Install
openclaw skills install ai-api-transit-station伝富AI-API文档技能 - 快速查询和使用302+个AI接口,涵盖聊天、图像、视频、音频、Midjourney等多个类别
openclaw skills install ai-api-transit-station本技能帮助你调用伝富AI-API平台的302+个API接口。当用户需要调用AI能力时,使用此技能。
[!IMPORTANT] 请注意区分以下三个关键地址:
| 类型 | 地址 | 说明 |
|---|---|---|
| API请求地址 | https://api.winfull.cloud-ip.cc | 以此开头调用所有接口 (Base URL) |
| API官网/Token | https://api.winfull.cloud-ip.cc/ | 在此注册账户、充值、申请API Token |
| API文档地址 | https://winfull.apifox.cn/ | 查阅最新的接口文档、参数说明 |
认证方式: 所有请求必须在Header中携带Bearer Token
Authorization: Bearer sk-xxxxxxxx
完整文档地址:https://winfull.apifox.cn/
| 类别 | 接口数 | 说明 |
|---|---|---|
| 图像生成 | 82 | DALL·E、Flux、豆包、Ideogram、Imagen |
| 视频生成 | 54 | Sora、Veo、可灵、即梦、Minimax |
| 聊天 | 43 | GPT、Claude、Gemini、DeepSeek |
| 任务查询 | 33 | 异步任务查询 |
| 其他 | 24 | 文件上传、模型列表、代码执行等 |
| 函数调用 | 12 | Function Calling、Web搜索 |
| Replicate | 12 | Replicate平台模型 |
| 音乐生成 | 9 | Suno音乐生成 |
| Midjourney | 8 | Midjourney完整功能 |
| 音频 | 7 | TTS、Whisper、音频理解 |
| 系统API | 7 | Token管理、用户信息 |
| 可灵Kling | 6 | 可灵专属功能 |
| 文档处理 | 3 | PDF理解、文档解析 |
| 嵌入 | 2 | Embeddings向量化 |
总计: 302+ 个API接口
端点: POST /v1/chat/completions
import requests
response = requests.post(
"https://api.winfull.cloud-ip.cc/v1/chat/completions",
headers={
"Authorization": "Bearer sk-xxx",
"Content-Type": "application/json"
},
json={
"model": "gpt-5.2",
"messages": [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "你好"}
]
}
)
result = response.json()
print(result["choices"][0]["message"]["content"])
端点: POST /v1/images/generations
response = requests.post(
"https://api.winfull.cloud-ip.cc/v1/images/generations",
headers={
"Authorization": "Bearer sk-xxx",
"Content-Type": "application/json"
},
json={
"model": "gpt-image-1.5-all",
"prompt": "一只可爱的猫咪在草地上",
"size": "1024x1536"
}
)
result = response.json()
image_url = result["data"][0]["url"]
[!IMPORTANT] 图生视频必读: 如果需要使用本地图片生成视频,必须先将图片上传到图床获取公网URL,然后使用该URL传给视频生成接口。
两种方式:
- 上传本地图片到图床(推荐)
- 直接使用已有的公网图片地址
端点: POST https://imageproxy.zhongzhuan.chat/api/upload
# 方式1: 上传本地图片到图床
with open("reference_image.jpg", "rb") as f:
response = requests.post(
"https://imageproxy.zhongzhuan.chat/api/upload",
headers={"Authorization": "Bearer sk-xxx"},
files={"file": f}
)
result = response.json()
image_url = result["url"] # 获取图床URL
print(f"图片已上传: {image_url}")
# 方式2: 直接使用公网图片地址
# image_url = "https://example.com/your-image.jpg"
# 现在可以使用这个URL进行图生视频
curl示例:
curl --location --request POST 'https://imageproxy.zhongzhuan.chat/api/upload' \
--header 'Authorization: Bearer <token>' \
--form 'file=@"/path/to/your/image.png"'
创建视频: POST /v1/video/create
import time
# 如果需要使用参考图,先上传图片到图床
image_url = None
if use_reference_image:
with open("reference.jpg", "rb") as f:
upload_response = requests.post(
"https://imageproxy.zhongzhuan.chat/api/upload",
headers={"Authorization": "Bearer sk-xxx"},
files={"file": f}
)
image_url = upload_response.json()["url"]
print(f"参考图已上传: {image_url}")
# 步骤1: 创建视频任务
response = requests.post(
"https://api.winfull.cloud-ip.cc/v1/video/create",
headers={
"Authorization": "Bearer sk-xxx",
"Content-Type": "application/json"
},
json={
"model": "sora-2",
"prompt": "一只小狗在草地上奔跑",
"images": [image_url] if image_url else [], # 使用图床URL
"orientation": "portrait",
"duration": 15
}
)
result = response.json()
task_id = result["id"]
查询任务: GET /v1/video/query?id={task_id}
# 步骤2: 轮询查询任务状态
while True:
result = requests.get(
f"https://api.winfull.cloud-ip.cc/v1/video/query?id={task_id}",
headers={"Authorization": "Bearer sk-xxx"}
).json()
if result["status"] == "completed":
video_url = result["video_url"]
print(f"视频生成成功: {video_url}")
break
elif result["status"] == "failed":
raise Exception(f"视频生成失败: {result.get('error')}")
time.sleep(5)
端点: POST /v1/audio/speech
response = requests.post(
"https://api.winfull.cloud-ip.cc/v1/audio/speech",
headers={
"Authorization": "Bearer sk-xxx",
"Content-Type": "application/json"
},
json={
"model": "tts-1",
"input": "你好,世界!",
"voice": "alloy"
}
)
with open("output.mp3", "wb") as f:
f.write(response.content)
端点: POST /v1/audio/transcriptions
response = requests.post(
"https://api.winfull.cloud-ip.cc/v1/audio/transcriptions",
headers={"Authorization": "Bearer sk-xxx"},
files={"file": open("audio.mp3", "rb")},
data={"model": "whisper-1"}
)
result = response.json()
transcribed_text = result["text"]
提交Imagine任务: POST /mj/submit/imagine
response = requests.post(
"https://api.winfull.cloud-ip.cc/mj/submit/imagine",
headers={
"Authorization": "Bearer sk-xxx",
"Content-Type": "application/json"
},
json={
"prompt": "a beautiful sunset over the ocean --ar 16:9 --v 6"
}
)
result = response.json()
task_id = result["result"]
大多数生成类API(视频、音乐、部分图像)都是异步的:
轮询建议: 间隔5-10秒查询一次任务状态
Authorization: Bearer sk-xxxxxxxxhttps://imageproxy.zhongzhuan.chat/api/uploadimages 参数https://api.winfull.cloud-ip.cc 开头api_list.md 文件访问 https://api.winfull.cloud-ip.cc/ 注册账户,在控制台中申请API Token。
必须先将本地图片上传到图床:
# 1. 上传图片到图床
with open("image.jpg", "rb") as f:
upload_resp = requests.post(
"https://imageproxy.zhongzhuan.chat/api/upload",
headers={"Authorization": "Bearer sk-xxx"},
files={"file": f}
)
image_url = upload_resp.json()["url"]
# 2. 使用图片URL创建视频
video_resp = requests.post(
"https://api.winfull.cloud-ip.cc/v1/video/create",
headers={"Authorization": "Bearer sk-xxx", "Content-Type": "application/json"},
json={"model": "sora-2", "prompt": "描述", "images": [image_url]}
)
可以!如果图片已经在公网上,可以直接使用URL,无需上传:
image_url = "https://example.com/your-image.jpg"
# 直接使用这个URL创建视频
根据模型和视频长度不同,通常需要1-10分钟。建议每5-10秒轮询一次任务状态。