309 lines
13 KiB
Python
309 lines
13 KiB
Python
"""Chapter brief aggregation and Chinese chapter assembly."""
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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 concurrent.futures import ThreadPoolExecutor, as_completed
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from pathlib import Path
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from typing import Callable
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from scripts.runtime.roles import RoleDefinition, RuntimeProfile
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from scripts.runtime.skills import SkillRegistry
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from scripts.runtime.tasks import load_task_cards, validate_packet
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from scripts.runtime.workers import ChatClient
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def validate_chapter_brief(brief: dict) -> None:
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required = {
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"chapter_id",
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"chapter_title",
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"packet_ids",
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"core_claims",
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"evidence_items",
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"counter_evidence",
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"source_ids",
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"open_questions",
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"assembly_notes",
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}
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missing = sorted(required - set(brief))
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if missing:
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raise ValueError(f"chapter brief missing fields: {missing}")
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if not brief["chapter_id"]:
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raise ValueError("chapter_id required")
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if not brief["packet_ids"]:
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raise ValueError("chapter brief requires at least one packet")
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if not brief["core_claims"]:
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raise ValueError("chapter brief requires core_claims")
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if not brief["evidence_items"]:
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raise ValueError("chapter brief requires evidence_items")
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if not brief["counter_evidence"]:
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raise ValueError("chapter brief requires counter_evidence")
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def validate_compressed_finding(finding: dict) -> None:
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required = {
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"chapter_id",
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"chapter_title",
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"packet_ids",
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"chapter_thesis",
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"key_findings",
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"evidence_landings",
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"counter_evidence",
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"source_ids",
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"open_questions",
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"writing_plan",
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}
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missing = sorted(required - set(finding))
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if missing:
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raise ValueError(f"compressed finding missing fields: {missing}")
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if not finding["chapter_id"]:
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raise ValueError("chapter_id required")
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if not finding["packet_ids"]:
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raise ValueError("compressed finding requires packet_ids")
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if not finding["chapter_thesis"]:
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raise ValueError("compressed finding requires chapter_thesis")
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if not finding["key_findings"]:
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raise ValueError("compressed finding requires key_findings")
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if not finding["evidence_landings"]:
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raise ValueError("compressed finding requires evidence_landings")
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if not finding["counter_evidence"]:
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raise ValueError("compressed finding requires counter_evidence")
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def validate_chapter_markdown_citations(markdown: str, brief: dict) -> None:
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if "key_findings" in brief:
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validate_compressed_finding(brief)
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else:
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validate_chapter_brief(brief)
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cited = set(re.findall(r"\[(src_[A-Za-z0-9_-]+)\]", markdown))
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allowed = set(brief.get("source_ids") or [])
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unknown = sorted(cited - allowed)
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if unknown:
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raise ValueError(f"unknown citation ids in {brief['chapter_id']}: {unknown}")
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def _chapter_title_from_id(chapter_id: str) -> str:
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try:
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index = int(chapter_id.replace("ch", ""))
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return f"第{index}章"
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except ValueError:
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return chapter_id
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def build_chapter_briefs(project_root: Path) -> list[dict]:
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cards = load_task_cards(project_root / "phase2" / "task_cards.json")
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grouped: dict[str, list[tuple[str, dict]]] = {}
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for card in cards:
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packet_path = project_root / card.output_packet
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if not packet_path.exists():
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continue
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packet = json.loads(packet_path.read_text(encoding="utf-8"))
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validate_packet(packet)
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for chapter_id in card.chapter_ids:
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grouped.setdefault(chapter_id, []).append((card.task_id, packet))
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briefs: list[dict] = []
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out_dir = project_root / "phase2" / "chapter_briefs"
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out_dir.mkdir(parents=True, exist_ok=True)
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for chapter_id in sorted(grouped):
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packet_pairs = sorted(grouped[chapter_id], key=lambda item: item[0])
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packet_ids = [item[0] for item in packet_pairs]
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packets = [item[1] for item in packet_pairs]
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source_ids = sorted({sid for packet in packets for sid in packet.get("source_ids", [])})
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brief = {
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"chapter_id": chapter_id,
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"chapter_title": _chapter_title_from_id(chapter_id),
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"packet_ids": packet_ids,
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"core_claims": [claim for packet in packets for claim in packet.get("claims", [])],
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"evidence_items": [item for packet in packets for item in packet.get("evidence_items", [])],
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"counter_evidence": [item for packet in packets for item in packet.get("counter_evidence", [])],
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"source_ids": source_ids,
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"open_questions": [q for packet in packets for q in packet.get("open_questions", [])],
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"assembly_notes": [
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"用中文写正式章节，英文仅保留在必要的来源标题、原文摘录、DOI/URL 中。",
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"避免碎片化：不要按 packet 逐段堆砌，要先提炼本章主线，再组织证据。",
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"每个事实、数字和关键判断都必须保留 [src_xxx] 引用。",
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"必须纳入 counter_evidence，并说明它如何影响结论置信度。",
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],
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}
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validate_chapter_brief(brief)
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(out_dir / f"{chapter_id}.json").write_text(
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json.dumps(brief, ensure_ascii=False, indent=2) + "\n",
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encoding="utf-8",
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)
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briefs.append(brief)
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return briefs
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def _source_ids_from_item(item: dict) -> list[str]:
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if item.get("source_ids"):
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return list(item.get("source_ids") or [])
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if item.get("source_id"):
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return [item["source_id"]]
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return []
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def build_compressed_findings(project_root: Path) -> list[dict]:
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"""Compress packet-level evidence into chapter-level writing inputs.
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This is intentionally deterministic: it does not invent a better narrative,
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but it forces a chapter-level evidence map before any model writes prose.
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"""
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brief_dir = project_root / "phase2" / "chapter_briefs"
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if not brief_dir.exists() or not list(brief_dir.glob("ch*.json")):
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briefs = build_chapter_briefs(project_root)
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else:
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briefs = [
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json.loads(path.read_text(encoding="utf-8"))
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for path in sorted(brief_dir.glob("ch*.json"))
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]
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out_dir = project_root / "phase2" / "compressed_findings"
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out_dir.mkdir(parents=True, exist_ok=True)
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findings: list[dict] = []
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for brief in briefs:
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validate_chapter_brief(brief)
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core_claims = brief.get("core_claims") or []
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evidence_items = brief.get("evidence_items") or []
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first_claim = core_claims[0] if core_claims else {}
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chapter_thesis = first_claim.get("claim") or f"{brief['chapter_title']} 需要以证据为中心重写。"
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finding = {
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"chapter_id": brief["chapter_id"],
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"chapter_title": brief["chapter_title"],
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"packet_ids": brief["packet_ids"],
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"chapter_thesis": chapter_thesis,
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"key_findings": [
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{
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"finding": claim.get("claim") or claim.get("summary") or str(claim),
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"source_ids": _source_ids_from_item(claim),
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"confidence": claim.get("confidence", "medium"),
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}
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for claim in core_claims
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],
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"evidence_landings": [
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{
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"evidence": item.get("summary") or item.get("finding") or item.get("quote") or str(item),
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"source_ids": _source_ids_from_item(item),
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"landing_hint": item.get("landing_hint", "用于支撑本章关键判断或整改动作。"),
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}
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for item in evidence_items
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],
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"counter_evidence": brief["counter_evidence"],
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"source_ids": brief["source_ids"],
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"open_questions": brief["open_questions"],
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"writing_plan": [
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"先写本章判断，不按 packet 顺序堆砌。",
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"每个二级小节至少落下具体审计发现、法规要求、记录/参数或整改证据。",
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"正文末尾必须保留“证据落点与待补证据”表。",
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],
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}
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validate_compressed_finding(finding)
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(out_dir / f"{brief['chapter_id']}.json").write_text(
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json.dumps(finding, ensure_ascii=False, indent=2) + "\n",
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encoding="utf-8",
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)
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findings.append(finding)
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return findings
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def build_chapter_user_prompt(brief: dict) -> str:
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return (
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"请根据以下 compressed finding / chapter brief 写一章正式中文 Markdown 正文。\n"
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"目标是形成一个完整章节，而不是 packet 摘要。避免碎片化，按金字塔结构组织：章首先给结论，再用证据支撑。\n"
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"要求：标题必须是观点型判断；每个数字和事实保留 [src_xxx]；纳入反方证据；不要出现调度元数据。\n"
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"禁止写空泛咨询腔。每个二级小节都必须至少落下 2 个具体审计发现、法规要求、SOP/记录/参数/现场观察或整改证据；不要只写原则。\n"
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"正文末尾必须增加“证据落点与待补证据”小节，用表格列出：关键判断、已使用证据 source_id、已落地整改动作、仍缺证据。若证据不足，直接标注需回炉 Phase 2，不要用泛泛表述补齐。\n"
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"只输出 Markdown，不要输出解释。\n\n"
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f"{json.dumps(brief, ensure_ascii=False, indent=2)}"
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)
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class ChapterAssemblyWorker:
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def __init__(
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self,
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*,
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role: RoleDefinition,
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client: ChatClient,
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skill_registry: SkillRegistry | None = None,
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) -> None:
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self.role = role
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self.client = client
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self.skill_registry = skill_registry or SkillRegistry()
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def _system_prompt(self) -> str:
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skill_texts = []
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for name in self.role.skills:
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try:
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skill_texts.append(f"# Skill: {name}\n\n{self.skill_registry.read(name)}")
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except FileNotFoundError:
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skill_texts.append(f"# Skill: {name}\n\n[missing skill: {name}]")
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return (
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"你是 Deep Research v0.20 的中文章节组装 worker。\n"
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"你的职责是把结构化证据包收束成连贯章节，解决并发研究造成的碎片化。\n"
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"不得编造来源，不得删除关键反方证据。\n\n"
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+ "\n\n".join(skill_texts)
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)
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def write_chapter(self, *, project_root: Path, brief: dict) -> Path:
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if "key_findings" in brief:
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validate_compressed_finding(brief)
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else:
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validate_chapter_brief(brief)
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markdown = self.client.chat_complete(
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model=self.role.model,
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system=self._system_prompt(),
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user=build_chapter_user_prompt(brief),
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temperature=self.role.temperature,
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max_tokens=self.role.max_tokens,
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tag=f"chapter:{brief['chapter_id']}",
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)
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validate_chapter_markdown_citations(markdown, brief)
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out = project_root / "phase2" / "drafts" / f"{brief['chapter_id']}.md"
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out.parent.mkdir(parents=True, exist_ok=True)
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out.write_text(markdown.rstrip() + "\n", encoding="utf-8")
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return out
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def _write_chapter_error(project_root: Path, brief: dict, error: Exception) -> None:
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path = project_root / "phase2" / "chapter_errors" / f"{brief.get('chapter_id', 'unknown')}.json"
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path.parent.mkdir(parents=True, exist_ok=True)
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payload = {
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"chapter_id": brief.get("chapter_id"),
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"status": "failed",
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"error": str(error),
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}
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path.write_text(json.dumps(payload, ensure_ascii=False, indent=2) + "\n", encoding="utf-8")
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def run_chapter_assembly_workers(
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*,
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project_root: Path,
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briefs: list[dict],
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runtime: RuntimeProfile,
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client_factory: Callable[[RoleDefinition], ChatClient],
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workers: int,
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) -> int:
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role = runtime.role_for_task("chapter_assembly")
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max_workers = max(1, min(workers, role.max_concurrency))
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def run_one(brief: dict) -> tuple[dict, Path | None, Exception | None]:
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try:
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worker = ChapterAssemblyWorker(role=role, client=client_factory(role))
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return brief, worker.write_chapter(project_root=project_root, brief=brief), None
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except Exception as error:
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return brief, None, error
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written = 0
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with ThreadPoolExecutor(max_workers=max_workers) as pool:
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futures = [pool.submit(run_one, brief) for brief in briefs]
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for future in as_completed(futures):
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brief, path, error = future.result()
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if error is not None:
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_write_chapter_error(project_root, brief, error)
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continue
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if path is None:
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_write_chapter_error(project_root, brief, RuntimeError("chapter worker returned no output path"))
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continue
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written += 1
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return written
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