Semantic code searcher and codebase utility

AI semantic search for Zotero, with a built-in MCP server for AI agents (Claude Code, Codex). Find papers by meaning. 100% local and private.

Agent Fusion is a local RAG semantic search engine that gives AI agents instant access to your code, documentation (Markdown, Word, PDF). Query your codebase from code agents without hallucinations. Runs 100% locally, includes a lightweight embedding model, and optional multi-agent task orchestration. Deploy with a single JAR

Enhanced MCP server for semantic code search with call-graph proximity, recency ranking, and find-similar-code. Built for AI coding assistants.

Semantic search web app using the Large Language Model (LLM) Cohere for embeddings to match context and meaning, rather than keywords.

A semantic search application built using FastAPI, Pinecone, and Sentence Transformers to match questions from Quora dataset.

The Zero-Overhead, Agent-Ready AI Memory Backbone. Ultra‑fast, SIMD‑accelerated semantic search engine built on Java Vector API + modern JVM technologies.

Production-ready semantic vector search for Django — searches across FK, M2M, and reverse relations by traversing your model graph. Pluggable backends: ChromaDB, FAISS, Qdrant.

An advanced semantic search and knowledge retrieval framework designed for academic research and intelligent information discovery.

An open-source platform democratizing Generative AI Applications. Build and deploy AI-powered tools without extensive expertise. Features flexible data integration, semantic search, and LLM integration. Create sophisticated AI applications using your private knowledge bases.

🤖 That's a simple LLM semantic search that implements RAG concepts with help of LangChain and OpenAI API.

The goal of this project is to build a small Discord Bot that search messages in discord channels. It does semantic search along simple word search. It is compatible with multiple LLM Semantic Models, like Bert or e5 for instance.

Get your Error Solution by just Pasting Error.

Designed specifically for content designers working with AI systems. Materials include practical examples, templates, checklists, code samples, and actionable frameworks

CitOmni knowledge base package for structured ingest, chunking, hybrid retrieval, synonym expansion, and grounded AI answers.

AI-Spaces integrates React, Redux Toolkit, and FastAPI to build an advanced platform for interacting with AI models. Users can input questions or upload documents to receive precise, AI-driven summaries, creating a seamless and intuitive experience for modern web applications.

AI-powered repository intelligence and failure-aware debugging foundation.

A production-ready, enterprise-grade Agentic RAG ingestion pipeline built with n8n, Supabase (pgvector), and AI embeddings. Implements event-driven orchestration, hybrid RAG for structured and unstructured data, vector similarity search, and multi-tenant architecture to deliver client-isolated, retrieval-ready knowledge bases.

RAG-powered file organizer using sentence-transformers and KMeans clustering with a Gradio chatbot for semantic document search

Outil d'assistance à candidater : scraping multi-sources, filtre local, ranking sémantique, génération CV+lettre+email, brouillons Gmail (sans envoi).