sematic-search

Local-first 3-in-1 AI memory layer & MCP server for Claude Code, Codex, Grok, Gemini, VS Code and Cursor. Fuses session history, codebase indexing & concept graphs in SQLite. Enables zero-cloud, privacy-first context & instant recall, supports multi-agent swarms.

Search your files across your devices with natural language | 使用自然语言跨设备搜索文件的桌面应用

Build Semantic Search with S-BERT and Fine-tune your model in unsupervised way

A Repository-Aware, Knowledge-Learning local MCP that understands your codebase in Real Time powered by Hybrid Semantic + Full-Text Engine, both supports claude code and codex

An easy-to-use vector database.

Vim style TUI with Repository-Aware, Self-Evolving Agent That Understands Codebase in Real Time powered by Hybrid Semantic + Full-Text Engine

LLM-assistant that searches PubMed, retrieves abstracts or full-texts, and generates answers using OpenAI ChatGPT. Features a custom RAG pipeline, semantic search, and knowledge graph generation.

Agentic RAG with LangGraph 🔥

TalaDB - The embedded vector and document database for on-device AI.

A Local AI PDF Assistant built using Streamlit, Ollama, Qdrant and RAG.

AI-focused news aggregator that ranks, summarizes, and deduplicates articles about artificial intelligence in real time.

A .NET-based AI project leveraging Retrieval-Augmented Generation (RAG) and OpenAI to provide efficient, intelligent search capabilities for team documentation.

Self-hosted, open-source Moorcheh - run semantic search, RAG, and document indexing on your own infrastructure with Docker.

Your Knowledge Partner for Academic Discovery

Provider-free persistent cognition for AI agents: verified memory, failure frontiers, proof-gated branches, and reversible learning.

A RAG (Retrieval-Augmented Generation) pipeline implementation using .NET 10, Gemini AI, and Qdrant Vector Database.

Hybrid AI assistant combining Keras intent classification, FAISS vector semantic memory, and a self-learning LLM pipeline.

Amgix Now is a high-performance hybrid search engine from the Amgix family

AI-powered developer documentation search engine using RAG (Retrieval-Augmented Generation) with FAISS, Sentence Transformers, and local LLM (Ollama). Enables fast, context-aware answers from Python, Django, Flask, FastAPI, NumPy, and Pandas docs.