Aliyun Wan Image

• Set DASHSCOPE_API_KEY in your environment, or add dashscope_api_key to ~/.alibabacloud/credentials.

Critical model names

• wan2.7-image-pro — professional version, supports 4K output
• wan2.7-image — faster generation, up to 2K

Capabilities

API endpoint

Sync (recommended):

POST https://dashscope.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation

Async (for long tasks):

POST https://dashscope.aliyuncs.com/api/v1/services/aigc/image-generation/generation
Header: X-DashScope-Async: enable

Normalized interface (image.generate)

Request

• prompt (string, required) — up to 5000 characters
• size (string, optional) — 1K, 2K (default), 4K (pro only), or WxH pixel values
• n (int, optional) — number of images, 1-4 (default 4), or 1-12 with enable_sequential
• seed (int, optional) — range [0, 2147483647]
• reference_image (string/array, optional) — URL or base64, up to 9 images
• enable_sequential (bool, optional) — group image generation mode
• thinking_mode (bool, optional, default true) — enhanced reasoning (text-to-image only)
• bbox_list (array, optional) — bounding boxes for interactive editing
• color_palette (array, optional) — custom color theme (3-10 colors with hex+ratio)
• watermark (bool, optional, default false)

Response

• image_url (string) — PNG, valid for 24 hours
• image_count (int)
• size (string) — actual output resolution
• seed (int)

Quick start (Python + DashScope SDK)

import os
from dashscope.aigc.image_generation import ImageGeneration

def generate_image(req: dict) -> dict:
    messages = [
        {
            "role": "user",
            "content": [{"text": req["prompt"]}],
        }
    ]

    # Add reference images if provided
    ref_images = req.get("reference_images") or []
    if req.get("reference_image"):
        ref_images = [req["reference_image"]] + ref_images
    for img in ref_images:
        messages[0]["content"].append({"image": img})

    params = {
        "model": req.get("model", "wan2.7-image"),
        "messages": messages,
        "size": req.get("size", "2K"),
        "n": req.get("n", 1),
        "api_key": os.getenv("DASHSCOPE_API_KEY"),
        "seed": req.get("seed"),
        "watermark": req.get("watermark", False),
    }

    if req.get("enable_sequential"):
        params["enable_sequential"] = True
    if req.get("thinking_mode") is not None:
        params["thinking_mode"] = req["thinking_mode"]
    if req.get("bbox_list"):
        params["bbox_list"] = req["bbox_list"]
    if req.get("color_palette"):
        params["color_palette"] = req["color_palette"]

    response = ImageGeneration.call(**params)

    content = response.output["choices"][0]["message"]["content"]
    images = [item["image"] for item in content if isinstance(item, dict) and item.get("image")]

    return {
        "image_urls": images,
        "image_count": response.usage.get("image_count"),
        "size": response.usage.get("size"),
    }

Size reference

Error handling

Output location

• Default output: output/aliyun-wan-image/images/
• Override base dir with OUTPUT_DIR.

Anti-patterns

• Do not invent model names; use wan2.7-image or wan2.7-image-pro only.
• Do not use 4K size with wan2.7-image (only pro supports 4K).
• Do not use enable_sequential with bbox_list — they are separate modes.
• Image URLs expire after 24 hours; download and persist immediately.

Workflow

1. Confirm user intent: text-to-image, image editing, group generation, or interactive editing.
2. Select appropriate model (pro for 4K or higher quality, standard for speed).
3. Execute with explicit parameters and bounded scope.
4. Download and save generated images before URL expiration.

References

• See references/api_reference.md for full HTTP API details.
• See references/sources.md for source links.