Hello,
I would like to specify the api version that Weaviate uses to query the Azure OpenAI endpoint.
If it is an environment parameter for the docker container, what value would it be? Is it
AZURE_OPENAI_API_VERSION
OPENAI_API_VERSION
something else?
Additionally I have the issue that I want to use a “text-embedding-3-large” - which is deployed on azure - with 1536 dimensions. Anyhow, after creating the collection, the “model” parameter of the collection lists the “model” parameter as “text-embedding-3-large”. As far as I found out the model can only be specified in the OpenAI class directly, not in Azure OpenAI. Can I just ignore the wrong “model” parameter of the created collection or will this be an issue?
THANKS
Weaviate Server Version:
Deployment Method:
Multi Node? No
Client Language and Version: 1.28
Multitenancy?: No
Hey @franz_hals
Please have a look at:
opened 12:20PM - 05 Mar 25 UTC
bug
### How to reproduce this bug?
When creating a collection using the text2vec_az… ure_openai vectorizer and specifying the parameters:
```
resource_name="RES_HERE",
deployment_id="DEPLOY_ID_HERE"
```
Regardless of what is added in the configuration, the result always defaults to the model text-embedding-3-small and dimensions 1536, instead of the expected model from Azure OpenAI.
Code used to reproduce:
```
from weaviate.classes.config import Configure, Property, DataType
client.collections.create(
"embed",
# Define properties
properties=[
Property(name="embed_desc", data_type=DataType.TEXT),
],
vectorizer_config=[
# Set a named vector
Configure.NamedVectors.text2vec_azure_openai(
resource_name="RESOURCE_NAME",
deployment_id="DEPLOYMENT_ID",
name="embed_descNamedVector",
source_properties=["embed_desc"]
)
]
)
```
OR
```
from weaviate.classes.config import Configure, Property, DataType
client.collections.create(
"CollNam",
# Define properties
properties=[
Property(name="embedding", data_type=DataType.TEXT),
],
vectorizer_config=Configure.Vectorizer.text2vec_azure_openai(
resource_name="RES_HERE",
deployment_id="DEPLOY_ID_HERE"
)
)
```
### What is the expected behavior?
- The vectorizer should respect the resource_name and deployment_id and use the correct Azure OpenAI model.
- The correct configuration reflect on the collection definition.
### What is the actual behavior?
- Despite specifying a different resource_name and deployment_id, the model is always set to text-embedding-3-small and the dimensions remain 1536.
- This occurs consistently across different Weaviate versions.
### Supporting information
- Attached are screenshots demonstrating the issue below.
- The bug persists on multiple setups.
- It also occurs on 1.27 version.
<img width="1425" alt="Image" src="https://github.com/user-attachments/assets/6c214004-6f00-4b0f-bfba-abbae25b1ecb" />
### Server Version
1.29.0
### Weaviate Setup
Single Node
### Nodes count
1
### Code of Conduct
- [x] I have read and agree to the Weaviate's [Contributor Guide](https://weaviate.io/developers/contributor-guide) and [Code of Conduct](https://weaviate.io/service/code-of-conduct)
Let me know if that reflects what you are reporting and feel free to add a comment there in the Github issue if needed.
Regards,
1 Like
Hi Mohamed, thanks for creating the issue - it reflects my experience except that I did not try for bigger vector dimensions than 1536.
1 Like
