Perhaps all intelligent chat robots have the following implementation ideas?
First, obtain the chat content through code (no language limit), then transfer the chat content to the AI background, and finally transfer the obtained AI reply to the chat interface via the original route.
In this process, the difficulties are:
How to obtain the chat content;
How to call AI reply;
How to automatically reply correctly.
In the process of development, you will find that the last item: how to correct every dialogue is the most difficult.
Download PyOfficeRobot
pip install PyOfficeRobot
1 line of code to implement WeChat robot ChatGPT
import PyOfficeRobot PyOfficeRobot.chat.chat_by_gpt(who='程序员', api_key='你的api_key')
Only 2 parameters are listed above:
who='Programmer': required, the person you want to reply intelligently;
api_key='your api_key': required, your own ChatGPT
In fact, there are a series of parameters inside the method, but our project is mainly used by novices, so I filled them all in If you are a professional developer, you can refer to the instructions below to modify it. (from OpenAI official website)
completions = openai.Completion.create( engine=model_engine, prompt=prompt, max_tokens=max_tokens, # 生成结果时的最大 tokens 数。平均一个汉字是 2 个 tokens,text-davinci-003 最多是 4000 个 tokens,也就是 2000 个汉字左右 n=n, stop=stop, temperature=temperature, # 控制结果的随机性,如果希望结果更有差异性 0.9,或者希望有固定结果可以尝试 0.0 top_p=top_p, # 一个可用于代替 temperature 的参数,对应机器学习中 nucleus sampling,如果设置 0.1 意味着只考虑构成前 10% 概率质量的 tokens frequency_penalty=frequency_penalty, # 控制字符的重复度,取值为 -2.0 ~ 2.0 之间的数字 presence_penalty=presence_penalty # 控制主题的重复度,取值为 -2.0 ~ 2.0 之间的数字 )
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