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weaviate-integration

Automação Autor: a5c-ai

Configuração de banco de dados vetorial Weaviate com consultas GraphQL e busca híbrida.

1.4kestrelas
Atualizado há 4 meses
Ver no GitHub ↗ Licença: MIT

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Ler descrição completa

Weaviate Integration Skill

Capabilities

  • Set up Weaviate cluster (cloud or self-hosted)
  • Define schemas with properties and vectorizers
  • Implement GraphQL queries
  • Configure hybrid search (vector + keyword)
  • Set up multi-tenancy
  • Implement batch import operations

Target Processes

  • vector-database-setup
  • rag-pipeline-implementation

Implementation Details

Core Operations

  1. Schema Management: Class definitions and properties
  2. Data Import: Single and batch object creation
  3. Vector Search: nearVector, nearText queries
  4. Hybrid Search: Combined vector and BM25
  5. GraphQL: Flexible querying with Get and Aggregate

Configuration Options

  • Vectorizer modules (text2vec-, multi2vec-)
  • Replication factor
  • Sharding configuration
  • Multi-tenancy settings
  • Module configuration

Best Practices

  • Design schema for query patterns
  • Use appropriate vectorizer
  • Enable hybrid search for better recall
  • Configure proper backups
  • Monitor resource usage

Dependencies

  • weaviate-client
  • langchain-weaviate
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