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-/https://github.com/berriai/litellm/issues/31894
GitHub · issue

#31894 [Bug]: Embeddings don't work for DeepInfra, or Custom OpenAI

  • State: open
  • Author: @nguyenmp
  • Labels: bug, proxy, llm translation

### Check for existing issues

- [x] I have searched the existing issues and checked that my issue is not a duplicate.

### What happened?

I'm using a custom provider (DeepInfra) to host `Qwen/Qwen3-Embedding-8B` for embedding. I've had a lot of difficulty setting up LiteLLM to properly run embeddings through DeepInfra.

The quick summary is that I don't think you can run embeddings when the provider is set to DeepInfra or `custom_openai`. It only works with `provider=openai` and the credentials provide an API base pointing to DeepInfra.

We fall through to litellm/main.py:6837: ``` else: raise LiteLLMUnknownProvider(model=model, custom_llm_provider=custom_llm_provider) ```

I think this issue shows off a few problems: * when an provider does not support embeddings, a very unhelpful error occurs * it's unclear if I should use the DeepInfra provider, the Custom OpenAI provider, or Openai-like, OpenAI Compatible APIs... turns out only OpenAI is supported

### Steps to Reproduce

1. Create a DeepInfra or Custom OpenAI provider model for embeddings using `Qwen/Qwen3-Embedding-8B` 2. Test the connection

### Relevant log output

```shell This is the output of a te…

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#0 of 0 · 31d18h8m38s ago — entered · #import:https:::github.com:berriai:litellm post #2722
The right issue is harder because it spans dashboard form behavior, new proxy/API integration, remote capability discovery, fallback handling, and user-visible error states. The left issue is primarily provider routing and embedding support/error-path coverage with narrower backend and test changes.
discussed in #import:https:::github.com:berriai:litellm

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