大模型调用 · 视频任务教程示例

# 环境变量
export MODELS_AI_API_KEY="sk-你的密钥"
export BASE_URL="https://api.modelsai.cn"
 
# 通用请求头
# Authorization: Bearer $MODELS_AI_API_KEY
# Content-Type: application/json

curl -X POST "https://api.modelsai.cn/v1/chat/completions" \
  -H "Authorization: Bearer $MODELS_AI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-4o",
    "messages": [
      {"role": "system", "content": "你是一个简洁的中文助手"},
      {"role": "user", "content": "用一句话介绍你自己"}
    ],
    "stream": false
  }'
# 响应：choices[0].message.content 为模型回复

curl -N -X POST "https://api.modelsai.cn/v1/chat/completions" \
  -H "Authorization: Bearer $MODELS_AI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-4o",
    "messages": [
      {"role": "user", "content": "写一首关于春天的四行短诗"}
    ],
    "stream": true
  }'
# 返回 text/event-stream，逐段输出 data: {...}
# 以 data: [DONE] 结束

from openai import OpenAI
 
client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://api.modelsai.cn/v1",
)
 
resp = client.chat.completions.create(
    model="gpt-4o",
    messages=[
        {
            "role": "user",
            "content": [
                {"type": "text", "text": "这张图里有什么？"},
                {
                    "type": "image_url",
                    "image_url": {
                        "url": "https://your-cdn.example.com/photo.jpg",
                    },
                },
            ],
        }
    ],
)
print(resp.choices[0].message.content)

curl -X POST "https://api.modelsai.cn/v1/messages" \
  -H "Authorization: Bearer $MODELS_AI_API_KEY" \
  -H "Content-Type: application/json" \
  -H "anthropic-version: 2023-06-01" \
  -d '{
    "model": "claude-sonnet-4-5",
    "max_tokens": 1024,
    "messages": [
      {"role": "user", "content": "用一句话介绍你自己"}
    ],
    "stream": false
  }'
# 响应：content[0].text 为模型回复

curl -X POST "https://api.modelsai.cn/v1/responses" \
  -H "Authorization: Bearer $MODELS_AI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-4o",
    "input": "用一句话介绍你自己",
    "stream": false
  }'
# 响应：output_text 为模型回复

curl -X POST "https://api.modelsai.cn/v1/contents/generations/tasks" \
  -H "Authorization: Bearer $MODELS_AI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "doubao-seedance-1-0-pro",
    "content": [
      {
        "type": "text",
        "text": "一只橘猫在草地上奔跑，电影感镜头，浅景深"
      }
    ]
  }'

curl -X POST "https://api.modelsai.cn/v1/contents/generations/tasks" \
  -H "Authorization: Bearer $MODELS_AI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "doubao-seedance-1-0-pro",
    "content": [
      {
        "type": "image_url",
        "image_url": {
          "url": "https://your-cdn.example.com/input.png"
        }
      },
      {
        "type": "text",
        "text": "人物轻轻回头微笑，镜头缓慢推近"
      }
    ]
  }'

# 将 {id} 替换为创建任务返回的 id / task_id
curl "https://api.modelsai.cn/v1/contents/generations/tasks/{id}" \
  -H "Authorization: Bearer $MODELS_AI_API_KEY"

"""
端到端示例：上传素材 → 同步状态 → 生成视频 → 轮询结果
依赖：pip install requests
"""
import os
import time
import requests
 
BASE = "https://api.modelsai.cn"
HEADERS = {
    "Authorization": f"Bearer {os.environ['MODELS_AI_API_KEY']}",
    "Content-Type": "application/json",
}
 
 
def api(method, path, json=None, timeout=60):
    resp = requests.request(
        method, BASE + path, headers=HEADERS, json=json, timeout=timeout
    )
    resp.raise_for_status()
    return resp.json()
 
 
# ---------- 1. 上传素材 ----------
asset = api("POST", "/volc/ctyun-assets", {
    "url": "https://your-cdn.example.com/portrait.png",
    "assetType": "Image",
    "name": "demo-portrait",
})
asset_id = asset["data"]
print("asset_id =", asset_id)
 
# ---------- 2. 同步素材状态，等待 Active ----------
for _ in range(30):
    status = api("POST", f"/volc/ctyun-assets/{asset_id}/sync")["data"]
    print("asset status:", status)
    if status == "Active":
        break
    if status == "Failed":
        raise SystemExit("素材审核/处理失败，请检查 URL 与内容合规")
    time.sleep(2)
 
# ---------- 3. 提交视频任务 ----------
# 若模型支持素材引用，可将素材 URL 写入 content
created = api("POST", "/v1/contents/generations/tasks", {
    "model": "doubao-seedance-1-0-pro",
    "content": [
        {"type": "text", "text": "人物在窗边看书，自然光，电影感"},
    ],
})
task_id = created.get("id") or created.get("task_id")
print("task_id =", task_id)
 
# ---------- 4. 轮询任务直至终态 ----------
for _ in range(120):
    task = api("GET", f"/v1/contents/generations/tasks/{task_id}", timeout=30)
    status = task.get("status")
    print("task status:", status)
 
    if status == "succeeded":
        video_url = (task.get("content") or {}).get("video_url")
        print("video_url =", video_url)
        break
    if status in ("failed", "expired"):
        print("error:", task.get("error"))
        break
    time.sleep(5)
else:
    print("轮询超时，请稍后在控制台「视频任务」中查看")