Havuz

Open-source toolkit for reliable RAG pipelines: convert PDFs to Markdown, clean documents, inspect chunks, compare chunking strategies, and

AI-Powered Research Assistant for Academic Paper Discovery, Analysis, and Citation Intelligence

Handling 10M+ docs using RAG with zero hallucinatons

A context harness for AI agents: all your scattered context — code, memory, docs, databases, SaaS — in one searchable, browsable, file-like

2026 年编程导航 AI 编程实战新项目，基于 Taro + React + FastAPI + DeepSeek 的 AI 闯关学习小程序，支持一句话 / 文本主题 AI 出题、闯关答题与即时讲解、联网搜索增强、RAG 私有知识库出题、AI 生图配图、微信登录与通关复盘报告。

AI, fully local on your computer.

211 free visual cards about large language models, from tokenization to deployment. Full collection: 376 cards.

Self-hosted RAG platform for AI document search across GitHub, Notion, Google Drive, local files, and web sources with citations.

Microsoft Foundry Local - Workshop - Build AI apps locally with Foundry Local - RAG, agents, and multi-agent workflows in Python, JS, and C#

基于 Spring AI 2.0 的生产级 ERP 智能助手｜Production-ready ERP AI assistant with RAG, Tool Calling, chat memory, dynamic SQL tools, multi-tenancy and E

Preserve knowledge, sustain wisdom forever.

All-in-one local AI hub for Obsidian — LLM chat with vault tools, MCP servers, RAG, workflow automation, encryption, and edit history. Fully

RuvNet Brain — a downloadable, source-grounded brain for Claude Code over Reuven Cohen's (rUv's) RuvNet stack: RuVector/RVF, Ruflo, AgentDB,

Long-term, cross-project memory for AI coding agents. Your own Obsidian vault as the source of truth. Daemonless and without opaque database

[ACL'26 Main] Official code for "LegalGraphRAG: Multi-Agent Graph Retrieval-Augmented Generation for Reliable Legal Reasoning".

Chat with the videos you've saved: evidence-backed answers with timestamps that jump back to the source. Browser extension + MCP, self-hosta

Turn any document into clean, AI-ready Markdown — locally on your machine. Desktop app for Windows, macOS & Linux powered by MarkItDown, Doc

Native AI inference for PHP 8.3+ - run ONNX, GGUF (llama.cpp) and RubixML models directly in your PHP process via FFI. Chat, streaming, embe

GIS agent是一个基于 ArcGIS Pro 3.6 的 arcpy构建的开源的地理空间智能体（AI Agent）框架。其核心设计采用独特的三层抽象架构（模型抽象、输出标准化、提示词动态适配），将您的自然语言指令与底层大语言模型及专业 GIS 工具链解耦。智能体自身能通过

Namaste AI — Free handwritten notes and study material covering AI concepts from the Namaste AI course. Explore the history of AI, neural ne

AI Business OS: multi-agent platform with RAG, OCR, speech & workflow automation. FastAPI + LangGraph + Celery + Flutter. Production-grade,

FDE 中文成长手册：24 周 Forward Deployed Engineer 教程，贯通商业决策、一线问题发现、RAG/MCP 工程交付与运营交接。

Give any MCP-capable agent persistent memory: remember/recall over a tiered store with hybrid vector + keyword retrieval. Single Go binary,

端到端智能体平台：把本机的 AI Agent 变成人人可用的 Web 产品（Vue 3 + Flask + Go WS 网关 + Docker 部署）

Long-term memory for AI agents with no LLM call: an MCP server and Claude Code plugin, plus local-first context compression for LLM apps.

⭐️ Self-hostable AI support for Discord, GitHub, Slack & Discourse communities. Answers from your knowledge source, checked by a second AI a

In-memory graph database and Gremlin traversal engine in Rust: browser playground, CLI, MCP server for AI agents, durable store, Python bind

Athena RAG Intelligence – AI-powered document intelligence platform with RAG, semantic search, source citations, voice assistant, analytics,

Jev RAG (Jev-RAG / JevRAG): open-source local knowledge search with BM25 + Jev reranking, agentic and hybrid retrieval, cited answers, and r

One embedding space for text, image, video, audio, thermal, motion, and touch. Open weights, self-hostable.

Self-hosted long-term memory for AI coding agents: Postgres+pgvector doc-RAG (component/constraint map + hybrid RRF + cross-encoder rerank)

Evidence-assisted Yu-Gi-Oh! rulings for OCG and TCG, with card-text checks and cited sources. TCG public preview.

Your AI agent, fluent in Australian tax.

Add AI agents to your .NET app: your methods become tools with role checks and human confirmation. Use the ready-made chat widget in Blazor

AI pair programming in your terminal — one static binary, sub-ms startup, any model

Ask questions across your Markdown notes using a fully local Graph RAG engine. Built for Obsidian vaults, works with any folder of Markdown

Caura (formerly MemClaw) — governed shared memory for AI agent fleets. Multi-agent, multi-tenant, MCP-native. Trust tiers, keystone policies

Adaptive Chunking: automatically select the best chunking method per document for RAG. Accepted at LREC 2026.

The memory your AI should have had from the start. Automatic capture, automatic recall, 100% local. One SQLite file, zero cloud. Works with

Local-first persistent memory for AI coding agents (Claude Code, Cursor, Codex) over MCP. Decisions, lessons and facts live in one SQLite fi

UmaDev: A coding agent that works like a real dev team, commanding the Claude Code / Codex / OpenCode you already use.

Fast, AI-agent-native code search in Rust — hybrid BM25 + semantic, Tree-sitter AST chunking, dependency & impact analysis. Drop-in replacem

中文互联网内容的个人 AI 稍后读 + 知识库 · Read-later + AI knowledge base for the Chinese internet

A lightweight embedded database engine that natively fuses vector search, graph, and document-oriented metadata within a single storage kern

Open-source video processing core and CLI. Search and annotate local videos with your own model endpoints.

Self-hosted AI customer-support platform — per-KB RAG on Qdrant, 13 LLM providers, SSE streaming, embeddable chat widget. FastAPI + Vite + S

Find, connect, rediscover your notes — a local-first second brain for Obsidian. Semantic search with strong Chinese/CJK, relation graphs and

デジタル庁のガバメントAI「源内(GENAI)」を完全ローカル(ローカルLLM/OpenAI互換)で動かす非公式プロジェクト。SAML認証(Keycloak)・RAG(Qdrant)・文字起こし(Whisper)・画像生成(SD)・チーム単位ナレッジをローカル完結。

Find out what your coding agents already know. Docmancer indexes the memory, rules, and instructions Claude Code, Codex, Cursor, and Gemini

A cognition aware database engine for AI agent memory. Purpose built in Rust with WAL, HNSW, knowledge graphs, and speculative context pre a