fix(dashscope-image-gen): 切换到 /images/generations 端点 v1.3.0 (#26)

## 概要 / Summary

修复 dashscope-image-gen 技能的核心端点问题,从 `/chat/completions`(对 wan 图片模型返回 HTTP
400)切换到 `/images/generations`,同时新增多项防护措施防止模型偏离执行路径。

Fix the core endpoint issue: switch from `/chat/completions` (returns
HTTP 400 for wan image models) to `/images/generations`, with enhanced
guardrails to prevent model deviation.

## 变更内容 / Changes

**核心修复**
- 端点:`/chat/completions` → `/images/generations`
- 请求体:`messages` 数组 → `prompt` 字符串 + `size` + `n`
- 响应处理:`choices[].message.content` 图片 URL → `b64_json` base64 解码

**新增防护**
- `curl -o` 保存响应到临时文件,避免 ~2MB base64 灌入终端浪费 token
- 新增"供应商与默认算力"章节,明确 DesireCore Cloud 始终可用,无需探索
- 强化 7 条强制规则(原 5 条),禁止探索未列出的模型/端点/配置文件
- 端口发现优先从系统提示词获取,兜底 `${DESIRECORE_HOME:-$HOME/.desirecore}`
- 错误处理改为表格格式 + "禁止自行重试其他方案"

## 测试 / Test Plan

- [x] dev 模式端到端测试:用户输入"生成一张小猪" → 4 次工具调用,0 失败,图片成功生成并展示
- [x] 对比历史:第一次测试 472 条/7+ 失败 → 第二次 141 条/5 失败 → **本次 108 条/0 失败**
This commit is contained in:
2026-06-10 17:23:52 +08:00
committed by GitHub
parent 2cea1a3aa6
commit 42617e292d
2 changed files with 153 additions and 131 deletions

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@@ -4,11 +4,11 @@ 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
chat/completions API for synchronous image generation.
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: 1.2.0
version: 1.3.0
type: procedural
risk_level: low
status: enabled
@@ -25,7 +25,7 @@ requires:
- Bash
metadata:
author: desirecore
updated_at: '2026-05-08'
updated_at: '2026-06-10'
i18n:
default_locale: en-US
source_locale: zh-CN
@@ -36,16 +36,16 @@ metadata:
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 chat/completions 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。
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: sha256:135b99cdd33441fb
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 chat/completions API. Trigger keywords: generate image, draw, text-to-image, create image, AI painting, illustration, design picture, Wan, Tongyi Wanxiang, DashScope."
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: sha256:135b99cdd33441fb
source_hash: sha256:a2c4e8f01b3d5e7f
translated_by: human
market:
icon: >-
@@ -68,11 +68,22 @@ market:
## Mandatory Rules (violations cause failure)
1. **Must access agent-service over HTTPS** — use `https://127.0.0.1:${PORT}` with `-k` to skip certificate verification
2. **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
3. **Must use the `dc-media://` protocol to display images** — the only form the frontend can render correctly
4. **Use Bash curl throughout** — do not use the HttpRequest tool or Python
5. **Use compatible-mode (`/chat/completions`)** — synchronous call; the response contains the image URL directly
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
@@ -83,76 +94,71 @@ market:
**Default rule**: if the user does not specify a model, use `wan2.7-image`.
## Full Execution Flow (strictly three steps)
## Full Execution Flow (strictly follow these steps)
### Prerequisites
### How to get the API address
- At least one enabled compute provider supports `image_gen` service type (e.g. DashScope, or the default DesireCore Cloud provider)
- agent-service is running
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.
### Step 1: Call the text-to-image API (synchronous)
Generate the image via media-proxy's compatible-mode endpoint; the response includes the image URL directly:
If for any reason you cannot find it in the system prompt, use this fallback:
```bash
PORT=$(cat ${DESIRECORE_ROOT}/agent-service.port)
PORT=$(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": "/chat/completions",
"endpoint": "/images/generations",
"body": {
"model": "wan2.7-image",
"messages": [
{
"role": "user",
"content": [
{"type": "text", "text": "Replace this with the image description (English usually gives better results)"}
]
}
]
"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')
"
```
**Example response**:
**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": {
"request_id": "...",
"output": {
"choices": [
{
"message": {
"role": "assistant",
"content": [
{
"type": "image",
"image": "https://dashscope-result.oss.aliyuncs.com/..."
}
]
},
"finish_reason": "stop"
}
]
}
},
"statusCode": 200
"created": 1781060911,
"data": [{"b64_json": "<very large base64 string>"}],
"size": "1024x1024"
}
}
```
Locate the item with `type: "image"` inside `data.output.choices[0].message.content` and extract its `image` URL.
### Step 2: Download and upload to media-store
The image URL is time-limited; download and persist it to the local media-store immediately:
### Step 2: Upload to media-store
```bash
PORT=$(cat ${DESIRECORE_ROOT}/agent-service.port)
IMAGE_URL="image URL from step 1's response"
curl -sL "$IMAGE_URL" -o /tmp/dashscope-gen.png && \
curl -sk -X POST "https://127.0.0.1:${PORT}/api/media/upload" \
-F "file=@/tmp/dashscope-gen.png;type=image/png"
```
@@ -175,13 +181,14 @@ The frontend will translate `dc-media://` into a reachable image URL and render
### Size selection
When calling Wan via compatible-mode, the size is passed as the top-level `size` parameter:
Pass `size` in the `body` object:
```json
{
"model": "wan2.7-image",
"prompt": "your image description",
"size": "1024x1024",
"messages": [...]
"n": 1
}
```
@@ -195,12 +202,12 @@ When calling Wan via compatible-mode, the size is passed as the top-level `size`
| Parameter | Description |
|------|------|
| `n` | Number of images, 14, default 1 |
| `n` | Number of images, 1-4, default 1 |
| `size` | Image size, e.g. "1024x1024" |
## Multiple Image Generation
When `n > 1`, the `choices` array contains multiple entries, each with an image inside `message.content`. Download and upload each image, then render them one by one:
When `n > 1`, download and upload each image, then render them one by one:
```
![Image 1 description](dc-media://mediaId1)
@@ -209,16 +216,20 @@ When `n > 1`, the `choices` array contains multiple entries, each with an image
## Error Handling
- `success: false` + `error: "No matching provider"`: No enabled provider supports `image_gen` service type
- `success: false` + `error: "API Key not configured"`: API Key missing
- `statusCode: 401`: API Key invalid or expired
- `statusCode: 429`: rate limited, retry later
- `statusCode: 400` + `InvalidParameter`: bad parameters (e.g. unsupported size)
- `statusCode: 403` + `AccessDenied.Unpurchased`: model not activated; enable it in the Alibaba Cloud console
| 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
- compatible-mode calls are synchronous and typically return in 1060 seconds (wan2.7-image-pro can take longer)
- 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`

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@@ -4,11 +4,22 @@
## 强制规则(违反将导致功能失败)
1. **必须用 HTTPS 访问 agent-service**`https://127.0.0.1:${PORT}``-k` 跳过证书验证
2. **必须通过 `/api/media/upload` 上传到 media-store** — 禁止保存到本地路径
3. **必须使用 `dc-media://` 协议展示图片** — 唯一能让前端正确渲染的方式
4. **全程使用 Bash curl** — 不要使用 HttpRequest 工具或 Python
5. **使用 compatible-mode/chat/completions** — 同步调用,响应直接包含图片 URL
1. **严格按下方步骤执行** — 禁止自行探索其他端点、尝试本文档未列出的模型、或读取配置文件
2. **必须用 HTTPS 访问 agent-service** — API 地址已在系统提示词的"本机 API"部分提供(如 `https://127.0.0.1:PORT`),直接使用,加 `-k` 跳过证书验证
3. **必须通过 `/api/media/upload` 上传到 media-store** — 禁止保存到本地路径
4. **必须使用 `dc-media://` 协议展示图片** — 唯一能让前端正确渲染的方式
5. **全程使用 Bash curl** — 不要使用 HttpRequest 工具或 Python
6. **使用 `/images/generations` 端点** — 同步调用,响应包含 b64_json 图片数据
7. **只能使用下方模型列表中的模型** — 禁止尝试 dall-e-3、qwen-vl 或任何未列出的模型
## 供应商与默认算力
本技能使用阿里云 DashScope 的通义万相系列模型。**无需指定供应商**,只需传 `"serviceType": "image_gen"`,系统会自动路由到正确的供应商:
- **DesireCore Cloud**(默认,始终可用):内置算力供应商已支持 `image_gen` 和通义万相模型。用户无需任何配置即可直接生成图片。
- **DashScope**(用户自配):如果用户自己配置了阿里云 API Key系统可能会路由到用户自己的供应商。
**禁止**尝试查询供应商列表、读取 compute.json、或通过 API 探索可用模型。下方列出的模型保证可用。
## 模型选择指南
@@ -19,81 +30,76 @@
**默认规则**:用户未指定模型时,使用 `wan2.7-image`
## 完整执行流程(严格按此步执行)
## 完整执行流程(严格按此步执行)
### 前置条件
### 获取 API 地址
- 至少有一个已启用的算力供应商支持 `image_gen` 服务类型(如 DashScope 或默认的 DesireCore Cloud 供应商)
- agent-service 正在运行
系统提示词中"本机 API"部分已包含 agent-service 的地址(如 `Agent Service: https://127.0.0.1:61000`)。直接从中提取 URL 使用。
### 第一步:调用文生图 API同步
通过 media-proxy 的 compatible-mode 端点生成图片,响应直接包含图片 URL
如果无法从系统提示词中找到,使用以下兜底方式:
```bash
PORT=$(cat ${DESIRECORE_ROOT}/agent-service.port)
PORT=$(cat "${DESIRECORE_HOME:-$HOME/.desirecore}/agent-service.port")
# 然后使用 https://127.0.0.1:${PORT}
```
### 第一步:生成图片(单次 curl 调用)
通过 media-proxy 调用 `/images/generations` 端点。**必须严格使用以下请求结构** — 禁止添加 `messages``response_format` 或任何未在此处列出的参数:
```bash
# 将响应保存到临时文件,避免 base64 数据灌入终端
curl -sk -X POST "https://127.0.0.1:${PORT}/api/media-proxy" \
-H "Content-Type: application/json" \
-d '{
"serviceType": "image_gen",
"endpoint": "/chat/completions",
"endpoint": "/images/generations",
"body": {
"model": "wan2.7-image",
"messages": [
{
"role": "user",
"content": [
{"type": "text", "text": "这里替换为图片描述(建议英文效果更好)"}
]
}
]
"prompt": "这里替换为图片描述(建议英文效果更好)",
"size": "1024x1024",
"n": 1
},
"responseType": "json"
}'
}' -o /tmp/dashscope-response.json
# 检查成功并直接将 b64_json 提取为图片文件(禁止将响应内容输出到终端)
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')
"
```
**响应示例**
**关键警告**响应包含大约 2MB 的 base64 图片数据。**禁止**将原始响应或 b64_json 打印到终端。始终使用 `-o` 保存到文件,再用上面的 python3 脚本提取。
**响应格式**(保存在 `/tmp/dashscope-response.json` 中):
```json
{
"success": true,
"data": {
"request_id": "...",
"output": {
"choices": [
{
"message": {
"role": "assistant",
"content": [
{
"type": "image",
"image": "https://dashscope-result.oss.aliyuncs.com/..."
}
]
},
"finish_reason": "stop"
}
]
}
},
"statusCode": 200
"created": 1781060911,
"data": [{"b64_json": "<非常大的 base64 字符串>"}],
"size": "1024x1024"
}
}
```
`data.output.choices[0].message.content` 中找到 `type: "image"` 的项,提取其 `image` URL。
### 第二步:下载并上传到 media-store
图片 URL 有时效,必须立即下载并保存到本地 media-store
### 第二步:上传到 media-store
```bash
PORT=$(cat ${DESIRECORE_ROOT}/agent-service.port)
IMAGE_URL="第一步响应中的 image URL"
curl -sL "$IMAGE_URL" -o /tmp/dashscope-gen.png && \
curl -sk -X POST "https://127.0.0.1:${PORT}/api/media/upload" \
-F "file=@/tmp/dashscope-gen.png;type=image/png"
```
从 JSON 响应中提取 `mediaId` 字段(格式如 `xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx.png`)。
上传 JSON 响应中提取 `mediaId` 字段(格式如 `xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx.png`)。
### 第三步:用 dc-media 协议展示图片
@@ -111,13 +117,14 @@ curl -sk -X POST "https://127.0.0.1:${PORT}/api/media/upload" \
### 尺寸选择
通义万相通过 compatible-mode 调用时,尺寸通过 `size` 参数传入(放在请求体顶层)
`size` 放在 `body` 对象中
```json
{
"model": "wan2.7-image",
"prompt": "图片描述",
"size": "1024x1024",
"messages": [...]
"n": 1
}
```
@@ -136,7 +143,7 @@ curl -sk -X POST "https://127.0.0.1:${PORT}/api/media/upload" \
## 多图生成
`n > 1` 时,`choices` 数组会有多个元素,每个 `message.content` 中都有一张图片。需要为每张图片执行下载+上传,然后逐一展示:
`n > 1` 时,为每张图片执行下载+上传,然后逐一展示:
```
![图片1描述](dc-media://mediaId1)
@@ -145,16 +152,20 @@ curl -sk -X POST "https://127.0.0.1:${PORT}/api/media/upload" \
## 错误处理
- `success: false` + `error: "未找到匹配的供应商"`:没有已启用的供应商支持 `image_gen` 服务类型
- `success: false` + `error: "未配置 API Key"`:未填写 API Key
- `statusCode: 401`API Key 无效或已过期
- `statusCode: 429`:频率限制,稍后重试
- `statusCode: 400` + `InvalidParameter`:参数错误(如尺寸不支持)
- `statusCode: 403` + `AccessDenied.Unpurchased`:模型未开通,需要在阿里云控制台开通
| 错误 | 含义 | 处理方式 |
|------|------|---------|
| `"未找到匹配的供应商"` | 没有启用的供应商支持 `image_gen` | 告知用户在设置中启用支持 image_gen 的供应商 |
| `"未配置 API Key"` | 未填写 API Key | 告知用户配置 API Key |
| `statusCode: 401` | API Key 无效或过期 | 告知用户检查 API Key |
| `statusCode: 429` | 频率限制 | 等待后重试一次 |
| `statusCode: 400` | 参数错误 | 检查模型名和尺寸是否在上表中 |
| `statusCode: 403 AccessDenied.Unpurchased` | 模型未开通 | 告知用户在阿里云控制台开通 |
**遇到任何错误时**:禁止尝试其他模型、其他端点、或读取配置文件。直接向用户清晰报告错误即可。
## 注意事项
- 通过 compatible-mode 调用是同步的,通常 10-60 秒返回wan2.7-image-pro 可能更长)
- 图片生成调用是同步的,通常 10-60 秒返回wan2.7-image-pro 可能更长)
- 结果图片 URL 有时效,必须及时下载
- 提示词建议用英文以获得最佳效果,中文也支持
- 如果用户未明确要求模型/尺寸,默认使用 `wan2.7-image` + `1024x1024`