Vercel AI SDK Integration

The Chutes.ai Provider for Vercel AI SDK allows you to use open-source AI models hosted on Chutes.ai with the Vercel AI SDK. It supports a wide range of capabilities including chat, streaming, tool calling, and multimodal generation.

Features

✅ Language Models: Complete support for chat and text completion
✅ Streaming: Real-time Server-Sent Events (SSE) streaming
✅ Tool Calling: Full function/tool calling support
✅ Multimodal: Image, Video, Audio (TTS/STT/Music) generation
✅ Chute Warmup: Pre-warm chutes for instant response times
✅ Type-Safe: Fully typed for excellent IDE support

Installation

Install the provider and the AI SDK:

npm install @chutes-ai/ai-sdk-provider ai

Note: For Next.js projects with TypeScript, AI SDK v5 is recommended:

npm install @chutes-ai/ai-sdk-provider ai@^5.0.0

Configuration

1. Get API Key

Get your API key from Chutes.ai and set it as an environment variable:

export CHUTES_API_KEY=your-api-key-here

2. Initialize Provider

You can initialize the provider with your API key.

import { createChutes } from "@chutes-ai/ai-sdk-provider";

const chutes = createChutes({
  apiKey: process.env.CHUTES_API_KEY,
});

Language Models

Text Generation

Generate text using any LLM hosted on Chutes.

import { generateText } from "ai";

const model = chutes("https://chutes-deepseek-ai-deepseek-v3.chutes.ai");

const result = await generateText({
  model,
  prompt: "Explain quantum computing in simple terms",
});

console.log(result.text);

Streaming Responses

Stream responses in real-time for a better user experience.

import { streamText } from "ai";

const result = await streamText({
  model: chutes("https://chutes-meta-llama-llama-3-1-70b-instruct.chutes.ai"),
  prompt: "Write a story about a space traveler.",
});

for await (const chunk of result.textStream) {
  process.stdout.write(chunk);
}

Tool Calling

Connect LLMs to external data and functions.

import { z } from "zod";

const result = await generateText({
  model: chutes("https://chutes-deepseek-ai-deepseek-v3.chutes.ai"),
  tools: {
    getWeather: {
      description: "Get the current weather",
      parameters: z.object({
        location: z.string().describe("City name"),
      }),
      execute: async ({ location }) => {
        return { temp: 72, condition: "Sunny", location };
      },
    },
  },
  prompt: "What is the weather in San Francisco?",
});

Multimodal Capabilities

Image Generation

Generate images using models like FLUX.

import * as fs from "fs";

const imageModel = chutes.imageModel("flux-dev");

const result = await imageModel.doGenerate({
  prompt: "A cyberpunk city with neon lights and flying cars",
  size: "1024x1024",
});

const base64Data = result.images[0].split(",")[1];
fs.writeFileSync("city.png", Buffer.from(base64Data, "base64"));

Text-to-Speech (TTS)

Convert text to speech using over 50 available voices.

const audioModel = chutes.audioModel("your-tts-chute-id");

const result = await audioModel.textToSpeech({
  text: "Welcome to the future of AI.",
  voice: "af_bella", // American Female - Bella
});

fs.writeFileSync("output.mp3", result.audio);

Speech-to-Text (STT)

Transcribe audio files.

const audioModel = chutes.audioModel("your-stt-chute-id");
const audioBuffer = fs.readFileSync("recording.mp3");

const transcription = await audioModel.speechToText({
  audio: audioBuffer,
  language: "en",
});

console.log(transcription.text);

Advanced Features

Chute Warmup (Therm)

Pre-warm chutes to eliminate cold starts.

// Warm up a chute
const result = await chutes.therm.warmup("your-chute-id");

if (result.isHot) {
  console.log("Chute is ready!");
} else {
  console.log("Warming up...");
}

Embeddings

Generate vector embeddings for semantic search.

import { embedMany } from "ai";

const embeddingModel = chutes.textEmbeddingModel("text-embedding-3-small");

const { embeddings } = await embedMany({
  model: embeddingModel,
  values: ["Hello world", "Machine learning is cool"],
});

Developers