weaviate-search

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.