vector-embeddings

Enterprise-grade (40m+ LOC) codebase intelligence, zero-setup, local & private Plugin/Skill/Extension or MCP: hybrid semantic search, polyglot dependency graphs, symbol-level impact analysis & call-flow, interactive HTML viewer, cross-project & branch-aware search, DB/API/infra knowledge. 61% less tokens, 84% fewer calls, 37x faster. Cloud in beta.

local-first semantic code search engine

Shared Single-file memory layer for all your agents, sub mili-second RAG over text, photo and video on Apple Silicon.. No Server. No API. One File. Pure Swift

🔎 SimilaritySearchKit is a Swift package providing on-device text embeddings and semantic search functionality for iOS and macOS applications.

Turn your images and videos into a personal knowledge base

Browser-local AI code Q&A engine. Chat with your codebase, ensure privacy, and optimize LLM collaboration.

Memory for AI that works like yours—local, instant, persistent. 13x faster than Pinecone, 5x leaner than RAG. Finds what RAG misses. Zero cloud, zero cost.

Next-token prediction in JavaScript — build fast language and diffusion models.

Browse the top 10,000 packages on PyPI with the help of vector embeddings

⚡ Super fast clustering for high-dimensional vectors on CPUs (x86, ARM) and GPUs — for Python and C++. Faster clustering of vector embeddings than FAISS

YouTubeGPT • AI Chat with 100+ videos ft. YouTuber Marques Brownlee (@ MKBHD) ⚡️🔴🤖💬

Automatos AI: Open-source platform for advanced context engineering and multi-agent orchestration in enterprise automation. Built on frontier research in RAG, vector embeddings, cognitive tools, emergent symbols, and neural field theory—powered by FastAPI, Next.js, and PostgreSQL.

AI chat over the US Constitution 📜 💬 🇺🇸

.NET library for local embedding generation using ONNX and Microsoft.Extensions.AI

YouTubeGPT • AI Chat with 100+ videos ft. YouTuber Matt Wolfe (@mreflow) 🐺🟣🤖💬

a vector embedding database with multiple storage engines and AI embedding integrations

AI pipeline built with the honc and workers-ai. vector embeddings, web scraping and processing with Cloudflare Workflows (beta)

Semantic QA with a markdown database: Query any markdown file using vector embedding, Pinecone vector database and GPT (langchain). A weaker version of privateGPT

UC Berkeley CS186 AI Chatbot 🤖 🖥️ 🐻

rudradb-opin-examples is for example implementations of the pip install rudradb-opin