddings 🦄 🦄

A 5-way embedding model for text, audio, image, video, and 3D point clouds.

Harvest-first Rust toolkit for open data metadata: sync 300+ portals (CKAN, DCAT, SPARQL, data.json, Socrata, OpenDataSoft, ArcGIS, CSW, STAC ) into PostgreSQL, add optional local embeddings and semantic search. Ceres Open Data Index (2M+ datasets) on Hugging Face.

Vectra is a unified Ruby client for vector databases. Write once, switch providers seamlessly.

Decentralized vector database on Bittensor — content-addressed semantic memory for AI

High-performance LLM query cache with semantic search. Reduce API costs 80% and latency from 8.5s to 1ms using Redis + Qdrant vector DB. Multi-provider support (OpenAI, Anthropic).

Elixir RAG library with multi-LLM routing (Gemini, Claude, OpenAI, Ollama), GraphRAG, knowledge graphs, modular retrievers/rerankers, composable pipelines, pgvector integration, advanced chunking, and tool-using agents. Fork of bitcrowd/rag.

The data layer for AI with Vector, Graph and Vector-Math built into one single rust engine

🧠 Multimodal Retrieval-Augmented Generation that "weaves" together text and images seamlessly. 🪡

chew through any source into clean datasets! a fast ingestion, RAG & fine-tuning toolkit

Visual tool to compare 6 RAG chunking strategies side-by-side with grading and query selection

AI powered Google Calendar events summarizer built using Next.js, Supabase and Google Gemini

NeuroLens is a premium, state-of-the-art Document Retrieval-Augmented Generation (RAG) system. It combines an immersive, holographic, sci-fi-themed React frontend with a high-performance FastAPI backend.

Deterministic context database for AI agents. Same query → same context, every time.

This is a repository to let you know the implementation of a basic RAG pipeline using LangChain in Supabase Edge Functions.

Persistent memory and identity protocol for AI systems with evidence-aware recall and inspectable memory.

Memory architectures that evolve with your agent