ChatGptAPI中文文档_chatgpt api文档

准备调用ChatGPT接口，过了一遍官方接口文档，由于没有学过AI相关知识，有些参数和术语还是不太了解，有些单词使用很生僻的意思，翻译的很生硬，先大致翻译一遍，后面再看下手册理解下，回过头来补充下这个API文档，帮助理解。感觉prompt(提示)、Embeddings(嵌入)、Fine-tunes(微调)有点牛逼。

介绍

要安装官方 Python 绑定，请运行以下命令：

pip install openai
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要安装官方 Node.js 库，请在 Node.js 项目目录中运行以下命令：

npm install openai
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认证

OpenAI API 使用 API 密钥进行身份验证。访问您的API 密钥页面以检索您将在请求中使用的 API 密钥。

**请记住，您的 API 密钥是秘密的！**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。生产请求必须通过您自己的后端服务器进行路由，您的 API 密钥可以从环境变量或密钥管理服务中安全加载。

所有 API 请求都应在 HTTP 标头中包含您的 API 密钥，Authorization如下所示：

Authorization: Bearer OPENAI_API_KEY
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请求组织

对于属于多个组织的用户，您可以传递一个标头来指定哪个组织用于 API 请求。来自这些 API 请求的使用将计入指定组织的订阅配额。

curl命令示例：

curl https://api.openai.com/v1/models \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -H "OpenAI-Organization: org-oiD85Cuq7BToDgSamwH7synm"
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Python 包的示例openai：

import os
import openai
openai.organization = "org-oiD85Cuq7BToDgSamwH7synm"
openai.api_key = os.getenv("OPENAI_API_KEY")
openai.Model.list()
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Node.js 包的示例openai：

import { Configuration, OpenAIApi } from "openai";
const configuration = new Configuration({
    organization: "org-oiD85Cuq7BToDgSamwH7synm",
    apiKey: process.env.OPENAI_API_KEY,
});
const openai = new OpenAIApi(configuration);
const response = await openai.listEngines();
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组织 ID 可以在您的组织设置页面上找到。

发出请求

您可以将下面的命令粘贴到您的终端中以运行您的第一个 API 请求。确保替换$OPENAI_API_KEY为您的秘密 API 密钥。

curl https://api.openai.com/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -d '{
     "model": "gpt-3.5-turbo",
     "messages": [{"role": "user", "content": "Say this is a test!"}],
     "temperature": 0.7
   }'
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此请求查询模型以完成以提示“ Say this is a testgpt-3.5-turbo ”开头的文本。您应该会收到类似于以下内容的响应：

{
   "id":"chatcmpl-abc123",
   "object":"chat.completion",
   "created":1677858242,
   "model":"gpt-3.5-turbo-0301",
   "usage":{
      "prompt_tokens":13,
      "completion_tokens":7,
      "total_tokens":20
   },
   "choices":[
      {
         "message":{
            "role":"assistant",
            "content":"\n\nThis is a test!"
         },
         "finish_reason":"stop",
         "index":0
      }
   ]
}

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现在你已经生成了你的第一个聊天完成。我们可以看到finish_reasonisstop这意味着 API 返回了模型生成的完整完成。在上面的请求中，我们只生成了一条消息，但是您可以设置参数n来生成多条消息选择。在这个例子中，gpt-3.5-turbo更多的是用于传统的文本完成任务。该模型还针对聊天应用程序进行了优化。

模型

列出并描述 API 中可用的各种模型。您可以参考模型文档以了解可用的模型以及它们之间的区别。

列出型号

GET https://api.openai.com/v1/models

列出当前可用的模型，并提供有关每个模型的基本信息，例如所有者和可用性。

# 请求示例
curl https://api.openai.com/v1/models \
  -H "Authorization: Bearer $OPENAI_API_KEY"
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//响应
{
  "data": [
    {
      "id": "model-id-0",
      "object": "model",
      "owned_by": "organization-owner",
      "permission": [...]
    },
    {
      "id": "model-id-1",
      "object": "model",
      "owned_by": "organization-owner",
      "permission": [...]
    },
    {
      "id": "model-id-2",
      "object": "model",
      "owned_by": "openai",
      "permission": [...]
    },
  ],
  "object": "list"
}
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检索模型

检索模型实例，提供有关模型的基本信息，例如所有者和权限。

GET https://api.openai.com/v1/models/{model}

路径参数

完成(Completions)

给定一个提示，该模型将返回一个或多个预测的完成，并且还可以返回每个位置的替代标记的概率。

创建完成(Create completion)

为提供的提示和参数创建完成

POST https://api.openai.com/v1/completions

请求体

示例请求

curl https://api.openai.com/v1/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -d '{
    "model": "text-davinci-003",
    "prompt": "Say this is a test",
    "max_tokens": 7,
    "temperature": 0
  }'
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参数

{
  "model": "text-davinci-003",
  "prompt": "Say this is a test",
  "max_tokens": 7,
  "temperature": 0,
  "top_p": 1,
  "n": 1,
  "stream": false,
  "logprobs": null,
  "stop": "\n"
}
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响应

{
  "id": "cmpl-uqkvlQyYK7bGYrRHQ0eXlWi7",
  "object": "text_completion",
  "created": 1589478378,
  "model": "text-davinci-003",
  "choices": [
    {
      "text": "\n\nThis is indeed a test",
      "index": 0,
      "logprobs": null,
      "finish_reason": "length"
    }
  ],
  "usage": {
    "prompt_tokens": 5,
    "completion_tokens": 7,
    "total_tokens": 12
  }
}
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聊天

给定聊天对话，模型将返回聊天完成响应。

创建聊天完成

为聊天消息创建完成

POST https://api.openai.com/v1/chat/completions

请求体

示例请求

curl https://api.openai.com/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -d '{
    "model": "gpt-3.5-turbo",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'
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参数

{
  "model": "gpt-3.5-turbo",
  "messages": [{"role": "user", "content": "Hello!"}]
}
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响应

{
  "id": "chatcmpl-123",
  "object": "chat.completion",
  "created": 1677652288,
  "choices": [{
    "index": 0,
    "message": {
      "role": "assistant",
      "content": "\n\nHello there, how may I assist you today?",
    },
    "finish_reason": "stop"
  }],
  "usage": {
    "prompt_tokens": 9,
    "completion_tokens": 12,
    "total_tokens": 21
  }
}
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编辑

给定提示和指令，模型将返回提示的编辑版本。

创建编辑

为提供的输入、指令和参数创建新的编辑。

POST https://api.openai.com/v1/edits

请求体

示例请求

curl https://api.openai.com/v1/edits \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -d '{
    "model": "text-davinci-edit-001",
    "input": "What day of the wek is it?",
    "instruction": "Fix the spelling mistakes"
  }'
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参数

{
  "model": "text-davinci-edit-001",
  "input": "What day of the wek is it?",
  "instruction": "Fix the spelling mistakes",
}
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响应

{
  "object": "edit",
  "created": 1589478378,
  "choices": [
    {
      "text": "What day of the week is it?",
      "index": 0,
    }
  ],
  "usage": {
    "prompt_tokens": 25,
    "completion_tokens": 32,
    "total_tokens": 57
  }
}
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图片

给定提示和/或输入图像，模型将生成新图像。

相关指南：图像生成

创建图像

根据提示创建图像。

POST https://api.openai.com/v1/images/generations

请求体

示例请求

curl https://api.openai.com/v1/images/generations \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -d '{
    "prompt": "A cute baby sea otter",
    "n": 2,
    "size": "1024x1024"
  }'
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参数

{
  "prompt": "A cute baby sea otter",
  "n": 2,
  "size": "1024x1024"
}
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响应

{
  "created": 1589478378,
  "data": [
    {
      "url": "https://..."
    },
    {
      "url": "https://..."
    }
  ]
}
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创建图像编辑

在给定原始图像和提示的情况下创建编辑或扩展图像。

POST https://api.openai.com/v1/images/edits

请求体

示例请求

curl https://api.openai.com/v1/images/edits \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -F image="@otter.png" \
  -F mask="@mask.png" \
  -F prompt="A cute baby sea otter wearing a beret" \
  -F n=2 \
  -F size="1024x1024"
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响应

{
  "created": 1589478378,
  "data": [
    {
      "url": "https://..."
    },
    {
      "url": "https://..."
    }
  ]
}
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创建图像变体

创建给定图像的变体。

POST https://api.openai.com/v1/images/variations

请求体

请求示例

curl https://api.openai.com/v1/images/variations \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -F image="@otter.png" \
  -F n=2 \
  -F size="1024x1024"
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响应

{
  "created": 1589478378,
  "data": [
    {
      "url": "https://..."
    },
    {
      "url": "https://..."
    }
  ]
}
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嵌入

获取给定输入的矢量表示，机器学习模型和算法可以轻松使用该表示。

相关指南：嵌入

创建嵌入

创建表示输入文本的嵌入向量。

POST https://api.openai.com/v1/embeddings

请求体

请求示例

curl https://api.openai.com/v1/embeddings \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "input": "The food was delicious and the waiter...",
    "model": "text-embedding-ada-002"
  }'
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参数

{
  "model": "text-embedding-ada-002",
  "input": "The food was delicious and the waiter..."
}
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响应

{
  "object": "list",
  "data": [
    {
      "object": "embedding",
      "embedding": [
        0.0023064255,
        -0.009327292,
        .... (1536 floats total for ada-002)
        -0.0028842222,
      ],
      "index": 0
    }
  ],
  "model": "text-embedding-ada-002",
  "usage": {
    "prompt_tokens": 8,
    "total_tokens": 8
  }
}
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音频

了解如何将音频转换为文本。

相关指南：语音转文本

创建转录

将音频转录为输入语言。

POST https://api.openai.com/v1/audio/transcriptions

请求体

请求示例

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

{
  "file": "audio.mp3",
  "model": "whisper-1"
}
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响应

{
  "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."
}
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创建翻译

将音频翻译成英文。

POST https://api.openai.com/v1/audio/translations

请求体

请求示例

curl https://api.openai.com/v1/audio/translations \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -H "Content-Type: multipart/form-data" \
  -F file="@/path/to/file/german.m4a" \
  -F model="whisper-1"
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参数

{
  "file": "german.m4a",
  "model": "whisper-1"
}
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响应

{
  "text": "Hello, my name is Wolfgang and I come from Germany. Where are you heading today?"
}
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文件

文件用于上传可与微调等功能一起使用的文档。

列出文件

返回属于用户组织的文件列表。

GET https://api.openai.com/v1/files

请求示例

curl https://api.openai.com/v1/files \
  -H "Authorization: Bearer $OPENAI_API_KEY"
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响应

{
  "data": [
    {
      "id": "file-ccdDZrC3iZVNiQVeEA6Z66wf",
      "object": "file",
      "bytes": 175,
      "created_at": 1613677385,
      "filename": "train.jsonl",
      "purpose": "search"
    },
    {
      "id": "file-XjGxS3KTG0uNmNOK362iJua3",
      "object": "file",
      "bytes": 140,
      "created_at": 1613779121,
      "filename": "puppy.jsonl",
      "purpose": "search"
    }
  ],
  "object": "list"
}
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上传文件

上传包含要跨各种端点/功能使用的文档的文件。目前，一个组织上传的所有文件的大小最大可达 1 GB。如果您需要增加存储限制，请联系我们。

POST https://api.openai.com/v1/files

请求体

请求示例

curl https://api.openai.com/v1/files \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -F purpose="fine-tune" \
  -F file="@mydata.jsonl"
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响应

{
  "id": "file-XjGxS3KTG0uNmNOK362iJua3",
  "object": "file",
  "bytes": 140,
  "created_at": 1613779121,
  "filename": "mydata.jsonl",
  "purpose": "fine-tune"
}
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删除文件

删除文件。

DELETE https://api.openai.com/v1/files/{file_id}

路径参数

请求示例

curl https://api.openai.com/v1/files/file-XjGxS3KTG0uNmNOK362iJua3 \
  -X DELETE \
  -H "Authorization: Bearer $OPENAI_API_KEY"
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响应

{
  "id": "file-XjGxS3KTG0uNmNOK362iJua3",
  "object": "file",
  "deleted": true
}
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检索文件

返回有关特定文件的信息。

GET https://api.openai.com/v1/files/{file_id}

路径参数

请求示例

curl https://api.openai.com/v1/files/file-XjGxS3KTG0uNmNOK362iJua3 \
  -H "Authorization: Bearer $OPENAI_API_KEY"
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响应

{
  "id": "file-XjGxS3KTG0uNmNOK362iJua3",
  "object": "file",
  "bytes": 140,
  "created_at": 1613779657,
  "filename": "mydata.jsonl",
  "purpose": "fine-tune"
}
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检索文件内容

返回指定文件的内容

GET https://api.openai.com/v1/files/{file_id}/content

路径参数

请求示例

curl https://api.openai.com/v1/files/file-XjGxS3KTG0uNmNOK362iJua3/content \
  -H "Authorization: Bearer $OPENAI_API_KEY" > file.jsonl
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微调

管理微调作业以根据您的特定训练数据定制模型。

相关指南：微调模型

创建微调

创建一个从给定数据集微调指定模型的作业。

响应包括排队作业的详细信息，包括作业状态和完成后微调模型的名称。

了解有关微调的更多信息

POST https://api.openai.com/v1/fine-tunes

请求体

请求示例

curl https://api.openai.com/v1/fine-tunes \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -d '{
    "training_file": "file-XGinujblHPwGLSztz8cPS8XY"
  }'
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响应

{
  "id": "ft-AF1WoRqd3aJAHsqc9NY7iL8F",
  "object": "fine-tune",
  "model": "curie",
  "created_at": 1614807352,
  "events": [
    {
      "object": "fine-tune-event",
      "created_at": 1614807352,
      "level": "info",
      "message": "Job enqueued. Waiting for jobs ahead to complete. Queue number: 0."
    }
  ],
  "fine_tuned_model": null,
  "hyperparams": {
    "batch_size": 4,
    "learning_rate_multiplier": 0.1,
    "n_epochs": 4,
    "prompt_loss_weight": 0.1,
  },
  "organization_id": "org-...",
  "result_files": [],
  "status": "pending",
  "validation_files": [],
  "training_files": [
    {
      "id": "file-XGinujblHPwGLSztz8cPS8XY",
      "object": "file",
      "bytes": 1547276,
      "created_at": 1610062281,
      "filename": "my-data-train.jsonl",
      "purpose": "fine-tune-train"
    }
  ],
  "updated_at": 1614807352,
}
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微调列表

列出您的组织的微调作业

GET https://api.openai.com/v1/fine-tunes

请求示例

curl https://api.openai.com/v1/fine-tunes \
  -H "Authorization: Bearer $OPENAI_API_KEY"
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响应

{
  "object": "list",
  "data": [
    {
      "id": "ft-AF1WoRqd3aJAHsqc9NY7iL8F",
      "object": "fine-tune",
      "model": "curie",
      "created_at": 1614807352,
      "fine_tuned_model": null,
      "hyperparams": { ... },
      "organization_id": "org-...",
      "result_files": [],
      "status": "pending",
      "validation_files": [],
      "training_files": [ { ... } ],
      "updated_at": 1614807352,
    },
    { ... },
    { ... }
  ]
}
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微调检索

获取有关微调作业的信息。

了解有关微调的更多信息

GET https://api.openai.com/v1/fine-tunes/{fine_tune_id}

路径参数

请求示例

curl https://api.openai.com/v1/fine-tunes/ft-AF1WoRqd3aJAHsqc9NY7iL8F \
  -H "Authorization: Bearer $OPENAI_API_KEY"
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响应

{
  "id": "ft-AF1WoRqd3aJAHsqc9NY7iL8F",
  "object": "fine-tune",
  "model": "curie",
  "created_at": 1614807352,
  "events": [
    {
      "object": "fine-tune-event",
      "created_at": 1614807352,
      "level": "info",
      "message": "Job enqueued. Waiting for jobs ahead to complete. Queue number: 0."
    },
    {
      "object": "fine-tune-event",
      "created_at": 1614807356,
      "level": "info",
      "message": "Job started."
    },
    {
      "object": "fine-tune-event",
      "created_at": 1614807861,
      "level": "info",
      "message": "Uploaded snapshot: curie:ft-acmeco-2021-03-03-21-44-20."
    },
    {
      "object": "fine-tune-event",
      "created_at": 1614807864,
      "level": "info",
      "message": "Uploaded result files: file-QQm6ZpqdNwAaVC3aSz5sWwLT."
    },
    {
      "object": "fine-tune-event",
      "created_at": 1614807864,
      "level": "info",
      "message": "Job succeeded."
    }
  ],
  "fine_tuned_model": "curie:ft-acmeco-2021-03-03-21-44-20",
  "hyperparams": {
    "batch_size": 4,
    "learning_rate_multiplier": 0.1,
    "n_epochs": 4,
    "prompt_loss_weight": 0.1,
  },
  "organization_id": "org-...",
  "result_files": [
    {
      "id": "file-QQm6ZpqdNwAaVC3aSz5sWwLT",
      "object": "file",
      "bytes": 81509,
      "created_at": 1614807863,
      "filename": "compiled_results.csv",
      "purpose": "fine-tune-results"
    }
  ],
  "status": "succeeded",
  "validation_files": [],
  "training_files": [
    {
      "id": "file-XGinujblHPwGLSztz8cPS8XY",
      "object": "file",
      "bytes": 1547276,
      "created_at": 1610062281,
      "filename": "my-data-train.jsonl",
      "purpose": "fine-tune-train"
    }
  ],
  "updated_at": 1614807865,
}
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取消微调

立即取消微调作业

POST https://api.openai.com/v1/fine-tunes/{fine_tune_id}/cancel

路径参数

请求示例

curl https://api.openai.com/v1/fine-tunes/ft-AF1WoRqd3aJAHsqc9NY7iL8F/cancel \
  -H "Authorization: Bearer $OPENAI_API_KEY"
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响应

{
  "id": "ft-xhrpBbvVUzYGo8oUO1FY4nI7",
  "object": "fine-tune",
  "model": "curie",
  "created_at": 1614807770,
  "events": [ { ... } ],
  "fine_tuned_model": null,
  "hyperparams": { ... },
  "organization_id": "org-...",
  "result_files": [],
  "status": "cancelled",
  "validation_files": [],
  "training_files": [
    {
      "id": "file-XGinujblHPwGLSztz8cPS8XY",
      "object": "file",
      "bytes": 1547276,
      "created_at": 1610062281,
      "filename": "my-data-train.jsonl",
      "purpose": "fine-tune-train"
    }
  ],
  "updated_at": 1614807789,
}
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列出微调事件

获取微调作业细粒度的状态更新

GET https://api.openai.com/v1/fine-tunes/{fine_tune_id}/events

路径参数

查询参数

请求示例

curl https://api.openai.com/v1/fine-tunes/ft-AF1WoRqd3aJAHsqc9NY7iL8F/events \
  -H "Authorization: Bearer $OPENAI_API_KEY"
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响应

{
  "object": "list",
  "data": [
    {
      "object": "fine-tune-event",
      "created_at": 1614807352,
      "level": "info",
      "message": "Job enqueued. Waiting for jobs ahead to complete. Queue number: 0."
    },
    {
      "object": "fine-tune-event",
      "created_at": 1614807356,
      "level": "info",
      "message": "Job started."
    },
    {
      "object": "fine-tune-event",
      "created_at": 1614807861,
      "level": "info",
      "message": "Uploaded snapshot: curie:ft-acmeco-2021-03-03-21-44-20."
    },
    {
      "object": "fine-tune-event",
      "created_at": 1614807864,
      "level": "info",
      "message": "Uploaded result files: file-QQm6ZpqdNwAaVC3aSz5sWwLT."
    },
    {
      "object": "fine-tune-event",
      "created_at": 1614807864,
      "level": "info",
      "message": "Job succeeded."
    }
  ]
}
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删除微调模型

删除微调模型。您必须在您的组织中拥有所有者角色。

DELETE https://api.openai.com/v1/models/{model}

路径参数

请求示例

curl https://api.openai.com/v1/models/curie:ft-acmeco-2021-03-03-21-44-20 \
  -X DELETE \
  -H "Authorization: Bearer $OPENAI_API_KEY"
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响应

{
  "id": "curie:ft-acmeco-2021-03-03-21-44-20",
  "object": "model",
  "deleted": true
}
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适度

给定输入文本，如果模型将其分类为违反 OpenAI 的内容策略，则输出。

相关指南：适度

创建适度

分类文本是否违反 OpenAI 的内容政策

POST https://api.openai.com/v1/moderations

请求体

请求体

示例请求

curl https://api.openai.com/v1/moderations \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -d '{
    "input": "I want to kill them."
  }'
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请求

{
  "input": "I want to kill them."
}
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响应

{
  "id": "modr-5MWoLO",
  "model": "text-moderation-001",
  "results": [
    {
      "categories": {
        "hate": false,
        "hate/threatening": true,
        "self-harm": false,
        "sexual": false,
        "sexual/minors": false,
        "violence": true,
        "violence/graphic": false
      },
      "category_scores": {
        "hate": 0.22714105248451233,
        "hate/threatening": 0.4132447838783264,
        "self-harm": 0.005232391878962517,
        "sexual": 0.01407341007143259,
        "sexual/minors": 0.0038522258400917053,
        "violence": 0.9223177433013916,
        "violence/graphic": 0.036865197122097015
      },
      "flagged": true
    }
  ]
}
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categories中各个字段的含义如下

参数详情

标记

GPT 系列模型使用标记处理文本，标记是文本中常见的字符序列。这些模型了解这些标记之间的统计关系，并且擅长生成标记序列中的下一个标记。

下面是官网提供的分词工具，我输入了一串英文，这里面就有10个标记。

一个有用的经验法则是，对于普通英文文本，一个标记通常对应于 ~4 个字符的文本。这相当于大约 ¾ 个单词（因此 100 个标记 ~= 75 个单词）。

频率和存在惩罚

Completions API中发现的频率和存在惩罚可用于降低对令牌重复序列进行采样的可能性。他们通过添加贡献直接修改 logits（非标准化对数概率）来工作。

mu[j] -> mu[j] - c[j] * alpha_frequency - float(c[j] > 0) * alpha_presence
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在该情况下：

• mu[j]是第 j 个标记的对数
• c[j]是在当前位置之前对该令牌进行采样的频率
• 如果c[j] > 0， float(c[j] > 0)为1，否则为 0
• alpha_frequency是频率惩罚系数
• alpha_presence是存在惩罚系数

正如我们所见，存在惩罚是一种一次性的加性贡献，适用于所有至少被采样过一次的标记，而频率惩罚是与特定标记被采样的频率成正比的贡献。

如果目标只是稍微减少重复样本，则惩罚系数的合理值约为 0.1 到 1。如果目标是强烈抑制重复，那么可以将系数增加到 2，但这会显着降低样本质量。负值可用于增加重复的可能性。

最终用户ID

在您的请求中发送最终用户 ID 可以成为帮助 OpenAI 监控和检测滥用的有用工具。如果我们在您的应用程序中检测到任何违反政策的情况，这允许 OpenAI 为您的团队提供更多可操作的反馈。

ID 应该是唯一标识每个用户的字符串。我们建议散列他们的用户名或电子邮件地址，以避免向我们发送任何识别信息。如果您向未登录的用户提供产品预览，您可以改为发送会话 ID。

您可以通过参数在 API 请求中包含最终用户 ID，user如下所示：

response = openai.Completion.create(
  model="text-davinci-003",
  prompt="This is a test",
  max_tokens=5,
  user="user123456"
)
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各种语言OpenAi库

手册原文链接 https://platform.openai.com/docs/libraries

Python库

我们提供了一个 Python 库，您可以按如下方式安装它：

pip install openai
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安装后，您可以使用绑定和您的密钥运行以下命令：

import os
import openai

# Load your API key from an environment variable or secret management service
openai.api_key = os.getenv("OPENAI_API_KEY")

response = openai.Completion.create(model="text-davinci-003", prompt="Say this is a test", temperature=0, max_tokens=7)
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绑定还将安装一个命令行实用程序，您可以按如下方式使用：

$ openai api completions.create -m text-davinci-003 -p "Say this is a test" -t 0 -M 7 --stream
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Node.js 库

我们还有一个 Node.js 库，您可以通过在 Node.js 项目目录中运行以下命令来安装它：

$ npm install openai
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安装后，您可以使用该库和您的密钥运行以下命令：

const { Configuration, OpenAIApi } = require("openai");
const configuration = new Configuration({
  apiKey: process.env.OPENAI_API_KEY,
});
const openai = new OpenAIApi(configuration);
const response = await openai.createCompletion({
  model: "text-davinci-003",
  prompt: "Say this is a test",
  temperature: 0,
  max_tokens: 7,
});
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其他语言社区库

下面的库由更广泛的开发人员社区构建和维护。

请注意，OpenAI 不会验证这些项目的正确性或安全性。

C# / .NET

• Betalgo.OpenAI.GPT3 by Betalgo
• OpenAI-API-dotnet by OkGoDoIt

Crystal

• openai-crystal by sferik

Go

• go-gpt3 by sashabaranov

Java

• openai-java by Theo Kanning

Kotlin

• openai-kotlin by Mouaad Aallam

Node.js

• openai-api by Njerschow
• openai-api-node by erlapso
• gpt-x by ceifa
• gpt3 by poteat
• gpts by thencc
• @dalenguyen/openai by dalenguyen
• tectalic/openai by tectalic

PHP

• orhanerday/open-ai by orhanerday
• tectalic/openai by tectalic

Python

• chronology by OthersideAI

R

• rgpt3 by ben-aaron188

Ruby

• openai by nileshtrivedi
• ruby-openai by alexrudall

Scala

• openai-scala-client by cequence-io

Swift

• OpenAIKit by dylanshine

Unity

• OpenAi-Api-Unity by hexthedev

Unreal Engine

• OpenAI-Api-Unreal by KellanM