migrate model into adapter

README.md

@@ -53,7 +53,7 @@ A powerful, type-safe AI SDK for building AI-powered applications.
 Import only the functionality you need for smaller bundle sizes:
 
 ```typescript
-// Only chat functionality - no embedding or summarization code bundled
+// Only chat functionality - no summarization code bundled
 import { openaiText } from '@tanstack/ai-openai/adapters'
 import { generate } from '@tanstack/ai'
 

docs/adapters/anthropic.md

@@ -18,11 +18,8 @@ npm install @tanstack/ai-anthropic
 import { chat } from "@tanstack/ai";
 import { anthropicText } from "@tanstack/ai-anthropic";
 
-const adapter = anthropicText();
-
 const stream = chat({
-  adapter,
-  model: "claude-sonnet-4-5",
+  adapter: anthropicText("claude-sonnet-4-5"),
   messages: [{ role: "user", content: "Hello!" }],
 });
 ```
@@ -38,8 +35,7 @@ const adapter = createAnthropicChat(process.env.ANTHROPIC_API_KEY!, {
 });
 
 const stream = chat({
-  adapter,
-  model: "claude-sonnet-4-5",
+  adapter: adapter("claude-sonnet-4-5"),
   messages: [{ role: "user", content: "Hello!" }],
 });
 ```
@@ -63,14 +59,11 @@ const adapter = createAnthropicChat(process.env.ANTHROPIC_API_KEY!, config);
 import { chat, toStreamResponse } from "@tanstack/ai";
 import { anthropicText } from "@tanstack/ai-anthropic";
 
-const adapter = anthropicText();
-
 export async function POST(request: Request) {
   const { messages } = await request.json();
 
   const stream = chat({
-    adapter,
-    model: "claude-sonnet-4-5",
+    adapter: anthropicText("claude-sonnet-4-5"),
     messages,
   });
 
@@ -85,8 +78,6 @@ import { chat, toolDefinition } from "@tanstack/ai";
 import { anthropicText } from "@tanstack/ai-anthropic";
 import { z } from "zod";
 
-const adapter = anthropicText();
-
 const searchDatabaseDef = toolDefinition({
   name: "search_database",
   description: "Search the database",
@@ -101,8 +92,7 @@ const searchDatabase = searchDatabaseDef.server(async ({ query }) => {
 });
 
 const stream = chat({
-  adapter,
-  model: "claude-sonnet-4-5",
+  adapter: anthropicText("claude-sonnet-4-5"),
   messages,
   tools: [searchDatabase],
 });
@@ -114,8 +104,7 @@ Anthropic supports various provider-specific options:
 
 ```typescript
 const stream = chat({
-  adapter: anthropicText(),
-  model: "claude-sonnet-4-5",
+  adapter: anthropicText("claude-sonnet-4-5"),
   messages,
   modelOptions: {
     max_tokens: 4096,
@@ -148,8 +137,7 @@ Cache prompts for better performance and reduced costs:
 
 ```typescript
 const stream = chat({
-  adapter: anthropicText(),
-  model: "claude-sonnet-4-5",
+  adapter: anthropicText("claude-sonnet-4-5"),
   messages: [
     {
       role: "user",
@@ -166,7 +154,6 @@ const stream = chat({
       ],
     },
   ],
-  model: "claude-sonnet-4-5",
 });
 ```
 
@@ -178,11 +165,8 @@ Anthropic supports text summarization:
 import { summarize } from "@tanstack/ai";
 import { anthropicSummarize } from "@tanstack/ai-anthropic";
 
-const adapter = anthropicSummarize();
-
 const result = await summarize({
-  adapter,
-  model: "claude-sonnet-4-5",
+  adapter: anthropicSummarize("claude-sonnet-4-5"),
   text: "Your long text to summarize...",
   maxLength: 100,
   style: "concise", // "concise" | "bullet-points" | "paragraph"
@@ -237,7 +221,6 @@ Creates an Anthropic summarization adapter with an explicit API key.
 
 ## Limitations
 
-- **Embeddings**: Anthropic does not support embeddings natively. Use OpenAI or Gemini for embedding needs.
 - **Image Generation**: Anthropic does not support image generation. Use OpenAI or Gemini for image generation.
 
 ## Next Steps

docs/adapters/gemini.md

@@ -4,7 +4,7 @@ id: gemini-adapter
 order: 3
 ---
 
-The Google Gemini adapter provides access to Google's Gemini models, including text generation, embeddings, image generation with Imagen, and experimental text-to-speech.
+The Google Gemini adapter provides access to Google's Gemini models, including text generation, image generation with Imagen, and experimental text-to-speech.
 
 ## Installation
 
@@ -18,11 +18,8 @@ npm install @tanstack/ai-gemini
 import { chat } from "@tanstack/ai";
 import { geminiText } from "@tanstack/ai-gemini";
 
-const adapter = geminiText();
-
 const stream = chat({
-  adapter,
-  model: "gemini-2.5-pro",
+  adapter: geminiText("gemini-2.5-pro"),
   messages: [{ role: "user", content: "Hello!" }],
 });
 ```
@@ -38,8 +35,7 @@ const adapter = createGeminiChat(process.env.GEMINI_API_KEY!, {
 });
 
 const stream = chat({
-  adapter,
-  model: "gemini-2.5-pro",
+  adapter: adapter("gemini-2.5-pro"),
   messages: [{ role: "user", content: "Hello!" }],
 });
 ```
@@ -63,14 +59,11 @@ const adapter = createGeminiChat(process.env.GEMINI_API_KEY!, config);
 import { chat, toStreamResponse } from "@tanstack/ai";
 import { geminiText } from "@tanstack/ai-gemini";
 
-const adapter = geminiText();
-
 export async function POST(request: Request) {
   const { messages } = await request.json();
 
   const stream = chat({
-    adapter,
-    model: "gemini-2.5-pro",
+    adapter: geminiText("gemini-2.5-pro"),
     messages,
   });
 
@@ -85,8 +78,6 @@ import { chat, toolDefinition } from "@tanstack/ai";
 import { geminiText } from "@tanstack/ai-gemini";
 import { z } from "zod";
 
-const adapter = geminiText();
-
 const getCalendarEventsDef = toolDefinition({
   name: "get_calendar_events",
   description: "Get calendar events for a date",
@@ -101,8 +92,7 @@ const getCalendarEvents = getCalendarEventsDef.server(async ({ date }) => {
 });
 
 const stream = chat({
-  adapter,
-  model: "gemini-2.5-pro",
+  adapter: geminiText("gemini-2.5-pro"),
   messages,
   tools: [getCalendarEvents],
 });
@@ -114,8 +104,7 @@ Gemini supports various model-specific options:
 
 ```typescript
 const stream = chat({
-  adapter: geminiText(),
-  model: "gemini-2.5-pro",
+  adapter: geminiText("gemini-2.5-pro"),
   messages,
   modelOptions: {
     maxOutputTokens: 2048,
@@ -149,52 +138,6 @@ modelOptions: {
 }
 ```
 
-## Embeddings
-
-Generate text embeddings for semantic search and similarity:
-
-```typescript
-import { embedding } from "@tanstack/ai";
-import { geminiEmbedding } from "@tanstack/ai-gemini";
-
-const adapter = geminiEmbedding();
-
-const result = await embedding({
-  adapter,
-  model: "gemini-embedding-001",
-  input: "The quick brown fox jumps over the lazy dog",
-});
-
-console.log(result.embeddings);
-```
-
-### Batch Embeddings
-
-```typescript
-const result = await embedding({
-  adapter: geminiEmbedding(),
-  model: "gemini-embedding-001",
-  input: [
-    "First text to embed",
-    "Second text to embed",
-    "Third text to embed",
-  ],
-});
-```
-
-### Embedding Model Options
-
-```typescript
-const result = await embedding({
-  adapter: geminiEmbedding(),
-  model: "gemini-embedding-001",
-  input: "...",
-  modelOptions: {
-    taskType: "RETRIEVAL_DOCUMENT", // or "RETRIEVAL_QUERY", "SEMANTIC_SIMILARITY", etc.
-  },
-});
-```
-
 ## Summarization
 
 Summarize long text content:
@@ -203,11 +146,8 @@ Summarize long text content:
 import { summarize } from "@tanstack/ai";
 import { geminiSummarize } from "@tanstack/ai-gemini";
 
-const adapter = geminiSummarize();
-
 const result = await summarize({
-  adapter,
-  model: "gemini-2.5-pro",
+  adapter: geminiSummarize("gemini-2.5-pro"),
   text: "Your long text to summarize...",
   maxLength: 100,
   style: "concise", // "concise" | "bullet-points" | "paragraph"
@@ -224,11 +164,8 @@ Generate images with Imagen:
 import { generateImage } from "@tanstack/ai";
 import { geminiImage } from "@tanstack/ai-gemini";
 
-const adapter = geminiImage();
-
 const result = await generateImage({
-  adapter,
-  model: "imagen-3.0-generate-002",
+  adapter: geminiImage("imagen-3.0-generate-002"),
   prompt: "A futuristic cityscape at sunset",
   numberOfImages: 1,
 });
@@ -240,8 +177,7 @@ console.log(result.images);
 
 ```typescript
 const result = await generateImage({
-  adapter: geminiImage(),
-  model: "imagen-3.0-generate-002",
+  adapter: geminiImage("imagen-3.0-generate-002"),
   prompt: "...",
   modelOptions: {
     aspectRatio: "16:9", // "1:1" | "3:4" | "4:3" | "9:16" | "16:9"
@@ -261,11 +197,8 @@ Generate speech from text:
 import { generateSpeech } from "@tanstack/ai";
 import { geminiSpeech } from "@tanstack/ai-gemini";
 
-const adapter = geminiSpeech();
-
 const result = await generateSpeech({
-  adapter,
-  model: "gemini-2.5-flash-preview-tts",
+  adapter: geminiSpeech("gemini-2.5-flash-preview-tts"),
   text: "Hello from Gemini TTS!",
 });
 
@@ -307,18 +240,6 @@ Creates a Gemini text/chat adapter with an explicit API key.
 
 **Returns:** A Gemini text adapter instance.
 
-### `geminiEmbed(config?)`
-
-Creates a Gemini embedding adapter using environment variables.
-
-**Returns:** A Gemini embed adapter instance.
-
-### `createGeminiEmbed(apiKey, config?)`
-
-Creates a Gemini embedding adapter with an explicit API key.
-
-**Returns:** A Gemini embed adapter instance.
-
 ### `geminiSummarize(config?)`
 
 Creates a Gemini summarization adapter using environment variables.