ai-core/adapter-configuration

# Adapter Configuration

> **Dependency:** This skill builds on ai-core. Read it first for critical rules.

> **Before implementing:** Ask the user which provider and model they want.
> Then fetch the latest available models from the provider's source code
> (check the adapter's model metadata file, e.g. `packages/ai-openai/src/model-meta.ts`)
> or from the provider's API/docs to recommend the most current model.
> The model lists in this skill and its reference files may be outdated.
> Always verify against the source before recommending a specific model.

## Setup

Create an adapter and use it with `chat()`:

```typescript
import { chat, toServerSentEventsResponse } from '@tanstack/ai'
import { openaiText } from '@tanstack/ai-openai'

const stream = chat({
  adapter: openaiText('gpt-5.2'),
  messages,
  modelOptions: {
    temperature: 0.7,
    max_output_tokens: 1000,
  },
})

return toServerSentEventsResponse(stream)
```

The adapter factory function takes the model name as a string literal and an
optional config object (API key, base URL, etc.). The model name is passed
into the factory, not into `chat()`.

Sampling options (`temperature`, token limits, `top_p`/`topP`, etc.) live
inside `modelOptions` using each provider's native key — they are **not**
top-level options on `chat()`. See the per-provider table in
[Configuring Sampling](#5-configuring-sampling) below.

## Core Patterns

### 1. Adapter Selection

Each provider has a dedicated package with tree-shakeable adapter factories.
The text adapter is the primary one for chat/completions:

| Provider          | Package                          | Factory                                     | Env Var                                           |
| ----------------- | -------------------------------- | ------------------------------------------- | ------------------------------------------------- |
| OpenAI            | `@tanstack/ai-openai`            | `openaiText`                                | `OPENAI_API_KEY`                                  |
| Anthropic         | `@tanstack/ai-anthropic`         | `anthropicText`                             | `ANTHROPIC_API_KEY`                               |
| Gemini            | `@tanstack/ai-gemini`            | `geminiText`                                | `GOOGLE_API_KEY` or `GEMINI_API_KEY`              |
| Grok (xAI)        | `@tanstack/ai-grok`              | `grokText`                                  | `XAI_API_KEY`                                     |
| Groq              | `@tanstack/ai-groq`              | `groqText`                                  | `GROQ_API_KEY`                                    |
| OpenRouter        | `@tanstack/ai-openrouter`        | `openRouterText`                            | `OPENROUTER_API_KEY`                              |
| Ollama            | `@tanstack/ai-ollama`            | `ollamaText`                                | `OLLAMA_HOST` (default: `http://localhost:11434`) |
| OpenAI-compatible | `@tanstack/ai-openai/compatible` | `openaiCompatible` / `openaiCompatibleText` | provider-specific (passed via `apiKey`)           |

```typescript
// Each factory takes model as first arg, optional config as second
import { openaiText } from '@tanstack/ai-openai'
import { anthropicText } from '@tanstack/ai-anthropic'
import { geminiText } from '@tanstack/ai-gemini'
import { grokText } from '@tanstack/ai-grok'
import { groqText } from '@tanstack/ai-groq'
import { openRouterText } from '@tanstack/ai-openrouter'
import { ollamaText } from '@tanstack/ai-ollama'

// Model string is passed to the factory, NOT to chat()
const adapter = openaiText('gpt-5.2')
const adapter2 = anthropicText('claude-sonnet-4-6')
const adapter3 = geminiText('gemini-2.5-pro')
const adapter4 = grokText('grok-4')
const adapter5 = groqText('llama-3.3-70b-versatile')
const adapter6 = openRouterText('anthropic/claude-sonnet-4')
const adapter7 = ollamaText('llama3.3')

// Optional: pass explicit API key
const adapterWithKey = openaiText('gpt-5.2', {
  apiKey: 'sk-...',
})
```

### 2. Runtime Adapter Switching

Use an adapter factory map to switch providers dynamically based on user
input or configuration:

```typescript
import { chat, toServerSentEventsResponse } from '@tanstack/ai'
import type { TextAdapter } from '@tanstack/ai/adapters'
import { openaiText } from '@tanstack/ai-openai'
import { anthropicText } from '@tanstack/ai-anthropic'
import { geminiText } from '@tanstack/ai-gemini'

// Define a map of provider+model to adapter factory calls
const adapters: Record<string, () => TextAdapter> = {
  'openai/gpt-5.2': () => openaiText('gpt-5.2'),
  'anthropic/claude-sonnet-4-6': () => anthropicText('claude-sonnet-4-6'),
  'gemini/gemini-2.5-pro': () => geminiText('gemini-2.5-pro'),
}

export function handleChat(providerModel: string, messages: Array<any>) {
  const createAdapter = adapters[providerModel]
  if (!createAdapter) {
    throw new Error(`Unknown provider/model: ${providerModel}`)
  }

  const stream = chat({
    adapter: createAdapter(),
    messages,
  })

  return toServerSentEventsResponse(stream)
}
```

### 3. Configuring Reasoning / Thinking

Different providers expose reasoning/thinking through their `modelOptions`:

```typescript
import { chat } from '@tanstack/ai'
import { openaiText } from '@tanstack/ai-openai'
import { anthropicText } from '@tanstack/ai-anthropic'
import { geminiText } from '@tanstack/ai-gemini'

// OpenAI: reasoning with effort and summary
const openaiStream = chat({
  adapter: openaiText('gpt-5.2'),
  messages,
  modelOptions: {
    reasoning: {
      effort: 'high',
      summary: 'auto',
    },
  },
})

// Anthropic: extended thinking with budget_tokens
const anthropicStream = chat({
  adapter: anthropicText('claude-sonnet-4-6'),
  messages,
  modelOptions: {
    max_tokens: 16000,
    thinking: {
      type: 'enabled',
      budget_tokens: 8000, // must be >= 1024 and < max_tokens
    },
  },
})

// Anthropic: adaptive thinking (claude-sonnet-