用Mistral打造習慣養成機器人 | 原創，AI翻譯
在這篇網誌文章中，我們探討如何利用Python和GitHub Actions創建一個習慣提醒機器人。這個機器人透過Telegram API發送自動化提醒訊息，並整合Mistral AI生成情境相關的提示。透過GitHub Actions排程任務，機器人能定時發送通知，鼓勵持續養成習慣。我們將逐步介紹從環境設定、腳本編寫到部署的完整流程，為自動化習慣追蹤系統提供實用指南。
代碼
import os
import requests
import argparse
import re
import datetime
from dotenv import load_dotenv
import random
# 從.env檔案加載環境變量
load_dotenv()
# 環境變量
TELEGRAM_HABIT_BOT_API_KEY = os.environ.get("TELEGRAM_HABIT_BOT_API_KEY")
TELEGRAM_CHAT_ID = os.environ.get("TELEGRAM_CHAT_ID")
MISTRAL_API_KEY = os.environ.get("MISTRAL_API_KEY")
# Telegram訊息長度限制
TELEGRAM_MAX_LENGTH = 4096
def send_telegram_message(bot_token, chat_id, message):
"""使用Telegram Bot API發送訊息到指定聊天室"""
if not bot_token or not chat_id:
print("錯誤：TELEGRAM_HABIT_BOT_API_KEY或TELEGRAM_CHAT_ID未設定")
return False
url = f"https://api.telegram.org/bot{bot_token}/sendMessage"
# 移除Markdown星號和URL以確保Telegram兼容性
message_no_stars = message.replace('*', '')
url_pattern = re.compile(r'(https?://[^\s]+)')
message_no_links = url_pattern.sub('', message_no_stars)
# 若訊息超過Telegram長度限制則進行分割
messages = []
msg = message_no_links
while len(msg) > TELEGRAM_MAX_LENGTH:
split_idx = msg.rfind('\n', 0, TELEGRAM_MAX_LENGTH)
if split_idx == -1 or split_idx < TELEGRAM_MAX_LENGTH // 2:
split_idx = TELEGRAM_MAX_LENGTH
messages.append(msg[:split_idx])
msg = msg[split_idx:]
messages.append(msg)
success = True
for part in messages:
params = {
"chat_id": chat_id,
"text": part,
"parse_mode": "Markdown"
}
try:
response = requests.post(url, params=params)
response.raise_for_status()
print(f"成功發送Telegram訊息部分（{len(part)}字元）")
except requests.exceptions.RequestException as e:
print(f"發送Telegram訊息時出錯：{e}")
success = False
return success
def call_mistral_api(prompt, model="mistral-large-latest"):
"""調用Mistral API生成回應"""
if not MISTRAL_API_KEY:
print("錯誤：未設定MISTRAL_API_KEY環境變量")
return None
url = "https://api.mistral.ai/v1/chat/completions"
headers = {
"Content-Type": "application/json",
"Accept": "application/json",
"Authorization": f"Bearer {MISTRAL_API_KEY}"
}
data = {
"model": model,
"messages": [
{
"role": "user",
"content": prompt
}
],
"temperature": 0.7, # 調整溫度參數控制創造性
"max_tokens": 300 # 限制回應長度
}
try:
print(f"使用模型調用Mistral API：{model}")
response = requests.post(url, headers=headers, json=data)
response.raise_for_status()
response_json = response.json()
if response_json.get('choices'):
content = response_json['choices'][0]['message']['content']
print(f"Mistral API內容：{content}")
return content
print(f"Mistral API錯誤：無效的回應格式：{response_json}")
return None
except requests.exceptions.RequestException as e:
print(f"Mistral API錯誤：{e}")
return None
def generate_copilot_message():
"""透過Mistral API生成鼓勵使用Copilot的技術提示句子"""
prompt = (
f"為後端工程師生成一個獨特且具體的技術提示句子"
"隨機選擇以下一項技術：Java、Spring Boot、Control-M、IBM WebSphere、Maven、多線程、Nexus、Windows、JVM、Service-NOW、Python、AI或DevOps、Linux。算法與銀行業"
"格式為'卡在[具體挑戰]？問問Copilot！'或'遇到[任務]困難？找Copilot幫忙！'"
"確保挑戰多樣化（例如配置、調試、優化）。"
"保持句子在300字元以內，避免使用Markdown或URL，僅輸出句子。"
)
message = call_mistral_api(prompt)
if message:
return message.strip()[:300]
return "卡在設定Control-M訂單日期？問問Copilot！"
def main():
parser = argparse.ArgumentParser(description="Telegram習慣提醒機器人")
parser.add_argument("--job", choices=["send_reminder", "send_message"], required=True, help="執行任務")
parser.add_argument("--message", type=str, help="'send_message'任務要發送的訊息")
args = parser.parse_args()
if args.job == "send_reminder":
if TELEGRAM_HABIT_BOT_API_KEY and TELEGRAM_CHAT_ID:
message = generate_copilot_message()
send_telegram_message(TELEGRAM_HABIT_BOT_API_KEY, TELEGRAM_CHAT_ID, message)
else:
print("錯誤：TELEGRAM_HABIT_BOT_API_KEY或TELEGRAM_CHAT_ID未設定")
elif args.job == "send_message":
if TELEGRAM_HABIT_BOT_API_KEY and TELEGRAM_CHAT_ID:
message = args.message if args.message else "來自機器人的預設測試訊息！"
send_telegram_message(TELEGRAM_HABIT_BOT_API_KEY, TELEGRAM_CHAT_ID, message)
else:
print("錯誤：TELEGRAM_HABIT_BOT_API_KEY或TELEGRAM_CHAT_ID未設定")
if __name__ == "__main__":
main()
GitHub Action
name: 習慣提醒
on:
schedule:
# 每10分鐘運行一次（每小時的0、10、20、30、40、50分），UTC時間05:00–13:00，週一至週五
# 05:00–13:00 UTC = 北京時間13:00–21:00（UTC+8）
- cron: '0,10,20,30,40,50 5-13 * * 1-5'
workflow_dispatch:
# 允許手動觸發測試
inputs:
message:
description: '測試用的自訂訊息（可選）'
required: false
default: '來自GitHub Actions的測試訊息'
job:
description: '要運行的任務（可選）'
required: false
default: 'send_message'
push:
branches: ["main"]
paths:
- 'scripts/bot/habit_bot.py'
- '.github/workflows/habit_reminder.yml'
concurrency:
group: 'habit_reminder'
cancel-in-progress: false
jobs:
habit_reminder_job:
runs-on: ubuntu-latest
environment: github-pages
env:
TELEGRAM_HABIT_BOT_API_KEY: $
TELEGRAM_CHAT_ID: $
MISTRAL_API_KEY: $
steps:
- name: 檢出存儲庫
uses: actions/checkout@v4
with:
fetch-depth: 5
- name: 設置Python 3.13
uses: actions/setup-python@v4
with:
python-version: "3.13"
- name: 安裝依賴
run: |
python -m pip install --upgrade pip
pip install -r requirements.txt
- name: 運行習慣提醒腳本（排程任務）
run: python scripts/bot/habit_bot.py --job send_reminder
if: github.event_name == 'schedule'
- name: 運行習慣提醒腳本（手動觸發）
run: python scripts/bot/habit_bot.py --job $ --message "$"
if: github.event_name == 'workflow_dispatch'
- name: 推送至main分支時通知
run: python scripts/bot/habit_bot.py --job send_message --message "習慣機器人的代碼變更已推送至main分支"
if: github.event_name == 'push'