OpenLLM API接口文档

curl -X POST "http://your-api-domain/v1/chat/completions" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model": "gemini-2.5-pro",
    "messages": [
      {
        "role": "user",
        "content": "你好，请介绍一下你自己"
      }
    ],
    "stream": false,
    "temperature": 0.7,
    "max_tokens": 1000
  }'

curl -X POST "http://your-api-domain/v1/chat/completions" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model": "gemini-2.5-pro",
    "messages": [
      {
        "role": "user",
        "content": "请写一首关于春天的诗"
      }
    ],
    "stream": true
  }'

from openai import OpenAI

# 使用您的API端点和密钥
client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="http://your-api-domain/v1"
)

# 调用聊天接口
response = client.chat.completions.create(
    model="gemini-2.5-pro",
    messages=[
        {"role": "user", "content": "你好，请介绍一下你自己"}
    ]
)

print(response.choices[0].message.content)

curl -X POST "http://your-api-domain/v1/responses" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model": "gpt-4o",
    "input": [
      {
        "role": "user",
        "content": [
          {
            "type": "input_text",
            "text": "这张图片是什么颜色的？"
          },
          {
            "type": "input_image",
            "image_url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mP8z8BQDwAEhQGAhKmMIQAAAABJRU5ErkJggg=="
          }
        ]
      }
    ]
  }'

curl -X POST "http://your-api-domain/v1/responses" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model": "gpt-4o",
    "input": [
      {
        "role": "user",
        "content": [
          {
            "type": "input_text",
            "text": "这张图片描述了什么内容？"
          },
          {
            "type": "input_image",
            "image_url": "https://storage.googleapis.com/img-output/bg.png"
          }
        ]
      }
    ]
  }'

curl -X GET "http://your-api-domain/v1/models" \
  -H "Authorization: Bearer YOUR_API_KEY"

from openai import OpenAI

# 使用您的API端点和密钥
client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="http://your-api-domain/v1"
)

# 获取模型列表
models = client.models.list()

# 打印所有可用模型
for model in models.data:
    print(f"模型ID: {model.id}, 创建时间: {model.created}")

{
  "object": "list",
  "data": [
    {
      "id": "gemini-2.5-pro",
      "object": "model",
      "created": 1640995200,
      "owned_by": "openllms"
    },
    {
      "id": "gemini-2.5-flash",
      "object": "model",
      "created": 1640995200,
      "owned_by": "openllms"
    },
    {
      "id": "gpt-4o",
      "object": "model",
      "created": 1640995200,
      "owned_by": "openllms"
    },
    {
      "id": "gpt-4",
      "object": "model",
      "created": 1640995200,
      "owned_by": "openllms"
    }
  ]
}

curl -X POST "http://your-api-domain/v1/images/generations" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model": "nano-banana-pro",
    "prompt": "A cute baby sea otter",
    "size": "1:1"
  }'

{
  "created": 1713833628,
  "data": [
    {
      "b64_json": "..."
    }
  ],
  "usage": {
    "total_tokens": 100,
    "input_tokens": 50,
    "output_tokens": 50,
    "input_tokens_details": {
      "text_tokens": 10,
      "image_tokens": 40
    }
  }
}

import requests
import base64

API_URL = "http://your-api-domain/v1/images/generations"
API_KEY = "YOUR_API_KEY"

headers = {
    "Authorization": f"Bearer {API_KEY}",
    "Content-Type": "application/json"
}

data = {
    "model": "nano-banana-pro",
    "prompt": "A cute baby sea otter",
    "size": "1:1"
}

response = requests.post(API_URL, json=data, headers=headers)

if response.status_code == 200:
    result = response.json()
    for item in result.get('data', []):
        if 'b64_json' in item:
            img_data = base64.b64decode(item['b64_json'])
            with open("output.png", 'wb') as f:
                f.write(img_data)
            print("图片已保存: output.png")
else:
    print(f"请求失败: {response.status_code}, {response.text}")

curl -X POST "http://your-api-domain/v1/images/edits" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -F "model=nano-banana-pro" \
  -F "prompt=Put the cloth on the girl" \
  -F "size=16:9" \
  -F "image=@/path/to/girl.png" \
  -F "image=@/path/to/cloth.png"

curl -X POST "http://your-api-domain/v1/images/edits" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -F "model=nano-banana-pro" \
  -F "prompt=Replace the masked area with a beautiful sunset" \
  -F "size=1:1" \
  -F "image=@/path/to/girl.png" \
  -F "mask=@/path/to/mask.png"

{
  "created": 1234567890,
  "data": [
    {
      "b64_json": "base64编码的生成图片数据"
    }
  ]
}

import requests
import base64
import json

API_URL = "http://your-api-domain/v1/images/edits"
API_KEY = "YOUR_API_KEY"

def main():
    API_URL = "http://your-api-domain/v1/images/edits"
    API_KEY = "YOUR_API_KEY"

    # 准备文件
    files = [
        ("image", ("girl.png", open("girl.png", "rb"), "image/png")),
        ("image", ("cloth.png", open("cloth.png", "rb"), "image/png")),
    ]

    # 准备表单数据
    data = {
        "model": "nano-banana-pro",
        "prompt": "Put the cloth on the girl",
        "size": "16:9"
    }

    headers = {
        "Authorization": f"Bearer {API_KEY}"
    }

    # 发送请求
    response = requests.post(API_URL, data=data, files=files, headers=headers, timeout=300)

    if response.status_code == 200:
        result = response.json()
        for i, item in enumerate(result.get('data', [])):
            if 'b64_json' in item:
                img_data = base64.b64decode(item['b64_json'])
                with open(f"output_{i+1}.png", 'wb') as f:
                    f.write(img_data)
                print(f"图片已保存: output_{i+1}.png")
    else:
        print(f"请求失败: {response.status_code}, {response.text}")

    # 关闭文件
    for _, file_obj in files:
        file_obj[1].close()


if __name__ == "__main__":
    main()

{
  "id": "video_task_abc123xyz"
}

{
  "id": "video_task_abc123xyz",
  "status": "processing",
  "progress": 45,
  "fail_reason": null
}

import requests

API_URL = "http://your-api-domain"
API_KEY = "YOUR_API_KEY"
task_id = "video_task_abc123xyz"

url = f"{API_URL}/v1/videos/{task_id}/content"
headers = {"Authorization": f"Bearer {API_KEY}"}

response = requests.get(url, headers=headers, stream=True)

if response.status_code == 200:
    with open("output_video.mp4", "wb") as f:
        for chunk in response.iter_content(chunk_size=8192):
            f.write(chunk)
    print("视频下载成功!")
else:
    print(f"下载失败: {response.status_code}")

import requests
import time
import os

# =================== 配置 ===================
API_URL = "http://your-api-domain/v1"
API_KEY = "YOUR_API_KEY"
MODEL = "veo-3.1"
PROMPT = "a cat running"
SECONDS = "8"
IMAGE_PATH = None  # 图生视频时设置为图片路径，如: "/path/to/image.png"

CHECK_INTERVAL = 5  # 每5秒检查一次状态
TIMEOUT = 600       # 最长等待10分钟

# =============================================

def create_video_task():
    """步骤1: 创建视频生成任务"""
    url = f"{API_URL}/videos"
    headers = {"Authorization": f"Bearer {API_KEY}"}

    if IMAGE_PATH:
        # 图生视频：使用 multipart/form-data
        with open(IMAGE_PATH, 'rb') as f:
            files = {'input_reference': f}
            data = {
                'model': MODEL,
                'prompt': PROMPT,
                'seconds': SECONDS
            }
            response = requests.post(url, headers=headers, data=data, files=files)
    else:
        # 文生视频：使用 JSON
        data = {
            'model': MODEL,
            'prompt': PROMPT,
            'seconds': SECONDS
        }
        response = requests.post(url, headers=headers, json=data)

    if response.status_code == 200:
        result = response.json()
        print(f"任务创建成功! ID: {result.get('id')}")
        return result.get('id')
    else:
        print(f"创建失败: {response.status_code}, {response.text}")
        return None


def get_status(task_id):
    """步骤2: 查询任务状态"""
    url = f"{API_URL}/videos/{task_id}"
    headers = {"Authorization": f"Bearer {API_KEY}"}
    response = requests.get(url, headers=headers)

    if response.status_code == 200:
        return response.json()
    else:
        print(f"查询状态失败: {response.status_code}")
        return None


def download_video(task_id):
    """步骤3: 下载视频"""
    url = f"{API_URL}/videos/{task_id}/content"
    headers = {"Authorization": f"Bearer {API_KEY}"}

    response = requests.get(url, headers=headers, stream=True)

    if response.status_code == 200:
        filename = f"video_{task_id}.mp4"
        with open(filename, 'wb') as f:
            for chunk in response.iter_content(chunk_size=8192):
                f.write(chunk)
        print(f"下载成功! 文件: {filename}")
        return True
    else:
        print(f"下载失败: {response.status_code}")
        return False


def main():
    print("=" * 50)
    print("   AI 视频生成工具")
    print("=" * 50)

    # 1. 创建任务
    task_id = create_video_task()
    if not task_id:
        return

    # 2. 轮询状态
    print(f"等待视频生成... (每{CHECK_INTERVAL}秒检查一次)")
    start_time = time.time()

    while True:
        elapsed = int(time.time() - start_time)
        if elapsed > TIMEOUT:
            print(f"超时! 已等待 {TIMEOUT} 秒")
            break

        status_data = get_status(task_id)
        if status_data:
            status = status_data.get('status')
            progress = status_data.get('progress', 0)
            print(f"[{elapsed}s] 状态: {status} | 进度: {progress}%")

            # 成功
            if status in ['completed', 'succeeded']:
                print("视频生成完成!")
                download_video(task_id)
                return

            # 失败
            elif status in ['failed', 'FAILURE']:
                reason = status_data.get('fail_reason', '未知错误')
                print(f"视频生成失败: {reason}")
                return

        time.sleep(CHECK_INTERVAL)


if __name__ == "__main__":
    main()