自动新闻摘要机器人 | 原创，AI翻译
这篇帖子展示了一个基于Python的新闻机器人，它利用Mistral API抓取并汇总来自Hacker News、GitHub Trending和《纽约时报》（中文版）的热门新闻，通过Telegram发送简洁的每日简报，并通过GitHub Actions工作流实现自动化执行。是轻松跟进科技和全球新闻的理想工具。以下是每日新闻摘要的示例。
每日新闻摘要 - 2025年6月7日
Hacker News
-
网页显示Facebook与当前浏览器不兼容，建议更新至支持的浏览器以继续使用服务。
-
卢旺达的仇恨电台通过使用暗语煽动听众杀害图西族人，引发了种族灭绝。
-
Railway推出Railpack取代Nixpacks，旨在解决困扰20万用户的可扩展性和依赖管理问题，以更顺畅地过渡至支持1亿用户。
-
文章深入探讨了Radiant AI的遗产，这是一个曾承诺用于《上古卷轴IV：湮没》但最终大部分被删减的有争议且雄心勃勃的AI系统。
-
《华盛顿邮报》建议用户通过停用Chrome和删除Meta应用来增强隐私保护。
GitHub Trending
-
Cognee通过可扩展、模块化的ECL管道，仅用五行代码即可为AI代理创建动态记忆。
-
NetBird结合了基于WireGuard的点对点覆盖网络与集中化、精细的访问控制，简化了安全私密网络的建设。
-
NoteGen是一款AI驱动的跨平台Markdown笔记应用，整合录音与书写功能，将碎片化知识组织成连贯的笔记。
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Scrapy是一个快速、高级的Python网页爬取和抓取框架，专为从网站提取结构化数据而设计。
-
React Bits提供了一系列免费、开源的动画化、交互式且可定制的React组件，用于增强网页界面。
《纽约时报》（中文版）
-
中国国家主席习近平与美国总统特朗普通话后，双方同意进一步开展贸易谈判，以缓解关税和稀土供应方面的紧张局势。
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中国近期的争议凸显了公众对社会不平等的普遍不满，认为成功往往取决于关系而非能力。
-
中国加强对稀土金属走私的打击，导致全球行业供应严重中断，北京正收紧控制以将这些关键资源作为战略工具。
-
特朗普与马斯克之间不断升级的冲突可能产生重大影响，双方都在利用自身的影响力和资源对抗对方。
-
中国暂停出口七种稀土金属及其磁铁，导致美国和欧洲工厂可能因严重短缺而关闭。
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("错误：未设置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]+)')
# 移除消息中的所有星号（用于加粗/斜体）
message_no_stars = message.replace('*', '')
# 移除消息中的链接
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"成功发送Telegram消息部分（{len(part)}字符）。")
except requests.exceptions.RequestException as e:
print(f"发送Telegram消息时出错：{e}")
success = False
return success
def fetch_html_content(url):
try:
print(f"从以下URL获取HTML内容：{url}")
response = requests.get(url, timeout=15, verify=False)
response.raise_for_status()
print(f"成功从以下URL获取HTML内容：{url}")
return response.text
except requests.exceptions.RequestException as e:
print(f"无法获取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"从Hacker News提取了{len(links)}个链接。")
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"从GitHub提取了{len(links)}个热门仓库。")
return links
def call_mistral_api(prompt, model="mistral-small-latest"):
api_key = MISTRAL_API_KEY
if not api_key:
print("错误：未设置MISTRAL_API_KEY环境变量。")
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"使用模型调用Mistral API：{model}")
print(f"发送的提示：{prompt[:1000]}...")
response = requests.post(url, headers=headers, json=data)
response.raise_for_status()
response_json = response.json()
print(f"Mistral API响应：{response_json}")
if response_json and response_json.get('choices'):
content = response_json['choices'][0]['message']['content']
print(f"Mistral API内容：{content}")
return content
else:
print(f"Mistral API错误：无效的响应格式：{response_json}")
return None
except requests.exceptions.RequestException as e:
print(f"Mistral API错误：{e}")
if hasattr(e, "response") and e.response is not None:
print(f"响应状态码：{e.response.status_code}")
print(f"响应内容：{e.response.text}")
return None
def fetch_and_summarize(url, fallback_title=None):
print(f"正在摘要：{url}")
html = fetch_html_content(url)
if not html:
return {"url": url, "summary": "无法获取内容。", "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("未设置MISTRAL_API_KEY。返回前15个词作为摘要。")
return limit_to_n_words(text, 15)
prompt = (
"如果原文是中文，请用英文摘要。"
"用清晰简洁的英文摘要以下网页内容。"
"聚焦于最重要的一个观点或见解。"
"摘要应约300字符。"
"仅输出摘要句子：\n"
f"标题：{title if title else ''}\n"
f"{text}\n"
f"{'原文链接：' + url if url else ''}"
)
summary = call_mistral_api(prompt)
if summary is None:
return limit_to_n_words(text, 15)
# 最后截断至300字符
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 += "未找到项目。\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)
# 最后将每个摘要截断至300字符
summary = summary[:300]
text += f"{idx}. {summary}\n\n" # 在摘要之间添加额外空行
text += "\n"
return text
# --- 《纽约时报》（中文版）集成 ---
def extract_nytimes_links(html, max_links=5):
"""
从cn.nytimes.com主页提取链接。
仅包含以'https://cn.nytimes.com/'开头的链接。
"""
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"从主页提取了{len(links)}个链接。")
return links
def summarize_nytimes_article(url):
html = fetch_html_content(url)
if not html:
return {"url": url, "summary": "无法获取内容。", "title": url}
soup = BeautifulSoup(html, 'html.parser')
# 尝试提取文章主标题
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():
# 检查--test参数
is_test = "--test" in sys.argv
today = datetime.datetime.now().strftime("%Y-%m-%d")
report = f"每日新闻摘要 - {today}\n\n"
if is_test:
# 仅抓取一个链接并发送一个摘要（《纽约时报》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, "《纽约时报》（中文版）")
if ny_summaries:
if send_telegram_message(report):
print("测试摘要成功发送至Telegram。")
sys.exit(0)
else:
print("发送测试摘要至Telegram失败。")
sys.exit(1)
else:
print("未收集到新闻，未发送至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")
# --- 《纽约时报》（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=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, "《纽约时报》（中文版）")
if any([hn_summaries, gh_summaries, ny_summaries]):
if len(report) > TELEGRAM_MAX_LENGTH:
print(f"报告超过{TELEGRAM_MAX_LENGTH}字符，将被分割为多条消息。")
if send_telegram_message(report):
print("每日新闻报告成功发送至Telegram。")
sys.exit(0)
else:
print("发送每日新闻报告至Telegram失败。")
sys.exit(1)
else:
print("未收集到新闻，未发送至Telegram。")
sys.exit(1)
if __name__ == "__main__":
main()
name: 新闻机器人
on:
schedule:
# 每天北京时间上午9点（UTC凌晨1点）运行。
- cron: '0 1 * * *'
workflow_dispatch: # 允许手动触发
push:
# 仅当两个文件在同一提交/推送中更改时触发
# 这需要下面的过滤作业来检查两个文件
paths:
- scripts/nytimes/news_bot.py
- .github/workflows/news.yml
concurrency:
group: 'news'
cancel-in-progress: false
jobs:
发送新闻:
runs-on: ubuntu-latest
environment: github-pages
env:
TELEGRAM_BOT_API_KEY: $
MISTRAL_API_KEY: $
steps:
- name: 检出仓库
uses: actions/checkout@v4
with:
fetch-depth: 5
- name: 设置Python 3.10.x
uses: actions/setup-python@v4
with:
python-version: "3.10.x"
- name: 安装依赖
run: |
python -m pip install --upgrade pip
pip install -r requirements.simple.txt
- name: 运行新闻机器人脚本
run: python scripts/nytimes/news_bot.py