A simple vector search task implementation using Weaviate vector database with pre-built model for vector embedding.
docker and docker-compose
docker-compose up --build
Note: The first time you run the service, it will take some time to populate the database.
docker-compose down
The service will be available at http://0.0.0.0:8000. OpenAPI documentation is available at http://0.0.0.0:8000/docs.
This API contains /query endpoint which can be used to search for similar items in the database. It has the following parameters:
- q: query string for vector search
- filters: list of phrases to filter the results (exactly match)
Example:
curl -X 'GET' \
'http://0.0.0.0:8000/query?q=smart%20computer&filters=python&limit=10&offset=0' \
-H 'accept: application/json'