1. Transformers module
Transformers vectorizer use models children of the “BERT” model brought by Google, which led to the current machine learning/artificial intelligence revolution.
Create a docker compose file from Weaviate wizzard : select the Text transformers vectorizer, with a specific transformer model among the list. Then start the docker container.
- (1) Select the “Text” vectorizer type
- (2) Select the “Transformers” vectorizer
- (3) Select a transformer model in the list.
Now, let’s create our index:
- (1) Select the text2vec-transformers
- (2) Set a name for you index, visible in WPSOLR admin
- (3) Set a name for your Weaviate class (index)
- (4) Set the url of your Weaviate docker container
- (5) Create the index. Done!
Connect to the Weaviate GraphQL console at https://console.semi.technology/console with url https://localhost:8080, to check our new index (class):
2 Select your data
- (1) (2) (3) select the index you just created
- (4) Choose a filter: “Near Text” to perform a vector search (search on concepts), or “Where” to perform a keywords search (classic search that works with words)
- (5) Set a similarity for your “Near Text” search. The closer to “1”, the more precise is the vector search.
3 Index your data