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> - 0.9: https://docs.nvidia.com/nemo-helix/v0.9/llms.txt
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> - 0.7: https://docs.nvidia.com/nemo-helix/v0.7/llms.txt
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# OpenAI Inference Proxy PUT

PUT http://localhost:8080/apis/inference-gateway/v2/workspaces/{workspace}/openai/-/{trailing_uri}
Content-Type: application/json

Proxy requests to OpenAI-compatible inference endpoints.

All inference requests must resolve to a `VirtualModel`. The platform's
provider reconciler auto-creates an implicit `autoprovisioned` VirtualModel
for every served model entity (named after the entity, with
`default_model_entity` set to the entity ref) so this is the typical case;
operators can also create custom VirtualModels for routing, plugin chains,
LoRA escape-hatches, etc. Requests for which no VirtualModel can be found
return `404`.

Reference: https://docs.nvidia.com/nemo-helix/documentation/reference/api-reference/inference-gateway/openai-proxy-put

## Request

### Path parameters

- `workspace` (string, required)
- `trailing_uri` (string, required)

### Body (application/json)

This endpoint expects a map from string to any.

- `map from string to any`

## Response

### 200

Proxy PUT request to OpenAI-compatible endpoint

- `map from string to any`

## Errors

### 422 Unprocessable Entity Error

Validation Error

- `detail` (list of ValidationError, optional)

## Types

### ValidationError

- `loc` (list of ValidationErrorLocItems, required)
- `msg` (string, required)
- `type` (string, required)
- `input` (any, optional)
- `ctx` (map from string to any, optional)

### ValidationErrorLocItems

- string
- integer

## Examples

**Request**

```json
{
  "messages": [
    {
      "content": "Hello!",
      "role": "user"
    }
  ],
  "model": "YOUR_MODEL_NAME"
}
```

**Response**

```json
{}
```

**SDK Code**

```python Inference Gateway_openai_proxy_put_example
import requests

url = "http://localhost:8080/apis/inference-gateway/v2/workspaces/workspace/openai/-/v1%2Fchat%2Fcompletions"

payload = {
    "messages": [
        {
            "content": "Hello!",
            "role": "user"
        }
    ],
    "model": "YOUR_MODEL_NAME"
}
headers = {"Content-Type": "application/json"}

response = requests.put(url, json=payload, headers=headers)

print(response.json())
```

```javascript Inference Gateway_openai_proxy_put_example
const url = 'http://localhost:8080/apis/inference-gateway/v2/workspaces/workspace/openai/-/v1%2Fchat%2Fcompletions';
const options = {
  method: 'PUT',
  headers: {'Content-Type': 'application/json'},
  body: '{"messages":[{"content":"Hello!","role":"user"}],"model":"YOUR_MODEL_NAME"}'
};

try {
  const response = await fetch(url, options);
  const data = await response.json();
  console.log(data);
} catch (error) {
  console.error(error);
}
```