chore (docs): Further OpenAI compatible doc updates.

content/docs/02-foundations/02-providers-and-models.mdx

@@ -34,12 +34,12 @@ The AI SDK comes with several providers that you can use to interact with differ
 - [xAI Grok Provider](/providers/ai-sdk-providers/xai) (`@ai-sdk/xai`)
 - [Together.ai Provider](/providers/ai-sdk-providers/togetherai) (`@ai-sdk/togetherai`)
 - [Cohere Provider](/providers/ai-sdk-providers/cohere) (`@ai-sdk/cohere`)
+- [Fireworks](/providers/ai-sdk-providers/fireworks)
 - [Groq](/providers/ai-sdk-providers/groq) (`@ai-sdk/groq`)
 
 You can also use the OpenAI provider with OpenAI-compatible APIs:
 
 - [Perplexity](/providers/ai-sdk-providers/perplexity)
-- [Fireworks](/providers/ai-sdk-providers/fireworks)
 - [LM Studio](/providers/openai-compatible-providers/lmstudio)
 - [Baseten](/providers/openai-compatible-providers/baseten)
 

content/providers/02-openai-compatible-providers/10-perplexity.mdx

@@ -10,18 +10,18 @@ It offers an OpenAI compatible API that you can use with the AI SDK.
 
 ## Setup
 
-The Perplexity provider is available via the `@ai-sdk/openai` module as it is compatible with the OpenAI API.
+The Perplexity provider is available via the `@ai-sdk/openai-compatible` module as it is compatible with the OpenAI API.
 You can install it with
 
 <Tabs items={['pnpm', 'npm', 'yarn']}>
   <Tab>
-    <Snippet text="pnpm add @ai-sdk/openai" dark />
+    <Snippet text="pnpm add @ai-sdk/openai-compatible" dark />
   </Tab>
   <Tab>
-    <Snippet text="npm install @ai-sdk/openai" dark />
+    <Snippet text="npm install @ai-sdk/openai-compatible" dark />
   </Tab>
   <Tab>
-    <Snippet text="yarn add @ai-sdk/openai" dark />
+    <Snippet text="yarn add @ai-sdk/openai-compatible" dark />
   </Tab>
 </Tabs>
 
@@ -30,11 +30,13 @@ You can install it with
 To use Perplexity, you can create a custom provider instance with the `createOpenAI` function from `@ai-sdk/openai`:
 
 ```ts
-import { createOpenAI } from '@ai-sdk/openai';
+import { createOpenAICompatible } from '@ai-sdk/openai-compatible';
 
-const perplexity = createOpenAI({
+const perplexity = createOpenAICompatible({
   name: 'perplexity',
-  apiKey: process.env.PERPLEXITY_API_KEY ?? '',
+  headers: {
+    Authorization: `Bearer ${process.env.PERPLEXITY_API_KEY}`,
+  },
   baseURL: 'https://api.perplexity.ai/',
 });
 ```
@@ -53,12 +55,14 @@ const model = perplexity('llama-3.1-sonar-large-32k-online');
 You can use Perplexity language models to generate text with the `generateText` function:
 
 ```ts
-import { createOpenAI } from '@ai-sdk/openai';
+import { createOpenAICompatible } from '@ai-sdk/openai-compatible';
 import { generateText } from 'ai';
 
-const perplexity = createOpenAI({
+const perplexity = createOpenAICompatible({
   name: 'perplexity',
-  apiKey: process.env.PERPLEXITY_API_KEY ?? '',
+  headers: {
+    Authorization: `Bearer ${process.env.PERPLEXITY_API_KEY}`,
+  },
   baseURL: 'https://api.perplexity.ai/',
 });
 

content/providers/02-openai-compatible-providers/30-lmstudio.mdx

@@ -5,36 +5,36 @@ description: Use the LM Studio OpenAI compatible API with the AI SDK.
 
 # LM Studio Provider
 
-[LM Studio](https://lmstudio.ai/) is user interface for running local models.
+[LM Studio](https://lmstudio.ai/) is a user interface for running local models.
 
 It contains an OpenAI compatible API server that you can use with the AI SDK.
 You can start the local server under the [Local Server tab](https://lmstudio.ai/docs/basics/server) in the LM Studio UI ("Start Server" button).
 
 ## Setup
 
-The LM Studio provider is available via the `@ai-sdk/openai` module as it is compatible with the OpenAI API.
+The LM Studio provider is available via the `@ai-sdk/openai-compatible` module as it is compatible with the OpenAI API.
 You can install it with
 
 <Tabs items={['pnpm', 'npm', 'yarn']}>
   <Tab>
-    <Snippet text="pnpm add @ai-sdk/openai" dark />
+    <Snippet text="pnpm add @ai-sdk/openai-compatible" dark />
   </Tab>
   <Tab>
-    <Snippet text="npm install @ai-sdk/openai" dark />
+    <Snippet text="npm install @ai-sdk/openai-compatible" dark />
   </Tab>
   <Tab>
-    <Snippet text="yarn add @ai-sdk/openai" dark />
+    <Snippet text="yarn add @ai-sdk/openai-compatible" dark />
   </Tab>
 </Tabs>
 
 ## Provider Instance
 
-To use LM Studio, you can create a custom provider instance with the `createOpenAI` function from `@ai-sdk/openai`:
+To use LM Studio, you can create a custom provider instance with the `createOpenAICompatible` function from `@ai-sdk/openai-compatible`:
 
 ```ts
-import { createOpenAI } from '@ai-sdk/openai';
+import { createOpenAICompatible } from '@ai-sdk/openai-compatible';
 
-const lmstudio = createOpenAI({
+const lmstudio = createOpenAICompatible({
   name: 'lmstudio',
   baseURL: 'http://localhost:1234/v1',
   maxRetries: 1, // immediately error if the server is not running
@@ -62,12 +62,11 @@ const model = lmstudio('llama-3.2-1b');
 You can use LM Studio language models to generate text with the `generateText` function:
 
 ```ts
-import { createOpenAI } from '@ai-sdk/openai';
+import { createOpenAICompatible } from '@ai-sdk/openai-compatible';
 import { generateText } from 'ai';
 
-const lmstudio = createOpenAI({
+const lmstudio = createOpenAICompatible({
   name: 'lmstudio',
-  apiKey: 'not-needed',
   baseURL: 'https://localhost:1234/v1',
 });
 
@@ -91,18 +90,17 @@ const model = lmstudio.embedding('text-embedding-nomic-embed-text-v1.5');
 ### Example - Embedding a Single Value
 
 ```tsx
-import { createOpenAI } from '@ai-sdk/openai';
+import { createOpenAICompatible } from '@ai-sdk/openai-compatible';
 import { embed } from 'ai';
 
-const lmstudio = createOpenAI({
+const lmstudio = createOpenAICompatible({
   name: 'lmstudio',
-  apiKey: 'not-needed',
   baseURL: 'https://localhost:1234/v1',
 });
 
 // 'embedding' is a single embedding object (number[])
 const { embedding } = await embed({
-  model: lmstudio.embedding('text-embedding-nomic-embed-text-v1.5'),
+  model: lmstudio.textEmbeddingModel('text-embedding-nomic-embed-text-v1.5'),
   value: 'sunny day at the beach',
 });
 ```
@@ -114,16 +112,21 @@ it is often useful to embed many values at once (batch embedding).
 
 The AI SDK provides the [`embedMany`](/docs/reference/ai-sdk-core/embed-many) function for this purpose.
 Similar to `embed`, you can use it with embeddings models,
-e.g. `lmstudio.embedding('text-embedding-nomic-embed-text-v1.5')` or `lmstudio.embedding('text-embedding-bge-small-en-v1.5')`.
+e.g. `lmstudio.textEmbeddingModel('text-embedding-nomic-embed-text-v1.5')` or `lmstudio.textEmbeddingModel('text-embedding-bge-small-en-v1.5')`.
 
 ```tsx
-import { createOpenAI } from '@ai-sdk/openai';
+import { createOpenAICompatible } from '@ai-sdk/openai';
 import { embedMany } from 'ai';
 
+const lmstudio = createOpenAICompatible({
+  name: 'lmstudio',
+  baseURL: 'https://localhost:1234/v1',
+});
+
 // 'embeddings' is an array of embedding objects (number[][]).
 // It is sorted in the same order as the input values.
 const { embeddings } = await embedMany({
-  model: lmstudio.embedding('text-embedding-nomic-embed-text-v1.5'),
+  model: lmstudio.textEmbeddingModel('text-embedding-nomic-embed-text-v1.5'),
   values: [
     'sunny day at the beach',
     'rainy afternoon in the city',

content/providers/02-openai-compatible-providers/40-baseten.mdx

@@ -10,27 +10,27 @@ It allows you to deploy models that are OpenAI API compatible that you can use w
 
 ## Setup
 
-The Baseten provider is available via the `@ai-sdk/openai` module as it is compatible with the OpenAI API.
+The Baseten provider is available via the `@ai-sdk/openai-compatible` module as it is compatible with the OpenAI API.
 You can install it with
 
 <Tabs items={['pnpm', 'npm', 'yarn']}>
   <Tab>
-    <Snippet text="pnpm add @ai-sdk/openai" dark />
+    <Snippet text="pnpm add @ai-sdk/openai-compatible" dark />
   </Tab>
   <Tab>
-    <Snippet text="npm install @ai-sdk/openai" dark />
+    <Snippet text="npm install @ai-sdk/openai-compatible" dark />
   </Tab>
   <Tab>
-    <Snippet text="yarn add @ai-sdk/openai" dark />
+    <Snippet text="yarn add @ai-sdk/openai-compatible" dark />
   </Tab>
 </Tabs>
 
 ## Provider Instance
 
-To use Baseten, you can create a custom provider instance with the `createOpenAI` function from `@ai-sdk/openai`:
+To use Baseten, you can create a custom provider instance with the `createOpenAICompatible` function from `@ai-sdk/openai-compatible`:
 
 ```ts
-import { createOpenAI } from '@ai-sdk/openai';
+import { createOpenAICompatible } from '@ai-sdk/openai-compatible';
 
 const BASETEN_MODEL_ID = '<deployment-id>';
 const BASETEN_DEPLOYMENT_ID = null;
@@ -41,9 +41,11 @@ const basetenExtraPayload = {
   deployment_id: BASETEN_DEPLOYMENT_ID,
 };
 
-const baseten = createOpenAI({
+const baseten = createOpenAICompatible({
   name: 'baseten',
-  apiKey: process.env.BASETEN_API_KEY ?? '',
+  headers: {
+    Authorization: `Bearer ${process.env.BASETEN_API_KEY}`,
+  },
   baseURL: 'https://bridge.baseten.co/v1/direct',
   fetch: async (url, request) => {
     const bodyWithBasetenPayload = JSON.stringify({
@@ -71,7 +73,7 @@ const model = baseten('ultravox');
 You can use Baseten language models to generate text with the `generateText` function:
 
 ```ts
-import { createOpenAI } from '@ai-sdk/openai';
+import { createOpenAICompatible } from '@ai-sdk/openai-compatible';
 import { generateText } from 'ai';
 
 const BASETEN_MODEL_ID = '<deployment-id>';
@@ -83,9 +85,11 @@ const basetenExtraPayload = {
   deployment_id: BASETEN_DEPLOYMENT_ID,
 };
 
-const baseten = createOpenAI({
+const baseten = createOpenAICompatible({
   name: 'baseten',
-  apiKey: process.env.BASETEN_API_KEY ?? '',
+  headers: {
+    Authorization: `Bearer ${process.env.BASETEN_API_KEY}`,
+  },
   baseURL: 'https://bridge.baseten.co/v1/direct',
   fetch: async (url, request) => {
     const bodyWithBasetenPayload = JSON.stringify({
@@ -107,7 +111,7 @@ console.log(text);
 Baseten language models are also able to generate text in a streaming fashion with the `streamText` function:
 
 ```ts
-import { createOpenAI } from '@ai-sdk/openai';
+import { createOpenAICompatible } from '@ai-sdk/openai-compatible';
 import { streamText } from 'ai';
 
 const BASETEN_MODEL_ID = '<deployment-id>';
@@ -119,9 +123,11 @@ const basetenExtraPayload = {
   deployment_id: BASETEN_DEPLOYMENT_ID,
 };
 
-const baseten = createOpenAI({
+const baseten = createOpenAICompatible({
   name: 'baseten',
-  apiKey: process.env.BASETEN_API_KEY ?? '',
+  headers: {
+    Authorization: `Bearer ${process.env.BASETEN_API_KEY}`,
+  },
   baseURL: 'https://bridge.baseten.co/v1/direct',
   fetch: async (url, request) => {
     const bodyWithBasetenPayload = JSON.stringify({

content/providers/02-openai-compatible-providers/index.mdx

@@ -42,7 +42,9 @@ import { createOpenAICompatible } from '@ai-sdk/openai-compatible';
 
 const provider = createOpenAICompatible({
   name: 'provider-name',
-  apiKey: process.env.PROVIDER_API_KEY ?? '',
+  headers: {
+    Authorization: `Bearer ${process.env.PROVIDER_API_KEY}`,
+  },
   baseURL: 'https://api.provider.com/v1',
 });
 ```
@@ -66,7 +68,9 @@ import { generateText } from 'ai'
 
 const provider = createOpenAICompatible({
   name: 'provider-name',
-  apiKey: process.env.PROVIDER_API_KEY ?? '',
+  headers: {
+    Authorization: `Bearer ${process.env.PROVIDER_API_KEY}`,
+  },
   baseURL: 'https://api.provider.com/v1'
 })
 
@@ -102,11 +106,11 @@ const model = createOpenAICompatible<
   ExampleCompletionModelIds,
   ExampleEmbeddingModelIds
 >({
-  baseURL: 'https://api.example.com/v1',
   name: 'example',
   headers: {
     Authorization: `Bearer ${process.env.MY_API_KEY}`,
   },
+  baseURL: 'https://api.example.com/v1',
 });
 
 // Subsequent calls to e.g. `model.chatModel` will auto-complete the model id