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

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.

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

Operational Database for AI Agents Provide causality lineage, DAG, and State Replay , build to make AI Agents auditable Reliable and EU AI ACT compliant

.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

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

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

This tool provides a fast and efficient way to convert text into vector embeddings and store them in the Qdrant search engine. Built with Rust, this tool is designed to handle large datasets and deliver lightning-fast search results.

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.

Flask API for generating text embeddings using OpenAI or sentence_transformers

The open-source, self-hosted alternative to NotebookLM.

Build an AI Driven Portfolio App with NextJS and Tailwind CSS. We will learn advance AI Technologies like vector embedding and vector databases along with how to work with Open AI's APIs. This is an amazing project to impress recruiters a lot and showcase your skillset.