--- name: dashscope-image-gen description: >- Use this skill when the user wants to generate images. Supports multiple models: gpt-image-2 (default, via DesireCore Cloud), wan2.7-image-pro and wan2.7-image (when user has DashScope configured). Uses OpenAI-compatible /images/generations API for synchronous image generation. Use when the user mentions: generate image, draw, text-to-image, create image, AI painting, illustration, design picture. license: Complete terms in LICENSE.txt version: 1.4.1 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: '2026-06-15' i18n: default_locale: en-US source_locale: zh-CN locales: - zh-CN - en-US zh-CN: name: AI 文生图 short_desc: AI 文本生成图片技能（支持 GPT Image / 通义万相） description: >- 当用户希望生成图片时使用此技能。支持多种模型：gpt-image-2（默认，通过 DesireCore Cloud）、wan2.7-image-pro / wan2.7-image（用户自行配置阿里云 DashScope 时可用）。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。 body: ./SKILL.zh-CN.md source_hash: sha256:b3d5f7a91c2e4068 translated_by: human en-US: name: AI Image Generation short_desc: AI text-to-image generation (GPT Image / Wan models) description: "Use this skill when the user wants to generate images. Supports multiple models: gpt-image-2 (default via DesireCore Cloud), wan2.7-image-pro / wan2.7-image (when user has DashScope configured). Uses the OpenAI-compatible /images/generations API. Trigger keywords: generate image, draw, text-to-image, create image, AI painting, illustration, design picture." body: ./SKILL.md source_hash: sha256:8398726504b70586 translated_by: human market: icon: >- short_desc: AI text-to-image generation (GPT Image / Wan models) 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 the local 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 You do NOT need to specify a provider — just pass `"serviceType": "image_gen"` and the system will automatically route to the correct provider. **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 | |-------|----------------|-------------| | gpt-image-2 | High quality, fast, versatile styles | **Default** — use when user does not specify a model | | wan2.7-image | Standard high quality (requires DashScope provider) | Only when user explicitly asks for Wan / DashScope | | wan2.7-image-pro | Flagship, 4K resolution (requires DashScope provider) | Only when user explicitly asks for top quality Wan model | **Default rule**: if the user does not specify a model, use `gpt-image-2`. **Note**: `wan2.7-image` and `wan2.7-image-pro` only work when the user has configured their own Alibaba Cloud DashScope provider. If you get an error with these models, fall back to `gpt-image-2`. ## Full Execution Flow (strictly follow these steps) ### How to get the API address The system prompt already contains the agent-service API address under the local API section (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:${PORT}/api/media-proxy" \ -H "Content-Type: application/json" \ -d '{ "serviceType": "image_gen", "endpoint": "/images/generations", "body": { "model": "gpt-image-2", "prompt": "Replace this with the image description (English usually gives better results)", "size": "1024x1024", "n": 1 }, "responseType": "json" }' -o /tmp/dashscope-response.json # Check success and extract b64_json directly to image file (NEVER cat the response to stdout) python3 -c " import json, base64, sys with open('/tmp/dashscope-response.json') as f: resp = json.load(f) if not resp.get('success'): print('ERROR:', json.dumps(resp, ensure_ascii=False)[:500]) sys.exit(1) b64 = resp['data']['data'][0]['b64_json'] with open('/tmp/dashscope-gen.png', 'wb') as f: f.write(base64.b64decode(b64)) print('OK: saved to /tmp/dashscope-gen.png') " ``` **CRITICAL**: The response contains a large base64 image (~2MB). NEVER print the raw response or b64_json to the terminal. Always save to file with `-o` and extract with the python3 script above. **Response format** (saved in `/tmp/dashscope-response.json`): ```json { "success": true, "data": { "created": 1781060911, "data": [{"b64_json": ""}], "size": "1024x1024" } } ``` ### Step 2: Upload to media-store ```bash curl -sk -X POST "https://127.0.0.1:${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: ``` ![Image description](dc-media://replace-with-mediaId) ``` For example: `![White fox in a forest](dc-media://a1b2c3d4-e5f6-47a8-b9c0-d1e2f3a4b5c6.png)` 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": "gpt-image-2", "prompt": "your image description", "size": "1024x1024", "n": 1 } ``` | User intent | size value | |-------------|-----------| | Square / avatar / default | "1024x1024" | | Landscape / scenery / wallpaper | "1536x1024" | | Portrait / mobile / poster | "1024x1536" | ### 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: ``` ![Image 1 description](dc-media://mediaId1) ![Image 2 description](dc-media://mediaId2) ``` ## 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` + `model_price_error` | Model not available on current provider | Switch to `gpt-image-2` and retry | | `statusCode: 400` | Other bad parameters | Check model name and size are from the tables above | **On model error**: If `wan2.7-image` or `wan2.7-image-pro` fails with `model_price_error`, automatically retry with `gpt-image-2`. Do NOT ask the user before retrying. **On other errors**: Report the error to the user clearly. Do NOT try alternative endpoints or read config files. ## Notes - Image generation calls are synchronous and typically return in 10-60 seconds - English prompts usually produce the best results; Chinese is also supported - When the user does not specify a model or size, default to `gpt-image-2` + `1024x1024`