Developer Documentation

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://atengin.atomclub.cn/v1"
)

with open("audio.mp3", "rb") as f:
    transcription = client.audio.transcriptions.create(
        model="whisper-1",
        file=f,
        language="zh",
        response_format="json"
    )

print(transcription.text)

{
  "text": "你好，欢迎使用原子引擎的语音转写功能。",
  "task": "transcribe",
  "language": "zh",
  "duration": 3.45,
  "words": []
}

{
  "candidates": [
    {
      "content": {
        "parts": [
          {
            "inlineData": {
              "mimeType": "audio/wav",
              "data": "<base64_encoded_audio_data>"
            }
          }
        ]
      }
    }
  ]
}

{
  "text": "你好，这是一段翻译文本。"
}

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://atengin.atomclub.cn/v1"
)

response = client.chat.completions.create(
    model="gpt-4o",
    messages=[
        {"role": "system", "content": "你是一个 helpful 的助手。"},
        {"role": "user", "content": "用一句话解释量子计算。"}
    ],
    temperature=0.7,
    max_tokens=256
)

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

{
  "id": "chatcmpl-abc123",
  "object": "chat.completion",
  "created": 1699900000,
  "model": "gpt-4o",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "量子计算利用量子比特的叠加和纠缠特性，在特定问题上实现远超经典计算的速度优势。"
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 23,
    "completion_tokens": 45,
    "total_tokens": 68
  }
}

import anthropic

client = anthropic.Anthropic(
    api_key="YOUR_API_KEY",
    base_url="https://atengin.atomclub.cn"
)

message = client.messages.create(
    model="claude-3-5-sonnet-20241022",
    max_tokens=1024,
    system="你是一个专业的翻译助手。",
    messages=[
        {"role": "user", "content": "Translate to Chinese: Hello, how are you?"}
    ]
)

print(message.content[0].text)

{
  "id": "msg_01XFDUDYJgAACzvnptvVoYEL",
  "type": "message",
  "role": "assistant",
  "content": [
    {
      "type": "text",
      "text": "你好，你好吗？"
    }
  ],
  "model": "claude-3-5-sonnet-20241022",
  "stop_reason": "end_turn",
  "usage": {
    "input_tokens": 12,
    "output_tokens": 8
  }
}

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://atengin.atomclub.cn/v1"
)

response = client.completions.create(
    model="gpt-3.5-turbo-instruct",
    prompt="Once upon a time",
    max_tokens=50
)

print(response.choices[0].text)

{
  "id": "cmpl-abc123",
  "object": "text_completion",
  "choices": [
    {
      "text": ", there was a brave knight who traveled far and wide.",
      "index": 0,
      "finish_reason": "length"
    }
  ],
  "usage": {
    "prompt_tokens": 4,
    "completion_tokens": 15,
    "total_tokens": 19
  }
}

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://atengin.atomclub.cn/v1"
)

response = client.embeddings.create(
    model="text-embedding-004",
    input="原子引擎是一个多模型 API 网关。"
)

embedding = response.data[0].embedding
print(f"维度: {len(embedding)}")

{
  "object": "list",
  "data": [
    {
      "object": "embedding",
      "index": 0,
      "embedding": [0.0123, -0.0456, 0.0789]
    }
  ],
  "model": "text-embedding-004",
  "usage": {
    "prompt_tokens": 12,
    "total_tokens": 12
  }
}

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://atengin.atomclub.cn/v1"
)

response = client.embeddings.create(
    model="text-embedding-3-small",
    input="原子引擎是一个多模型 API 网关。"
)

embedding = response.data[0].embedding
print(f"维度: {len(embedding)}")

{
  "object": "list",
  "data": [
    {
      "object": "embedding",
      "index": 0,
      "embedding": [0.0123, -0.0456, 0.0789]
    }
  ],
  "model": "text-embedding-3-small",
  "usage": {
    "prompt_tokens": 12,
    "total_tokens": 12
  }
}

{
  "models": [
    {
      "name": "gemini-pro",
      "display_name": "Gemini Pro",
      "context_length": 32768,
      "supported_generation_methods": ["generateContent", "countTokens"]
    },
    {
      "name": "gemini-1.5-pro",
      "display_name": "Gemini 1.5 Pro",
      "context_length": 1048576,
      "supported_generation_methods": ["generateContent", "countTokens"]
    }
  ]
}

from openai import OpenAI

client = OpenAI(api_key="YOUR_API_KEY", base_url="https://atengin.atomclub.cn/v1")
response = client.chat.completions.create(
    model="gemini-pro",
    messages=[{"role": "user", "content": "Explain quantum computing."}]
)
print(response.choices[0].message.content)

{
  "id": "chatcmpl-abc123",
  "model": "gemini-pro",
  "choices": [{"message": {"role": "assistant", "content": "Quantum computing uses qubits..."}, "finish_reason": "stop"}],
  "usage": {"prompt_tokens": 10, "completion_tokens": 45, "total_tokens": 55}
}

import requests

resp = requests.post("https://atengin.atomclub.cn/v1/gemini/relay",
    headers={"Authorization": "Bearer YOUR_API_KEY"},
    json={"model": "gemini-pro", "contents": [{"parts": [{"text": "What is the capital of France?"}]}]}
)
print(resp.json()["candidates"][0]["content"]["parts"][0]["text"])

{
  "candidates": [{"content": {"parts": [{"text": "The capital of France is Paris."}]}, "finishReason": "STOP"}],
  "usageMetadata": {"promptTokenCount": 10, "candidatesTokenCount": 8, "totalTokenCount": 18}
}

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://atengin.atomclub.cn/v1"
)

with open("original.png", "rb") as img, open("mask.png", "rb") as mask:
    response = client.images.edit(
        image=img,
        mask=mask,
        prompt="Add a rainbow in the sky",
        n=1,
        size="1024x1024"
    )

print(response.data[0].url)

{
  "created": 1699900000,
  "data": [
    {
      "url": "https://cdn.atengin.atomclub.cn/images/edited_abc.png"
    }
  ]
}

{
  "choices": [
    {
      "message": {
        "role": "assistant",
        "content": [
          {
            "type": "image_url",
            "image_url": {"url": "data:image/png;base64,<base64_data>"}
          }
        ]
      }
    }
  ]
}

{
  "candidates": [
    {
      "content": {
        "parts": [
          {
            "inlineData": {
              "mimeType": "image/png",
              "data": "<base64_encoded_image_data>"
            }
          }
        ]
      }
    }
  ]
}

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://atengin.atomclub.cn/v1"
)

response = client.images.generate(
    model="dall-e-3",
    prompt="A cat in an astronaut suit standing on the moon, cyberpunk style.",
    n=1,
    size="1024x1024"
)

print(response.data[0].url)

{
  "created": 1699900000,
  "data": [
    {
      "url": "https://cdn.atengin.atomclub.cn/images/abc123.png",
      "revised_prompt": "A cyberpunk-style illustration of a cat in an astronaut suit standing on the moon..."
    }
  ]
}

{
  "created": 1699900000,
  "data": [
    {
      "url": "https://cdn.atengin.atomclub.cn/images/edited_abc123.png"
    }
  ]
}

{
  "created": 1699900000,
  "data": [
    {
      "url": "https://cdn.atengin.atomclub.cn/images/abc123.png"
    }
  ]
}

{
  "task_id": "task_kling_img2vid_abc123",
  "status": "completed",
  "video_url": "https://cdn.atengin.atomclub.cn/video/kling_img2vid_abc123.mp4"
}

{
  "task_id": "task_kling_img2vid_abc123",
  "status": "processing"
}

{
  "task_id": "task_kling_abc123",
  "status": "completed",
  "video_url": "https://cdn.atengin.atomclub.cn/video/kling_abc123.mp4"
}

{
  "task_id": "task_kling_abc123",
  "status": "processing"
}

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://atengin.atomclub.cn/v1"
)

models = client.models.list()
for model in models.data:
    print(f"{model.id} — {model.owned_by}")

{
  "object": "list",
  "data": [
    {
      "id": "gpt-4o",
      "object": "model",
      "owned_by": "openai",
      "context_length": 128000,
      "created": 1719000000
    },
    {
      "id": "claude-3-5-sonnet-20241022",
      "object": "model",
      "owned_by": "anthropic",
      "context_length": 200000,
      "created": 1700000000
    },
    {
      "id": "text-embedding-3-small",
      "object": "model",
      "owned_by": "openai",
      "context_length": 8191,
      "created": 1700000000
    }
  ]
}

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://atengin.atomclub.cn/v1"
)

response = client.moderations.create(
    input="I want to hurt someone.",
    model="text-moderation-latest"
)

flagged = response.results[0].flagged
print(f"违规: {flagged}")
print(f"类别: {response.results[0].categories}")

{
  "id": "modr-abc123",
  "model": "text-moderation-latest",
  "results": [
    {
      "flagged": true,
      "categories": {
        "violence": true,
        "self-harm": false,
        "hate": false
      },
      "category_scores": {
        "violence": 0.92,
        "self-harm": 0.01,
        "hate": 0.03
      }
    }
  ]
}

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://atengin.atomclub.cn/v1"
)

response = client.responses.create(
    model="gpt-4o",
    input="What is the weather in Tokyo?",
    tools=[{"type": "web_search"}]
)

print(response.output_text)

{
  "id": "resp_abc123",
  "model": "gpt-4o",
  "status": "completed",
  "output": [
    {
      "type": "message",
      "role": "assistant",
      "content": [
        {
          "type": "output_text",
          "text": "Currently in Tokyo, it is 28°C and sunny."
        }
      ]
    }
  ],
  "usage": {
    "input_tokens": 45,
    "output_tokens": 32,
    "total_tokens": 77
  }
}

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://atengin.atomclub.cn/v1"
)

response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Hello"}]
)

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://atengin.atomclub.cn/v1"
)

response = client.embeddings.create(
    model="bge-reranker-v2-m3",
    query="如何部署一个 Python Web 应用？",
    documents=[
        "Python 是一种编程语言。",
        "使用 Gunicorn + Nginx 部署 Django 应用的完整指南。",
        "Docker 容器化部署最佳实践。",
        "Flask 和 Django 都是 Python Web 框架。"
    ],
    top_n=2
)

for r in response.data:
    print(f"[{r['relevance_score']:.4f}] {documents[r['index']]}")

{
  "id": "rerank-abc123",
  "model": "bge-reranker-v2-m3",
  "data": [
    {
      "index": 1,
      "document": {"text": "使用 Gunicorn + Nginx 部署 Django 应用的完整指南。"},
      "relevance_score": 0.9234
    },
    {
      "index": 3,
      "document": {"text": "Flask 和 Django 都是 Python Web 框架。"},
      "relevance_score": 0.5678
    }
  ]
}

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://atengin.atomclub.cn/v1"
)

response = client.audio.speech.create(
    model="tts-1-hd",
    voice="nova",
    input="你好，欢迎使用原子引擎 API。",
    response_format="mp3"
)

response.stream_to_file("speech.mp3")

Content-Type: audio/mpeg
Content-Disposition: attachment; filename="speech.mp3"

<binary audio data>

{
  "task_id": "task_video_abc123",
  "status": "queued"
}

import requests

resp = requests.post(
    "https://atengin.atomclub.cn/v1/video/generations",
    headers={"Authorization": "Bearer YOUR_API_KEY"},
    json={
        "prompt": "A golden retriever running through sunflowers",
        "duration": 4
    }
)
task = resp.json()
print(f"任务 ID: {task['task_id']}")

{
  "task_id": "task_video_abc123",
  "status": "processing",
  "created_at": "2024-01-01T00:00:00Z"
}

{
  "task_id": "task_video_abc123",
  "status": "completed",
  "video_url": "https://cdn.atengin.atomclub.cn/video/abc123.mp4"
}

{"task_id": "task_video_abc123", "status": "completed", "video_url": "https://cdn.example.com/video/abc123.mp4"}

{
  "task_id": "task_jimeng_abc123",
  "status": "processing"
}