/weaviate-integration

name: weaviate-integration
description: Weaviate vector database setup with GraphQL queries and hybrid search
allowed-tools:
  - Read
  - Write
  - Edit
  - Bash
  - Glob
  - Grep
graph:
  domains: [domain:software-engineering]
  specializations: [specialization:ai-agents-conversational]
  skillAreas: [skill-area:retrieval-augmented-generation, skill-area:search-indexing]
  roles: [role:ml-engineer, role:backend-engineer]
  workflows: [workflow:ml-model-lifecycle, workflow:feature-development]

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