# Open Responses Provider

The [Open Responses](https://www.openresponses.org/) provider connects AI SDK
Core to language model servers that implement an Open Responses-compatible
`POST` endpoint. Open Responses is an open specification based on the OpenAI
Responses API.

Use `@ai-sdk/open-responses` for third-party or self-hosted endpoints that
implement this protocol, such as LM Studio. If you call OpenAI directly and
need OpenAI-specific provider options or built-in tools, use the
[`@ai-sdk/openai` provider](/providers/ai-sdk-providers/openai) instead.

## Setup

The Open Responses provider is available in the `@ai-sdk/open-responses` module. You can install it with

<InstallPackages packages="@ai-sdk/open-responses" />

## Provider Instance

Create an Open Responses provider instance using `createOpenResponses`:

```ts
import { createOpenResponses } from '@ai-sdk/open-responses';

const openResponses = createOpenResponses({
  name: 'lmstudio',
  url: 'http://localhost:1234/v1/responses',
});
```

The `name` and `url` options are required:

- **name** _string_

  Provider name. Used in the model's provider identifier and as the key for
  provider options.

- **url** _string_

  Full URL for the Open Responses API `POST` endpoint. Pass the endpoint URL,
  such as `http://localhost:1234/v1/responses`, not only its base URL.

You can use the following optional settings to customize the Open Responses provider instance:

- **apiKey** _string_

  API key that is sent as a bearer token in the `Authorization` header.

- **headers** _Record&lt;string,string&gt;_

  Custom headers to include in the requests.

- **fetch** _(input: RequestInfo, init?: RequestInit) => Promise&lt;Response&gt;_

  Custom [fetch](https://developer.mozilla.org/en-US/docs/Web/API/fetch) implementation.
  Defaults to the global `fetch` function.

### Endpoint Examples

For a local LM Studio server that does not require authentication:

```ts
import { createOpenResponses } from '@ai-sdk/open-responses';

const lmstudio = createOpenResponses({
  name: 'lmstudio',
  url: 'http://localhost:1234/v1/responses',
});
```

For the OpenAI Responses API:

```ts
import { createOpenResponses } from '@ai-sdk/open-responses';

const openAIResponses = createOpenResponses({
  name: 'openai',
  url: 'https://api.openai.com/v1/responses',
  apiKey: process.env.OPENAI_API_KEY,
});
```

You can use the same setup with another compatible service by changing the
`name`, `url`, authentication, and model ID.

## Language Models

The Open Responses provider instance is a function that you can invoke to create a language model:

```ts
const model = openResponses('your-model-id');
```

The model ID is passed to the endpoint unchanged.

You can use Open Responses models with the `generateText` and `streamText` functions,
and they support structured data generation with [`Output`](/docs/reference/ai-sdk-core/output)
(see [AI SDK Core](/docs/ai-sdk-core)).

### Generate Text

```ts
import { createOpenResponses } from '@ai-sdk/open-responses';
import { generateText } from 'ai';

const openResponses = createOpenResponses({
  name: 'lmstudio',
  url: 'http://localhost:1234/v1/responses',
});

const { text } = await generateText({
  model: openResponses('your-model-id'),
  prompt: 'Invent a new holiday and describe its traditions.',
});

console.log(text);
```

### Stream Text

```ts
import { createOpenResponses } from '@ai-sdk/open-responses';
import { streamText } from 'ai';

const openResponses = createOpenResponses({
  name: 'lmstudio',
  url: 'http://localhost:1234/v1/responses',
});

const result = streamText({
  model: openResponses('your-model-id'),
  prompt: 'Invent a new holiday and describe its traditions.',
});

for await (const textPart of result.textStream) {
  process.stdout.write(textPart);
}
```

## Reasoning and Provider Options

Use the top-level [`reasoning`](/docs/ai-sdk-core/reasoning) setting to control
reasoning effort. The provider maps supported values to the Open Responses
`reasoning.effort` field.

The provider also supports `reasoningSummary` through `providerOptions`. The
provider option key must match the `name` passed to `createOpenResponses`:

```ts
import {
  createOpenResponses,
  type OpenResponsesLanguageModelOptions,
} from '@ai-sdk/open-responses';
import { generateText } from 'ai';

const lmstudio = createOpenResponses({
  name: 'lmstudio',
  url: 'http://localhost:1234/v1/responses',
});

const { text, reasoningText } = await generateText({
  model: lmstudio('your-reasoning-model-id'),
  reasoning: 'high',
  providerOptions: {
    lmstudio: {
      reasoningSummary: 'detailed',
    } satisfies OpenResponsesLanguageModelOptions,
  },
  prompt: 'Explain why the sky appears blue.',
});

console.log(reasoningText);
console.log(text);
```

`reasoningSummary` accepts `'auto'`, `'concise'`, or `'detailed'`. Reasoning
support and accepted values depend on the endpoint and model.

## File Inputs

The provider supports image and non-image file inputs in user messages. Images
are sent as `input_image` parts, while other media types, such as PDFs, are
sent as `input_file` parts.

You can provide a file as inline data:

```ts
import { createOpenResponses } from '@ai-sdk/open-responses';
import { readFileSync } from 'node:fs';
import { generateText } from 'ai';

const openResponses = createOpenResponses({
  name: 'lmstudio',
  url: 'http://localhost:1234/v1/responses',
});

const { text } = await generateText({
  model: openResponses('your-file-capable-model-id'),
  messages: [
    {
      role: 'user',
      content: [
        {
          type: 'text',
          text: 'Summarize this document.',
        },
        {
          type: 'file',
          data: readFileSync('./document.pdf'),
          mediaType: 'application/pdf',
          filename: 'document.pdf',
        },
      ],
    },
  ],
});

console.log(text);
```

You can also set `data` to a `URL`. The endpoint and model must support the
file's media type. Provider file references, such as OpenAI file IDs, and
file data in `{ type: 'text', text: '...' }` format are not supported by this
provider.

## Limitations

- Stop sequences, `topK`, and `seed` are not supported and are ignored with warnings.
- The provider supports language models only. It does not provide embedding or
  image generation models.
- AI SDK function tools are supported. Provider-specific built-in tools and
  options require a dedicated provider implementation.


## Navigation

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