name: weaviate-search description: "Perform hybrid vector and keyword search using Weaviate at {{WEAVIATE_HOST}}:{{WEAVIATE_PORT}}." metadata: openclaw: emoji: "🔮"
Weaviate Search
Weaviate is available at http://{{WEAVIATE_HOST}}:{{WEAVIATE_PORT}} within the Docker network.
Create a Class
curl -X POST "http://{{WEAVIATE_HOST}}:{{WEAVIATE_PORT}}/v1/schema" \
-H "Content-Type: application/json" \
-d '{"class": "Document", "vectorizer": "none", "properties": [{"name": "content", "dataType": ["text"]}]}'
Add Objects
curl -X POST "http://{{WEAVIATE_HOST}}:{{WEAVIATE_PORT}}/v1/objects" \
-H "Content-Type: application/json" \
-d '{"class": "Document", "properties": {"content": "Hello world"}, "vector": [0.1, 0.2, 0.3]}'
Search
curl -X POST "http://{{WEAVIATE_HOST}}:{{WEAVIATE_PORT}}/v1/graphql" \
-H "Content-Type: application/json" \
-d '{"query": "{Get {Document(nearVector: {vector: [0.1, 0.2, 0.3]}, limit: 5) {content}}}"}'
Tips for AI Agents
- Weaviate supports hybrid search combining vector and BM25 keyword search.
- Use GraphQL for complex queries with filters and aggregations.
- Multi-tenancy enables isolated datasets per tenant.