TanStack · AlemTuzlak · Dec 18, 2025 · Dec 17, 2025 · Dec 17, 2025 · Dec 17, 2025
diff --git a/README.md b/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'
 

diff --git a/docs/adapters/anthropic.md b/docs/adapters/anthropic.md
@@ -221,7 +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

diff --git a/docs/adapters/gemini.md b/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
 
@@ -138,47 +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 result = await embedding({
-  adapter: geminiEmbedding("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("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("gemini-embedding-001"),
-  input: "...",
-  modelOptions: {
-    taskType: "RETRIEVAL_DOCUMENT", // or "RETRIEVAL_QUERY", "SEMANTIC_SIMILARITY", etc.
-  },
-});
-```
-
 ## Summarization
 
 Summarize long text content:
@@ -281,18 +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.

diff --git a/docs/adapters/ollama.md b/docs/adapters/ollama.md
@@ -170,45 +170,6 @@ modelOptions: {
 }
 ```
 
-## Embeddings
-
-Generate text embeddings locally:
-
-```typescript
-import { embedding } from "@tanstack/ai";
-import { ollamaEmbedding } from "@tanstack/ai-ollama";
-
-const result = await embedding({
-  adapter: ollamaEmbedding("nomic-embed-text"),
-  input: "The quick brown fox jumps over the lazy dog",
-});
-
-console.log(result.embeddings);
-```
-
-### Embedding Models
-
-First, pull an embedding model:
-
-```bash
-ollama pull nomic-embed-text
-# or
-ollama pull mxbai-embed-large
-```
-
-### Batch Embeddings
-
-```typescript
-const result = await embedding({
-  adapter: ollamaEmbedding("nomic-embed-text"),
-  input: [
-    "First text to embed",
-    "Second text to embed",
-    "Third text to embed",
-  ],
-});
-```
-
 ## Summarization
 
 Summarize long text content locally:
@@ -299,18 +260,6 @@ Creates an Ollama text/chat adapter with a custom host.
 
 **Returns:** An Ollama text adapter instance.
 
-### `ollamaEmbed(options?)`
-
-Creates an Ollama embedding adapter.
-
-**Returns:** An Ollama embed adapter instance.
-
-### `createOllamaEmbed(host?, options?)`
-
-Creates an Ollama embedding adapter with a custom host.
-
-**Returns:** An Ollama embed adapter instance.
-
 ### `ollamaSummarize(options?)`
 
 Creates an Ollama summarization adapter.

diff --git a/docs/adapters/openai.md b/docs/adapters/openai.md
@@ -4,7 +4,7 @@ id: openai-adapter
 order: 1
 ---
 
-The OpenAI adapter provides access to OpenAI's models, including GPT-4o, GPT-5, embeddings, image generation (DALL-E), text-to-speech (TTS), and audio transcription (Whisper).
+The OpenAI adapter provides access to OpenAI's models, including GPT-4o, GPT-5, image generation (DALL-E), text-to-speech (TTS), and audio transcription (Whisper).
 
 ## Installation
 
@@ -132,49 +132,6 @@ modelOptions: {
 
 When reasoning is enabled, the model's reasoning process is streamed separately from the response text and appears as a collapsible thinking section in the UI.
 
-## Embeddings
-
-Generate text embeddings for semantic search and similarity:
-
-```typescript
-import { embedding } from "@tanstack/ai";
-import { openaiEmbedding } from "@tanstack/ai-openai";
-
-const result = await embedding({
-  adapter: openaiEmbedding("text-embedding-3-small"),
-  input: "The quick brown fox jumps over the lazy dog",
-});
-
-console.log(result.embeddings); // Array of embedding vectors
-```
-
-### Batch Embeddings
-
-```typescript
-const result = await embedding({
-  adapter: openaiEmbedding("text-embedding-3-small"),
-  input: [
-    "First text to embed",
-    "Second text to embed",
-    "Third text to embed",
-  ],
-});
-
-// result.embeddings contains an array of vectors
-```
-
-### Embedding Model Options
-
-```typescript
-const result = await embedding({
-  adapter: openaiEmbedding("text-embedding-3-small"),
-  input: "...",
-  modelOptions: {
-    dimensions: 512, // Reduce dimensions for smaller storage
-  },
-});
-```
-
 ## Summarization
 
 Summarize long text content:
@@ -321,18 +278,6 @@ Creates an OpenAI chat adapter with an explicit API key.
 
 **Returns:** An OpenAI chat adapter instance.
 
-### `openaiEmbedding(config?)`
-
-Creates an OpenAI embedding adapter using environment variables.
-
-**Returns:** An OpenAI embedding adapter instance.
-
-### `createOpenaiEmbedding(apiKey, config?)`
-
-Creates an OpenAI embedding adapter with an explicit API key.
-
-**Returns:** An OpenAI embed adapter instance.
-
 ### `openaiSummarize(config?)`
 
 Creates an OpenAI summarization adapter using environment variables.

diff --git a/docs/api/ai.md b/docs/api/ai.md
@@ -71,30 +71,6 @@ const result = await summarize({
 
 A `SummarizationResult` with the summary text.
 
-## `embedding(options)`
-
-Creates embeddings for text input.
-
-```typescript
-import { embedding } from "@tanstack/ai";
-import { openaiEmbedding } from "@tanstack/ai-openai";
-
-const result = await embedding({
-  adapter: openaiEmbedding("text-embedding-3-small"),
-  input: "Text to embed",
-});
-```
-
-### Parameters
-
-- `adapter` - An AI adapter instance with model
-- `input` - Text or array of texts to embed
-- `modelOptions?` - Model-specific options
-
-### Returns
-
-An `EmbeddingResult` with embeddings array.
-
 ## `toolDefinition(config)`
 
 Creates an isomorphic tool definition that can be instantiated for server or client execution.
@@ -289,11 +265,10 @@ interface Tool {
 ## Usage Examples
 
 ```typescript
-import { chat, summarize, embedding, generateImage } from "@tanstack/ai";
+import { chat, summarize, generateImage } from "@tanstack/ai";
 import {
   openaiText,
   openaiSummarize,
-  openaiEmbedding,
   openaiImage,
 } from "@tanstack/ai-openai";
 
@@ -356,12 +331,6 @@ const summary = await summarize({
   maxLength: 100,
 });
 
-// --- Embeddings
-const embeddings = await embedding({
-  adapter: openaiEmbedding("text-embedding-3-small"),
-  input: "Text to embed",
-});
-
 // --- Image generation
 const image = await generateImage({
   adapter: openaiImage("dall-e-3"),