Anthropic | TanStack AI Docs

The Anthropic adapter provides access to Claude models, including Claude Sonnet 4.5, Claude Opus 4.5, and more.

Installation

bash

npm install @tanstack/ai-anthropic

npm install @tanstack/ai-anthropic

Basic Usage

typescript

import { chat } from "@tanstack/ai";
import { anthropicText } from "@tanstack/ai-anthropic";

const stream = chat({
  adapter: anthropicText("claude-sonnet-4-5"),
  messages: [{ role: "user", content: "Hello!" }],
});

import { chat } from "@tanstack/ai";
import { anthropicText } from "@tanstack/ai-anthropic";

const stream = chat({
  adapter: anthropicText("claude-sonnet-4-5"),
  messages: [{ role: "user", content: "Hello!" }],
});

Basic Usage - Custom API Key

typescript

import { chat } from "@tanstack/ai";
import { createAnthropicChat } from "@tanstack/ai-anthropic";

const adapter = createAnthropicChat(process.env.ANTHROPIC_API_KEY!, {
  // ... your config options
});

const stream = chat({
  adapter: adapter("claude-sonnet-4-5"),
  messages: [{ role: "user", content: "Hello!" }],
});

import { chat } from "@tanstack/ai";
import { createAnthropicChat } from "@tanstack/ai-anthropic";

const adapter = createAnthropicChat(process.env.ANTHROPIC_API_KEY!, {
  // ... your config options
});

const stream = chat({
  adapter: adapter("claude-sonnet-4-5"),
  messages: [{ role: "user", content: "Hello!" }],
});

Configuration

typescript

import { createAnthropicChat, type AnthropicChatConfig } from "@tanstack/ai-anthropic";

const config: Omit<AnthropicChatConfig, 'apiKey'> = {
  baseURL: "https://api.anthropic.com", // Optional, for custom endpoints
};

const adapter = createAnthropicChat(process.env.ANTHROPIC_API_KEY!, config);

import { createAnthropicChat, type AnthropicChatConfig } from "@tanstack/ai-anthropic";

const config: Omit<AnthropicChatConfig, 'apiKey'> = {
  baseURL: "https://api.anthropic.com", // Optional, for custom endpoints
};

const adapter = createAnthropicChat(process.env.ANTHROPIC_API_KEY!, config);

Example: Chat Completion

typescript

import { chat, toServerSentEventsResponse } from "@tanstack/ai";
import { anthropicText } from "@tanstack/ai-anthropic";

export async function POST(request: Request) {
  const { messages } = await request.json();

  const stream = chat({
    adapter: anthropicText("claude-sonnet-4-5"),
    messages,
  });

  return toServerSentEventsResponse(stream);
}

import { chat, toServerSentEventsResponse } from "@tanstack/ai";
import { anthropicText } from "@tanstack/ai-anthropic";

export async function POST(request: Request) {
  const { messages } = await request.json();

  const stream = chat({
    adapter: anthropicText("claude-sonnet-4-5"),
    messages,
  });

  return toServerSentEventsResponse(stream);
}

Example: With Tools

typescript

import { chat, toolDefinition } from "@tanstack/ai";
import { anthropicText } from "@tanstack/ai-anthropic";
import { z } from "zod";

const searchDatabaseDef = toolDefinition({
  name: "search_database",
  description: "Search the database",
  inputSchema: z.object({
    query: z.string(),
  }),
});

const searchDatabase = searchDatabaseDef.server(async ({ query }) => {
  // Search database
  return { results: [] };
});

const stream = chat({
  adapter: anthropicText("claude-sonnet-4-5"),
  messages,
  tools: [searchDatabase],
});

import { chat, toolDefinition } from "@tanstack/ai";
import { anthropicText } from "@tanstack/ai-anthropic";
import { z } from "zod";

const searchDatabaseDef = toolDefinition({
  name: "search_database",
  description: "Search the database",
  inputSchema: z.object({
    query: z.string(),
  }),
});

const searchDatabase = searchDatabaseDef.server(async ({ query }) => {
  // Search database
  return { results: [] };
});

const stream = chat({
  adapter: anthropicText("claude-sonnet-4-5"),
  messages,
  tools: [searchDatabase],
});

Model Options

Anthropic supports various provider-specific options:

typescript

const stream = chat({
  adapter: anthropicText("claude-sonnet-4-5"),
  messages,
  modelOptions: {
    max_tokens: 4096,
    temperature: 0.7,
    top_p: 0.9,
    top_k: 40,
    stop_sequences: ["END"],
  },
});

const stream = chat({
  adapter: anthropicText("claude-sonnet-4-5"),
  messages,
  modelOptions: {
    max_tokens: 4096,
    temperature: 0.7,
    top_p: 0.9,
    top_k: 40,
    stop_sequences: ["END"],
  },
});

Thinking (Extended Thinking)

Enable extended thinking with a token budget. This allows Claude to show its reasoning process, which is streamed as thinking chunks:

typescript

modelOptions: {
  thinking: {
    type: "enabled",
    budget_tokens: 2048, // Maximum tokens for thinking
  },
}

modelOptions: {
  thinking: {
    type: "enabled",
    budget_tokens: 2048, // Maximum tokens for thinking
  },
}

Note: max_tokens must be greater than budget_tokens. The adapter automatically adjusts max_tokens if needed.

Prompt Caching

Cache prompts for better performance and reduced costs:

typescript

const stream = chat({
  adapter: anthropicText("claude-sonnet-4-5"),
  messages: [
    {
      role: "user",
      content: [
        {
          type: "text",
          content: "What is the capital of France?",
          metadata: {
            cache_control: {
              type: "ephemeral",
            },
          },
        },
      ],
    },
  ],
});

const stream = chat({
  adapter: anthropicText("claude-sonnet-4-5"),
  messages: [
    {
      role: "user",
      content: [
        {
          type: "text",
          content: "What is the capital of France?",
          metadata: {
            cache_control: {
              type: "ephemeral",
            },
          },
        },
      ],
    },
  ],
});

Summarization

Anthropic supports text summarization:

typescript

import { summarize } from "@tanstack/ai";
import { anthropicSummarize } from "@tanstack/ai-anthropic";

const result = await summarize({
  adapter: anthropicSummarize("claude-sonnet-4-5"),
  text: "Your long text to summarize...",
  maxLength: 100,
  style: "concise", // "concise" | "bullet-points" | "paragraph"
});

console.log(result.summary);

import { summarize } from "@tanstack/ai";
import { anthropicSummarize } from "@tanstack/ai-anthropic";

const result = await summarize({
  adapter: anthropicSummarize("claude-sonnet-4-5"),
  text: "Your long text to summarize...",
  maxLength: 100,
  style: "concise", // "concise" | "bullet-points" | "paragraph"
});

console.log(result.summary);