> ## Documentation Index
> Fetch the complete documentation index at: https://docs.tensormesh.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Migration From OpenAI And Fireworks

> What changes when moving an existing OpenAI- or Fireworks-style chat integration onto the current Tensormesh SDK surface.

The current Tensormesh SDK supports the narrowest migration path on the inference side:

* serverless chat completions
* serverless Responses client
* no embeddings client

## Fastest Serverless Migration

If your existing app already uses chat completions, serverless is the closest fit.

```python theme={null}
from tensormesh import Tensormesh
from tensormesh.types import ChatMessage

client = Tensormesh(inference_api_key="YOUR_INFERENCE_API_KEY")

serverless_model_name = "YOUR_SERVERLESS_MODEL_NAME"
completion = client.inference.serverless.chat.completions.create(
    model=serverless_model_name,
    messages=[ChatMessage(role="user", content="Say hello.")],
)

print(completion.choices[0].message.content)
```

## What Changes From OpenAI Or Fireworks

* Serverless uses `client.inference.serverless.chat.completions.create(...)`, not `client.chat.completions.create(...)`.
* Serverless also exposes `client.inference.serverless.responses.create(...)` when you want the verified responses surface.
* This SDK does not currently expose embeddings.
* Message content is text-oriented in this SDK surface; multimodal content-part request shapes are not modeled here.
* Structured output is limited to `response_format={"type": "json_object"}` or `ResponseFormat(type="json_object")`. JSON Schema-style `json_schema` response formats are not supported on this surface.
* CLI login state is not read automatically by the Python SDK. Application code must pass credentials explicitly or via the documented SDK environment variables.

## Recommended Decision

* Use serverless for an OpenAI-style chat flow on this SDK surface.
* If you do not already know a valid serverless model name, start with [Choose A Serverless Model Name](/serverless-model-selection) before copying the serverless example.

## Related Guides

* [Getting Started](/sdk/guides/getting-started)
* [Auth And Config](/sdk/guides/auth-and-config)
* [Inference](/sdk/guides/inference)

## Related Reference

* [Raw Inference API Reference](/api-reference)
* [Choose A Serverless Model Name](/serverless-model-selection)