自動新聞摘要機器人 | 原創，AI翻譯
這篇貼文展示了一個基於Python的新聞機器人，它利用Mistral API從Hacker News、GitHub Trending和《紐約時報》（中文版）抓取並摘要頂尖新聞。該機器人透過Telegram發送簡潔的每日報告，並使用GitHub Actions工作流程實現自動化執行。這是一個輕鬆掌握科技與全球新聞的理想工具。以下是每日新聞摘要的範例。
每日新聞摘要 - 2025年6月7日
Hacker News
-
網頁顯示Facebook與當前瀏覽器不相容，建議更新至支援的瀏覽器以繼續使用服務。
-
盧安達的仇恨廣播透過隱晦語言煽動聽眾殺害圖西族人，導致種族滅絕。
-
Railway推出Railpack取代Nixpacks，旨在解決阻礙20萬用戶的擴展性與依賴管理問題，以更順暢地支援1億用戶。
-
文章深入探討Radiant AI的遺產，這是一個曾承諾用於《上古卷軸IV：遺忘之都》但最終被大幅刪減的爭議性AI系統。
-
《華盛頓郵報》建議用戶停止使用Chrome並刪除Meta的應用程式以提升隱私保護。
GitHub Trending
-
Cognee透過可擴展的模組化ECL管道，僅用五行代碼即可為AI代理創建動態記憶體。
-
NetBird結合基於WireGuard的點對點覆蓋網絡與集中化細粒度存取控制，簡化安全私密網絡的建立。
-
NoteGen是一款AI驅動的跨平台Markdown筆記應用，整合錄音與書寫功能，將零散知識組織成連貫筆記。
-
Scrapy是一個快速、高階的Python網頁爬取框架，專為從網站提取結構化數據而設計。
-
React Bits提供免費開源的動畫化、互動式且可自訂的React元件集合，以增強網頁介面。
《紐約時報》（中文版）
-
中國國家主席習近平與美國總統川普通話後，雙方同意進一步貿易談判以緩解關稅與稀土供應的緊張局勢。
-
中國近期的爭議凸顯公眾對社會不平等的普遍不滿，認為成功往往取決於關係而非能力。
-
中國加強打擊稀土金屬走私，導致全球產業供應嚴重中斷，北京正收緊管制以將這些關鍵資源作為戰略工具。
-
川普與馬斯克之間的衝突升級可能帶來重大影響，雙方皆運用影響力與資源互相抗衡。
-
中國暫停出口七種稀土金屬及其磁鐵，導致美國與歐洲可能出現工廠關閉的嚴重短缺。
import requests
from bs4 import BeautifulSoup
import os
from dotenv import load_dotenv
import datetime
import sys
import re
import time
load_dotenv()
TELEGRAM_BOT_TOKEN = os.environ.get("TELEGRAM_BOT_API_KEY")
TELEGRAM_CHAT_ID = os.environ.get("TELEGRAM_CHAT_ID", "610574272")
MISTRAL_API_KEY = os.environ.get("MISTRAL_API_KEY")
TELEGRAM_MAX_LENGTH = 4096
def send_telegram_message(message):
if not TELEGRAM_BOT_TOKEN or not TELEGRAM_CHAT_ID:
print("錯誤：未設定TELEGRAM_BOT_API_KEY或TELEGRAM_CHAT_ID。")
return False
url = f"https://api.telegram.org/bot{TELEGRAM_BOT_TOKEN}/sendMessage"
url_pattern = re.compile(r'(https?://[^\s]+)')
# 移除訊息中的所有星號（用於粗體/斜體）
message_no_stars = message.replace('*', '')
# 移除訊息中的連結
message_no_links = url_pattern.sub('', message_no_stars)
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": TELEGRAM_CHAT_ID,
"text": part,
}
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 fetch_html_content(url):
try:
print(f"從以下網址獲取HTML內容：{url}")
response = requests.get(url, timeout=15, verify=False)
response.raise_for_status()
print(f"成功從以下網址獲取HTML內容：{url}")
return response.text
except requests.exceptions.RequestException as e:
print(f"無法獲取URL：{url} - {e}")
return None
def extract_hacker_news_links(html, max_links=5):
soup = BeautifulSoup(html, 'html.parser')
links = []
seen = set()
for item in soup.select('.titleline > a'):
url = item['href']
title = item.text.strip()
if url.startswith('item?id='):
url = f"https://news.ycombinator.com/{url}"
if url not in seen and title:
links.append({'url': url, 'text': title})
seen.add(url)
if len(links) >= max_links:
break
print(f"從Hacker News提取了{len(links)}個連結。")
return links
def extract_github_trending(html, max_links=5):
soup = BeautifulSoup(html, 'html.parser')
links = []
for repo in soup.select('article.Box-row h2 a'):
url = f"https://github.com{repo['href']}"
title = re.sub(r'\s+', ' ', repo.text).strip()
if title and url:
links.append({'url': url, 'text': title})
if len(links) >= max_links:
break
print(f"從GitHub提取了{len(links)}個熱門儲存庫。")
return links
def call_mistral_api(prompt, model="mistral-small-latest"):
api_key = MISTRAL_API_KEY
if not api_key:
print("錯誤：未設定MISTRAL_API_KEY環境變數。")
return None
url = "https://api.mistral.ai/v1/chat/completions"
headers = {
"Content-Type": "application/json",
"Accept": "application/json",
"Authorization": f"Bearer {api_key}"
}
data = {
"model": model,
"messages": [
{
"role": "user",
"content": prompt
}
]
}
try:
print(f"使用模型呼叫Mistral API：{model}")
print(f"發送的提示：{prompt[:1000]}...")
response = requests.post(url, headers=headers, json=data)
response.raise_for_status()
response_json = response.json()
print(f"Mistral API回應：{response_json}")
if response_json and response_json.get('choices'):
content = response_json['choices'][0]['message']['content']
print(f"Mistral API內容：{content}")
return content
else:
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}")
if hasattr(e, "response") and e.response is not None:
print(f"回應狀態碼：{e.response.status_code}")
print(f"回應內容：{e.response.text}")
return None
def fetch_and_summarize(url, fallback_title=None):
print(f"摘要：{url}")
html = fetch_html_content(url)
if not html:
return {"url": url, "summary": "無法獲取內容。", "title": fallback_title or url}
soup = BeautifulSoup(html, 'html.parser')
title = soup.title.text.strip() if soup.title else (fallback_title or url)
paragraphs = soup.find_all('p')
text_content = "\n".join(p.get_text() for p in paragraphs)
if not text_content or len(text_content) < 100:
text_content = soup.get_text(separator="\n")
text_content = text_content.strip()
if len(text_content) > 3000:
text_content = text_content[:3000]
summary = ai_summarize(text_content, url, title)
return {"url": url, "summary": summary, "title": title}
def limit_to_n_words(text, n):
words = text.strip().split()
if len(words) <= n:
return text.strip()
return ' '.join(words[:n]) + "..."
def ai_summarize(text, url=None, title=None):
if not MISTRAL_API_KEY:
print("未設定MISTRAL_API_KEY。返回前15個字作為摘要。")
return limit_to_n_words(text, 15)
prompt = (
"若原文為中文，請以英文摘要。"
"以清晰簡潔的英文摘要以下網頁內容。"
"聚焦於單一最重要的觀點或見解。"
"摘要應約300字元。"
"僅輸出摘要句子：\n"
f"標題：{title if title else ''}\n"
f"{text}\n"
f"{'原始連結：' + url if url else ''}"
)
summary = call_mistral_api(prompt)
if summary is None:
return limit_to_n_words(text, 15)
# 最後截斷至300字元
return summary.strip()[:300]
def generate_summarized_report(summaries, source_name):
text = f"{source_name}\n"
text += "-" * len(source_name) + "\n"
if not summaries:
text += "未找到項目。\n\n"
return text
url_pattern = re.compile(r'(https?://[^\s]+)')
for idx, item in enumerate(summaries, 1):
summary = item.get('summary', '').replace('\n', ' ').replace('\r', ' ').strip()
summary = summary.replace('*', '')
summary = url_pattern.sub('', summary)
# 最後將每個摘要截斷至300字元
summary = summary[:300]
text += f"{idx}. {summary}\n\n" # 在摘要之間添加額外換行
text += "\n"
return text
# --- 《紐約時報》（cn.nytimes.com）整合 ---
def extract_nytimes_links(html, max_links=5):
"""
從cn.nytimes.com主頁提取連結。
僅包含以'https://cn.nytimes.com/'開頭的連結。
"""
soup = BeautifulSoup(html, 'html.parser')
links = []
for a in soup.find_all('a', href=True):
url = a['href']
if url.startswith('https://cn.nytimes.com/'):
links.append({
'url': url,
'text': a.text.strip()
})
if len(links) >= max_links:
break
print(f"從主頁提取了{len(links)}個連結。")
return links
def summarize_nytimes_article(url):
html = fetch_html_content(url)
if not html:
return {"url": url, "summary": "無法獲取內容。", "title": url}
soup = BeautifulSoup(html, 'html.parser')
# 嘗試提取文章主標題
title_element = soup.select_one('.article-area .article-content .article-header header h1')
title = title_element.text.strip() if title_element else (soup.title.text.strip() if soup.title else url)
# 提取文章正文
article_area = soup.find('section', class_='article-body')
if article_area:
article_text = article_area.get_text(separator='\n', strip=True)
else:
article_text = soup.get_text(separator='\n', strip=True)
if not article_text or len(article_text) < 100:
article_text = soup.get_text(separator='\n', strip=True)
if len(article_text) > 3000:
article_text = article_text[:3000]
summary = ai_summarize(article_text, url, title)
return {"url": url, "summary": summary, "title": title}
def main():
# 檢查--test參數
is_test = "--test" in sys.argv
today = datetime.datetime.now().strftime("%Y-%m-%d")
report = f"每日新聞摘要 - {today}\n\n"
if is_test:
# 僅爬取一個連結並發送一個摘要（《紐約時報》中文版）
ny_html = fetch_html_content('https://m.cn.nytimes.com')
ny_links = []
ny_summaries = []
if ny_html:
ny_links = extract_nytimes_links(ny_html, max_links=1)
if ny_links:
link = ny_links[0]
summary = summarize_nytimes_article(link['url'])
ny_summaries.append(summary)
report = generate_summarized_report(ny_summaries, "《紐約時報》（中文版）")
if ny_summaries:
if send_telegram_message(report):
print("測試摘要成功發送至Telegram。")
sys.exit(0)
else:
print("發送測試摘要至Telegram失敗。")
sys.exit(1)
else:
print("未收集到新聞，未發送任何內容至Telegram。")
sys.exit(1)
else:
# --- Hacker News ---
hn_html = fetch_html_content('https://news.ycombinator.com')
hn_links = []
hn_summaries = []
if hn_html:
hn_links = extract_hacker_news_links(hn_html)
for link in hn_links:
summary = fetch_and_summarize(link['url'], fallback_title=link['text'])
hn_summaries.append(summary)
time.sleep(2)
report += generate_summarized_report(hn_summaries, "Hacker News")
# --- GitHub Trending ---
gh_html = fetch_html_content('https://github.com/trending')
gh_links = []
gh_summaries = []
if gh_html:
gh_links = extract_github_trending(gh_html)
for link in gh_links:
summary = fetch_and_summarize(link['url'], fallback_title=link['text'])
gh_summaries.append(summary)
time.sleep(2)
report += generate_summarized_report(gh_summaries, "GitHub Trending")
# --- 《紐約時報》（cn.nytimes.com） ---
ny_html = fetch_html_content('https://m.cn.nytimes.com')
ny_links = []
ny_summaries = []
if ny_html:
ny_links = extract_nytimes_links(ny_html, max_links=5)
for link in ny_links:
summary = summarize_nytimes_article(link['url'])
ny_summaries.append(summary)
time.sleep(2)
report += generate_summarized_report(ny_summaries, "《紐約時報》（中文版）")
if any([hn_summaries, gh_summaries, ny_summaries]):
if len(report) > TELEGRAM_MAX_LENGTH:
print(f"報告超過{TELEGRAM_MAX_LENGTH}字元，將分割成多條訊息。")
if send_telegram_message(report):
print("每日新聞報告成功發送至Telegram。")
sys.exit(0)
else:
print("發送每日新聞報告至Telegram失敗。")
sys.exit(1)
else:
print("未收集到新聞，未發送任何內容至Telegram。")
sys.exit(1)
if __name__ == "__main__":
main()
name: 新聞機器人
on:
schedule:
# 每天北京時間上午9點（UTC凌晨1點）執行。
- cron: '0 1 * * *'
workflow_dispatch: # 允許手動觸發
push:
# 僅當兩個文件在同一提交/推送中更改時觸發
# 這需要下方過濾工作檢查兩個文件
paths:
- scripts/nytimes/news_bot.py
- .github/workflows/news.yml
concurrency:
group: 'news'
cancel-in-progress: false
jobs:
發送新聞:
runs-on: ubuntu-latest
environment: github-pages
env:
TELEGRAM_BOT_API_KEY: $
MISTRAL_API_KEY: $
steps:
- name: 檢出儲存庫
uses: actions/checkout@v4
with:
fetch-depth: 5
- name: 設定Python 3.10.x
uses: actions/setup-python@v4
with:
python-version: "3.10.x"
- name: 安裝依賴
run: |
python -m pip install --upgrade pip
pip install -r requirements.simple.txt
- name: 執行新聞機器人腳本
run: python scripts/nytimes/news_bot.py