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国内AI时讯

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This commit is contained in:
王礼
2026-07-02 15:10:37 +08:00
parent eef4c76e3f
commit 1dc2fed5fa
10 changed files with 305 additions and 37 deletions
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7
daily/format_wecom.py
View File

@@ -18,6 +18,7 @@ ICONS = {
"emerging": "🌱",
"topic": "🤖",
"ainews": "🌍",
"cnainews": "🇨🇳",
"pick": "📦",
"theme": "🎯",
"file": "📄",
@@ -231,6 +232,7 @@ def build_wecom_report(
topic_name: str,
topic_repos: list[dict[str, Any]],
ai_news: list[dict[str, Any]] | None = None,
cn_ai_news: list[dict[str, Any]] | None = None,
pick_command: str,
) -> str:
lines = [
@@ -250,6 +252,11 @@ def build_wecom_report(
lines.extend(_ai_news_lines(ai_news))
lines.append("")
if cn_ai_news:
lines.append(f"{ICONS['cnainews']} **国内 AI 时讯 Top {len(cn_ai_news)}**")
lines.extend(_ai_news_lines(cn_ai_news))
lines.append("")
lines.append(f"{ICONS['trending']} **Skills Trending Top {len(trending)}**")
for rank, item in enumerate(trending, 1):
lines.extend(_skill_line(rank, item, badge=item.get("badge", "")))

38
daily/generate.py
View File

@@ -42,7 +42,14 @@ from daily.github.auth import github_html_headers
from daily.github.search import fetch_emerging_repos, fetch_topic_hot_repos
from daily.github.trending import fetch_github_trending, trending_data_source_note
from daily.localize import LocalizeJob, localize_descriptions, needs_chinese
from daily.news.fetch import fetch_ai_news, format_news_section, prepare_wecom_news_items
from daily.news.fetch import (
fetch_ai_news,
fetch_cn_ai_news,
format_cn_news_section,
format_news_section,
prepare_wecom_cn_news_items,
prepare_wecom_news_items,
)
from daily.report_data import (
build_full_payload,
build_llm_input,
@@ -90,6 +97,7 @@ def _localize_descriptions_in_place(
github_emerging: list[dict[str, Any]],
github_topic: list[dict[str, Any]],
ai_news: dict[str, Any],
cn_ai_news: dict[str, Any] | None = None,
) -> None:
full_limit = full_desc_limit()
news_limit = news_summary_limit()
@@ -264,6 +272,7 @@ def _build_highlights(
github_trending: list[dict[str, Any]],
github_emerging: list[dict[str, Any]],
ai_news: dict[str, Any] | None = None,
cn_ai_news: dict[str, Any] | None = None,
) -> list[str]:
points: list[str] = []
if ai_news and ai_news.get("enabled"):
@@ -278,6 +287,20 @@ def _build_highlights(
n0 = ai_news["flat"][0]
pub = f" · {n0['published_fmt']}" if n0.get("published_fmt") else ""
points.append(f"🌍 AI 时讯 [{n0['title']}]({n0['link']})（`{n0.get('source_name', '?')}`{pub}）")
if cn_ai_news and cn_ai_news.get("enabled"):
top_cn = prepare_wecom_cn_news_items(cn_ai_news)
if top_cn:
n0 = top_cn[0]
pub = f" · {n0['published_fmt']}" if n0.get("published_fmt") else ""
points.append(
f"🇨🇳 国内 AI [{n0['title']}]({n0['link']})（`{n0.get('source_name', '?')}`{pub}）"
)
elif cn_ai_news.get("flat"):
n0 = cn_ai_news["flat"][0]
pub = f" · {n0['published_fmt']}" if n0.get("published_fmt") else ""
points.append(
f"🇨🇳 国内 AI [{n0['title']}]({n0['link']})（`{n0.get('source_name', '?')}`{pub}）"
)
if trending:
t0 = trending[0]
points.append(f"📈 Skills 榜首 **{t0.get('title')}**（{_format_installs(t0.get('installs', 0))}）")
@@ -418,6 +441,7 @@ def generate_report() -> tuple[str, str, Path, Path]:
seen_repos.update(r["repo"] for r in github_emerging)
topic_name, github_topic = fetch_topic_hot_repos(topic_fetch_n, exclude=seen_repos)
ai_news = fetch_ai_news()
cn_ai_news = fetch_cn_ai_news()
wecom_limits = {
"trending": wecom_trending,
@@ -428,6 +452,7 @@ def generate_report() -> tuple[str, str, Path, Path]:
"emerging": wecom_emerging,
"topic": wecom_topic,
"ai_news": env_int("DAILY_WECOM_AI_NEWS", 10),
"cn_ai_news": env_int("DAILY_WECOM_CN_AI_NEWS", 8),
}
llm_input = build_llm_input(
date_str=date_str,
@@ -439,6 +464,7 @@ def generate_report() -> tuple[str, str, Path, Path]:
github_topic=github_topic,
topic_name=topic_name,
ai_news=ai_news,
cn_ai_news=cn_ai_news,
wecom_limits=wecom_limits,
)
save_json(
@@ -476,6 +502,7 @@ def generate_report() -> tuple[str, str, Path, Path]:
github_emerging=github_emerging,
github_topic=github_topic,
ai_news=ai_news,
cn_ai_news=cn_ai_news,
descriptions=editorial.get("descriptions") or {},
)
editorial_theme = theme_line_from_editorial(editorial) or None
@@ -484,7 +511,7 @@ def generate_report() -> tuple[str, str, Path, Path]:
# 完整版归档：中文化 + 加长摘要（已是中文的条目会跳过翻译）
_localize_descriptions_in_place(
trending, hot, github_trending, github_emerging, github_topic, ai_news
trending, hot, github_trending, github_emerging, github_topic, ai_news, cn_ai_news
)
themes = _theme_clusters(feed)
@@ -494,7 +521,7 @@ def generate_report() -> tuple[str, str, Path, Path]:
"",
f"> 生成时间：{now.strftime('%Y-%m-%d %H:%M')} (UTC+8) ",
f"> skills 数据更新：{updated} ",
"> 数据来源：[skills.sh/trending](https://skills.sh/trending) · [skills.sh/hot](https://skills.sh/hot) · 国际 AI RSS",
"> 数据来源：[skills.sh/trending](https://skills.sh/trending) · [skills.sh/hot](https://skills.sh/hot) · 国际/国内 AI RSS",
"",
"---",
"",
@@ -538,6 +565,8 @@ def generate_report() -> tuple[str, str, Path, Path]:
section_no = 6
lines.extend(format_news_section(ai_news, section_no=section_no))
section_no += 1
lines.extend(format_cn_news_section(cn_ai_news, section_no=section_no))
section_no += 1
watch = (env("GITHUB_REPOS") or "").strip()
if watch:
@@ -581,9 +610,10 @@ def generate_report() -> tuple[str, str, Path, Path]:
time_str=time_str,
updated=updated,
highlights=editorial_highlights
or _build_highlights(trending, hot, github_trending, github_emerging, ai_news),
or _build_highlights(trending, hot, github_trending, github_emerging, ai_news, cn_ai_news),
theme_line=editorial_theme or _detect_theme_line(feed),
ai_news=prepare_wecom_news_items(ai_news),
cn_ai_news=prepare_wecom_cn_news_items(cn_ai_news),
trending=[
_prepare_skill_item(item, prev_ids, r)
for r, item in enumerate(

14
daily/news/__init__.py
View File

@@ -1,3 +1,13 @@
from daily.news.fetch import fetch_ai_news, format_news_section
from daily.news.fetch import (
fetch_ai_news,
fetch_cn_ai_news,
format_cn_news_section,
format_news_section,
)
__all__ = ["fetch_ai_news", "format_news_section"]
__all__ = [
"fetch_ai_news",
"fetch_cn_ai_news",
"format_news_section",
"format_cn_news_section",
]

1
daily/news/feeds.py
View File

@@ -10,6 +10,7 @@ class NewsFeed:
name: str
url: str
slow: bool = False # 限速源（如 Reddit）串行抓取
ai_filter: bool = False # 综合源仅保留标题命中 AI 关键词的条目
@dataclass(frozen=True)

71
daily/news/feeds_cn.py Normal file
View File

@@ -0,0 +1,71 @@
"""国内 AI 时讯 RSS 源定义（按类别分组）。"""
from __future__ import annotations
from daily.news.feeds import NewsCategory, NewsFeed
# 综合源 ai_filter=True 时，仅保留标题命中以下词之一的条目
CN_AI_TITLE_KEYWORDS: tuple[str, ...] = (
"人工智能",
"大模型",
"智能体",
"多模态",
"AIGC",
"LLM",
"GPT",
"Claude",
"Gemini",
"ChatGPT",
"OpenAI",
"Anthropic",
"Copilot",
"Agent",
"AI ",
" AI",
"AI·",
"AI业务",
"AI模型",
"AI助手",
"AI工具",
"AI编程",
"AI 编程",
"AI版",
"AI Agent",
"推理模型",
"深度学习",
"机器学习",
"Function Calling",
)
CN_NEWS_CATEGORIES: tuple[NewsCategory, ...] = (
NewsCategory(
id="media",
name="AI 专业媒体",
icon="📰",
feeds=(
NewsFeed("量子位", "https://www.qbitai.com/feed"),
NewsFeed("InfoQ 中文", "https://www.infoq.cn/feed/AI"),
),
),
NewsCategory(
id="tech",
name="综合科技",
icon="📱",
feeds=(
NewsFeed("36氪", "https://36kr.com/feed", ai_filter=True),
NewsFeed("雷锋网", "https://www.leiphone.com/feed"),
NewsFeed(
"Google News · AI",
"https://news.google.com/rss/search?q=人工智能+OR+大模型+OR+Agent+OR+LLM&hl=zh-CN&gl=CN&ceid=CN:zh-Hans",
),
),
),
NewsCategory(
id="dev",
name="开发者社区",
icon="💻",
feeds=(
NewsFeed("掘金", "https://juejin.cn/rss", ai_filter=True),
),
),
)

168
daily/news/fetch.py
View File

@@ -1,4 +1,4 @@
"""抓取并整理国际 AI 时讯 RSS。"""
"""抓取并整理国际 / 国内 AI 时讯 RSS。"""
from __future__ import annotations
@@ -17,7 +17,8 @@ import certifi
import httpx
from daily.config import env, env_int, news_summary_limit
from daily.news.feeds import NEWS_CATEGORIES, NewsCategory
from daily.news.feeds import NEWS_CATEGORIES, NewsCategory, NewsFeed
from daily.news.feeds_cn import CN_AI_TITLE_KEYWORDS, CN_NEWS_CATEGORIES
logger = logging.getLogger(__name__)
@@ -39,6 +40,11 @@ def _enabled() -> bool:
return raw not in {"0", "false", "no", "off"}
def _cn_enabled() -> bool:
raw = (env("DAILY_CN_AI_NEWS") or "1").strip().lower()
return raw not in {"0", "false", "no", "off"}
def _hours_window() -> int:
return max(1, env_int("DAILY_AI_NEWS_HOURS", 72))
@@ -55,6 +61,27 @@ def _wecom_limit() -> int:
return max(1, env_int("DAILY_WECOM_AI_NEWS", 10))
def _wecom_cn_limit() -> int:
return max(1, env_int("DAILY_WECOM_CN_AI_NEWS", 8))
def _matches_cn_ai_title(title: str) -> bool:
text = title.strip()
if not text:
return False
lower = text.lower()
for keyword in CN_AI_TITLE_KEYWORDS:
if keyword.lower() in lower:
return True
return False
def _filter_ai_entries(entries: list[dict[str, Any]], *, ai_filter: bool) -> list[dict[str, Any]]:
if not ai_filter:
return entries
return [item for item in entries if _matches_cn_ai_title(item.get("title", ""))]
def _now_utc() -> datetime:
return datetime.now(timezone.utc)
@@ -255,18 +282,23 @@ def _reddit_fetch_urls(feed_url: str) -> list[str]:
return [primary, fallback]
def _fetch_one(client: httpx.Client, category: NewsCategory, feed_url: str, feed_name: str) -> list[dict[str, Any]]:
def _fetch_one(
client: httpx.Client,
category: NewsCategory,
feed: NewsFeed,
) -> list[dict[str, Any]]:
last_exc: Exception | None = None
for url in _reddit_fetch_urls(feed_url):
for url in _reddit_fetch_urls(feed.url):
try:
headers = _request_headers(dict(client.headers), url)
resp = client.get(url, headers=headers)
resp.raise_for_status()
return _parse_feed(resp.text, feed_name, category)
entries = _parse_feed(resp.text, feed.name, category)
return _filter_ai_entries(entries, ai_filter=feed.ai_filter)
except Exception as exc:
last_exc = exc
continue
logger.warning("RSS fetch failed [%s] %s: %s", feed_name, feed_url, last_exc)
logger.warning("RSS fetch failed [%s] %s: %s", feed.name, feed.url, last_exc)
return []
@@ -299,33 +331,29 @@ def _sort_key(item: dict[str, Any]) -> tuple[int, datetime]:
return (0, dt)
def fetch_ai_news() -> dict[str, Any]:
"""按类别抓取 AI 时讯，返回 {enabled, hours, categories, flat, stats}。"""
if not _enabled():
return {"enabled": False, "categories": [], "flat": [], "stats": {}}
def _fetch_news(categories: tuple[NewsCategory, ...]) -> dict[str, Any]:
hours = _hours_window()
per_feed = _per_feed_limit()
per_category = _per_category_limit()
cutoff = _now_utc() - timedelta(hours=hours)
headers = {"User-Agent": USER_AGENT, "Accept": "application/rss+xml, application/atom+xml, application/xml, text/xml, */*"}
tasks: list[tuple[NewsCategory, str, str, bool]] = []
for category in NEWS_CATEGORIES:
tasks: list[tuple[NewsCategory, NewsFeed]] = []
for category in categories:
for feed in category.feeds:
tasks.append((category, feed.url, feed.name, feed.slow))
tasks.append((category, feed))
raw_by_category: dict[str, list[dict[str, Any]]] = {c.id: [] for c in NEWS_CATEGORIES}
raw_by_category: dict[str, list[dict[str, Any]]] = {c.id: [] for c in categories}
stats = {"feeds_total": len(tasks), "feeds_ok": 0, "items_raw": 0}
with httpx.Client(timeout=15.0, verify=certifi.where(), follow_redirects=True, headers=headers) as client:
fast_tasks = [t for t in tasks if not t[3]]
slow_tasks = [t for t in tasks if t[3]]
fast_tasks = [t for t in tasks if not t[1].slow]
slow_tasks = [t for t in tasks if t[1].slow]
with ThreadPoolExecutor(max_workers=8) as pool:
futures = {
pool.submit(_fetch_one, client, cat, url, name): (cat.id, name)
for cat, url, name, _slow in fast_tasks
pool.submit(_fetch_one, client, cat, feed): (cat.id, feed.name)
for cat, feed in fast_tasks
}
for future in as_completed(futures):
cat_id, feed_name = futures[future]
@@ -339,13 +367,13 @@ def fetch_ai_news() -> dict[str, Any]:
stats["items_raw"] += len(entries)
raw_by_category[cat_id].extend(entries[:per_feed])
for cat, url, name, _slow in slow_tasks:
entries = _fetch_one(client, cat, url, name)
for cat, feed in slow_tasks:
entries = _fetch_one(client, cat, feed)
if entries:
stats["feeds_ok"] += 1
stats["items_raw"] += len(entries)
raw_by_category[cat.id].extend(entries[:per_feed])
if _is_reddit_url(url):
if _is_reddit_url(feed.url):
time.sleep(2.0)
else:
time.sleep(1.0)
@@ -353,7 +381,7 @@ def fetch_ai_news() -> dict[str, Any]:
categories_out: list[dict[str, Any]] = []
flat: list[dict[str, Any]] = []
for category in NEWS_CATEGORIES:
for category in categories:
items = raw_by_category[category.id]
items = [i for i in items if _within_window(i, cutoff)]
items.sort(key=_sort_key, reverse=True)
@@ -384,16 +412,57 @@ def fetch_ai_news() -> dict[str, Any]:
}
def fetch_ai_news() -> dict[str, Any]:
"""按类别抓取国际 AI 时讯，返回 {enabled, hours, categories, flat, stats}。"""
if not _enabled():
return {"enabled": False, "categories": [], "flat": [], "stats": {}}
return _fetch_news(NEWS_CATEGORIES)
def fetch_cn_ai_news() -> dict[str, Any]:
"""按类别抓取国内 AI 时讯，返回 {enabled, hours, categories, flat, stats}。"""
if not _cn_enabled():
return {"enabled": False, "categories": [], "flat": [], "stats": {}}
return _fetch_news(CN_NEWS_CATEGORIES)
def format_news_section(news: dict[str, Any], *, section_no: int, wecom_limit: int | None = None) -> list[str]:
return _format_news_section(
news,
section_no=section_no,
title="国际 AI 时讯",
disabled_hint="AI 时讯已关闭（`DAILY_AI_NEWS=0`）。",
wecom_limit=wecom_limit,
)
def format_cn_news_section(news: dict[str, Any], *, section_no: int, wecom_limit: int | None = None) -> list[str]:
return _format_news_section(
news,
section_no=section_no,
title="国内 AI 时讯",
disabled_hint="国内 AI 时讯已关闭（`DAILY_CN_AI_NEWS=0`）。",
wecom_limit=wecom_limit,
)
def _format_news_section(
news: dict[str, Any],
*,
section_no: int,
title: str,
disabled_hint: str,
wecom_limit: int | None = None,
) -> list[str]:
if not news.get("enabled"):
return ["---", "", f"## {section_no}、国际 AI 时讯", "", "*AI 时讯已关闭（`DAILY_AI_NEWS=0`）。*", ""]
return ["---", "", f"## {section_no}、{title}", "", f"*{disabled_hint}*", ""]
categories = news.get("categories") or []
hours = news.get("hours", 72)
lines = [
"---",
"",
f"## {section_no}、国际 AI 时讯",
f"## {section_no}、{title}",
"",
f"> 近 **{hours}h** · {news.get('stats', {}).get('feeds_ok', 0)}/{news.get('stats', {}).get('feeds_total', 0)} 源可用",
"",
@@ -460,3 +529,52 @@ def prepare_wecom_news_items(news: dict[str, Any]) -> list[dict[str, Any]]:
}
)
return items
def prepare_wecom_cn_news_items(news: dict[str, Any]) -> list[dict[str, Any]]:
if not news.get("enabled"):
return []
limit = _wecom_cn_limit()
flat = _dedupe_items(news.get("flat") or [])
flat.sort(key=_sort_key, reverse=True)
preferred = ("media", "tech", "dev")
picked: list[dict[str, Any]] = []
seen_links: set[str] = set()
seen_sources: set[str] = set()
for cat in preferred:
for item in flat:
link = _normalize_link(item.get("link", ""))
source = item.get("source_name", "?")
if item.get("category_id") != cat or not link or link in seen_links or source in seen_sources:
continue
picked.append(item)
seen_links.add(link)
seen_sources.add(source)
if len(picked) >= limit:
break
if len(picked) >= limit:
break
if len(picked) < limit:
for item in flat:
link = _normalize_link(item.get("link", ""))
if not link or link in seen_links:
continue
picked.append(item)
seen_links.add(link)
if len(picked) >= limit:
break
items: list[dict[str, Any]] = []
for item in picked[:limit]:
items.append(
{
"title": item.get("title", "?"),
"link": item.get("link", ""),
"source_name": item.get("source_name", "?"),
"published_fmt": item.get("published_fmt", ""),
"desc_short": _clean_text(item.get("summary", ""), 36),
}
)
return items

18
daily/report_data.py
View File

@@ -8,7 +8,7 @@ from typing import Any
from daily.config import OUTPUT_DIR, env_int
from daily.delta import build_movement_baseline, build_movement_context, compare_depth
from daily.news.fetch import prepare_wecom_news_items
from daily.news.fetch import prepare_wecom_cn_news_items, prepare_wecom_news_items
from daily.skills_group import group_skills_by_source
@@ -54,9 +54,14 @@ def _slim_github(item: dict[str, Any]) -> dict[str, Any]:
}
def _slim_news_items(ai_news: dict[str, Any], limit: int) -> list[dict[str, Any]]:
def _slim_news_items(
ai_news: dict[str, Any],
limit: int,
*,
prepare=prepare_wecom_news_items,
) -> list[dict[str, Any]]:
items: list[dict[str, Any]] = []
for item in prepare_wecom_news_items(ai_news):
for item in prepare(ai_news):
items.append(
{
"link": item.get("link", ""),
@@ -98,10 +103,12 @@ def build_llm_input(
github_topic: list[dict[str, Any]],
topic_name: str,
ai_news: dict[str, Any],
cn_ai_news: dict[str, Any],
wecom_limits: dict[str, int],
) -> dict[str, Any]:
"""供 Cursor 编辑的精简 JSON（不含完整 markdown）。"""
news_limit = wecom_limits.get("ai_news", 10)
cn_news_limit = wecom_limits.get("cn_ai_news", 8)
depth = compare_depth()
trend_cmp = trending[:depth]
hot_cmp = hot[:depth]
@@ -153,6 +160,11 @@ def build_llm_input(
"repos": [_slim_github(x) for x in topic_slice],
},
"ai_news": _slim_news_items(ai_news, news_limit) if ai_news.get("enabled") else [],
"cn_ai_news": _slim_news_items(
cn_ai_news, cn_news_limit, prepare=prepare_wecom_cn_news_items
)
if cn_ai_news.get("enabled")
else [],
"movement": movement,
"movement_baseline": movement_baseline,
}