Agentes de IA
gortex
Gortex, in Go — built for high-performance code-intelligence engine for ai agents.
★ 1,9 mil estrelasApache-2.0
Ver o guia →LibreAI / Agentes de IA / qdrant
// agents · qdrant/qdrant
qdrant
qdrant é um projeto de agentes de IA de código aberto de qdrant (qdrant/qdrant no GitHub). Tem 34.969 estrelas no GitHub e 2.731 forks, é publicado sob a licença Apache-2.0 e foi atualizado pela última vez no GitHub em 8 de outubro de 2026.
A high-performance vector search engine for next-gen AI.
★ 35,0 mil estrelas⑂ 2,7 mil forksApache-2.0atualizado out 2026
▦ visual: o README deste projeto não inclui nenhuma captura incorporável,
então aqui vai um marcador. O guia abaixo está completo mesmo assim.
então aqui vai um marcador. O guia abaixo está completo mesmo assim.
// dados do projeto
Dados do projeto
- Repositório
- qdrant/qdrant
- Estrelas no GitHub
- 34.969
- Forks
- 2.731
- Licença
- Apache-2.0
- Última atualização no GitHub
- 8 de outubro de 2026
- Categoria
- Agentes de IA
- Tipo de ficha
- Guia de instalação completo
- Site oficial
- Official site
// como funciona
Como funciona
- Pick a first task
Choose one real workload to test the project against.
- Download the project
Clone it locally and read through the getting-started guide.
- Wire up dependencies
Install the stack it needs and set any environment variables.
- Run and verify
Execute the starter example and check results before going further.
// recursos
Por que as pessoas gostam tanto
Hybrid search
Combines vector and keyword search in one query.
HNSW indexing
Fast approximate nearest neighbor queries.
Rust performance
Low-latency, memory-efficient core.
Rich filtering
Payload-based structured filtering alongside vectors.
Cloud option
Managed cloud available alongside self-hosting.
Apache-2.0
Permissive licensing.
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// execute você mesmo
Execute você mesmo
- Step 1 — Clone the repo
Download the source and move into the project folder.
git clone https://github.com/qdrant/qdrant.git cd qdrant - Step 2 — Build
Compile the Rust engine.
cargo build --release - Step 3 — Run it
Start the server (Docker is the fastest path per the docs).
# see docs for the Docker quickstart ./target/release/qdrant
// casos de uso
O que você pode criar
- Add semantic search to an AI product.
- Build RAG over large document collections.
- Run image similarity search.
- Prototype recommendation features quickly.
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// perguntas frequentes
Perguntas frequentes
Who maintains Qdrant?
It is maintained by the qdrant organization at qdrant/qdrant, with 2,731 forks. Check the changelog for the latest stable release.
Is Qdrant free to use?
The open-source engine is free under Apache-2.0; the managed cloud is the paid path.
Do I need a paid API to use it?
Self-hosting is free. You only pay if you choose the managed cloud or for the embedding/LLM APIs you call.
How does it compare to other vector databases?
Compare with Milvus, Weaviate, and Chroma on operations, filtering, and scale.
How do I get started?
The Docker quickstart in the docs is the fastest route; load a sample collection and run a search.
// continue explorando
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Baixe o qdrant
Grátis e aberto: pegue o código-fonte, dê uma estrela no repositório e comece a criar.