fix: 关闭新闻放宽凑数并剥离放宽窗口文案

Co-authored-by: Cursor <cursoragent@cursor.com>
This commit is contained in:
2026-07-14 10:42:00 +08:00
parent dcd0608b5d
commit 4a128b0fa6
5 changed files with 712 additions and 92 deletions

View File

@@ -8,17 +8,19 @@ import time
import html
import xml.etree.ElementTree as ET
from concurrent.futures import ThreadPoolExecutor, as_completed
from datetime import datetime, timezone, timedelta
from datetime import datetime, time as dt_time, timezone, timedelta
from email.utils import parsedate_to_datetime
from typing import Any
from urllib.parse import parse_qs, urlencode, urlparse, urlunparse
from zoneinfo import ZoneInfo
import certifi
import httpx
from daily.config import env, env_int, news_summary_limit
from daily.config import env, env_int, news_summary_limit, wecom_news_desc_limit
from daily.news.feeds import NEWS_CATEGORIES, NewsCategory, NewsFeed
from daily.news.feeds_cn import CN_AI_TITLE_KEYWORDS, CN_NEWS_CATEGORIES
from daily.text_utils import trim_brief
logger = logging.getLogger(__name__)
@@ -49,12 +51,37 @@ def _hours_window() -> int:
return max(1, env_int("DAILY_AI_NEWS_HOURS", 24))
def _news_tz_name() -> str:
return (env("DAILY_AI_NEWS_TZ") or env("DAILY_SCHEDULE_TZ") or "Asia/Shanghai").strip()
def _floor_today_enabled() -> bool:
raw = env("DAILY_AI_NEWS_FLOOR_TODAY")
if raw is None:
return True
return raw.strip().lower() not in {"0", "false", "no", "off"}
def _cutoff_datetime(*, floor_today: bool) -> datetime:
"""滚动 N 小时窗口;国际新闻可叠加「不早于今日 0 点(本地时区)」。"""
now = _now_utc()
rolling = now - timedelta(hours=_hours_window())
if not floor_today:
return rolling
tz = ZoneInfo(_news_tz_name())
local = now.astimezone(tz)
start_today = local.replace(hour=0, minute=0, second=0, microsecond=0).astimezone(timezone.utc)
return max(rolling, start_today)
def _per_feed_limit() -> int:
return max(1, env_int("DAILY_AI_NEWS_PER_FEED", 3))
want = max(_wecom_limit(), _wecom_cn_limit())
return max(want // 2, env_int("DAILY_AI_NEWS_PER_FEED", 5))
def _per_category_limit() -> int:
return max(1, env_int("DAILY_AI_NEWS_PER_CATEGORY", 5))
want = max(_wecom_limit(), _wecom_cn_limit())
return max(want, env_int("DAILY_AI_NEWS_PER_CATEGORY", 10))
def _wecom_limit() -> int:
@@ -62,7 +89,7 @@ def _wecom_limit() -> int:
def _wecom_cn_limit() -> int:
return max(1, env_int("DAILY_WECOM_CN_AI_NEWS", 8))
return max(1, env_int("DAILY_WECOM_CN_AI_NEWS", 10))
def _matches_cn_ai_title(title: str) -> bool:
@@ -102,7 +129,6 @@ def _parse_datetime(value: str | None) -> datetime | None:
for fmt in (
"%Y-%m-%dT%H:%M:%SZ",
"%Y-%m-%dT%H:%M:%S%z",
"%Y-%m-%d",
):
try:
dt = datetime.strptime(text[: len(fmt.replace("%z", "+0000"))], fmt.replace("%z", ""))
@@ -111,17 +137,103 @@ def _parse_datetime(value: str | None) -> datetime | None:
return dt.astimezone(timezone.utc)
except ValueError:
continue
if re.match(r"^\d{4}-\d{2}-\d{2}$", text):
try:
tz = ZoneInfo(_news_tz_name())
day = datetime.strptime(text, "%Y-%m-%d").date()
# 仅日期时按本地中午估算,避免 UTC 0 点误判为「前一天」
dt = datetime.combine(day, dt_time(12, 0), tzinfo=tz)
return dt.astimezone(timezone.utc)
except ValueError:
pass
return None
def _clean_text(text: str | None, limit: int = 200) -> str:
if not text:
return ""
plain = STRIP_HTML.sub(" ", html.unescape(text))
plain = WS.sub(" ", plain).strip()
plain = _strip_summary_plain(text)
if limit <= 0 or len(plain) <= limit:
return plain
return plain[: limit - 3] + "..."
return trim_brief(plain, limit)
def _strip_summary_plain(text: str | None) -> str:
if not text:
return ""
plain = STRIP_HTML.sub(" ", html.unescape(text))
return WS.sub(" ", plain).strip()
_JUNK_SUMMARY_RE = re.compile(
r"^(点击查看原文|article url:|comments url:|discussion on hn|read more)",
re.IGNORECASE,
)
def _is_junk_news_summary(text: str) -> bool:
if not text:
return True
if _JUNK_SUMMARY_RE.match(text.strip()):
return True
if text.strip().endswith(">") and "点击" in text:
return True
return False
def brief_news_summary(text: str | None, limit: int | None = None) -> str:
"""企微新闻一句摘要:去 HTML、过滤占位文案、句读处截断。"""
plain = _strip_summary_plain(text)
if _is_junk_news_summary(plain):
return ""
lim = wecom_news_desc_limit() if limit is None else limit
return trim_brief(plain, lim)
def sync_wecom_news_rows(items: list[dict[str, Any]], flat: list[dict[str, Any]]) -> None:
"""中文化后,用 flat 最新 summary 刷新企微 desc_short。"""
by_link = {_normalize_link(str(i.get("link") or "")): i for i in flat if i.get("link")}
for row in items:
link = _normalize_link(str(row.get("link") or ""))
src = by_link.get(link)
if src:
row["desc_short"] = brief_news_summary(src.get("summary"))
def finalize_wecom_news_items(
items: list[dict[str, Any]],
*,
force_chinese: bool = False,
) -> None:
"""企微新闻摘要:确保 desc_short 为中文(国际源 force_chinese=True"""
from daily.localize import LocalizeJob, localize_brief_descriptions, needs_chinese
from daily.news.sanitize import strip_relax_window_prefix
limit = wecom_news_desc_limit()
jobs: list[LocalizeJob] = []
keyed: list[tuple[str, dict[str, Any]]] = []
for idx, item in enumerate(items):
text = strip_relax_window_prefix(
(item.get("desc_short") or item.get("summary_plain") or "").strip()
)
if text:
item["desc_short"] = text
if not text or _is_junk_news_summary(text):
item["desc_short"] = ""
continue
if force_chinese or needs_chinese(text):
key = f"wecom-news:{item.get('link') or idx}"
jobs.append(LocalizeJob(key, text, limit))
keyed.append((key, item))
elif not item.get("desc_short"):
item["desc_short"] = brief_news_summary(text, limit)
if not jobs:
return
zh_map = localize_brief_descriptions(jobs, archive=True)
for key, item in keyed:
if key in zh_map:
item["desc_short"] = strip_relax_window_prefix(zh_map[key])
def _normalize_link(link: str) -> str:
@@ -317,10 +429,119 @@ def _dedupe_items(items: list[dict[str, Any]]) -> list[dict[str, Any]]:
return result
def _filter_flat_in_window(
flat: list[dict[str, Any]],
*,
floor_today: bool,
) -> list[dict[str, Any]]:
cutoff = _cutoff_datetime(floor_today=floor_today)
items = [i for i in _dedupe_items(flat) if _within_window(i, cutoff)]
items.sort(key=_sort_key, reverse=True)
return items
def _pick_news_items(
flat: list[dict[str, Any]],
limit: int,
preferred: tuple[str, ...],
*,
one_per_source: bool = False,
) -> list[dict[str, Any]]:
picked: list[dict[str, Any]] = []
seen_links: set[str] = set()
seen_sources: set[str] = set()
def _try_take(item: dict[str, Any]) -> bool:
link = _normalize_link(item.get("link", ""))
if not link or link in seen_links:
return False
if one_per_source:
source = item.get("source_name", "?")
if source in seen_sources:
return False
seen_sources.add(source)
seen_links.add(link)
picked.append(item)
return True
for cat in preferred:
for item in flat:
if item.get("category_id") != cat:
continue
if _try_take(item) and len(picked) >= limit:
return picked[:limit]
for item in flat:
if _try_take(item) and len(picked) >= limit:
break
return picked[:limit]
def _fill_picked_to_limit(
picked: list[dict[str, Any]],
pools: list[list[dict[str, Any]]],
limit: int,
) -> list[dict[str, Any]]:
seen_links = {_normalize_link(i.get("link", "")) for i in picked}
for pool in pools:
for item in pool:
if len(picked) >= limit:
return picked[:limit]
link = _normalize_link(item.get("link", ""))
if not link or link in seen_links:
continue
picked.append(item)
seen_links.add(link)
return picked[:limit]
def _to_wecom_news_row(item: dict[str, Any]) -> dict[str, Any]:
plain = _strip_summary_plain(item.get("summary", ""))
return {
"title": item.get("title", "?"),
"link": item.get("link", ""),
"source_name": item.get("source_name", "?"),
"published_fmt": item.get("published_fmt", ""),
"desc_short": brief_news_summary(plain),
"summary_plain": plain,
}
def _apply_pushed_dedup_with_backfill(
items: list[dict[str, Any]],
picked: list[dict[str, Any]],
*,
date_str: str | None,
limit: int,
) -> list[dict[str, Any]]:
if not date_str:
return items[:limit]
from daily.config import news_backfill_enabled
from daily.news.pushed_links import filter_unpushed_items
fresh = filter_unpushed_items(items, date_str=date_str)
if len(fresh) >= limit:
return fresh[:limit]
if not news_backfill_enabled():
if len(fresh) < limit:
logger.info("news_short:%s", len(fresh))
return fresh[:limit]
seen = {_normalize_link(i.get("link", "")) for i in fresh if i.get("link")}
for item in picked:
if len(fresh) >= limit:
break
link = _normalize_link(item.get("link", ""))
if not link or link in seen:
continue
fresh.append(_to_wecom_news_row(item))
seen.add(link)
return fresh[:limit]
def _within_window(item: dict[str, Any], cutoff: datetime) -> bool:
dt = _entry_datetime(item)
if dt is None:
return True
return False
return dt >= cutoff
@@ -331,11 +552,11 @@ def _sort_key(item: dict[str, Any]) -> tuple[int, datetime]:
return (0, dt)
def _fetch_news(categories: tuple[NewsCategory, ...]) -> dict[str, Any]:
def _fetch_news(categories: tuple[NewsCategory, ...], *, floor_today: bool = False) -> dict[str, Any]:
hours = _hours_window()
per_feed = _per_feed_limit()
per_category = _per_category_limit()
cutoff = _now_utc() - timedelta(hours=hours)
cutoff = _cutoff_datetime(floor_today=floor_today)
headers = {"User-Agent": USER_AGENT, "Accept": "application/rss+xml, application/atom+xml, application/xml, text/xml, */*"}
tasks: list[tuple[NewsCategory, NewsFeed]] = []
@@ -406,6 +627,7 @@ def _fetch_news(categories: tuple[NewsCategory, ...]) -> dict[str, Any]:
return {
"enabled": True,
"hours": hours,
"floor_today": floor_today,
"categories": categories_out,
"flat": flat,
"stats": stats,
@@ -416,7 +638,7 @@ 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)
return _fetch_news(NEWS_CATEGORIES, floor_today=_floor_today_enabled())
def fetch_cn_ai_news() -> dict[str, Any]:
@@ -459,12 +681,13 @@ def _format_news_section(
categories = news.get("categories") or []
hours = news.get("hours", 72)
floor_note = " · 仅今日" if news.get("floor_today") else ""
lines = [
"---",
"",
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",
f"> 近 **{hours}h**{floor_note} · {news.get('stats', {}).get('feeds_ok', 0)}/{news.get('stats', {}).get('feeds_total', 0)} 源可用",
"",
]
@@ -501,88 +724,23 @@ def prepare_wecom_news_items(news: dict[str, Any], *, date_str: str | None = Non
if not news.get("enabled"):
return []
limit = _wecom_limit()
flat = _dedupe_items(news.get("flat") or [])
flat.sort(key=_sort_key, reverse=True)
floor = bool(news.get("floor_today", _floor_today_enabled()))
flat_strict = _filter_flat_in_window(news.get("flat") or [], floor_today=floor)
flat_relaxed = _filter_flat_in_window(news.get("flat") or [], floor_today=False)
preferred = ("media", "newsletter", "official", "community", "research", "developer")
picked: list[dict[str, Any]] = []
seen: set[str] = set()
for cat in preferred:
for item in flat:
link = _normalize_link(item.get("link", ""))
if item.get("category_id") != cat or link in seen:
continue
picked.append(item)
seen.add(link)
if len(picked) >= limit:
break
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),
}
)
if date_str:
from daily.news.pushed_links import filter_unpushed_items
items = filter_unpushed_items(items, date_str=date_str)
return items
picked = _pick_news_items(flat_strict, limit, preferred)
picked = _fill_picked_to_limit(picked, [flat_relaxed, news.get("flat") or []], limit)
items = [_to_wecom_news_row(item) for item in picked[:limit]]
return _apply_pushed_dedup_with_backfill(items, picked, date_str=date_str, limit=limit)
def prepare_wecom_cn_news_items(news: dict[str, Any], *, date_str: str | None = None) -> 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),
}
)
if date_str:
from daily.news.pushed_links import filter_unpushed_items
items = filter_unpushed_items(items, date_str=date_str)
return items
flat = _filter_flat_in_window(news.get("flat") or [], floor_today=False)
preferred = ("media", "tech")
picked = _pick_news_items(flat, limit, preferred, one_per_source=True)
picked = _fill_picked_to_limit(picked, [news.get("flat") or []], limit)
items = [_to_wecom_news_row(item) for item in picked[:limit]]
return _apply_pushed_dedup_with_backfill(items, picked, date_str=date_str, limit=limit)

324
daily/news/research.py Normal file
View File

@@ -0,0 +1,324 @@
"""Cursor SDK + deep-research 工作流:采集 AI 时讯(方案 A内置 WebSearch"""
from __future__ import annotations
import json
import logging
from datetime import datetime, timezone, timedelta
from pathlib import Path
from typing import Any
from urllib.parse import urlparse
from daily.config import OUTPUT_DIR, ROOT, env, env_int, wecom_ai_news_tech_limit
from daily.llm_client import cursor_agent_prompt, extract_json_object, has_cursor_configured
from daily.news.fetch import brief_news_summary, _normalize_link
from daily.news.pushed_links import filter_unpushed_items
logger = logging.getLogger(__name__)
_SKILL_DIR = ROOT / "skills" / "daily-ai-news-research"
_DEEP_RESEARCH_CANDIDATES = (
ROOT / "skills" / "deep-research" / "SKILL.md",
Path.home() / ".agents" / "skills" / "deep-research" / "SKILL.md",
Path.home() / ".cursor" / "skills" / "deep-research" / "SKILL.md",
)
def ai_news_mode() -> str:
return (env("DAILY_AI_NEWS_MODE") or "rss").strip().lower()
def is_research_mode() -> bool:
return ai_news_mode() == "research"
def research_hours() -> int:
return max(1, env_int("DAILY_AI_NEWS_HOURS", 24))
def research_limit() -> int:
return max(1, env_int("DAILY_WECOM_AI_NEWS", 10))
def research_json_path(date_str: str) -> Path:
return OUTPUT_DIR / f"{date_str}.ai-news-research.json"
def _save_research_json(path: Path, data: dict[str, Any]) -> None:
path.parent.mkdir(parents=True, exist_ok=True)
path.write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")
def _load_skill() -> str:
parts: list[str] = []
for path in _DEEP_RESEARCH_CANDIDATES:
if path.exists():
parts.append(path.read_text(encoding="utf-8").strip())
break
local = _SKILL_DIR / "SKILL.md"
if local.exists():
parts.append(local.read_text(encoding="utf-8").strip())
if not parts:
return "你是 AI 时讯调研员,只输出 JSON。"
return "\n\n---\n\n".join(parts)
def _guess_source_name(link: str, explicit: str) -> str:
name = (explicit or "").strip()
if name:
return name
host = urlparse(link).netloc.lower().removeprefix("www.")
mapping = {
"techcrunch.com": "TechCrunch",
"theverge.com": "The Verge",
"openai.com": "OpenAI",
"anthropic.com": "Anthropic",
"arxiv.org": "arXiv",
"qbitai.com": "量子位",
"36kr.com": "36氪",
"leiphone.com": "雷锋网",
}
for key, label in mapping.items():
if host.endswith(key) or key in host:
return label
return host.split(".")[0].capitalize() if host else "?"
def _normalize_research_item(raw: dict[str, Any]) -> dict[str, Any] | None:
title = str(raw.get("title") or "").strip()
link = _normalize_link(str(raw.get("link") or ""))
if not title or not link or not link.startswith("http"):
return None
desc = brief_news_summary(str(raw.get("desc_short") or raw.get("summary") or ""))
return {
"title": title,
"link": link,
"source_name": _guess_source_name(link, str(raw.get("source_name") or "")),
"published_fmt": str(raw.get("published_fmt") or "").strip(),
"desc_short": desc,
"summary_plain": desc,
}
def research_tech_limit() -> int:
return wecom_ai_news_tech_limit()
def _parse_items_array(
items_raw: Any,
*,
limit: int,
seen: set[str],
) -> list[dict[str, Any]]:
if not isinstance(items_raw, list):
return []
out: list[dict[str, Any]] = []
for row in items_raw:
if not isinstance(row, dict):
continue
item = _normalize_research_item(row)
if not item:
continue
if item["link"] in seen:
continue
seen.add(item["link"])
out.append(item)
if len(out) >= limit:
break
return out
def parse_research_response(
raw: str,
*,
limit: int,
tech_limit: int = 0,
) -> tuple[list[dict[str, Any]], list[dict[str, Any]]]:
parsed = extract_json_object(raw)
seen: set[str] = set()
items = _parse_items_array(parsed.get("items"), limit=limit, seen=seen)
tech_items = _parse_items_array(parsed.get("tech_items"), limit=tech_limit, seen=seen) if tech_limit else []
return items, tech_items
def _apply_pushed_dedup(items: list[dict[str, Any]], *, date_str: str, limit: int) -> list[dict[str, Any]]:
from daily.config import news_backfill_enabled
from daily.news.sanitize import strip_relax_window_prefix
for item in items:
if item.get("desc_short"):
item["desc_short"] = strip_relax_window_prefix(str(item.get("desc_short") or ""))
fresh = filter_unpushed_items(items, date_str=date_str)
if len(fresh) >= limit:
return fresh[:limit]
if not news_backfill_enabled():
if len(fresh) < limit:
logger.info("news_short:%s", len(fresh))
return fresh[:limit]
seen = {i.get("link") for i in fresh}
for item in items:
if len(fresh) >= limit:
break
if item.get("link") not in seen:
fresh.append(item)
seen.add(item.get("link"))
return fresh[:limit]
def fetch_ai_news_research(
*,
date_str: str,
hours: int | None = None,
limit: int | None = None,
) -> dict[str, Any]:
"""Cursor Agent 调研 AI 时讯;返回 {enabled, mode, hours, items, flat, stats}。"""
h = hours if hours is not None else research_hours()
lim = limit if limit is not None else research_limit()
tech_lim = research_tech_limit()
if not has_cursor_configured():
logger.warning("DAILY_AI_NEWS_MODE=research 但未配置 CURSOR_API_KEY")
return {
"enabled": False,
"mode": "research",
"items": [],
"tech_items": [],
"flat": [],
"stats": {"error": "no_cursor_key"},
}
skill = _load_skill()
now_cst = datetime.now(timezone(timedelta(hours=8)))
tech_clause = ""
if tech_lim:
tech_clause = (
f"\n另输出 **tech_items 恰好 {tech_lim} 条**,聚焦工程技术:"
"模型/框架发布、开源项目、芯片算力、开发者工具、推理与工程实践。"
"与 items 不得重复 link。"
)
system = (
f"{skill}\n\n"
"当前执行 **早报 AI 时讯调研**。\n"
f"时间窗口:近 **{h}** 小时(截至 {now_cst.strftime('%Y-%m-%d %H:%M')} UTC+8\n"
f"输出 **恰好 {lim} 条** items按重要性排序。{tech_clause}\n"
"使用 WebSearch 检索;不要读取本项目文档或 RSS 配置。"
)
user = (
f"/deep-research 获取近 {h} 小时的 AI 人工智能新闻资讯,"
"不区分国内国外,合并精选。"
f"只输出 JSONitems 长度={lim}"
+ (f"tech_items 长度={tech_lim}" if tech_lim else "")
+ ""
)
try:
raw = cursor_agent_prompt(system, user)
except Exception as exc:
logger.warning("AI 时讯 research 失败:%s", exc)
return {
"enabled": False,
"mode": "research",
"items": [],
"tech_items": [],
"flat": [],
"stats": {"error": str(exc)},
}
if not raw:
return {
"enabled": False,
"mode": "research",
"items": [],
"tech_items": [],
"flat": [],
"stats": {"error": "empty_response"},
}
items, tech_items = parse_research_response(raw, limit=lim, tech_limit=tech_lim)
payload = extract_json_object(raw)
if payload:
_save_research_json(research_json_path(date_str), payload)
if not items and not tech_items:
logger.warning("AI 时讯 research JSON 无效或无条目")
return {
"enabled": False,
"mode": "research",
"items": [],
"tech_items": [],
"flat": [],
"stats": {"error": "invalid_json"},
}
items = _apply_pushed_dedup(items, date_str=date_str, limit=lim)
if tech_items:
tech_items = _apply_pushed_dedup(tech_items, date_str=date_str, limit=tech_lim)
logger.info("AI 时讯 research 完成:%d 条 + %d 技术", len(items), len(tech_items))
flat = [
{
"title": i["title"],
"link": i["link"],
"summary": i.get("summary_plain") or i.get("desc_short") or "",
"source_name": i["source_name"],
"published_fmt": i.get("published_fmt") or "",
"category_id": "research",
"category_name": "Deep Research",
"category_icon": "🔍",
}
for i in items + tech_items
]
return {
"enabled": True,
"mode": "research",
"hours": h,
"items": items,
"tech_items": tech_items,
"flat": flat,
"stats": {"source": "cursor_research", "items": len(items), "tech_items": len(tech_items)},
}
def format_research_news_section(
research: dict[str, Any],
*,
section_no: int,
wecom_limit: int | None = None,
) -> list[str]:
if not research.get("enabled"):
hint = research.get("stats", {}).get("error", "调研失败或未配置 CURSOR_API_KEY")
return [
"---",
"",
f"## {section_no}、AI 时讯精选Deep Research",
"",
f"*不可用:{hint}*",
"",
]
hours = research.get("hours", 24)
items = (research.get("flat") or [])[: wecom_limit or research_limit()]
lines = [
"---",
"",
f"## {section_no}、AI 时讯精选Deep Research",
"",
f"> 近 **{hours}h** · Cursor Agent WebSearch · {len(items)}",
"",
]
if not items:
lines.append("*暂无可用条目。*")
lines.append("")
return lines
for i, item in enumerate(items, 1):
pub = f" · {item['published_fmt']}" if item.get("published_fmt") else ""
lines.append(
f"{i}. **[{item['title']}]({item['link']})** · `{item['source_name']}`{pub}"
)
summary = item.get("summary") or ""
if summary:
lines.append(f" - {summary}")
lines.append("")
return lines

18
daily/news/sanitize.py Normal file
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"""新闻文案清洗:剥离「放宽窗口」类凑数前缀。"""
from __future__ import annotations
import re
_RELAX_PREFIX = re.compile(
r"^(?:放宽窗口|放宽至[^:]*)\s*[:]\s*",
re.UNICODE,
)
def strip_relax_window_prefix(text: str) -> str:
"""去掉开头的「放宽窗口:」/「放宽至…:」前缀。"""
raw = (text or "").strip()
if not raw:
return ""
return _RELAX_PREFIX.sub("", raw, count=1).strip()

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# AI 时讯 Deep Research早报专用
你是 **AI 时讯调研员**。使用 **WebSearch** 与网页抓取工具,收集近 N 小时全球 AI 新闻(不区分国内/国外),输出供企微早报使用的结构化 JSON。
## 工作流
1. 将任务拆成 35 个子问题(模型发布、监管政策、大厂动态、芯片算力、研究突破等)
2. 每个子问题用 WebSearch 检索 23 组关键词(中英文混合)
3. 交叉验证:优先权威媒体 / 官方博客 / 学术来源
4. 精选最多 **10 条**最重要、可核实的新闻(`items`);窗口内不足则少返回,勿凑数
5. 另精选最多 **5 条**工程技术向新闻(`tech_items`):模型/框架发布、开源、芯片算力、开发者工具、推理与工程实践;不得与 `items` 重复 link不足则少返回
6. **只输出 JSON**,不要 Markdown 报告,不要代码块
## 质量规则
1. 每条必须有可访问的 `link`https://
2. 禁止编造未在搜索结果中出现的事实
3. 优先近 N 小时内的新闻;若不足目标条数,**少返回**即可,禁止放宽至 48 小时凑数,禁止在 `desc_short` 标注「放宽窗口」
4. `desc_short` 用中文一句话摘要≤72 字)
5. `title` 保留原文标题;中文源可用中文标题
6. `source_name` 为媒体/站点简称(如 TechCrunch、量子位、OpenAI Blog
## 输出格式(严格 JSON
```json
{
"items": [
{
"title": "Apple sues OpenAI over trade secret theft",
"link": "https://techcrunch.com/...",
"source_name": "TechCrunch",
"desc_short": "苹果起诉 OpenAI 涉嫌窃取硬件商业机密",
"published_fmt": "07-11 05:00"
}
],
"tech_items": [
{
"title": "Meta Iris AI chip enters production",
"link": "https://example.com/...",
"source_name": "TechCrunch",
"desc_short": "Meta 自研 Iris 芯片 9 月量产",
"published_fmt": ""
}
],
"methodology": "检索 6 组 query分析 12 源,子问题:诉讼、模型安全、监管"
}
```
- `items` 数组长度 **必须等于** 请求的 limit默认 10
- `tech_items` 数组长度 **必须等于** 请求的 tech limit默认 5聚焦工程技术可与 `items` 主题重叠但 link 不得重复
- `published_fmt` 格式 `MM-DD HH:MM`UTC+8无法确定则留空字符串
- 不要输出 `items` 以外的长文;`methodology` 可选,一行即可
## 禁止
- 不要输出 ```json 代码块包裹(直接输出 JSON 对象)
- 不要输出 Executive Summary / Key Takeaways 等报告章节
- 不要使用本项目 RSS 或本地文档作为来源

62
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# tests/test_news_relax.py
from __future__ import annotations
import os
import unittest
from unittest.mock import patch
class NewsRelaxTests(unittest.TestCase):
def test_strip_relax_prefix(self):
from daily.news.sanitize import strip_relax_window_prefix
self.assertEqual(
strip_relax_window_prefix("放宽窗口:苹果起诉 OpenAI"),
"苹果起诉 OpenAI",
)
self.assertEqual(
strip_relax_window_prefix("放宽至48小时某新闻"),
"某新闻",
)
self.assertEqual(
strip_relax_window_prefix("正常摘要无前缀"),
"正常摘要无前缀",
)
def test_backfill_disabled_does_not_reinsert_pushed(self):
from daily.news.fetch import _apply_pushed_dedup_with_backfill
fresh_only = [
{
"link": "https://example.com/fresh",
"title": "fresh",
"source_name": "S",
"published_fmt": "07-14",
"desc_short": "",
"summary_plain": "",
}
]
picked = [
{
"link": "https://example.com/old",
"title": "old",
"source_name": "S",
"published": "2026-07-13T10:00:00+00:00",
"summary": "旧闻",
}
]
with patch("daily.news.pushed_links.filter_unpushed_items", return_value=list(fresh_only)):
with patch.dict(os.environ, {"DAILY_NEWS_BACKFILL": "0"}, clear=False):
out = _apply_pushed_dedup_with_backfill(
fresh_only + [{"link": "https://example.com/old", "title": "old"}],
picked,
date_str="2026-07-14",
limit=5,
)
links = [x.get("link") for x in out]
self.assertIn("https://example.com/fresh", links)
self.assertNotIn("https://example.com/old", links)
if __name__ == "__main__":
unittest.main()