semantic-search

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.

Easily create semantic search based LLM applications

Implementation of Retrieval Augmented Generation model in typescript with Gemini LLM

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

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

AI News Scraper & Semantic Search: A Python application that scrapes news articles, uses GenAI to generate summaries and identify topics, and provides semantic search capabilities through vector embeddings

No longer maintained, please see the TypeScript client

Context Runtime — a database query planner for LLM context. Decides what a model sees before it answers; plans it, runs it through reused substrate, and learns from the outcome.

Using Semantic Kernel to obtain answer from a PDF document, with embeddings stored in Redis and HuggingFace to create embeddings.

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.

sovereign embedded vector database, single-file .nest container with content-addressable citations, reproducible builds, and offline-first model verification.

A standalone memory engine for AI agents in .NET, with hybrid retrieval, graph memory, pluggable providers, and behavior-shaped memories.

The blazingly fast in-memory vector database 🚀

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.

The most capable Calibre MCP server — full read/write tools plus multilingual semantic search over your whole ebook library or a single book. For Claude & any MCP client.

Intelligent Image Gallery with Uploads, Deduplication, and Text-Based Search Using Vector DB Qdrant

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

A personal AI knowledge assistant powered by RAG, semantic search, and document understanding for context-aware answers.