integrate-image

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Original

English

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Translation

Chinese

Integrate Image Generation

集成图像生成

PREREQUISITE: Run
+check-compatibility
first. Run
+fetch-api-reference
to load the latest API reference before integrating. Requires
+setup-api-key
for API credentials. Requires
+integrate-uploads
when the user has local reference images.

Help users add Runway image generation to their server-side code.

前置条件： 请先运行
+check-compatibility
。集成前运行
+fetch-api-reference
加载最新的API参考文档。需要运行
+setup-api-key
配置API凭证。如果用户有本地参考图，需要先执行
+integrate-uploads
。

帮助用户将Runway图像生成功能接入到服务端代码中。

Available Models

可用模型

Model	Best For	Cost	Speed
`gen4_image`	Highest quality	5 credits (720p), 8 credits (1080p)	Standard
`gen4_image_turbo`	Fast generation	2 credits	Fast
`gemini_2.5_flash`	Google Gemini model	5 credits	Standard

Model selection guidance:

Default recommendation: gen4_image
— best quality
Budget/speed: gen4_image_turbo
— cheapest and fastest

模型	适用场景	费用	速度
`gen4_image`	最高画质	5积分（720p），8积分（1080p）	标准
`gen4_image_turbo`	快速生成	2积分	快
`gemini_2.5_flash`	谷歌Gemini模型	5积分	标准

模型选择指南：

默认推荐：gen4_image
— 画质最佳
预算/速度优先：gen4_image_turbo
— 成本最低、速度最快

Endpoint:

POST /v1/text_to_image

接口：

POST /v1/text_to_image

Basic Text-to-Image

基础文生图

javascript

// Node.js SDK
import RunwayML from '@runwayml/sdk';

const client = new RunwayML();

const task = await client.textToImage.create({
  model: 'gen4_image',
  promptText: 'A serene Japanese garden with cherry blossoms and a koi pond',
  ratio: '1280:720'
}).waitForTaskOutput();

const imageUrl = task.output[0];

python

undefined

javascript

// Node.js SDK
import RunwayML from '@runwayml/sdk';

const client = new RunwayML();

const task = await client.textToImage.create({
  model: 'gen4_image',
  promptText: 'A serene Japanese garden with cherry blossoms and a koi pond',
  ratio: '1280:720'
}).waitForTaskOutput();

const imageUrl = task.output[0];

python

undefined

Python SDK

from runwayml import RunwayML

client = RunwayML()

task = client.text_to_image.create( model='gen4_image', prompt_text='A serene Japanese garden with cherry blossoms and a koi pond', ratio='1280:720' ).wait_for_task_output()

image_url = task.output[0]

undefined

from runwayml import RunwayML

client = RunwayML()

task = client.text_to_image.create( model='gen4_image', prompt_text='A serene Japanese garden with cherry blossoms and a koi pond', ratio='1280:720' ).wait_for_task_output()

image_url = task.output[0]

undefined

With Reference Images

带参考图生成

Reference images let you guide the generation with visual references. Use

@Tag

syntax in the prompt to reference specific images.

javascript

const task = await client.textToImage.create({
  model: 'gen4_image',
  promptText: '@EiffelTower painted in the style of @StarryNight',
  referenceImages: [
    { uri: 'https://example.com/eiffel-tower.jpg', tag: 'EiffelTower' },
    { uri: 'https://example.com/starry-night.jpg', tag: 'StarryNight' }
  ],
  ratio: '1280:720'
}).waitForTaskOutput();

python

task = client.text_to_image.create(
    model='gen4_image',
    prompt_text='@EiffelTower painted in the style of @StarryNight',
    reference_images=[
        {"uri": "https://example.com/eiffel-tower.jpg", "tag": "EiffelTower"},
        {"uri": "https://example.com/starry-night.jpg", "tag": "StarryNight"}
    ],
    ratio='1280:720'
).wait_for_task_output()

If the user has local reference images, upload them first with

+integrate-uploads

javascript

import fs from 'fs';

const refUpload = await client.uploads.createEphemeral(
  fs.createReadStream('/path/to/reference.jpg')
);

const task = await client.textToImage.create({
  model: 'gen4_image',
  promptText: 'A portrait in the style of @Reference',
  referenceImages: [
    { uri: refUpload.runwayUri, tag: 'Reference' }
  ],
  ratio: '1280:720'
}).waitForTaskOutput();

参考图可以通过视觉参考引导生成效果。在提示词中使用

@标签

语法来引用指定图片。

javascript

const task = await client.textToImage.create({
  model: 'gen4_image',
  promptText: '@EiffelTower painted in the style of @StarryNight',
  referenceImages: [
    { uri: 'https://example.com/eiffel-tower.jpg', tag: 'EiffelTower' },
    { uri: 'https://example.com/starry-night.jpg', tag: 'StarryNight' }
  ],
  ratio: '1280:720'
}).waitForTaskOutput();

python

task = client.text_to_image.create(
    model='gen4_image',
    prompt_text='@EiffelTower painted in the style of @StarryNight',
    reference_images=[
        {"uri": "https://example.com/eiffel-tower.jpg", "tag": "EiffelTower"},
        {"uri": "https://example.com/starry-night.jpg", "tag": "StarryNight"}
    ],
    ratio='1280:720'
).wait_for_task_output()

如果用户有本地参考图，请先使用

+integrate-uploads

上传：

javascript

import fs from 'fs';

const refUpload = await client.uploads.createEphemeral(
  fs.createReadStream('/path/to/reference.jpg')
);

const task = await client.textToImage.create({
  model: 'gen4_image',
  promptText: 'A portrait in the style of @Reference',
  referenceImages: [
    { uri: refUpload.runwayUri, tag: 'Reference' }
  ],
  ratio: '1280:720'
}).waitForTaskOutput();

Common Parameters

常用参数

Parameter	Type	Description
`model`	string	Model ID (required)
`promptText`	string	Text description of the image (required)
`ratio`	string	Aspect ratio, e.g. `'1280:720'` , `'720:1280'` , `'1080:1080'`
`referenceImages`	array	Optional. Array of `{ uri, tag }` objects for visual guidance

参数	类型	说明
`model`	string	模型ID（必填）
`promptText`	string	图片的文本描述（必填）
`ratio`	string	宽高比，例如 `'1280:720'` 、 `'720:1280'` 、 `'1080:1080'`
`referenceImages`	array	可选，用于视觉引导的 `{ uri, tag }` 对象数组

Integration Pattern

集成示例

Example: Express.js API Route

示例：Express.js API路由

javascript

import RunwayML from '@runwayml/sdk';
import express from 'express';

const client = new RunwayML();
const app = express();
app.use(express.json());

app.post('/api/generate-image', async (req, res) => {
  try {
    const { prompt, model = 'gen4_image', ratio = '1280:720', referenceImages } = req.body;

    const task = await client.textToImage.create({
      model,
      promptText: prompt,
      ratio,
      ...(referenceImages && { referenceImages })
    }).waitForTaskOutput();

    res.json({ imageUrl: task.output[0] });
  } catch (error) {
    console.error('Image generation failed:', error);
    res.status(500).json({ error: error.message });
  }
});

javascript

import RunwayML from '@runwayml/sdk';
import express from 'express';

const client = new RunwayML();
const app = express();
app.use(express.json());

app.post('/api/generate-image', async (req, res) => {
  try {
    const { prompt, model = 'gen4_image', ratio = '1280:720', referenceImages } = req.body;

    const task = await client.textToImage.create({
      model,
      promptText: prompt,
      ratio,
      ...(referenceImages && { referenceImages })
    }).waitForTaskOutput();

    res.json({ imageUrl: task.output[0] });
  } catch (error) {
    console.error('Image generation failed:', error);
    res.status(500).json({ error: error.message });
  }
});

Example: Next.js API Route

示例：Next.js API路由

typescript

// app/api/generate-image/route.ts
import RunwayML from '@runwayml/sdk';
import { NextRequest, NextResponse } from 'next/server';

const client = new RunwayML();

export async function POST(request: NextRequest) {
  const { prompt, referenceImages } = await request.json();

  try {
    const task = await client.textToImage.create({
      model: 'gen4_image',
      promptText: prompt,
      ratio: '1280:720',
      ...(referenceImages && { referenceImages })
    }).waitForTaskOutput();

    return NextResponse.json({ imageUrl: task.output[0] });
  } catch (error) {
    return NextResponse.json(
      { error: error instanceof Error ? error.message : 'Generation failed' },
      { status: 500 }
    );
  }
}

typescript

// app/api/generate-image/route.ts
import RunwayML from '@runwayml/sdk';
import { NextRequest, NextResponse } from 'next/server';

const client = new RunwayML();

export async function POST(request: NextRequest) {
  const { prompt, referenceImages } = await request.json();

  try {
    const task = await client.textToImage.create({
      model: 'gen4_image',
      promptText: prompt,
      ratio: '1280:720',
      ...(referenceImages && { referenceImages })
    }).waitForTaskOutput();

    return NextResponse.json({ imageUrl: task.output[0] });
  } catch (error) {
    return NextResponse.json(
      { error: error instanceof Error ? error.message : 'Generation failed' },
      { status: 500 }
    );
  }
}

Example: FastAPI Route

示例：FastAPI路由

python

from fastapi import FastAPI, HTTPException
from pydantic import BaseModel
from runwayml import RunwayML

app = FastAPI()
client = RunwayML()

class ImageRequest(BaseModel):
    prompt: str
    model: str = "gen4_image"
    ratio: str = "1280:720"
    reference_images: list[dict] | None = None

@app.post("/api/generate-image")
async def generate_image(req: ImageRequest):
    try:
        params = {
            "model": req.model,
            "prompt_text": req.prompt,
            "ratio": req.ratio,
        }
        if req.reference_images:
            params["reference_images"] = req.reference_images

        task = client.text_to_image.create(**params).wait_for_task_output()
        return {"image_url": task.output[0]}
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))

python

from fastapi import FastAPI, HTTPException
from pydantic import BaseModel
from runwayml import RunwayML

app = FastAPI()
client = RunwayML()

class ImageRequest(BaseModel):
    prompt: str
    model: str = "gen4_image"
    ratio: str = "1280:720"
    reference_images: list[dict] | None = None

@app.post("/api/generate-image")
async def generate_image(req: ImageRequest):
    try:
        params = {
            "model": req.model,
            "prompt_text": req.prompt,
            "ratio": req.ratio,
        }
        if req.reference_images:
            params["reference_images"] = req.reference_images

        task = client.text_to_image.create(**params).wait_for_task_output()
        return {"image_url": task.output[0]}
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))

Tips

注意事项

Output URLs expire in 24-48 hours. Download images to your own storage immediately.
Reference images use
@Tag
syntax in the prompt — the tag must match the
```
tag
```
field in the
```
referenceImages
```
array.
For local files, always upload via
```
+integrate-uploads
```
first, then use the
```
runway://
```
URI.
gen4_image_turbo
is the cheapest option at 2 credits per image — good for prototyping.

输出URL有效期为24-48小时。 请立即将图片下载到您自己的存储中。
参考图在提示词中使用
@标签
语法 — 标签必须与
```
referenceImages
```
数组中的
```
tag
```
字段匹配。
对于本地文件，请务必先通过
```
+integrate-uploads
```
上传，再使用返回的
```
runway://
```
URI。
gen4_image_turbo
是成本最低的选项，每张图仅需2积分 — 适合原型开发阶段使用。

integrate-image

Original

Translation

Integrate Image Generation

集成图像生成

Available Models

可用模型

Endpoint:
`POST /v1/text_to_image`

接口：
`POST /v1/text_to_image`

Basic Text-to-Image

基础文生图

Python SDK

Python SDK

With Reference Images

带参考图生成

Common Parameters

常用参数

Integration Pattern

集成示例

Example: Express.js API Route

示例：Express.js API路由

Example: Next.js API Route

示例：Next.js API路由

Example: FastAPI Route

示例：FastAPI路由

Tips

注意事项

integrate-image

Original

Translation

Integrate Image Generation

集成图像生成

Available Models

可用模型

Endpoint: POST /v1/text_to_image

接口：POST /v1/text_to_image

Basic Text-to-Image

基础文生图

Python SDK

Python SDK

With Reference Images

带参考图生成

Common Parameters

常用参数

Integration Pattern

集成示例

Example: Express.js API Route

示例：Express.js API路由

Example: Next.js API Route

示例：Next.js API路由

Example: FastAPI Route

示例：FastAPI路由

Tips

注意事项

Endpoint:
`POST /v1/text_to_image`

接口：
`POST /v1/text_to_image`