开发者（API）使用说明 ​

介绍 ​

本文档是对文本大模型、语音模型、图片生成等海量 API 的调用进行说明，您可以通过任何语言的 HTTP 请求、Python 或社区维护的库与 API 进行交互。本 API 与 OPENAI 官网完全兼容。在正式使用前需要通过客服购买API 令牌。

安装 ​

如果需要使用 Python 库的方式调用，请运行以下命令：

pip install openai

pip install openai

令牌验证 ​

本 API 同 OpenAPI 一样需要使用 API 令牌 进行身份验证。访问您的令牌管理页面或者从客服处获取。

请记住，您的 API 令牌的私密性！ 不要与他人共享或在任何客户端代码（浏览器、应用程序）中公开它。生产环境请求必须通过您自己的后端服务器进行路由，您的 API 令牌可以从环境变量或密钥管理服务安全地加载。 在你的bash/zsh环境中

export API_KEY="sk-xxxx" # 替换成您的API令牌

export API_KEY="sk-xxxx" # 替换成您的API令牌

所有 API 请求都应在 AuthorizationHTTP 标头中包含您的 API 令牌，如下 http 请求所示：

curl https://api.rcouyi.com/v1/models \
  -H "Authorization: Bearer $API_KEY"

curl https://api.rcouyi.com/v1/models \
  -H "Authorization: Bearer $API_KEY"

对话 ​

发出请求 ​

您可以将以下命令粘贴到终端中以运行您的第一个 API 请求。确保替换 $API_KEY 为您的私人 API 令牌。

• http:

  bash

  curl https://api.rcouyi.com/v1/chat/completions \
     -H "Content-Type: application/json" \
     -H "Authorization: Bearer $API_KEY" \
     -d '{
      "model": "gpt-3.5-turbo",
      "messages": [{"role": "user", "content": "Say this is a test!"}],
      "temperature": 0.7
     }'

  curl https://api.rcouyi.com/v1/chat/completions \
     -H "Content-Type: application/json" \
     -H "Authorization: Bearer $API_KEY" \
     -d '{
      "model": "gpt-3.5-turbo",
      "messages": [{"role": "user", "content": "Say this is a test!"}],
      "temperature": 0.7
     }'

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• python:

  • 方式 1：使用 openai 库更改 base url

    python

    # 如下使用方式注意openai的版本得1.0以下，比如0.28， pip install openai==0.28
    import openai
    openai.base_url = "https://api.rcouyi.com/"
    openai.api_key = $API_KEY # 替换成令牌管理页面中的秘钥
    resp = openai.ChatCompletion.create(
        model="gpt-3.5-turbo",
        messages=[
            {"role": "system", "content": "你是个有帮助的助手"},
            {"role": "user", "content": "你好么"},
        ]
    )
    print(resp[0]["message"]["content"]

    # 如下使用方式注意openai的版本得1.0以下，比如0.28， pip install openai==0.28
    import openai
    openai.base_url = "https://api.rcouyi.com/"
    openai.api_key = $API_KEY # 替换成令牌管理页面中的秘钥
    resp = openai.ChatCompletion.create(
        model="gpt-3.5-turbo",
        messages=[
            {"role": "system", "content": "你是个有帮助的助手"},
            {"role": "user", "content": "你好么"},
        ]
    )
    print(resp[0]["message"]["content"]

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  • 方式 2：使用 request 请求

    python

    import requests
    import json
    # 你的API密钥，确保它已经设置为环境变量
    API_KEY = os.getenv('API_KEY')
    # 请求URL
    url = "https://api.rcouyi.com/v1/chat/completions"
    # 请求头
    headers = {
          "Content-Type": "application/json",
          "Authorization": f"Bearer {API_KEY}"
      }
    
    # 请求数据
    data = {
        "model": "gpt-3.5-turbo",
        "messages": [{"role": "user", "content": "Say this is a test!"}],
        "temperature": 0.7
    }
    # 发送POST请求
    response = requests.post(url, headers=headers, json=data)
    # 打印响应内容
    print(response.json())

    import requests
    import json
    # 你的API密钥，确保它已经设置为环境变量
    API_KEY = os.getenv('API_KEY')
    # 请求URL
    url = "https://api.rcouyi.com/v1/chat/completions"
    # 请求头
    headers = {
          "Content-Type": "application/json",
          "Authorization": f"Bearer {API_KEY}"
      }
    
    # 请求数据
    data = {
        "model": "gpt-3.5-turbo",
        "messages": [{"role": "user", "content": "Say this is a test!"}],
        "temperature": 0.7
    }
    # 发送POST请求
    response = requests.post(url, headers=headers, json=data)
    # 打印响应内容
    print(response.json())

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  • 方式 3：流式（stream 方式） 调用

    python

    import os
    from openai import OpenAI
    client = OpenAI(
        api_key=os.getenv('API_KEY'),
        base_url="https://api.rcouyi.com/v1/",
    )
    
    response = client.chat.completions.create(
        model="gpt-3.5-turbo",
        messages=[
            {
                "role": "system",
                "content": "你是chatgpt，由 openAI 提供的人工智能助手，你更擅长中文和英文的对话。你会为用户提供安全，有帮助，准确的回答。同  时，你会拒绝一些涉及恐怖主义，种族歧视，黄色暴力等问题的回答。",
            },
            {
                "role": "user",
                "content": "你好，我叫李雷，1+1等于多少？"
            },
        ],
        temperature=0.3,
        stream=True,
    )
    
    collected_messages = []
    for idx, chunk in enumerate(response):
        # print("Chunk received, value: ", chunk)
        chunk_message = chunk.choices[0].delta
        if not chunk_message.content:
            continue
        collected_messages.append(chunk_message)  # save the message
        print(f"#{idx}: {''.join([m.content for m in collected_messages])}")
    print(f"Full conversation received: {''.join([m.content for m in collected_messages])}")
    ```

    import os
    from openai import OpenAI
    client = OpenAI(
        api_key=os.getenv('API_KEY'),
        base_url="https://api.rcouyi.com/v1/",
    )
    
    response = client.chat.completions.create(
        model="gpt-3.5-turbo",
        messages=[
            {
                "role": "system",
                "content": "你是chatgpt，由 openAI 提供的人工智能助手，你更擅长中文和英文的对话。你会为用户提供安全，有帮助，准确的回答。同  时，你会拒绝一些涉及恐怖主义，种族歧视，黄色暴力等问题的回答。",
            },
            {
                "role": "user",
                "content": "你好，我叫李雷，1+1等于多少？"
            },
        ],
        temperature=0.3,
        stream=True,
    )
    
    collected_messages = []
    for idx, chunk in enumerate(response):
        # print("Chunk received, value: ", chunk)
        chunk_message = chunk.choices[0].delta
        if not chunk_message.content:
            continue
        collected_messages.append(chunk_message)  # save the message
        print(f"#{idx}: {''.join([m.content for m in collected_messages])}")
    print(f"Full conversation received: {''.join([m.content for m in collected_messages])}")
    ```

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  上述两种非流式方式会得到： 此请求查询 gpt-3.5-turbo 模型以完成以“说这是测试”提示开头的文本。您应该收到类似于以下内容的 json 响应:

  json

    {
      "id": "chatcmpl-8gqkDUt3Gs3711qhHS8xgs6YR1Wyt",
      "object": "chat.completion",
      "created": 1705223217,
      "model": "gpt-3.5-turbo-0613",
      "choices": [
        {
          "index": 0,
          "message": {
            "role": "assistant",
            "content": "This is a test!"
          },
          "logprobs": null,
          "finish_reason": "stop"
        }
      ],
      "usage": {
        "prompt_tokens": 13,
        "completion_tokens": 5,
        "total_tokens": 18
      },
      "system_fingerprint": null
    }

    {
      "id": "chatcmpl-8gqkDUt3Gs3711qhHS8xgs6YR1Wyt",
      "object": "chat.completion",
      "created": 1705223217,
      "model": "gpt-3.5-turbo-0613",
      "choices": [
        {
          "index": 0,
          "message": {
            "role": "assistant",
            "content": "This is a test!"
          },
          "logprobs": null,
          "finish_reason": "stop"
        }
      ],
      "usage": {
        "prompt_tokens": 13,
        "completion_tokens": 5,
        "total_tokens": 18
      },
      "system_fingerprint": null
    }

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  对 流式 stream 格式的，返回类似如下：

  json

  data: {"id":"cmpl-1305b94c570f447fbde3180560736287","object":"chat.completion.chunk","created":1698999575,"model":"gpt3.5","choices":[{"index":0,"delta":{"role":"assistant"},"finish_reason":null}]}
  
  data: {"id":"cmpl-1305b94c570f447fbde3180560736287","object":"chat.completion.chunk","created":1698999575,"model":"gpt3.5","choices":[{"index":0,"delta":{"content":"你好"},"finish_reason":null}]}
  
  ...
  
  data: {"id":"cmpl-1305b94c570f447fbde3180560736287","object":"chat.completion.chunk","created":1698999575,"model":"gpt3.5","choices":[{"index":0,"delta":{"content":"。"},"finish_reason":null}]}
  
  data: {"id":"cmpl-1305b94c570f447fbde3180560736287","object":"chat.completion.chunk","created":1698999575,"model":"gpt3.5","choices":[{"index":0,"delta":{},"finish_reason":"stop","usage":{"prompt_tokens":19,"completion_tokens":13,"total_tokens":32}}]}
  
  data: [DONE]

  data: {"id":"cmpl-1305b94c570f447fbde3180560736287","object":"chat.completion.chunk","created":1698999575,"model":"gpt3.5","choices":[{"index":0,"delta":{"role":"assistant"},"finish_reason":null}]}
  
  data: {"id":"cmpl-1305b94c570f447fbde3180560736287","object":"chat.completion.chunk","created":1698999575,"model":"gpt3.5","choices":[{"index":0,"delta":{"content":"你好"},"finish_reason":null}]}
  
  ...
  
  data: {"id":"cmpl-1305b94c570f447fbde3180560736287","object":"chat.completion.chunk","created":1698999575,"model":"gpt3.5","choices":[{"index":0,"delta":{"content":"。"},"finish_reason":null}]}
  
  data: {"id":"cmpl-1305b94c570f447fbde3180560736287","object":"chat.completion.chunk","created":1698999575,"model":"gpt3.5","choices":[{"index":0,"delta":{},"finish_reason":"stop","usage":{"prompt_tokens":19,"completion_tokens":13,"total_tokens":32}}]}
  
  data: [DONE]

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参数说明 ​

• temperature： 温度为 0，多样性越低，确信度越高。温度越高，多样性越高，真实性越低
• 其他参数均可参考 openAI 官网定义

支持模型列表 ​

• gpt-3.5-turbo
• gpt-4
• gpt-4-1106-preview
• gpt-4-all
• gpt-4-vision-preview
• bing
• claude-2.1
• gemini-pro
• chatglm_pro
• SparkDesk
• qwen-plus
• ERNIE-Bot-4

只需要在请求时把模型名称换成上述想要的名称即可，比如用 claude（请求前请设置好API_KEY，比如export API_KEY="sk-xxx"）

curl https://api.rcouyi.com/v1/chat/completions \
    -H "Content-Type: application/json" \
    -H "Authorization: Bearer $API_KEY" \
    -d '{
        "model": "claude-2.1",
        "messages": [{"role": "user", "content": "Say this is a test!"}],
        "temperature": 0.7
      }'

curl https://api.rcouyi.com/v1/chat/completions \
    -H "Content-Type: application/json" \
    -H "Authorization: Bearer $API_KEY" \
    -d '{
        "model": "claude-2.1",
        "messages": [{"role": "user", "content": "Say this is a test!"}],
        "temperature": 0.7
      }'

语音 ​

TTS ​

将文本转换为语音。post https://api.openai.com/v1/audio/speech

curl https://api.rcouyi.com/v1/audio/speech \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "tts-1",
    "input": "你好啊",
    "voice": "alloy"
  }' \
  --output speech.mp3

curl https://api.rcouyi.com/v1/audio/speech \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "tts-1",
    "input": "你好啊",
    "voice": "alloy"
  }' \
  --output speech.mp3

参数说明：

• model：必填，下列为支持模型列表：
  • tts-1，tts-1-hd
• input：必填，要语音化的内容
• voice：必填，声音种类
  • alloy, echo, fable, onyx, nova, shimmer
• response_format：选填，返回文件的种类，默认为 mp3，可选种类为：
  • mp3, opus, aac, flac
• speed：选填，语速，默认为 1，值越小，速度越慢
  • 支持 0.25 到 4.0 之间
• 返回为语音文件

语音转文本 ​

将音频转录为输入语言。 post https://api.openai.com/v1/audio/transcriptions

curl https://api.openai.com/v1/audio/transcriptions \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: multipart/form-data" \
  -F file="@/path/to/file/audio.mp3" \
  -F model="whisper-1"

curl https://api.openai.com/v1/audio/transcriptions \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: multipart/form-data" \
  -F file="@/path/to/file/audio.mp3" \
  -F model="whisper-1"

返回

{
  "text": "Imagine the wildest idea that you've ever had, and you're curious about how it might scale to something that's a 100, a 1,000 times bigger. This is a place where you can get to do that."
}

{
  "text": "Imagine the wildest idea that you've ever had, and you're curious about how it might scale to something that's a 100, a 1,000 times bigger. This is a place where you can get to do that."
}

参数说明：

• file：必需的，要转录的音频文件对象（不是文件名），采用以下格式之一：flac、mp3、mp4、mpeg、mpga、m4a、ogg、wav 或 webm。
• model：必需的，要使用的模型的 ID。当前仅 whisper-1 可用。
• language：可选的，输入音频的语言。以 ISO-639-1 格式提供输入语言将提高准确性和延迟。
• prompt：可选的，用于指导模型风格或继续之前的音频片段的可选文本。提示应与音频语言相匹配。
• response_format：可选的，默认为 json，转录输出的格式，采用以下选项之一：json、text、srt、verbose_json 或 vtt。
• temperature：可选的，默认为 0，采样温度，介于 0 和 1 之间。较高的值（如 0.8）将使输出更加随机，而较低的值（如 0.2）将使其更加集中和确定性。如果设置为 0，模型将使用对数概率自动升高温度，直到达到特定阈值。 返回：转录的文本。