Distance between entrypoint and query node

Description

I have created a sanbox in Weaviate Cloud to test functionality before putting the vectorstore in production. I am testing openai embeddings:
“text-embedding-3-small” and “text-embedding-3-large”.

I tried to change dimensions of “text-embedding-3-large” to 256, to see how sould retrieval go, but I got error below. “distance between entrypoint and query node: 256 vs 1536”

Can I change dimensions in Sandbox? Or do I have to setup something additional when I am doing hybrid or smilarity search?

This is my setup:

    client = weaviate.connect_to_weaviate_cloud(
        cluster_url=weaviate_url,
        auth_credentials=Auth.api_key(weaviate_api_key),
        headers={"X-OpenAI-Api-Key": openai_api_key},
        # headers={"X-Google-Studio-Api-Key": google_studio_api_key},
    )

        vectorizer_config = Configure.Vectorizer.text2vec_openai(
            model=model,
            model_version="3",
            dimensions=dimensions,
        )

        client.collections.create(
            name=collection_name,
            vectorizer_config=vectorizer_config,
            vector_index_config=Configure.VectorIndex.hnsw(
                distance_metric=VectorDistances.COSINE
            ),
            properties=properties,
        )

I have changed now everything to model: str = “text-embedding-3-small”, and dimensions: int = 1536, and now retrieval works fine…

Second somehow related question: Does, Google’s “text-embedding-004” embedding works in sandbox? I had earlier some trouble setting it up…

Third question, are this integrations necessary (since this integrations don’t support Google’s embeddings):

    # integrations = [
    #     Integrations.openai(
    #         api_key=openai_api_key,
    #         requests_per_minute_embeddings=3000,
    #         tokens_per_minute_embeddings=1000000,
    #     ),
    # ]
    # client.integrations.configure(integrations)

Server Setup Information

  • Weaviate Server Version:
  • Deployment Method: sanbox in Weaviate Cloud
  • Multi Node? Number of Running Nodes: no
  • Client Language and Version: Python v4
  • Multitenancy?: No

Any additional Information

"StatusCode.UNKNOWN\n\tdetails = “explorer: get class: vector search: object vector search at index …: vector search: knn search: distance between entrypoint and query node: 256 vs 1536: vector lengths don't match”\n\tdebug_error_string = "UNKNOWN:Error received from peer "

hi @mklobucaric !!

Welcome to our community :hugs: !!

This seems related to this bug we have recently discovered:

Can you confirm that near_text will work, but the failing query is a hybrid one?

Thanks!

Thank you!

Yes, you are right, nearText works but hybrid not…