229 lines
8.1 KiB
Python
229 lines
8.1 KiB
Python
import re
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from collections import Counter
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from typing import Any
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SUMMARY_LENGTH_LIMITS = {
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"tldr": 2,
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"short": 4,
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"standard": 6,
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"detailed": 10,
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}
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ACTION_PREFIX_PATTERNS = [
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r"^(?:TODO|待办|action)[:：]?\s*(.+)$",
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r"^(?:需要|跟进)\s*(.+)$",
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]
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RISK_KEYWORDS = {
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"high": ["阻塞", "blocker", "故障", "失败", "严重", "不可用"],
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"medium": ["风险", "延迟", "异常", "超时", "报错"],
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"low": ["提醒", "注意", "观察", "待确认"],
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}
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BOOL_FIELDS = ["extract_actions", "extract_risks"]
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VALID_STYLES = {"daily_report", "digest", "meeting_digest", "executive"}
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VALID_LENGTHS = {"tldr", "short", "standard", "detailed"}
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def _clean_text(text: str) -> str:
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return re.sub(r"\s+", " ", (text or "").strip())
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def _normalize_key(text: str) -> str:
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text = _clean_text(text).lower()
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return re.sub(r"[^\w\u4e00-\u9fff]+", "", text)
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def _split_sentences(text: str) -> list[str]:
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raw_parts = re.split(r"[。！？；.!?;]+|\n+", text)
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return [_clean_text(part) for part in raw_parts if _clean_text(part)]
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def _sentence_tokens(sentence: str) -> list[str]:
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return re.findall(r"[A-Za-z0-9_-]+|[\u4e00-\u9fff]{2,}", sentence.lower())
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def _top_sentences(texts: list[str], limit: int) -> list[str]:
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sentences: list[str] = []
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for text in texts:
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sentences.extend(_split_sentences(text))
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if not sentences:
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return []
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token_counter = Counter()
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for sentence in sentences:
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token_counter.update(_sentence_tokens(sentence))
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scored: list[tuple[int, int, str]] = []
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for index, sentence in enumerate(sentences):
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score = sum(token_counter[token] for token in _sentence_tokens(sentence))
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scored.append((score, -index, sentence))
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ranked = [sentence for _, _, sentence in sorted(scored, reverse=True)]
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unique_ranked = []
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seen = set()
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for sentence in ranked:
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key = _normalize_key(sentence)
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if key and key not in seen:
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seen.add(key)
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unique_ranked.append(sentence)
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if len(unique_ranked) >= limit:
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break
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return unique_ranked
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def _trim_fragment(text: str, max_length: int = 80) -> str:
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fragment = re.split(r"[，,。；;!?]", text, maxsplit=1)[0]
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fragment = _clean_text(fragment)
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return fragment[:max_length].strip()
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def _extract_actions(texts: list[str]) -> list[dict[str, Any]]:
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items: list[dict[str, Any]] = []
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for text in texts:
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for sentence in _split_sentences(text):
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for pattern in ACTION_PREFIX_PATTERNS:
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match = re.match(pattern, sentence, re.IGNORECASE)
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if not match:
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continue
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task = _trim_fragment(match.group(1))
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if len(task) < 2:
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continue
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items.append({"task": task, "owner": None, "due_at": None, "blocker": None})
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break
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dedup = []
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seen = set()
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for item in items:
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key = _normalize_key(item["task"])
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if key and key not in seen:
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seen.add(key)
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dedup.append(item)
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return dedup[:10]
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def _extract_risks(texts: list[str]) -> list[dict[str, Any]]:
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risks: list[dict[str, Any]] = []
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for text in texts:
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for sentence in _split_sentences(text):
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lowered = sentence.lower()
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for impact, keywords in RISK_KEYWORDS.items():
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matched = next((keyword for keyword in keywords if keyword.lower() in lowered), None)
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if not matched:
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continue
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start = max(0, lowered.find(matched.lower()) - 18)
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end = min(len(sentence), lowered.find(matched.lower()) + len(matched) + 30)
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fragment = _clean_text(sentence[start:end])
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fragment = fragment[:120]
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if len(fragment) < 2:
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continue
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risks.append({"risk": fragment, "impact": impact, "mitigation": None})
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break
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dedup = []
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seen = set()
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for item in risks:
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key = _normalize_key(item["risk"])
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if key and key not in seen:
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seen.add(key)
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dedup.append(item)
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return dedup[:10]
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def _build_summary_line(sentences: list[str]) -> str:
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if not sentences:
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return "暂无可提炼的关键信息。"
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selected = sentences[:2]
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return "；".join(selected)
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def build_summary(payload: dict[str, Any]) -> dict[str, Any]:
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data = payload.get("data", {})
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sources = data.get("sources", [])
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texts = [_clean_text(source.get("content", "")) for source in sources if _clean_text(source.get("content", ""))]
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length = data.get("length", "standard")
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style = data.get("style", "daily_report")
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limit = SUMMARY_LENGTH_LIMITS.get(length, SUMMARY_LENGTH_LIMITS["standard"])
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top_sentences = _top_sentences(texts, limit)
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summary_line = _build_summary_line(top_sentences)
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summary_keys = {_normalize_key(sentence) for sentence in top_sentences[:2]}
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detail_sentences = [sentence for sentence in top_sentences if _normalize_key(sentence) not in summary_keys]
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sections = []
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if detail_sentences:
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if len(detail_sentences) == 1:
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sections = [{"title": "Key Updates", "bullets": detail_sentences}]
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else:
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midpoint = max(1, len(detail_sentences) // 2)
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sections = [
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{"title": "Key Updates", "bullets": detail_sentences[:midpoint]},
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{"title": "Notable Details", "bullets": detail_sentences[midpoint:]},
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]
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action_items = _extract_actions(texts) if data.get("extract_actions") else []
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risk_items = _extract_risks(texts) if data.get("extract_risks") else []
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markdown_lines = ["# Summary", "", "## Summary", f"- {summary_line}"]
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for section in sections:
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if not section["bullets"]:
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continue
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markdown_lines.extend(["", f"## {section['title']}"])
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markdown_lines.extend(f"- {bullet}" for bullet in section["bullets"])
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if action_items:
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markdown_lines.extend(["", "## Action Items"])
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markdown_lines.extend(f"- {item['task']}" for item in action_items)
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if risk_items:
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markdown_lines.extend(["", "## Risks"])
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markdown_lines.extend(f"- [{item['impact']}] {item['risk']}" for item in risk_items)
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schedule_payload = {
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"suggested_name": "Daily Summary",
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"message": "[Scheduled Task Triggered] 请立即汇总最新内容并输出结构化摘要，如有行动项和风险请一并列出，然后选择合适的通知方式发送给用户。",
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}
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return {
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"summary": summary_line,
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"sections": sections,
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"action_items": action_items,
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"risk_items": risk_items,
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"markdown": "\n".join(markdown_lines),
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"schedule_payload": schedule_payload,
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"style": style,
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}
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def _validate_source(source: Any, index: int) -> list[str]:
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errors = []
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if not isinstance(source, dict):
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return [f"data.sources[{index}] must be an object"]
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if not _clean_text(str(source.get("content", ""))):
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errors.append(f"data.sources[{index}].content is required")
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return errors
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def validate_payload(payload: dict[str, Any]) -> list[str]:
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errors = []
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data = payload.get("data")
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if not isinstance(data, dict):
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return ["data must be an object"]
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sources = data.get("sources")
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if not isinstance(sources, list) or not sources:
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errors.append("data.sources must be a non-empty array")
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else:
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for index, source in enumerate(sources):
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errors.extend(_validate_source(source, index))
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objective = data.get("objective")
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if not isinstance(objective, str) or not objective.strip():
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errors.append("data.objective is required")
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style = data.get("style")
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if style is not None and style not in VALID_STYLES:
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errors.append(f"data.style must be one of {sorted(VALID_STYLES)}")
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length = data.get("length")
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if length is not None and length not in VALID_LENGTHS:
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errors.append(f"data.length must be one of {sorted(VALID_LENGTHS)}")
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for field in BOOL_FIELDS:
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value = data.get(field)
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if value is not None and not isinstance(value, bool):
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errors.append(f"data.{field} must be a boolean")
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return errors
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