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# Diffusion Chat Completions API
vLLM-Omni supports generating and editing images via the `/v1/chat/completions`
endpoint using diffusion models. This page explains how to pass generation
parameters (such as `num_inference_steps`, `height`, `width`) to diffusion
models through this endpoint.
!!! tip
For dedicated endpoints that accept generation parameters as top-level
fields, see [Image Generation API](image_generation_api.md) and
[Image Edit API](image_edit_api.md).
## Passing Generation Parameters
The `/v1/chat/completions` endpoint follows the OpenAI Chat API schema, which
does not natively include diffusion-specific fields like `num_inference_steps`
or `height`. How you pass these extra fields depends on your client.
### curl / Python `requests`
Wrap generation parameters inside an `"extra_body"` key in the JSON body:
```bash
curl -s http://localhost:8091/v1/chat/completions \
-H "Content-Type: application/json" \
-d '{
"messages": [
{"role": "user", "content": "A beautiful landscape painting"}
],
"extra_body": {
"num_inference_steps": 50,
"seed": 42
}
}'
```
### OpenAI Python SDK
Use the `extra_body` **keyword argument**. The SDK automatically merges these
fields into the top-level request body:
```python
response = client.chat.completions.create(
model="Qwen/Qwen-Image",
messages=[{"role": "user", "content": "A beautiful landscape painting"}],
extra_body={
"num_inference_steps": 50,
"seed": 42,
},
)
```
!!! note "SDK `extra_body` vs. JSON `extra_body`"
These two `extra_body` usages look similar but work differently under the
hood. The SDK flattens the dict into the top-level request JSON, while the
curl/requests approach sends it as a nested `"extra_body"` key. Both are
handled correctly by the server.
!!! note "About the `ignored fields` warning"
You may see a log message like:
```
WARNING: The following fields were present in the request but ignored: {'height', 'width', ...}
```
This is **harmless**. It is emitted by vLLM's request validation layer
because these fields are not part of the standard OpenAI
`ChatCompletionRequest` schema. The fields are still stored internally
and correctly forwarded to the diffusion pipeline.
## Model-Specific Examples
For complete examples with full request/response details, see the model-specific
guides:
- [Text-to-Image (Qwen-Image)](../user_guide/examples/online_serving/text_to_image.md)
- [Image-to-Image (Qwen-Image-Edit, Qwen-Image-Layered)](../user_guide/examples/online_serving/image_to_image.md)
- [GLM-Image](../user_guide/examples/online_serving/glm_image.md)