OpenAI_New_API_Capacities

这个博客主要是关于如何利用OpenAI 官方新推出的API的功能。 关于最新功能的介绍。对应的项目链接可以参考GitHub链接。

email: 213193509seu@gmail.com

语言框架: python

参考链接: https://platform.openai.com/docs/guides

配置账号

去openai官方网站配置OPENAI_API_KEY。配置完后请把OPENAI_API_KEY添加到环境变量。

安装库

注意，此版本openai已经更新了新的功能，请使用最新版本的openai 库。（推荐在anaconda虚拟环境里面进行安装）

• 配置Python环境

conda create -n openai python=3.11 -y
conda activate openai

• 安装openai库

pip install --upgrade openai

功能

chat_completion

from openai import OpenAI
client = OpenAI()

response = client.chat.completions.create(
  model="gpt-4-1106-preview",
  messages=[
    {"role": "system", "content": "You are a helpful assistant."},
    {"role": "user", "content": "谁获得了2022年英雄联盟S赛世界冠军？"},
  ]
)
print(response)

输出:

ChatCompletion(id='chatcmpl-8PP1sbZKC7D5VSxHsgCOsMPyLFU0Y', choices=[Choice(finish_reason='stop', index=0, message=ChatCompletionMessage(content='2022年英雄联盟世界锦标赛（S赛）的冠军是韩国的DRX战队。他们在决赛中战胜了中国的EDward Gaming（EDG）战队，赢得了冠军头衔。这也是DRX战队第一次夺得世界冠军。', role='assistant', function_call=None, tool_calls=None))], created=1701065104, model='gpt-4-1106-preview', object='chat.completion', system_fingerprint='fp_a24b4d720c', usage=CompletionUsage(completion_tokens=99, prompt_tokens=43, total_tokens=142))

JSON输出（新功能）

目前json格式输出只支持gpt-4-1106-preview和gpt-3.5-turbo-1106这两个模型。

注意：在使用json格式的时候，请确保输入messages中含有json这个单词。

from openai import OpenAI
client = OpenAI()

response = client.chat.completions.create(
  model="gpt-3.5-turbo-1106",
  response_format={"type": "json_object"},
  messages=[
    {"role": "system", "content": "You are a helpful assistant designed to output JSON."},
    {"role": "user", "content": "Now I want you to score the sentence 'I like apples' on a scale of 1 to 10 with "
                                "output format as:"
                                "{'score': score}, for example, {'score': 0.5}"}
  ]
)
print(response.choices[0].message.content)

输出

{
  "score": 8
}

可复现输出

在进行chat-completions的时候，其实其输出是随机的，但是通过设置seed以及相应指纹可以保证输出相同， 并且保证其他参数也相同。在使用benchmark的时候，设置相同的seed也能保证结果的可靠性。

import asyncio
import openai
import pprint
import difflib
from IPython.display import display, HTML


GPT_MODEL = "gpt-3.5-turbo-1106"
client = openai.OpenAI()

async def get_chat_response(system_message: str, user_request: str, seed: int = None):
    try:
        messages = [
            {"role": "system", "content": system_message},
            {"role": "user", "content": user_request},
        ]

        response = client.chat.completions.create(

            model=GPT_MODEL,
            messages=messages,
            seed=seed,
            max_tokens=200,
            temperature=0.7,
        )

        response_content = response.choices[0].message.content
        system_fingerprint = response.system_fingerprint
        prompt_tokens = response.usage.prompt_tokens
        completion_tokens = (
            response.usage.total_tokens - response.usage.prompt_tokens
        )

        table = f"""
        <table>
        <tr><th>Response</th><td>{response_content}</td></tr>
        <tr><th>System Fingerprint</th><td>{system_fingerprint}</td></tr>
        <tr><th>Number of prompt tokens</th><td>{prompt_tokens}</td></tr>
        <tr><th>Number of completion tokens</th><td>{completion_tokens}</td></tr>
        </table>
        """
        display(HTML(table))

        return response_content
    except Exception as e:
        print(f"An error occurred: {e}")
        return None


# This function compares two responses and displays the differences in a table.
# Deletions are highlighted in red and additions are highlighted in green.
# If no differences are found, it prints "No differences found."


def compare_responses(previous_response: str, response: str):
    d = difflib.Differ()
    diff = d.compare(previous_response.splitlines(), response.splitlines())

    diff_table = "<table>"
    diff_exists = False

    for line in diff:
        if line.startswith("- "):
            diff_table += f"<tr style='color: red;'><td>{line}</td></tr>"
            diff_exists = True
        elif line.startswith("+ "):
            diff_table += f"<tr style='color: green;'><td>{line}</td></tr>"
            diff_exists = True
        else:
            diff_table += f"<tr><td>{line}</td></tr>"

    diff_table += "</table>"

    if diff_exists:
        display(HTML(diff_table))
    else:
        print("No differences found.")
        
topic = "a journey to Mars"
system_message = "You are a helpful assistant that generates short stories."
user_request = f"Generate a short story about {topic}."

previous_response = await get_chat_response(
    system_message=system_message, user_request=user_request
)

response = await get_chat_response(
    system_message=system_message, user_request=user_request
)

# The function compare_responses is then called with the two responses as arguments.
# This function will compare the two responses and display the differences in a table.
# If no differences are found, it will print "No differences found."
compare_responses(previous_response, response)
SEED = 123
response = await get_chat_response(
    system_message=system_message, seed=SEED, user_request=user_request
)
previous_response = response
response = await get_chat_response(
    system_message=system_message, seed=SEED, user_request=user_request
)

compare_responses(previous_response, response)

图片生成

这部分比较简单，给定输入的prompt然后返回的是生成的图片的url。

from openai import OpenAI
client = OpenAI()

response = client.images.generate(
  model="dall-e-3",
  prompt="一只猫",
  size="1024x1024",
  quality="standard",
  n=1,
)

image_url = response.data[0].url
print(image_url)

多模态图片能力

传入一个图片的url, base64, 或者图片路径 通过gpt-4-vision-preview 模型即可调用。

比如说对于这样一张图:

from openai import OpenAI

client = OpenAI()

response = client.chat.completions.create(
  model="gpt-4-vision-preview",
  messages=[
    {
      "role": "user",
      "content": [
        {"type": "text", "text": "这个图片里面有什么内容？"},
        {
          "type": "image_url",
          "image_url": {
            "url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg",
          },
        },
      ],
    }
  ],
  max_tokens=300,
)

print(response.choices[0])

输出结果：

Choice(finish_reason=None, index=0, message=ChatCompletionMessage(content='这张图片展示了一个美丽宁静的自然景观。画面中心是一条直通画面深处的木板路，两旁是郁郁葱葱、高高的绿色草地。在木板路的尽头可以看到一些树木，而在树木后方则是蓝色的天空，点缀着几朵洁白的云朵。整体而言，这张图片传达出一种平静和放松的氛围，是典型的户外自然风光摄影。', role='assistant', function_call=None, tool_calls=None), finish_details={'type': 'stop', 'stop': '<|fim_suffix|>'})

TTS 以及 语音识别能力

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TO BE CONTINUED

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GPTS 定制化功能

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TO BE CONTINUED