alibaba/wan-2.7-pro/text-to-image

文生图

PRO

Wan 2.7 Pro Text-to-Image API by Alibaba

alibaba/wan-2.7-pro/text-to-image

Text-to-image

Generates images from text prompts with Wan 2.7 image pro, supporting higher fidelity outputs and 4K-ready workflows.

输入

提示词 *

尺寸

数量

调色板

最少: 3 / 最多: 10

思考模式

随机种子

输出

空闲

生成的图片将在这里显示

配置参数后点击运行开始生成

每次运行将花费 $0.075。$10 可运行约 133 次。

你可以继续：

图生视频图生图

参数

代码示例
import requests
import time

# Step 1: Start image generation
generate_url = "https://api.atlascloud.ai/api/v1/model/generateImage"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "alibaba/wan-2.7-pro/text-to-image",  # Required. Model name. options: alibaba/wan-2.7-pro/text-to-image
    "prompt": "A beautiful landscape with mountains and lake",  # Required. Text prompt used to generate the image
    "size": "2K",  # Output image resolution. options: 1K | 2K | 4K
    "n": 1,  # Number of images to generate. (min: 1, max: 4)
    "color_palette": [
        {
            "hex": "example_hex",
            "ratio": "example_ratio"
        }
    ],
    "thinking_mode": True,  # Whether to enable thinking mode for higher-quality image generation
    "seed": -1,  # Random seed for image generation. (min: -1, max: 2147483647)
    "enable_sync_mode": False,  # Whether to wait for generation to finish and return the final result directly in the response
    "enable_base64_output": False,  # Whether to return the generated image as a Base64 string instead of a URL
}

generate_response = requests.post(generate_url, headers=headers, json=data)
generate_result = generate_response.json()
prediction_id = generate_result["data"]["id"]

# Step 2: Poll for result
poll_url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"

def check_status():
    while True:
        response = requests.get(poll_url, headers={"Authorization": "Bearer $ATLASCLOUD_API_KEY"})
        result = response.json()

        if result["data"]["status"] == "completed":
            print("Generated image:", result["data"]["outputs"][0])
            return result["data"]["outputs"][0]
        elif result["data"]["status"] == "failed":
            raise Exception(result["data"]["error"] or "Generation failed")
        else:
            # Still processing, wait 2 seconds
            time.sleep(2)

image_url = check_status()

安装

安装所需的依赖包。

pip install requests

认证

所有 API 请求需要通过 API Key 进行认证。您可以在 Atlas Cloud 控制台获取 API Key。

export ATLASCLOUD_API_KEY="your-api-key-here"

HTTP 请求头

import os

API_KEY = os.environ.get("ATLASCLOUD_API_KEY")
headers = {
    "Content-Type": "application/json",
    "Authorization": f"Bearer {API_KEY}"
}

保护好您的 API Key

切勿在客户端代码或公开仓库中暴露您的 API Key。请使用环境变量或后端代理。

提交请求

import requests

url = "https://api.atlascloud.ai/api/v1/model/generateImage"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "your-model",
    "prompt": "A beautiful landscape"
}

response = requests.post(url, headers=headers, json=data)
print(response.json())

提交请求

提交一个异步生成请求。API 返回一个 prediction ID，您可以用它来检查状态和获取结果。

POST/api/v1/model/generateImage

请求体

import requests

url = "https://api.atlascloud.ai/api/v1/model/generateImage"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}

data = {
    "model": "alibaba/wan-2.7-pro/text-to-image",
    "prompt": "A beautiful landscape with mountains and lake"
}

response = requests.post(url, headers=headers, json=data)
result = response.json()

print(f"Prediction ID: {result['data']['id']}")
print(f"Status: {result['data']['status']}")

响应

{
  "code": 200,
  "data": {
    "id": "pred_abc123",
    "status": "processing",
    "model": "model-name",
    "created_at": "2025-01-01T00:00:00Z"
  }
}

检查状态

轮询 prediction 端点以检查请求的当前状态。

GET/api/v1/model/prediction/{prediction_id}

轮询示例

import requests
import time

prediction_id = "pred_abc123"
url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }

while True:
    response = requests.get(url, headers=headers)
    result = response.json()
    status = result["data"]["status"]
    print(f"Status: {status}")

    if status in ["completed", "succeeded"]:
        output_url = result["data"]["outputs"][0]
        print(f"Output URL: {output_url}")
        break
    elif status == "failed":
        print(f"Error: {result['data'].get('error', 'Unknown')}")
        break

    time.sleep(3)

状态值

processing请求仍在处理中。

completed生成完成，输出可用。

succeeded生成成功，输出可用。

failed生成失败，请检查 error 字段。

完成响应

{
  "data": {
    "id": "pred_abc123",
    "status": "completed",
    "outputs": [
      "https://storage.atlascloud.ai/outputs/result.png"
    ],
    "metrics": {
      "predict_time": 8.3
    },
    "created_at": "2025-01-01T00:00:00Z",
    "completed_at": "2025-01-01T00:00:10Z"
  }
}

上传文件

将文件上传到 Atlas Cloud 存储，获取可在 API 请求中使用的 URL。使用 multipart/form-data 上传。

POST/api/v1/model/uploadMedia

上传示例

import requests

url = "https://api.atlascloud.ai/api/v1/model/uploadMedia"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }

with open("image.png", "rb") as f:
    files = {"file": ("image.png", f, "image/png")}
    response = requests.post(url, headers=headers, files=files)

result = response.json()
download_url = result["data"]["download_url"]
print(f"File URL: {download_url}")

响应

{
  "data": {
    "download_url": "https://storage.atlascloud.ai/uploads/abc123/image.png",
    "file_name": "image.png",
    "content_type": "image/png",
    "size": 1024000
  }
}

Input Schema

以下参数在请求体中被接受。

总计: 9必填: 2可选: 7

modelstringrequired

Model name.

Default: "alibaba/wan-2.7-pro/text-to-image"

alibaba/wan-2.7-pro/text-to-image

promptstringrequired

Text prompt used to generate the image. Maximum length is 5000 characters.

sizestring

Output image resolution.

Default: "2K"

1K2K4K

ninteger

Number of images to generate.

Default: 1Min: 1Max: 4

color_palettearray[object]

Min items: 3Max items: 10

hexstringrequired

ratiostringrequired

thinking_modeboolean

Whether to enable thinking mode for higher-quality image generation.

Default: true

seedinteger

Random seed for image generation. Range: 0 to 2147483647. Use -1 for a random seed.

Default: -1Min: -1Max: 2147483647

enable_sync_modeboolean

Whether to wait for generation to finish and return the final result directly in the response.

Default: false

enable_base64_outputboolean

Whether to return the generated image as a Base64 string instead of a URL.

Default: false

请求体示例

{
  "model": "alibaba/wan-2.7-pro/text-to-image",
  "prompt": "A beautiful landscape",
  "size": "2K",
  "n": 1,
  "thinking_mode": true,
  "seed": -1,
  "enable_sync_mode": false,
  "enable_base64_output": false
}

Output Schema

API 返回包含生成输出 URL 的 prediction 响应。

codeinteger

messagestring

dataunknown

响应示例

{
  "id": "pred_abc123",
  "status": "completed",
  "model": "model-name",
  "outputs": [
    "https://storage.atlascloud.ai/outputs/result.png"
  ],
  "metrics": {
    "predict_time": 8.3
  },
  "created_at": "2025-01-01T00:00:00Z",
  "completed_at": "2025-01-01T00:00:10Z"
}

Atlas Cloud Skills

Atlas Cloud Skills 将 400+ AI 模型直接集成到您的 AI 编程助手中。一条命令安装，即可用自然语言生成图像、视频和与 LLM 对话。

支持的客户端

Claude Code

OpenAI Codex

Gemini CLI

Cursor

Windsurf

VS Code

Trae

GitHub Copilot

Cline

Roo Code

Amp

Goose

Replit

40+ 支持的客户端

安装

npx skills add AtlasCloudAI/atlas-cloud-skills

设置 API Key

从 Atlas Cloud 控制台获取 API Key，并将其设置为环境变量。

export ATLASCLOUD_API_KEY="your-api-key-here"

功能

安装后，您可以在 AI 助手中使用自然语言访问所有 Atlas Cloud 模型。

图像生成使用 Nano Banana 2、Z-Image 等模型生成图像。

视频创作使用 Kling、Vidu、Veo 等模型从文本或图像创建视频。

LLM 对话与 Qwen、DeepSeek 等大语言模型对话。

媒体上传上传本地文件用于图像编辑和图生视频工作流。

MCP Server

Atlas Cloud MCP Server 通过 Model Context Protocol 将您的 IDE 与 400+ AI 模型连接。支持任何兼容 MCP 的客户端。

支持的客户端

Cursor

VS Code

Windsurf

Claude Code

OpenAI Codex

Gemini CLI

Cline

Roo Code

100+ 支持的客户端

安装

npx -y atlascloud-mcp

配置

将以下配置添加到您的 IDE 的 MCP 设置文件中。

{
  "mcpServers": {
    "atlascloud": {
      "command": "npx",
      "args": [
        "-y",
        "atlascloud-mcp"
      ],
      "env": {
        "ATLASCLOUD_API_KEY": "your-api-key-here"
      }
    }
  }
}

可用工具

atlas_generate_image从文本提示生成图像。

atlas_generate_video从文本或图像创建视频。

atlas_chat与大语言模型对话。

atlas_list_models浏览 400+ 可用 AI 模型。

atlas_quick_generate一步式内容创建，自动选择最佳模型。

atlas_upload_media上传本地文件用于 API 工作流。

了解更多

github.com/AtlasCloudAI/mcp-server

API Schema

{
  "info": {
    "title": "AtlasCloud API",
    "version": "1.0.0",
    "description": "The AtlasCloud API."
  },
  "openapi": "3.0.0",
  "paths": {
    "/api/v1/model/generateImage": {
      "post": {
        "requestBody": {
          "content": {
            "application/json": {
              "schema": {
                "$ref": "#/components/schemas/Input"
              }
            }
          },
          "required": true
        },
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/PredictionResponse"
                }
              }
            },
            "description": "The request status."
          }
        }
      },
      "x-api-name": "model_run"
    },
    "/api/v1/model/prediction/{request_id}": {
      "get": {
        "parameters": [
          {
            "in": "path",
            "name": "request_id",
            "required": true,
            "schema": {
              "description": "Request ID",
              "type": "string"
            }
          }
        ],
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/PredictionResponse"
                }
              }
            },
            "description": "Result of the request."
          }
        }
      },
      "x-api-name": "model_result"
    }
  },
  "components": {
    "schemas": {
      "Input": {
        "properties": {
          "model": {
            "type": "string",
            "description": "Model name.",
            "default": "alibaba/wan-2.7-pro/text-to-image",
            "enum": [
              "alibaba/wan-2.7-pro/text-to-image"
            ]
          },
          "prompt": {
            "description": "Text prompt used to generate the image. Maximum length is 5000 characters.",
            "type": "string"
          },
          "size": {
            "default": "2K",
            "description": "Output image resolution.",
            "enum": [
              "1K",
              "2K",
              "4K"
            ],
            "type": "string"
          },
          "n": {
            "default": 1,
            "minimum": 1,
            "maximum": 4,
            "description": "Number of images to generate.",
            "type": "integer"
          },
          "color_palette": {
            "type": "array",
            "minItems": 3,
            "maxItems": 10,
            "items": {
              "type": "object",
              "properties": {
                "hex": {
                  "type": "string",
                  "pattern": "^#[0-9A-Fa-f]{6}$"
                },
                "ratio": {
                  "type": "string",
                  "pattern": "^\\d+\\.\\d{2}%$"
                }
              },
              "required": [
                "hex",
                "ratio"
              ]
            }
          },
          "thinking_mode": {
            "default": true,
            "description": "Whether to enable thinking mode for higher-quality image generation.",
            "type": "boolean"
          },
          "seed": {
            "default": -1,
            "minimum": -1,
            "maximum": 2147483647,
            "description": "Random seed for image generation. Range: 0 to 2147483647. Use -1 for a random seed.",
            "type": "integer"
          },
          "enable_sync_mode": {
            "default": false,
            "description": "Whether to wait for generation to finish and return the final result directly in the response.",
            "disabled": true,
            "type": "boolean"
          },
          "enable_base64_output": {
            "default": false,
            "description": "Whether to return the generated image as a Base64 string instead of a URL.",
            "disabled": true,
            "type": "boolean"
          }
        },
        "required": [
          "model",
          "prompt"
        ],
        "type": "object",
        "x-order-properties": [
          "model",
          "prompt",
          "size",
          "n",
          "color_palette",
          "thinking_mode",
          "seed",
          "enable_sync_mode",
          "enable_base64_output"
        ]
      },
      "PredictionResponse": {
        "type": "object",
        "properties": {
          "code": {
            "type": "integer"
          },
          "message": {
            "type": "string"
          },
          "data": {
            "$ref": "#/components/schemas/PredictionData"
          }
        }
      },
      "PredictionData": {
        "type": "object",
        "properties": {
          "id": {
            "type": "string",
            "description": "Unique ID of the generation task."
          },
          "model": {
            "type": "string",
            "description": "Model used for the generation."
          },
          "outputs": {
            "type": "array",
            "description": "Generated image results. Each item is an image URL, or a Base64 string when Base64 output is enabled.",
            "items": {
              "type": "string"
            }
          },
          "urls": {
            "type": "object",
            "properties": {
              "get": {
                "type": "string"
              }
            }
          },
          "has_nsfw_contents": {
            "type": "array",
            "items": {
              "type": "boolean"
            }
          },
          "status": {
            "type": "string",
            "description": "Current task status, such as created, processing, completed, unknown, or failed."
          },
          "created_at": {
            "type": "string",
            "format": "date-time"
          },
          "error": {
            "type": "string",
            "description": "Error message returned when the task fails."
          }
        }
      }
    }
  },
  "servers": [
    {
      "url": "https://api.atlascloud.ai"
    }
  ]
}

LLM 友好的提示词模板

# alibaba/wan-2.7-pro/text-to-image

> Generates images from text prompts with Wan 2.7 image pro, supporting higher fidelity outputs and 4K-ready workflows.


## Overview

- **Submit endpoint (POST)**: `https://api.atlascloud.ai/api/v1/model/generateImage` — start an async generation; returns a `prediction_id`
- **Poll endpoint (GET)**: `https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}` — poll this until the prediction finishes
- **Model ID**: `alibaba/wan-2.7-pro/text-to-image`


## API Information

This model can be used via our HTTP API or more conveniently via our client libraries.
See the input and output schema below, as well as the usage examples.


### Input Schema

The API accepts the following input parameters:

- **`model`** (`string`, _required_):
  Model name.
  - Default: `"alibaba/wan-2.7-pro/text-to-image"`
  - Options: "alibaba/wan-2.7-pro/text-to-image"

- **`prompt`** (`string`, _required_):
  Text prompt used to generate the image. Maximum length is 5000 characters.

- **`size`** (`string`, _optional_):
  Output image resolution.
  - Default: `"2K"`
  - Options: "1K", "2K", "4K"

- **`n`** (`integer`, _optional_):
  Number of images to generate.
  - Default: `1`
  - Min: 1
  - Max: 4

- **`color_palette`** (`array[object]`, _optional_):
  - Min items: 3
  - Max items: 10
  - Item properties:
    - **`hex`** (`string`, _required_):

    - **`ratio`** (`string`, _required_):


- **`thinking_mode`** (`boolean`, _optional_):
  Whether to enable thinking mode for higher-quality image generation.
  - Default: `true`

- **`seed`** (`integer`, _optional_):
  Random seed for image generation. Range: 0 to 2147483647. Use -1 for a random seed.
  - Default: `-1`
  - Min: -1
  - Max: 2147483647

- **`enable_sync_mode`** (`boolean`, _optional_):
  Whether to wait for generation to finish and return the final result directly in the response.
  - Default: `false`

- **`enable_base64_output`** (`boolean`, _optional_):
  Whether to return the generated image as a Base64 string instead of a URL.
  - Default: `false`



**Required Parameters Example**:

```json
{
  "model": "alibaba/wan-2.7-pro/text-to-image",
  "prompt": ""
}
```


**Full Example**:

```json
{
  "model": "alibaba/wan-2.7-pro/text-to-image",
  "prompt": "",
  "size": "2K",
  "n": 1,
  "color_palette": [
    {
      "hex": "",
      "ratio": ""
    }
  ],
  "thinking_mode": true,
  "seed": -1,
  "enable_sync_mode": false,
  "enable_base64_output": false
}
```


### Output Schema

The API returns the following output format:


- **`code`** (`integer`, _optional_):

- **`message`** (`string`, _optional_):

- **`data`** (`string`, _optional_):



**Example Response**:

```json
{
  "code": 0,
  "message": "",
  "data": null
}
```


## Usage Examples

### cURL

```bash
# Step 1: Start generation (async)
curl -X POST "https://api.atlascloud.ai/api/v1/model/generateImage" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "alibaba/wan-2.7-pro/text-to-image",
  "prompt": "",
  "size": "2K",
  "n": 1,
  "color_palette": [
    {
      "hex": "",
      "ratio": ""
    }
  ],
  "thinking_mode": true,
  "seed": -1,
  "enable_sync_mode": false,
  "enable_base64_output": false
}'

# Response will contain: {"code": 200, "data": {"id": "prediction_id", "status": "processing"}}

# Step 2: Poll for result (replace {prediction_id} with the id returned above)
curl -X GET "https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY"

# Keep polling until status is "completed", "succeeded" or "failed"
# When completed, outputs will contain the generated content URL(s)
```

## Additional Resources

### Documentation

- [Model Playground](https://www.atlascloud.ai/models/alibaba/wan-2.7-pro/text-to-image)

暂无可用示例

加载中...

Alibaba WAN 2.7 Pro Text-to-Image

Alibaba WAN 2.7 Pro Text-to-Image is the higher-fidelity Wan 2.7 text generation tier. Compared with the standard model, it is better suited to richer detail, cleaner composition, and larger-format output workflows.

What makes it stand out?

Higher fidelity output: Better suited for scenes with dense detail, stronger material rendering, and cleaner structure.
4K-ready text generation: Official Wan 2.7 image documentation allows 4K output for text-only generation on the Pro model.
Creative controls: Supports flexible sizing, grouped generation, and repeatable exploration with seed control.
Production-oriented route: Better fit for polished marketing, concept art, and premium visual generation workflows.

Designed For

Teams preparing campaign visuals and presentation-ready hero images.
Creators who need more detail and stronger composition than the standard model.
Product and brand teams targeting high-resolution image deliverables.
Creative teams and professionals who need a stronger premium-quality text-to-image model.

Recommended size guidance:

Use 4K only for pure text-to-image generation.
For ordinary workflows, 2K remains the safest default.

How to Use

Describe the desired scene with enough detail to benefit from the Pro tier.
Choose 2K for most work, or 4K when you need larger text-only output.
Use thinking mode when visual reasoning and composition quality matter most.
Review the outputs and select the version that best matches your creative goal.

Wan 2.7 Pro Text-to-Image API by Alibaba

输入

输出

参数

代码示例

安装

认证

HTTP 请求头

提交请求

提交请求

请求体

响应

检查状态

轮询示例

状态值

完成响应

上传文件

上传示例

响应

Input Schema

请求体示例

Output Schema

响应示例

Atlas Cloud Skills

支持的客户端

安装

设置 API Key

功能

MCP Server

支持的客户端

安装

配置

可用工具

API Schema

LLM 友好的提示词模板

Alibaba WAN 2.7 Pro Text-to-Image

What makes it stand out?

Designed For

How to Use

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Wan-2.5 Text-to-image

Qwen-Image Edit Plus

Qwen-Image Edit

一个 API，畅享全模态 AI。

Join our Discord community

输入

输出

参数

代码示例

安装

认证

HTTP 请求头

提交请求

提交请求

请求体

响应

检查状态

轮询示例

状态值

完成响应

上传文件

上传示例

响应

Input Schema

请求体示例

Output Schema

响应示例