semantic-search

🧠 AI Second Brain — 100% Local Knowledge Management Private, self-hosted second brain. Store, search, and synthesize documents, images, and ideas with local LLMs (LLaVA, CLIP) and PostgreSQL + pgvector. Features multimodal search, knowledge graphs, gDrive streaming, and real-time analysis — all offline, no API keys, no cloud, no limits.

Local-first vector similarity search for Jazz Tools

Serverless, lightweight, and fast vector database on top of DynamoDB

Edge Vector search engine with Vulkan GPU acceleration, hierarchical indexing (HRM2), and native LangChain integration. Gaussian splat-based architecture for similarity search on resource-constrained devices.

Semantic search knowledge base for MCP-enabled AI assistants. Index local files or GitHub repos, query with natural language. Built on LanceDB vector storage. Works with Claude Desktop, Cursor, and other MCP clients.

Self-hosted AI knowledge base with hybrid semantic search (pgvector + FTS + RRF), MCP server, multi-provider LLM inference (Ollama, OpenAI, OpenRouter, llama.cpp), multimodal ingestion (vision, audio transcription, speaker diarization), and knowledge graph. Rust + PostgreSQL.

The official Rust client for the Pinecone vector database

GraphRAG over any codebase — a Neo4j knowledge graph of code entities plus a 3072-dim vector index, bridged so one natural-language query walks structure and ranks by meaning. Python · Neo4j · OpenAI embeddings · Streamlit · Docker. Hybrid semantic + structural code search.

An open source framework for Retrieval-Augmented System (RAG) uses semantic search helps to retrieve the expected results and generate human readable conversational response with the help of LLM (Large Language Model).

⚠️ DEPRECATED - Use https://github.com/SylphxAI/coderag instead

🧬 Self-optimizing vector database using MAP-Elites. 51x faster than ChromaDB, 82x faster than LanceDB, 100% recall. Auto-evolves optimal index configs via Quality Diversity.

Near-optimal vector quantization from Google's ICLR 2026 paper — 95% recall, 5x compression, zero preprocessing, pure Python FAISS replacement

🚀 Unified NLP Pipelines for Language Models

PostgreSQL-native semantic search engine with multi-modal capabilities. Add AI-powered search to your existing database without separate vector databases, vendor fees, or complex setup. Features text + image search using CLIP embeddings, native SQL joins, and 10-minute Docker deployment.

🧠 Predictable, embedded multimodal vector database & offline RAG engine for Edge AI (ARM64 / Zero-OOM). Built in C++20.

ChatGPT, embedding search, and retrieval-augmented generation for Squeak/Smalltalk

An intelligent research orchestration system that integrates large language models with scholarly data pipelines to enable contextual retrieval, cross-paper synthesis, and real-world knowledge extraction from scientific publications.

Evals framework for Information Retrieval Systems

Open-source, Python-first RAG platform with FastAPI APIs, LangGraph-native agents, pluggable vector stores (Qdrant/Weaviate/Milvus/pgvector/Elasticsearch), and multi-provider LLM support (OpenAI/Anthropic/Gemini/Ollama/vLLM).

A tool for performing semantic search within pdf documents leveraging sentence transformers.