OPEN AI x ChatGPT x LineBot 串接完整全紀錄

詳細步驟流程:

取得OPEN API KEY

LineBot Channel access token 、Channel secret

Vercel 匯入 GitHub 原碼

原碼部分

from flask import Flask, request, abort
from linebot import LineBotApi, WebhookHandler
from linebot.exceptions import InvalidSignatureError
from linebot.models import MessageEvent, TextMessage, TextSendMessage
from api.chatgpt import ChatGPT
import os
line_bot_api = LineBotApi(os.getenv("LINE_CHANNEL_ACCESS_TOKEN"))
line_handler = WebhookHandler(os.getenv("LINE_CHANNEL_SECRET"))
working_status = os.getenv("DEFALUT_TALKING", default = "true").lower() == "true"
app = Flask(__name__)
chatgpt = ChatGPT()
# domain root
@app.route('/')
def home():
    return 'Hello, World!'
@app.route("/webhook", methods=['POST'])
def callback():
    # get X-Line-Signature header value
    signature = request.headers['X-Line-Signature']
    # get request body as text
    body = request.get_data(as_text=True)
    app.logger.info("Request body: " + body)
    # handle webhook body
    try:
        line_handler.handle(body, signature)
    except InvalidSignatureError:
        abort(400)
    return 'OK'
@line_handler.add(MessageEvent, message=TextMessage)
def handle_message(event):
    global working_status
    
    if event.message.type != "text":
        return
    working_status = True
    if working_status:
        chatgpt.add_msg(f"Human:{event.message.text}?\n")
        reply_msg = chatgpt.get_response().replace("AI:", "", 1)
        chatgpt.add_msg(f"AI:{reply_msg}\n")
        line_bot_api.reply_message(
            event.reply_token,
            TextSendMessage(text=reply_msg))
if __name__ == "__main__":
    app.run()

from api.prompt import Prompt
import os
import openai
openai.api_key = os.getenv("OPENAI_API_KEY")
class ChatGPT:
    def __init__(self):
        self.prompt = Prompt()
        self.model = os.getenv("OPENAI_MODEL", default = "text-davinci-003")
        self.temperature = float(os.getenv("OPENAI_TEMPERATURE", default = 0))
        self.frequency_penalty = float(os.getenv("OPENAI_FREQUENCY_PENALTY", default = 0))
        self.presence_penalty = float(os.getenv("OPENAI_PRESENCE_PENALTY", default = 0.6))
        self.max_tokens = int(os.getenv("OPENAI_MAX_TOKENS", default = 240))
    def get_response(self):
        response = openai.Completion.create(
            model=self.model,
            prompt=self.prompt.generate_prompt(),
            temperature=self.temperature,
            frequency_penalty=self.frequency_penalty,
            presence_penalty=self.presence_penalty,
            max_tokens=self.max_tokens
        )
        return response['choices'][0]['text'].strip()
    def add_msg(self, text):
        self.prompt.add_msg(text)

import os
chat_language = os.getenv("INIT_LANGUAGE", default = "zh")
MSG_LIST_LIMIT = int(os.getenv("MSG_LIST_LIMIT", default = 20))
LANGUAGE_TABLE = {
  "zh": "嗨！",
  "en": "Hi!"
}
class Prompt:
    def __init__(self):
        self.msg_list = []
        self.msg_list.append(f"AI:{LANGUAGE_TABLE[chat_language]}")
    
    def add_msg(self, new_msg):
        if len(self.msg_list) >= MSG_LIST_LIMIT:
            self.remove_msg()
        self.msg_list.append(new_msg)
    def remove_msg(self):
        self.msg_list.pop(0)
    def generate_prompt(self):
        return '\n'.join(self.msg_list)

Flask==2.2.2

Flask==2.2.2
line-bot-sdk
openai

{
  "builds": [
    {
      "src": "api/index.py",
      "use": "@vercel/python"
    }
  ],
  "routes": [
    {
      "src": "/(.*)",
      "dest": "api/index.py"
    }
  ]
}

Vercel Environment Variables 環境設定

LineBot Webhook 設定

@app.route("/webhook", methods=['POST'])

QA

chatgpt 與 openai gpt3 有何差異

chatgpt 有api嗎

使用ChatGPT API

def get_response(self):
        response = openai.Completion.create(
            model=self.model,
            prompt=self.prompt.generate_prompt(),
            temperature=self.temperature,
            frequency_penalty=self.frequency_penalty,
            presence_penalty=self.presence_penalty,
            max_tokens=self.max_tokens
        )
        return response['choices'][0]['text'].strip()

import openai
openai.api_key = "YOUR_API_KEY"
response = openai.Completion.create(
engine="chatbot",
prompt="Hello, how are you today?",
max_tokens=20
)
print(response.text)

def __init__(self):
        self.prompt = Prompt()
        self.model = "chatbot"
        self.temperature = float(os.getenv("OPENAI_TEMPERATURE", default = 0))
        self.frequency_penalty = float(os.getenv("OPENAI_FREQUENCY_PENALTY", default = 0))
        self.presence_penalty = float(os.getenv("OPENAI_PRESENCE_PENALTY", default = 0.6))
        self.max_tokens = int(os.getenv("OPENAI_MAX_TOKENS", default = 240))
    def get_response(self):
        response = openai.Completion.create(
            model=self.model,
            prompt=self.prompt.generate_prompt(),
            temperature=self.temperature,
            frequency_penalty=self.frequency_penalty,
            presence_penalty=self.presence_penalty,
            max_tokens=self.max_tokens
        )
        return response['choices'][0]['text'].strip()

後記:

• Line 官方提供的 python flask 製作 linebot 的 sample code line/line-bot-sdk-python
• Vercel 官方提供的 python runtime Flask 範例 Deploy an example with Flask
• memochou1993/gpt-ai-assistant node.js 版本串接 vercel 範例
• Lanznx/HealthLineBot python Django 版本串接 vercel 範例
• howarder3/GPT-Linebot-python-flask-on-vercel python Flask 版本串接 vercel 範例