Decart | TanStack AI 文档

Decart 适配器提供访问 Decart 的图像和视频生成模型的功能。

安装

npm install @decartai/tanstack-ai-adapter

基本用法

typescript

import { generateImage } from "@tanstack/ai";
import { decartImage } from "@decartai/tanstack-ai-adapter";

const result = await generateImage({
  adapter: decartImage("lucy-pro-t2i"),
  prompt: "A serene mountain landscape at sunset",
});

基本用法 - 自定义 API 密钥

typescript

import { generateImage } from "@tanstack/ai";
import { createDecartImage } from "@decartai/tanstack-ai-adapter";

const adapter = createDecartImage("lucy-pro-t2i", process.env.DECART_API_KEY!);

const result = await generateImage({
  adapter,
  prompt: "A serene mountain landscape at sunset",
});

配置

typescript

import { createDecartImage, type DecartImageConfig } from "@decartai/tanstack-ai-adapter";

const config: Omit<DecartImageConfig, "apiKey"> = {
  baseUrl: "https://api.decart.ai", // Optional, for custom endpoints
};

const adapter = createDecartImage("lucy-pro-t2i", process.env.DECART_API_KEY!, config);

图像生成

使用 lucy-pro-t2i 生成图像

typescript

import { generateImage } from "@tanstack/ai";
import { decartImage } from "@decartai/tanstack-ai-adapter";

const result = await generateImage({
  adapter: decartImage("lucy-pro-t2i"),
  prompt: "A futuristic cityscape at night",
});

console.log(result.images[0].b64Json);

图像模型选项

typescript

const result = await generateImage({
  adapter: decartImage("lucy-pro-t2i"),
  prompt: "A portrait of a robot artist",
  modelOptions: {
    resolution: "720p",
    orientation: "portrait",
    seed: 42,
  },
});

选项	类型	默认	描述
分辨率	"720p"	"720p"	输出分辨率
方向	"portrait" \| "landscape"	"landscape"	图像方向
种子	number	-	用于可重复生成的种子

视频生成

视频生成使用异步任务/轮询架构。

创建视频任务

typescript

import { generateVideo } from "@tanstack/ai";
import { decartVideo } from "@decartai/tanstack-ai-adapter";

const { jobId } = await generateVideo({
  adapter: decartVideo("lucy-pro-t2v"),
  prompt: "A cat playing with a ball of yarn",
});

console.log("Job started:", jobId);

轮询状态

typescript

import { getVideoJobStatus } from "@tanstack/ai";
import { decartVideo } from "@decartai/tanstack-ai-adapter";

const status = await getVideoJobStatus({
  adapter: decartVideo("lucy-pro-t2v"),
  jobId,
});

console.log("Status:", status.status); // "pending" | "processing" | "completed" | "failed"

if (status.status === "completed" && status.url) {
  console.log("Video URL:", status.url);
}

包含轮询的完整示例

typescript

import { generateVideo, getVideoJobStatus } from "@tanstack/ai";
import { decartVideo } from "@decartai/tanstack-ai-adapter";

async function createVideo(prompt: string) {
  const adapter = decartVideo("lucy-pro-t2v");

  // Create the job
  const { jobId } = await generateVideo({ adapter, prompt });
  console.log("Job created:", jobId);

  // Poll for completion
  let status = "pending";
  while (status !== "completed" && status !== "failed") {
    await new Promise((resolve) => setTimeout(resolve, 5000));

    const result = await getVideoJobStatus({ adapter, jobId });
    status = result.status;
    console.log(`Status: ${status}`);

    if (result.status === "failed") {
      throw new Error("Video generation failed");
    }

    if (result.status === "completed" && result.url) {
      return result.url;
    }
  }
}

const videoUrl = await createVideo("A drone shot over a tropical beach");

视频模型选项

typescript

const { jobId } = await generateVideo({
  adapter: decartVideo("lucy-pro-t2v"),
  prompt: "A timelapse of a blooming flower",
  modelOptions: {
    resolution: "720p",
    orientation: "landscape",
    seed: 42,
  },
});