---
name: dashscope-image-gen
description: >-
Use this skill when the user wants to generate images using Alibaba Cloud
DashScope's Wan (通义万相) series models. Supports text-to-image with multiple
model tiers (wan2.7-image-pro, wan2.7-image). Uses OpenAI-compatible
images/generations API for synchronous image generation.
Use when 用户提到 生成图片、画图、文生图、创建图片、AI 绘画、
生成插图、画一张、帮我画、设计图片、通义万相、万相、阿里云画图、dashscope 画图。
license: Complete terms in LICENSE.txt
version: 1.3.0
type: procedural
risk_level: low
status: enabled
disable-model-invocation: false
provider: auto
tags:
- media
- image
- generation
- dashscope
- alibaba
requires:
tools:
- Bash
metadata:
author: desirecore
updated_at: '2026-06-10'
i18n:
default_locale: en-US
source_locale: zh-CN
locales:
- zh-CN
- en-US
zh-CN:
name: 阿里云 文生图
short_desc: 基于阿里云通义万相的文本生成图片技能
description: >-
当用户希望使用阿里云 DashScope 的通义万相系列模型生成图片时使用此技能。支持多种模型层级（wan2.7-image-pro / wan2.7-image）的文生图，通过 OpenAI 兼容的 images/generations API 同步生成图片。用户提到 生成图片、画图、文生图、创建图片、AI 绘画、生成插图、画一张、帮我画、设计图片、通义万相、万相、阿里云画图、dashscope 画图。
body: ./SKILL.zh-CN.md
source_hash: sha256:a2c4e8f01b3d5e7f
translated_by: human
en-US:
name: DashScope Image Generation
short_desc: Text-to-image generation using Alibaba Cloud Wan (通义万相) models
description: "Use this skill when the user wants to generate images using Alibaba Cloud DashScope's Wan (通义万相) series models. Supports text-to-image with multiple model tiers (wan2.7-image-pro, wan2.7-image) via the OpenAI-compatible images/generations API. Trigger keywords: generate image, draw, text-to-image, create image, AI painting, illustration, design picture, Wan, Tongyi Wanxiang, DashScope."
body: ./SKILL.md
source_hash: sha256:a2c4e8f01b3d5e7f
translated_by: human
market:
icon: >-
short_desc: 基于阿里云通义万相的文本生成图片技能
category: media
maintainer:
name: DesireCore Official
verified: true
channel: latest
---
# dashscope-image-gen Skill
## Mandatory Rules (violations cause failure)
1. **STRICTLY follow the execution steps below** — do NOT improvise, explore alternative endpoints, or try models not listed in this document
2. **Must access agent-service over HTTPS** — the API address is already provided in the system prompt under "本机 API" section (e.g. `https://127.0.0.1:PORT`); use it directly with `-k` to skip certificate verification
3. **Must upload to media-store via `/api/media/upload`** — `/tmp` is only a transient download/decode location, never use a local path as the final output
4. **Must use the `dc-media://` protocol to display images** — the only form the frontend can render correctly
5. **Use Bash curl throughout** — do not use the HttpRequest tool or Python
6. **Use `/images/generations` endpoint** — synchronous call; the response contains b64_json image data
7. **Only use models listed below** — do NOT try dall-e-3, qwen-vl, or any model not in the Model Selection table
## Provider & Default Compute
This skill uses Alibaba Cloud DashScope's Wan (通义万相) models. You do NOT need to specify a provider — just pass `"serviceType": "image_gen"` and the system will automatically route to the correct provider:
- **DesireCore Cloud** (default, always available): The built-in compute provider already supports `image_gen` with Wan models. Users can generate images immediately without any configuration.
- **DashScope** (user-configured): If the user has configured their own DashScope API key, the system may route to it.
**Never** try to query provider lists, read compute.json, or explore available models through API calls. The models listed below are guaranteed to work.
## Model Selection
| Model | Characteristics | When to use |
|------|------|---------|
| wan2.7-image-pro | Flagship, 4K resolution, thinking_mode | User asks for top quality, 4K, or rich detail |
| wan2.7-image | Standard high quality, thinking_mode | **Default**, for unspecified requests |
**Default rule**: if the user does not specify a model, use `wan2.7-image`.
## Full Execution Flow (strictly follow these steps)
### How to get the API address
The system prompt already contains the agent-service API address under "本机 API" (e.g. `Agent Service: https://127.0.0.1:61000`). Extract the URL from there and use it directly.
If for any reason you cannot find it in the system prompt, use this fallback:
```bash
PORT=$(cat "${DESIRECORE_HOME:-$HOME/.desirecore}/agent-service.port")
# Then use https://127.0.0.1:${PORT}
```
### Step 1: Generate the image (single curl command)
Call `/images/generations` through media-proxy. **You MUST use this exact request structure** — do not add `messages`, `response_format`, or any other parameters not shown here:
```bash
# Save response to a temp file to avoid base64 flooding the terminal
curl -sk -X POST "https://127.0.0.1:${PORT}/api/media-proxy" \
-H "Content-Type: application/json" \
-d '{
"serviceType": "image_gen",
"endpoint": "/images/generations",
"body": {
"model": "wan2.7-image",
"prompt": "Replace this with the image description (English usually gives better results)",
"size": "1024x1024",
"n": 1
},
"responseType": "json"
}' -o /tmp/dashscope-response.json
# Check success and extract b64_json directly to image file (NEVER cat the response to stdout)
python3 -c "
import json, base64, sys
with open('/tmp/dashscope-response.json') as f:
resp = json.load(f)
if not resp.get('success'):
print('ERROR:', json.dumps(resp, ensure_ascii=False)[:500])
sys.exit(1)
b64 = resp['data']['data'][0]['b64_json']
with open('/tmp/dashscope-gen.png', 'wb') as f:
f.write(base64.b64decode(b64))
print('OK: saved to /tmp/dashscope-gen.png')
"
```
**CRITICAL**: The response contains a large base64 image (~2MB). NEVER print the raw response or b64_json to the terminal. Always save to file with `-o` and extract with the python3 script above.
**Response format** (saved in `/tmp/dashscope-response.json`):
```json
{
"success": true,
"data": {
"created": 1781060911,
"data": [{"b64_json": ""}],
"size": "1024x1024"
}
}
```
### Step 2: Upload to media-store
```bash
curl -sk -X POST "https://127.0.0.1:${PORT}/api/media/upload" \
-F "file=@/tmp/dashscope-gen.png;type=image/png"
```
Pick the `mediaId` field from the JSON response (format `xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx.png`).
### Step 3: Render the image via the dc-media protocol
In your reply text, write Markdown image syntax directly:
```
```
For example: ``
The frontend will translate `dc-media://` into a reachable image URL and render it.
## Parameter Mapping
### Size selection
Pass `size` in the `body` object:
```json
{
"model": "wan2.7-image",
"prompt": "your image description",
"size": "1024x1024",
"n": 1
}
```
| User intent | size value |
|---------|-----------|
| Square / avatar / default | "1024x1024" |
| Landscape / scenery / wallpaper | "1792x1024" |
| Portrait / mobile / poster | "1024x1792" |
### Optional parameters (top-level body fields)
| Parameter | Description |
|------|------|
| `n` | Number of images, 1-4, default 1 |
| `size` | Image size, e.g. "1024x1024" |
## Multiple Image Generation
When `n > 1`, download and upload each image, then render them one by one:
```
```
## Error Handling
| Error | Meaning | Action |
|-------|---------|--------|
| `"No matching provider"` | No enabled provider supports `image_gen` | Tell user to enable a provider with image_gen support in settings |
| `"API Key not configured"` | API Key missing | Tell user to configure API key |
| `statusCode: 401` | API Key invalid or expired | Tell user to check API key |
| `statusCode: 429` | Rate limited | Wait and retry once |
| `statusCode: 400` | Bad parameters | Check model name and size are from the tables above |
| `statusCode: 403 AccessDenied.Unpurchased` | Model not activated | Tell user to enable the model in Alibaba Cloud console |
**On any error**: Do NOT try alternative models, alternative endpoints, or read config files. Report the error to the user clearly.
## Notes
- Image generation calls are synchronous and typically return in 10-60 seconds (wan2.7-image-pro can take longer)
- Image URLs expire; download promptly
- English prompts usually produce the best results; Chinese is also supported
- When the user does not specify a model or size, default to `wan2.7-image` + `1024x1024`