LibreAI / RAG e conhecimento / swirl-search
// rag · swirlai/swirl-search

swirl-search

swirl-search é um projeto de RAG e conhecimento de código aberto de swirlai (swirlai/swirl-search no GitHub). Tem 3.047 estrelas no GitHub e 288 forks, é publicado sob a licença Apache-2.0 e foi atualizado pela última vez no GitHub em 26 de setembro de 2026.

Federated AI search and RAG across 100+ apps — answers with sources, without moving your data

★ 3,0 mil estrelas⑂ 288 forksApache-2.0atualizado set 2026
▦ visual: o README deste projeto não inclui nenhuma captura incorporável,
então aqui vai um marcador. O guia abaixo está completo mesmo assim.
// dados do projeto

Dados do projeto

Estrelas no GitHub
3.047
Forks
288
Licença
Apache-2.0
Última atualização no GitHub
26 de setembro de 2026
Tipo de ficha
Guia de instalação completo
Site oficial
Official site
// como funciona

Como funciona

  1. Clarify your goal

    List the sources you want to search in one place — the README notes connectors across 100+ apps, and it searches Arxiv, European PMC and Google News out of the box.

  2. Get SWIRL

    Download the project's docker-compose.yaml (or clone the repo) with Docker installed and running.

  3. Install and configure

    Optionally set your own OpenAI key and host variables for real-time RAG, then pull and start the containers.

  4. Run your first search

    Open the Galaxy UI, log in, and run a question across your connected sources to see ranked, cited answers.

// recursos

Por que as pessoas gostam tanto

Federated live search

Queries run live against your sources in place, with the user's own permissions enforced at the source.

RAG with citations

Optionally generates an answer using the LLM of your choice, with sources you can click through to verify.

No vector database

No vector DB, ETL pipeline or duplicated copy of your data to secure and audit.

100+ connectors

Connects across a large library of enterprise and public sources (see the project's connector list).

Fast Docker start

Starts with one Docker Compose flow and is usable in about two minutes per the README.

Open Community edition

The open-source Community edition is Apache-2.0; a separate Enterprise edition adds features such as a three-pass reranker and an MCP server.

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// execute você mesmo

Execute você mesmo

  1. Clone the repo

    Clone SWIRL Search and enter the directory (alternatively just download its docker-compose.yaml).

    git clone https://github.com/swirlai/swirl-search.git
    cd swirl-search
  2. Download the compose file

    As the README quick start shows, you can fetch the compose file directly.

    curl https://raw.githubusercontent.com/swirlai/swirl-search/main/docker-compose.yaml -o docker-compose.yaml
  3. Start SWIRL

    Pull and start the containers, then open http://localhost:8000/galaxy and log in with admin / password.

    docker-compose pull && docker-compose up
// casos de uso

O que você pode criar

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// perguntas frequentes

Perguntas frequentes

Who maintains SWIRL?

It is developed by swirlai (SWIRL AI) as the open-source SWIRL Community edition, alongside a commercial Enterprise edition.

Is SWIRL free?

The Community edition in this repo is free and Apache-2.0 licensed. Enterprise features and managed support are a separate commercial offering.

Does it need a paid API key?

Federated search works without one; real-time RAG with OpenAI requires your own OpenAI API key, set via the OPENAI_API_KEY environment variable.

How does it compare to a vector-database RAG stack?

Typical stacks copy and embed all your data first. SWIRL queries sources live, in place, so there is no duplicate corpus to govern.

How do I get started?

Install Docker, download docker-compose.yaml, run docker-compose pull && docker-compose up, then open http://localhost:8000/galaxy.

// continue explorando

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// alternativas

Alternativas em RAG e conhecimento

Os outros projetos de RAG e conhecimento com mais estrelas no catálogo do LibreAI — a lista realista de alternativas se swirl-search não for o ideal para você.

// mais em rag

Mais em RAG e conhecimento

Projetos de RAG e conhecimento próximos no catálogo, os mais próximos em estrelas de swirl-search: continue explorando dos dois lados dele.

Baixe o swirl-search

Grátis e aberto: pegue o código-fonte, dê uma estrela no repositório e comece a criar.