Agentes de IA
MemoryOS
A memory operating system for long-term, personalized AI agents.
★ 1,6 mil estrelasApache-2.0
Ver o guia →wenlan é um projeto de RAG e conhecimento de código aberto de 7xuanlu (7xuanlu/wenlan no GitHub). Tem 79 estrelas no GitHub e 8 forks, é publicado sob a licença Apache-2.0 e foi atualizado pela última vez no GitHub em 4 de outubro de 2026.
Agent-fed knowledge base that distills learnings into cited wiki pages.
Download the source and enter the folder.
Compile the Rust binary.
Install the Claude Code or Codex plugin.
Agents capture learnings into cited pages.
Agents record what they learn.
Wiki pages you can verify.
Knowledge updates as agents work.
Fast, private by default.
Standard protocol for agent input.
Drop-in agent integrations.
Download the source and move into the project folder.
git clone https://github.com/7xuanlu/wenlan.git
cd wenlanCompile the optimized release.
cargo build --releaseLaunch the knowledge base.
./target/release/wenlanIt is an open-source project at 7xuanlu/wenlan with 8 forks.
Yes. It is Apache-2.0 licensed.
AI agents capture learnings through plugins and the MCP server.
Pages carry source citations so claims are checkable.
Local-first — on your own machine by default.
A memory operating system for long-term, personalized AI agents.
Self-improving memory layer that works across AI agent harnesses.
Knowledge-base — 本地优先的知识库桌面应用。markdown 编辑器 + 全文搜索（fts5） + 双向链接 / 知识图谱；多端, publicly avai...
OpenKB compiles your documents into a persistent, interlinked wiki knowledge base — no vector DB
A personal knowledge base that builds itself — drop in sources, get a persistent interlinked wiki.
Open-source LLM knowledge platform: turn raw documents into a queryable RAG, an autonomous reasoning agent, and a self-maintaining Wiki.
Os outros projetos de RAG e conhecimento com mais estrelas no catálogo do LibreAI — a lista realista de alternativas se wenlan não for o ideal para você.
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Lightweight OCR toolkit turning PDFs and images into structured, LLM-ready data in 100+ languages
MinerU — turns PDFs and Office documents into LLM-ready Markdown and JSON for agents and RAG pipelines, Apache-2.0 plus terms
Stop renting your intelligence. Own it with AnythingLLM. Everything you need for a powerful local-first agent experience
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A trilingual e-commerce knowledge base agents can install.
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A self-hostable markdown team wiki with a built-in MCP server.
Run rag-template locally: template for ai chatbots & document management using re.
Skills that let coding agents search and read your local documents.
Grátis e aberto: pegue o código-fonte, dê uma estrela no repositório e comece a criar.