weaviate-integration
Weaviate vector database setup with GraphQL queries and hybrid search
Best use case
weaviate-integration is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Weaviate vector database setup with GraphQL queries and hybrid search
Teams using weaviate-integration should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/weaviate-integration/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How weaviate-integration Compares
| Feature / Agent | weaviate-integration | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Weaviate vector database setup with GraphQL queries and hybrid search
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 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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