這裡是因為 Colab 改版, 目前才需要這麼複雜的安裝。
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!pip install -U tensorflow-probability
!pip install typing-extensions --upgrade
!pip install gradio
!pip install langchain
!pip install openai
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ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
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In [2]:
%matplotlib inline
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
1. 使用 OpenAI 的 API¶
我們先來安裝 openai 套件, 還有快速打造 Web App 的 gradio。
In [3]:
# 本來在這裡裝 openai 和 gradio, 但前面已經裝了
#
#!pip install openai
#!pip install gradio
3. 使用 ChatGPT API¶
首先使用 openai 套件。
In [4]:
from openai import OpenAI
把自己的金鑰貼上。
In [5]:
client = OpenAI(
# defaults to os.environ.get("OPENAI_API_KEY")
api_key="你的 API 金鑰",
)
ChatGPT API 的重點是要把之前對話的內容送給 ChatGPT, 然後他就會有個適當的回應!
角色 (role) 一共有三種, 分別是:
system: 這是對話機器人的「人設」user: 使用者assistant: ChatGPT 的回應
In [6]:
prompt = "我今天心情很不好。"
messages = [{"role":"system", "content":"你是一個非常溫暖的對話機器人，回應都簡短，儘量不要超過二十個字，而且有同理心。"},
{"role": "user", "content": prompt}]
In [7]:
messages
Out[7]:
[{'role': 'system', 'content': '你是一個非常溫暖的對話機器人，回應都簡短，儘量不要超過二十個字，而且有同理心。'},
{'role': 'user', 'content': '我今天心情很不好。'}]
現在我們來接 ChatGPT 的回應。
In [8]:
chat_completion = client.chat.completions.create(
messages=messages,
model="gpt-3.5-turbo",
)
In [9]:
chat_completion
Out[9]:
ChatCompletion(id='chatcmpl-8XT4spSlQ6esL4VNGZQlbmEy39i50', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='怎麼了？可以跟我分享嗎？', role='assistant', function_call=None, tool_calls=None))], created=1702987290, model='gpt-3.5-turbo-0613', object='chat.completion', system_fingerprint=None, usage=CompletionUsage(completion_tokens=16, prompt_tokens=77, total_tokens=93))
In [10]:
chat_completion.choices[0].message.content
Out[10]:
'怎麼了？可以跟我分享嗎？'
In [11]:
reply = chat_completion.choices[0].message.content
In [12]:
reply
Out[12]:
'怎麼了？可以跟我分享嗎？'
In [13]:
messages.append({"role":"assistant", "content":reply})
In [14]:
messages
Out[14]:
[{'role': 'system', 'content': '你是一個非常溫暖的對話機器人，回應都簡短，儘量不要超過二十個字，而且有同理心。'},
{'role': 'user', 'content': '我今天心情很不好。'},
{'role': 'assistant', 'content': '怎麼了？可以跟我分享嗎？'}]
4. 打造一個可以一直說下去的 ChatGPT¶
In [15]:
icon = "(*ﾟ▽ﾟ*): "
messages = [{"role":"system", "content":"你是一個非常溫暖的對話機器人，回應都簡短，儘量不要超過二十個字，而且有同理心。"}]
while True:
prompt = input('> ')
if 'bye' in prompt:
print('再見, 下次再聊!')
break
messages.append({"role": "user", "content": prompt})
chat_completion = client.chat.completions.create(
messages=messages,
model="gpt-3.5-turbo",
)
reply = chat_completion.choices[0].message.content
print(icon + reply)
print()
messages.append({"role": "assistant", "content": reply})
> 我覺得很難過 (*ﾟ▽ﾟ*): 為什麼呢？可以跟我說說嗎？ > Python 都不會寫 (*ﾟ▽ﾟ*): 沒關係，學習一門程式語言需要時間和練習。你可以從基礎開始，慢慢學習，我相信你能掌握Python的！加油！ > 同學都排擠我 (*ﾟ▽ﾟ*): 這讓你感到不舒服。試著與他們溝通，或尋找其他人與你有共同興趣的朋友。你不是孤單的，我在這裡支持你。 > 先這樣, bye 再見, 下次再聊!
5. 最後用 gradio 打造 ChatGPT 網路應用程式!¶
In [16]:
import gradio as gr
In [17]:
messages = [{"role":"system", "content":"你是一個非常溫暖的對話機器人，回應都簡短，儘量不要超過二十個字，而且有同理心。"}]
In [18]:
def pipi(prompt, history):
history = history or []
global messages
messages.append({"role": "user", "content": prompt})
chat_completion = client.chat.completions.create(
messages=messages,
model="gpt-3.5-turbo",
)
reply = chat_completion.choices[0].message.content
messages.append({"role": "assistant", "content": reply})
history = history + [[prompt, reply]]
return history, history
In [19]:
chatbot = gr.Chatbot()
In [22]:
iface = gr.Interface(pipi,
inputs=["text", "state"],
outputs=[chatbot, "state"],
title="療癒系拍拍機器人",
description="你有什麼心事, 歡迎來找我聊聊 :)")
In [23]:
iface.launch(share=True)
Colab notebook detected. To show errors in colab notebook, set debug=True in launch() Running on public URL: https://a070a50d7289189f1f.gradio.live This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)
Out[23]:
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