weaviate-integration
// Weaviate vector database setup with GraphQL queries and hybrid search
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stars:384
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updated:March 4, 2026
SKILL.mdreadonly
SKILL.md Frontmatter
nameweaviate-integration
descriptionWeaviate vector database setup with GraphQL queries and hybrid search
allowed-toolsRead,Write,Edit,Bash,Glob,Grep
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
- Schema Management: Class definitions and properties
- Data Import: Single and batch object creation
- Vector Search: nearVector, nearText queries
- Hybrid Search: Combined vector and BM25
- 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