194 lines
7.0 KiB
Python
194 lines
7.0 KiB
Python
#!/usr/bin/env python3
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from __future__ import annotations
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import json
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import re
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from pathlib import Path
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from typing import Any
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import fitz
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ROOT = Path("/Users/soldier/free-code/packages/insurance-ppt")
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COMPANIES_DIR = ROOT / "config" / "companies"
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KNOWLEDGE_ROOT = Path("/Users/soldier/Desktop/公司介绍")
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OUT_JSON = ROOT / "data" / "company-facts.generated.json"
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MANUAL_JSON = ROOT / "data" / "company-facts.manual.json"
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OUT_MD = ROOT / "outputs" / "company_factbook.md"
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PREFERRED_NAME = re.compile(r"(简介|簡介|概览|概覽|fact|factsheet|company|strength|overview|一图|企业信息图|業務簡介|业务简介)", re.I)
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PDF_EXT = {".pdf"}
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def read_pdf_text(path: Path, max_pages: int = 4) -> str:
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doc = fitz.open(path)
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pages = []
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for i in range(min(doc.page_count, max_pages)):
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pages.append(doc[i].get_text())
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doc.close()
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return "\n".join(pages)
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def first_match(patterns: list[str], text: str) -> str | None:
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for pattern in patterns:
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match = re.search(pattern, text, re.I)
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if match:
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value = match.group(1).strip()
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value = re.sub(r"\s+", " ", value)
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return value
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return None
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def choose_evidence_files(company: dict[str, Any]) -> list[Path]:
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files: list[Path] = []
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for directory in company.get("knowledgeDirectories", []):
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root = KNOWLEDGE_ROOT / directory
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if not root.exists():
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continue
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for path in root.rglob("*"):
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if path.suffix.lower() in PDF_EXT:
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files.append(path)
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ranked = sorted(
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files,
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key=lambda path: (
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0 if PREFERRED_NAME.search(path.name) else 1,
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len(path.name),
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),
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)
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return ranked[:3]
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def build_facts(company: dict[str, Any], text: str) -> list[dict[str, str]]:
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facts: list[dict[str, str]] = []
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def clean_rating(value: str | None, family: str) -> str | None:
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if not value:
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return None
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value = value.strip()
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if family in {"sp", "fitch"}:
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if re.fullmatch(r"(AAA|AA[+-]?|A[+-]?|BBB[+-]?|BB[+-]?|B[+-]?|CCC[+-]?|CC|C|D)", value):
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return value
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return None
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if family == "moodys":
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if re.fullmatch(r"(Aaa|Aa[1-3]|A[1-3]|Baa[1-3]|Ba[1-3]|B[1-3]|Caa[1-3]|Ca|C)", value):
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return value
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return None
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if family == "ambest":
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if re.fullmatch(r"(A\+\+|A\+|A|A-|B\+\+|B\+|B)", value):
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return value
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return None
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return None
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def add(label: str, value: str | None) -> None:
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if not value:
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return
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value = value.strip().strip("：: ")
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if not value:
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return
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if any(existing["label"] == label for existing in facts):
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return
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facts.append({"label": label, "value": value})
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add("成立时间", first_match([
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r"(?:成立于|成立於|创立于|創立於)\s*(\d{4}\s*年?)",
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r"(\d{4}\s*年成立)",
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], text))
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add("所属集团", first_match([
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r"(?:母公司|所属集团|隶属于|屬於)\s*[:：]?\s*([^\n。；]{4,50}(?:集团|集團|Group|Holdings|Financial))",
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r"([^\n。；]{4,50}(?:集团|集團|Group|Holdings|Financial))(?:旗下|附属机构|附屬機構)",
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], text))
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add("业务范围", first_match([
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r"(业务遍及[^\n。]{6,80})",
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r"(業務遍及[^\n。]{6,80})",
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r"(覆盖[^\n。]{6,80}市场)",
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r"(覆蓋[^\n。]{6,80}市場)",
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], text))
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add("标普评级", clean_rating(first_match([
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r"(?:标普|標普|S&P)[^A-Z0-9]{0,10}([A-Z]{1,3}[+-]?)",
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], text), "sp"))
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add("穆迪评级", clean_rating(first_match([
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r"(?:穆迪|Moody'?s)[^A-Za-z0-9]{0,10}([A-Za-z]{1,3}[0-3]?)",
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], text), "moodys"))
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add("惠誉评级", clean_rating(first_match([
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r"(?:惠誉|惠譽|Fitch)[^A-Z0-9]{0,10}([A-Z]{1,3}[+-]?)",
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], text), "fitch"))
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add("贝氏评级", clean_rating(first_match([
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r"(?:AM Best|A\.M\. Best)[^A-Z0-9]{0,10}([A-Z][+-]?)",
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], text), "ambest"))
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add("管理资产规模", first_match([
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r"(?:管理资产|管理資產|AUM|Assets under management)[^0-9]{0,20}([\d,.]+\s*(?:亿|億|十亿|百亿|万亿|billion|trillion)[^\n。；]{0,20})",
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], text))
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add("客户规模", first_match([
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r"(?:服务|服務)[^\n。]{0,12}([\d,.]+\s*(?:万|萬|million)[^\n。]{0,20}客户)",
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r"([\d,.]+\s*(?:万|萬|million)[^\n。]{0,20}客户)",
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], text))
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if not facts and company.get("companyHighlights"):
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highlight = company["companyHighlights"][0]["text"]
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facts.append({"label": "核心概况", "value": highlight})
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return facts[:6]
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def main() -> None:
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companies = []
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for path in sorted(COMPANIES_DIR.glob("*.json")):
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company = json.loads(path.read_text(encoding="utf-8"))
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evidence_files = choose_evidence_files(company)
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merged_text = "\n".join(read_pdf_text(file) for file in evidence_files[:2]) if evidence_files else ""
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facts = build_facts(company, merged_text)
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companies.append({
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"companyId": company["id"],
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"displayName": company["displayName"],
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"companyIntro": company.get("companyIntro", ""),
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"facts": facts,
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"evidenceFiles": [str(file) for file in evidence_files],
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})
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generated = {"companies": companies}
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OUT_JSON.parent.mkdir(parents=True, exist_ok=True)
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OUT_JSON.write_text(json.dumps(generated, ensure_ascii=False, indent=2), encoding="utf-8")
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manual_map = {}
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if MANUAL_JSON.exists():
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manual = json.loads(MANUAL_JSON.read_text(encoding="utf-8"))
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manual_map = {entry["companyId"]: entry for entry in manual.get("companies", [])}
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merged = []
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for entry in companies:
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override = manual_map.get(entry["companyId"])
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if override:
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merged.append({
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**entry,
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**override,
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"facts": override.get("facts") or entry.get("facts", []),
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"evidenceFiles": entry.get("evidenceFiles", []),
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})
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else:
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merged.append(entry)
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for company_id, override in manual_map.items():
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if not any(item["companyId"] == company_id for item in merged):
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merged.append(override)
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OUT_MD.parent.mkdir(parents=True, exist_ok=True)
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lines = ["# Company Factbook", ""]
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for entry in merged:
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lines.append(f"## {entry['displayName']} ({entry['companyId']})")
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lines.append("")
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lines.append(entry["companyIntro"] or "暂无概览")
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lines.append("")
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if entry["facts"]:
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for fact in entry["facts"]:
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lines.append(f"- {fact['label']}：{fact['value']}")
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else:
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lines.append("- 暂无可结构化事实，需补充简介类 PDF")
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if entry["evidenceFiles"]:
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lines.append(f"- 证据文件：{', '.join(Path(f).name for f in entry['evidenceFiles'])}")
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lines.append("")
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OUT_MD.write_text("\n".join(lines), encoding="utf-8")
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print(OUT_JSON)
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print(OUT_MD)
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if __name__ == "__main__":
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main()
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