semantic-search

khoj-ai/khoj

Your AI second brain. Self-hostable. Get answers from the web or your docs. Build custom agents, schedule automations, do deep research. Turn any online or local LLM into your personal, autonomous AI (gpt, claude, gemini, llama, qwen, mistral). Get started - free.

Tencent/WeKnora

Tencent's Go-based platform turns documents into RAG, agents and wikis — WeKnora is a Tencent open-source framework that converts raw documents into a queryable knowledge base, combining RAG retrieval, an autonomous reasoning agent, and a self-updating wiki. It ships with Chrome extension and WeChat Dialog integrations, aimed at teams building Q&A chatbots and internal knowledge tools.

xerj-org/xerj

A single Rust binary that gives AI coding agents real search — XERJ indexes code, docs, logs and PDFs locally for BM25, vector and hybrid search behind an Elasticsearch-compatible API. Its reference-coding feature lets agents like Claude Code or Cursor find and reuse solutions from similar open-source repos instead of re-reading files, cutting output tokens by up to 2.7x in testing.

arc53/DocsGPT

Self-hosted AI agents that answer strictly from your own documents — DocsGPT is a private, self-hosted platform for building AI agents and assistants grounded in your own docs, with a visual Agent Builder, deep research, document analysis, multi-model support and API connectors. A one-line install script makes it quick to run locally, aimed at teams wanting enterprise search without sending data to third parties.

memvid/memvid

A Single-File Memory Layer for AI Agents, No Database Needed — Memvid stores embeddings and knowledge in one portable, versioned file instead of a database, letting agents get instant retrieval and long-term memory offline. Rewritten in Rust with Python bindings, it targets teams wanting to drop complex RAG pipelines for something simpler and file-based.

neuml/txtai

A Single Framework Combining Vector Search, Graphs and LLM Agents — txtai bundles vector indexes, graph networks and relational databases into one embeddings database that powers semantic search, RAG and multi-model workflows. Rather than stitching together separate vector DB, graph and LLM tools, developers get a unified foundation for building autonomous agents and search-driven AI applications in Python.

cocoindex-io/cocoindex

Incremental indexing engine keeps agent context fresh — CocoIndex is a Rust-core, Python-exposed engine that re-syncs only the changed delta from codebases, Slack, meeting notes and docs into vector stores or knowledge graphs. It's built for teams running long-horizon AI agents or RAG pipelines that need continuously up-to-date context instead of full reindexing on every change.

deeplethe/utopia

A self-hosted world model that puts time and ontology at its core — Utopia is an open-source enterprise world model in Rust that pairs a bitemporal knowledge graph with pgvector-based semantic search. Unlike static knowledge graphs or vector stores, it builds time-awareness and ontology into its base layer, running conflict detection and reasoning as data arrives, fully offline for companies needing auditable, self-governed knowledge infrastructure.

ARahim3/DigUp

Search your computer by what's in your files: photos, PDFs, documents, recordings, videos and code. On-device on Mac, Windows and Linux, built on Google DeepMind's EmbeddingGemma 2.

asciimoo/hister

A personal, self-hosted search engine for your own browsing and files — Hister indexes full page contents from your browsing and local files, letting you search them again via web UI, terminal, or an AI assistant through MCP. It runs locally with no required configuration, supports importing browser history, bookmarks, and files, and installs via binary, Homebrew, or Docker.

Marker-Inc-Korea/AutoRAG

AutoRAG Reborn as a Personal Librarian Agent for Your Files — AutoRAG has pivoted from a Python RAG pipeline-optimization tool into AutoRAG 2.0, a TypeScript agent that acts as a personal librarian: it searches your computer, organizes files, and remembers key info on request. The original AutoRAG continues in the legacy/ folder with maintenance releases via PyPI, so existing RAG-pipeline users aren't stranded.

yoanbernabeu/grepai

Semantic Search & Call Graphs for AI Agents (100% Local)

yjid/kensaku

A Rust-based local search tool that reads inside files, images, and code — Kensaku is a fast, local file launcher that indexes not just filenames but the text inside documents, screenshots (via OCR), and code, searching 100,000 filenames in about a millisecond using ~12MB memory. It adds semantic search and exposes an MCP interface so AI agents can query your files directly, all without sending data off your machine.

byenzyme/enzyme

A local semantic index that lets coding agents cite your notes — Enzyme builds a local-first index of existing Markdown notes (folders, tags, links, dates) so agents like Claude Code or Codex can retrieve and cite related notes without sending everything to a frontier model. It claims 350x lower cost and 1000x faster search, targeting PKM/Obsidian users who want agent-aware semantic search over their own vault.

arvarik/contrack

Self-hosted contact management + tracking + online enrichment for your personal and professional needs 🐦‍⬛