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ThearchyHelios
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- 判定取值改为：支持 / 部分支持 / 证据相矛盾 / 证据不足 / 不是结论。只有证据和句子冲突才判相矛盾； 证据里没有相关信息判证据不足，并写明缺什么（比如 SQL、字段清单） - 出具判档不变松：证据相矛盾按 on_unsupported 降档或不予出具；证据不足记一条缺口，最多降档、不能判完整出具； 改造前的「证据不支持」照旧当相矛盾处理 - 补全证据摘录：表名附字段清单和类型（最多 60 个，快照不全时注明，遮罩列不列）；口径卡指标附上每个输入 取自哪次查询、哪一格，以及那次查询的 SQL；一律只读封存范围内的工件 - 理由上限从 60 字放宽到 120 字，在句子边界截断，不再截在半句中间 - 裁判模型：按需裁判也判断是否和写作模型相同、是否在价格表里，证据面板里醒目提示； 设置页没配裁判模型时写明「未单独配置，将使用助手的模型」 - 新判定带规则版本：改造前的判定在界面上标「按旧规则判定」，可以请模型按当前规则重新判断 - 界面：证据相矛盾用红色；证据不足用中性色和 ○，写明缺什么；讲方法、讲结构的句子在证据面板里直接列出 对应的 SQL 和字段清单；出具横幅、审计表、报告节点印章的计数都分开这两档 - 顺带写稳 check-publish 里一条等按钮状态的断言（并行时偶发）
637 lines
35 KiB
Python
637 lines
35 KiB
Python
"""报告撰写节点：模型只写引用标记，数字由系统从口径卡取出来渲染。
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以前「给人看的报告」是 llm 节点写的自由文本：数字是模型转写的，出处要到出口再按
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数值回头猜——同值的指标一多就猜错，模型顺手写的数也要到出口才被发现。这里把核对
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挪到写的那一刻：
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1. 建目录：收齐上游口径卡的指标和运行输入，编成 [[m:gmv]]、[[i:week]] 这样的引用
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2. 流式写作：模型写标记，StreamRenderer 边收边换成真值，流里看到的就是最终的数字
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3. 核对：compose_doc 切块、分句、切片段，找出裸数字和解析不了的引用
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4. 修复：有违规就把清单交回去重写，最多 max_repairs 次
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5. 收尾：文档落成 report_doc 工件，report.checked 事件进封存；仍然违规时按
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on_violation 失败（fail）或者照常产出、把违规片段标出来（flag）
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三期起目录里还有表和字段（这次运行冻结的表结构）、知识库检索的原话。可疑实体（反引号里
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写了个哪里都找不到的名字）只标注：不重写、不失败，受管级别的正式出具按缺口降档；表结构快照
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不全时核对不了的名字（unverified_entity）只标注。entities: off 整层不管表名、字段名。
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结论句策略 claims：off（默认）不管；require_citation 在写作提示里要求结论句挂依据（自动链接的
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名字不算依据），没挂的计入缺口、出口降档；judge 另外请一个模型按证据逐句判断（engine/judge.py）：
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- 正式运行在节点里判：写完、核对完之后判，判定写进文档的 unit.verdict，随文档一起封存。判定只标注、
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不改写正文；裁判没跑成、触顶了照样产出，没判的记未裁判并留下缺口，出口按 on_unsupported 判档
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- 探索运行不在节点里花这笔钱：候选句标「未裁判 · 按需」，点开哪句再判哪句（证据接口）
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- rewrite_once（默认关）：证据相矛盾、证据不足的句子连同理由交回写作者只改这几句，再判一次，最多一轮；
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改写稿冒出原稿没有的违规（只标注的可疑实体也算）就不采用
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- 裁判调用包在 @task 里，排在节点所有已有调用之后：「接着跑」时直接取 checkpoint 里的判定，
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不重复调用、不重复计费。写作调用不进 checkpoint，接着跑时会重写一稿——所以判定带着输入指纹，
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对不上这一稿的不用
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出口契约复核（io.py）用 report_catalog 按同一套参数重建目录、独立重算，不信这里的自查。
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"""
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from __future__ import annotations
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import time
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from collections import Counter
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from typing import Any
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from langchain_core.messages import AIMessage, BaseMessage, HumanMessage, SystemMessage
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from langgraph.func import task
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from app.core.errors import describe_exception, not_configured
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from app.core.events import EventType
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from app.db.base import SessionLocal
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from app.engine import judge as judging
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from app.engine.context import NodeContext, NodeError
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from app.engine.labels import field_label, option_label
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from app.engine.evidence import (
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CELLS_REASON,
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CLAIMS_RULE,
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ENTITY_KINDS,
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MARKER_RULES,
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StreamRenderer,
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build_catalog,
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catalog_prompt,
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compose_doc,
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describe_violations,
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ledger_enabled,
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)
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from app.engine.nodes.llm import _invoke_streaming, _model_spec, _report_call
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from app.engine.schema import (
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CLAIMS_JUDGE,
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CLAIMS_VALUES,
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JUDGE_ON_UNSUPPORTED,
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GraphNode,
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GraphSpec,
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NodeType,
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_ancestors,
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claims_problem,
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judge_problems,
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)
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from app.engine.state import GraphState, message_text, thinking_text
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from app.engine.toolcalls import leaked_markup, markup_warning
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from app.providers.factory import ProviderNotConfigured, get_chat_model
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ON_VIOLATION = ("fail", "flag")
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NUMBERS = ("strict", "off")
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#: 实体层：link（默认）核对表名、字段名并自动链接；off 整层不管（目录里不收表和字段）
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ENTITIES = ("link", "off")
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#: 结论句策略，和画布校验同一份（schema.CLAIMS_VALUES）：off / require_citation / judge
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CLAIMS = CLAIMS_VALUES
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#: 只标注、不让写作者重写也不判失败的违规：可疑实体（受管的正式出具按缺口降档）、表结构快照不全时
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#: 核对不了的名字（出口只标注）
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SOFT = frozenset({"unknown_entity", "unverified_entity"})
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#: 重写一次就是多一次整篇的模型调用，写不对的模型多给几次也大多写不对
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MAX_REPAIRS = 3
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ROLE = ("你是报告撰写人。报告里的每个数字都由系统从证据里取出来、按口径卡的格式渲染；"
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"你负责挑重点、组织结构、说清变化和原因。")
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MARKUP_NUDGE = ("你上一条回复把工具调用写成了文字。报告撰写不调用任何工具：能用的数据都在上面的"
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"证据目录里，直接用引用标记写报告正文。")
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#: 节点失败原因（给人看）。给模型的那句是上面的 MARKUP_NUDGE，「证据目录」是模型那边的说法
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MARKUP_ERROR = ("模型输出了工具调用的原始标记，而报告撰写节点不调用工具，数据已由系统提供。"
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"请换一个模型重试")
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#: 接着跑时 checkpoint 里缓存的判定最多翻几条去找这一稿的（每条都是先前某一稿的，对不上就往后翻）
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_STALE_LIMIT = 16
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# --------------------------------------------------------------------------
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# 目录与放行名单：出口复核要用同一套参数重建，所以不依赖 NodeContext
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# --------------------------------------------------------------------------
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def _setting(spec: GraphSpec, node: GraphNode, key: str, default: Any = None) -> Any:
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"""和 NodeContext.cfg 同一个规则：节点上没写就取图级 defaults。"""
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value = node.config.get(key)
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if value in (None, ""):
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return spec.defaults.get(key, default)
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return value
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def report_catalog(state: GraphState, spec: GraphSpec, node: GraphNode) -> dict[str, Any]:
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"""报告节点的证据目录。
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出口契约复核必须用这一个函数重建：参数（metrics_from、evidence_from、祖先范围）
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差一点，alias 集合就不一样——同一个指标 id 在两张卡里时，只收一张写 m:gmv，
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全收就得写 m:east.gmv——复核会把一份好好的报告判成引用解析不了。
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"""
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ledger = [e for e in state.get("evidence") or [] if isinstance(e, dict)]
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sources = _setting(spec, node, "evidence_from", "ancestors")
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if isinstance(sources, str) and sources != "ancestors":
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sources = [sources]
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if isinstance(sources, list):
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# evidence_from 只管查询、检索这类证据（连同查询当时的表结构）从哪几个节点来；指标从哪来由 metrics_from 管
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keep = {str(s) for s in sources}
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ledger = [e for e in ledger
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if e.get("kind") not in ("query", "retrieval", "schema") or e.get("node_id") in keep]
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catalog = build_catalog(
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nodes=state.get("nodes") or {},
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ledger=ledger,
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inputs=state.get("input") or {},
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metrics_from=_setting(spec, node, "metrics_from") or None,
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allowed=_ancestors(spec, node.id),
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)
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if report_entities(spec, node) == "off":
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# 目录里没有表和字段，写作目录也就不列；compose / verify 另传 entities=False，解析不了的原因照实说
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catalog = {alias: e for alias, e in catalog.items() if e.get("kind") not in ENTITY_KINDS}
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return catalog
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def report_entities(spec: GraphSpec, node: GraphNode) -> str:
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"""报告节点的实体层：link（默认）/ off。出口复核调 verify_doc 时传 entities=(这个值 == "link")。
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写错的值执行时节点会报错，这里只把 off 当 off，别的一律按默认。
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"""
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return "off" if _setting(spec, node, "entities", "link") == "off" else "link"
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def report_claims(spec: GraphSpec, node: GraphNode) -> str:
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"""报告节点的结论句策略：off / require_citation / judge。出口判档按它（和节点执行时同一个取值规则）。
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写错的值画布校验就拦了，执行时节点也会报错，这里只把没写当成 off。
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"""
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value = _setting(spec, node, "claims", "off")
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return value if isinstance(value, str) and value in CLAIMS else "off"
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def report_judge(spec: GraphSpec, node: GraphNode) -> dict[str, Any]:
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"""claims: judge 的子配置：节点上的 judge（没写取图级 defaults），写了的键原样保留——上限写 null 就是
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不限，没写的键运行时取设置里的默认（judge.report_budget）。rewrite_once、on_unsupported 补上缺省
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（false、degrade）：出口判档读 on_unsupported。写错的值画布校验就拦了，执行时节点也会报错。
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"""
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raw = _setting(spec, node, "judge")
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raw = raw if isinstance(raw, dict) else {}
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return {**raw, "rewrite_once": raw.get("rewrite_once") is True,
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"on_unsupported": raw.get("on_unsupported") if raw.get("on_unsupported") in JUDGE_ON_UNSUPPORTED
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else "degrade"}
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def report_allowance(spec: GraphSpec, node: GraphNode) -> list[Any]:
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"""报告自查放行的字面量：出口契约 report_from 指向它时，契约的 allow_numbers。
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契约放行、报告却不放行的话，写作者会为一个最终根本不算违规的数白白重写一次。
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反过来不成立：放行名单只由契约定，报告节点没有自己的名单——出口复核是独立的裁判。
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"""
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allowed: list[Any] = []
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for other in spec.nodes:
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contract = other.config.get("contract") if other.type == NodeType.OUTPUT else None
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if isinstance(contract, dict) and contract.get("report_from") == node.id:
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extra = contract.get("allow_numbers") or []
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allowed.extend(extra if isinstance(extra, list) else [extra])
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return allowed
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def report_cells_allowed(spec: GraphSpec, node: GraphNode, *, governed: bool) -> bool:
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"""报告能不能直接引用查询单元格：出口契约的 report_from 指着它、而那份契约不允许的，写作时就不给。
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出口复核按契约判（io.py），这里提前照同一条规则建目录：不然写作者照着提示写了单元格、自查
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通过，到出口才整段判成解析不了——受管出具直接不予出具。
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"""
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from app.engine.governance import cells_allowed
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contracts = [other.config.get("contract") for other in spec.nodes if other.type == NodeType.OUTPUT]
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return all(cells_allowed(c, governed=governed) for c in contracts
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if isinstance(c, dict) and c.get("report_from") == node.id)
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#: 目录里能被报告引用的几种来源（沙箱代码节点的登记只为说清为什么不能引用，不算）
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_CITABLE = {"metric": "口径卡指标", "query": "查询结果", "retrieval": "知识库检索", "input": "运行输入"}
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def _no_evidence(catalog: dict[str, Any], cells: bool) -> str | None:
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"""目录里没有可引用的来源时给一句话，说清缺的是哪种；有就返回 None。"""
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kinds = {entry.get("kind") for entry in catalog.values()}
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if not kinds & set(_CITABLE):
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return ("报告撰写节点的上游没有可引用的来源（" + "、".join(_CITABLE.values()) + "都没有），"
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f"报告中的数字都会被判为没有出处。请在它前面接入取数节点或口径卡，或检查「{field_label('metrics_from')}」")
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if not cells and not kinds & {"metric", "input"}:
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# 只有查询和检索：单元格引用不了，检索片段本来就只能当依据，一个数都没处引
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return (f"报告撰写节点的上游只有查询结果，没有口径卡指标，而{CELLS_REASON}，当前无法引用单元格，"
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"报告中的数字都会被判为没有出处。请在出具契约中开启「单元格引用」，或把要写的数字登记到口径卡")
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return None
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# --------------------------------------------------------------------------
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# 执行器
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# --------------------------------------------------------------------------
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class _RenderedStream:
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"""借 _invoke_streaming 的流式与回退逻辑，只在出口把 llm.token 换成渲染后的字。
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模型写的是 [[m:gmv]]，前端要看到的是「45,678.5元」。标记会被切在两个 chunk
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中间，StreamRenderer 攒到没有未闭合的 [[ 再放；调用结束时 flush 掉剩下的。
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"""
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def __init__(self, ctx: NodeContext, catalog: dict[str, Any], cells: bool = True) -> None:
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self._ctx = ctx
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self._catalog = catalog
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self._cells = cells
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self._renderer = StreamRenderer(catalog, cells_allowed=cells)
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def __getattr__(self, name: str) -> Any:
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return getattr(self._ctx, name)
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def emit(self, event_type: EventType | str, **data: Any) -> None:
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if event_type == EventType.LLM_TOKEN:
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if text := self._renderer.feed(str(data.get("delta") or "")):
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self._ctx.emit(EventType.LLM_TOKEN, delta=text)
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return
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if event_type == EventType.LOG and data.get("code") == "stream_fallback":
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# 流断在半路、退回非流式重来：攒着的半截不再放出去，免得和重来的那份接在一起
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self._renderer = StreamRenderer(self._catalog, cells_allowed=self._cells)
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self._ctx.emit(event_type, **data)
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def flush(self) -> None:
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if tail := self._renderer.flush():
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self._ctx.emit(EventType.LLM_TOKEN, delta=tail)
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async def _run_class(run_id: str) -> str | None:
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"""按运行记录上的 run_class 取：子图、审批之后续跑都是另起的执行上下文，只有运行记录靠得住。"""
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from app.db.models import Run
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async with SessionLocal() as session:
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run = await session.get(Run, run_id)
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return run.run_class if run is not None else None
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async def _default_on_violation(run_id: str) -> str:
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"""探索运行默认标注、照常产出；正式运行默认失败——封存的发布版不能带着裸数字出具。"""
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return "fail" if await _run_class(run_id) == "formal" else "flag"
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def _options(ctx: NodeContext) -> tuple[str, int]:
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numbers = str(ctx.cfg("numbers", "strict") or "strict")
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if numbers not in NUMBERS:
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raise NodeError(ctx.node.id, _only("numbers", NUMBERS, numbers))
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# 画布校验也拦这两项；执行时再守一道，报的是同一句话，免得写错的值被悄悄当成默认
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if problem := claims_problem(ctx.cfg("claims")):
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raise NodeError(ctx.node.id, problem)
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if ctx.cfg("claims") == CLAIMS_JUDGE and (problems := judge_problems(ctx.cfg("judge"))):
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raise NodeError(ctx.node.id, "；".join(message for _, message in problems))
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entities = ctx.cfg("entities", "link") or "link"
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if entities not in ENTITIES:
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raise NodeError(ctx.node.id, _only("entities", ENTITIES, entities))
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raw = ctx.cfg("max_repairs", 1)
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try:
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repairs = int(raw)
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except (TypeError, ValueError):
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raise NodeError(ctx.node.id, _repairs_problem(raw)) from None
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if isinstance(raw, bool) or not 0 <= repairs <= MAX_REPAIRS:
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raise NodeError(ctx.node.id, _repairs_problem(raw))
|
||
return numbers, repairs
|
||
|
||
|
||
def _only(key: str, allowed: tuple[str, ...], got: Any) -> str:
|
||
"""「「表名、字段名」只能是「核对」或「不核对」，当前为「x」」：写界面上的叫法，不写键名和枚举值。"""
|
||
names = [f"「{option_label(key, v)}」" for v in allowed]
|
||
listed = "或".join(names) if len(names) <= 2 else "、".join(names[:-1]) + "或" + names[-1]
|
||
return f"「{field_label(key, 'report')}」只能是{listed}，当前为「{got}」"
|
||
|
||
|
||
def _repairs_problem(raw: Any) -> str:
|
||
return f"「{field_label('max_repairs', 'report')}」需要填写 0 到 {MAX_REPAIRS} 的整数，当前为「{raw}」"
|
||
|
||
|
||
def _blocking(violations: list[dict[str, Any]], numbers: str) -> list[dict[str, Any]]:
|
||
"""要让写作者改的违规。numbers=off 时裸数字只记录不拦（文档和出口复核照样看得到）。
|
||
|
||
可疑实体只标注（SOFT）：一个反引号里的业务词也可能被当成名字，为它整篇重写、判失败都不值；
|
||
它留在文档和出口复核里，受管的正式出具按缺口降档。表结构快照不全时核对不了的名字同样只标注。
|
||
"""
|
||
return [v for v in violations if v.get("code") not in SOFT
|
||
and not (numbers == "off" and v.get("code") == "uncited_number")]
|
||
|
||
|
||
def _violation_key(violation: dict[str, Any]) -> tuple[str, str]:
|
||
"""认一处违规：(code, 点名的字)。点名的字按 text、ref、message 的顺序取第一个有的。"""
|
||
named = violation.get("text") or violation.get("ref") or violation.get("message") or ""
|
||
return str(violation.get("code") or ""), str(named)
|
||
|
||
|
||
def _new_violations(before: list[dict[str, Any]], after: list[dict[str, Any]]) -> list[dict[str, Any]]:
|
||
"""after 里 before 没有的违规，按 (code, 点名的字) 逐个抵消（同一个裸数字多写一处也算新的）。
|
||
|
||
全部违规都比，包括只标注、不让重写的那几类（SOFT）：改写稿冒出一个编造的表名，受管的正式出具就会
|
||
因此降档；去掉一处、又冒出另一处，总数没变，冒出来的也还是新的。
|
||
"""
|
||
left = Counter(_violation_key(v) for v in before)
|
||
fresh: list[dict[str, Any]] = []
|
||
for violation in after:
|
||
key = _violation_key(violation)
|
||
if left[key] > 0:
|
||
left[key] -= 1
|
||
else:
|
||
fresh.append(violation)
|
||
return fresh
|
||
|
||
|
||
def _named(violations: list[dict[str, Any]], limit: int = 3) -> str:
|
||
"""违规里点名的那几个字：「45678」「m:nope」。"""
|
||
names = [str(v.get("text") or v.get("ref") or "") for v in violations]
|
||
names = [n for n in dict.fromkeys(names) if n][:limit]
|
||
return "、".join(f"「{n}」" for n in names)
|
||
|
||
|
||
def _repair_request(violations: list[dict[str, Any]]) -> str:
|
||
return (
|
||
"你写的报告没有通过系统核对，问题如下：\n"
|
||
f"{describe_violations(violations)}\n\n"
|
||
"请重写整篇报告：所有数字都用引用标记写，只引用证据目录里有的指标和输入；"
|
||
"不要解释改了什么，只输出新的报告正文。"
|
||
)
|
||
|
||
|
||
def _messages(ctx: NodeContext, state: GraphState, catalog: dict[str, Any], cells: bool = True,
|
||
claims: str = "off") -> list[BaseMessage]:
|
||
system = ctx.render_str(ctx.cfg("system", ""), state)
|
||
instructions = ctx.render_str(ctx.cfg("instructions", ""), state).strip() \
|
||
or "根据下面的证据写一份简洁的报告，先总后分。"
|
||
rules = MARKER_RULES
|
||
if claims in ("require_citation", CLAIMS_JUDGE):
|
||
# 裁判只看写作者挂的依据：要判，就更得每句都挂上
|
||
rules = f"{rules}\n{CLAIMS_RULE}" + (f"\n{judging.JUDGE_RULE}" if claims == CLAIMS_JUDGE else "")
|
||
return [
|
||
SystemMessage(content="\n\n".join(p for p in (system, ROLE) if p)),
|
||
HumanMessage(content=(
|
||
f"{instructions}\n\n{catalog_prompt(catalog, cells_allowed=cells)}\n\n{rules}\n\n"
|
||
"只输出报告正文（Markdown），不要写撰写说明。"
|
||
)),
|
||
]
|
||
|
||
|
||
async def _store(doc: dict[str, Any], ctx: NodeContext) -> str | None:
|
||
from app.core.artifact_store import put_json
|
||
|
||
try:
|
||
return await put_json(doc, kind="report_doc", run_id=ctx.run.run_id, node_id=ctx.node.id,
|
||
meta={"stats": doc.get("stats") or {}})
|
||
except Exception as e: # noqa: BLE001 - 工件写失败不毁掉运行，只是这份报告点不开证据
|
||
ctx.emit(EventType.LOG, level="warn", code="evidence_store_failed",
|
||
message=f"报告文档保存失败（{describe_exception(e)}），报告中的数字将无法查看证据")
|
||
return None
|
||
|
||
|
||
async def run_report(state: GraphState, ctx: NodeContext) -> dict[str, Any]:
|
||
numbers, max_repairs = _options(ctx)
|
||
on_violation = str(ctx.cfg("on_violation", "") or "") or await _default_on_violation(ctx.run.run_id)
|
||
if on_violation not in ON_VIOLATION:
|
||
raise NodeError(ctx.node.id, _only("on_violation", ("flag", "fail"), on_violation))
|
||
|
||
async with SessionLocal() as session:
|
||
try:
|
||
model, model_id = await get_chat_model(session, _model_spec(ctx))
|
||
except ProviderNotConfigured as e:
|
||
raise NodeError(ctx.node.id, not_configured(e)) from e
|
||
|
||
spec = ctx.run.spec
|
||
catalog = report_catalog(state, spec, ctx.node)
|
||
allow = report_allowance(spec, ctx.node)
|
||
cells = True
|
||
# 结论句策略只对升级后发起的运行生效：升级前的运行（图里也不会有 claims）事件、产出一个字不加
|
||
evidence_on = ledger_enabled(ctx.run)
|
||
claims = report_claims(spec, ctx.node) if evidence_on else "off"
|
||
if evidence_on:
|
||
# 升级前发起的运行没有查询条目，单元格无从谈起，也就不多查这一次
|
||
from app.engine.governance import governed_formal
|
||
|
||
cells = report_cells_allowed(spec, ctx.node, governed=await governed_formal(ctx.run.run_id))
|
||
if warning := _no_evidence(catalog, cells):
|
||
ctx.emit(EventType.LOG, level="warn", code="report_no_evidence", message=warning)
|
||
|
||
messages = _messages(ctx, state, catalog, cells, claims)
|
||
started = time.perf_counter()
|
||
spent: list[dict[str, Any]] = []
|
||
nudged = False
|
||
|
||
async def draft(payload: list[BaseMessage]) -> tuple[BaseMessage, str]:
|
||
nonlocal nudged
|
||
stream = _RenderedStream(ctx, catalog, cells)
|
||
began = time.perf_counter()
|
||
response = await _invoke_streaming(model, payload, stream, model_id) # type: ignore[arg-type]
|
||
stream.flush()
|
||
spent.append(_report_call(ctx, response, model_id, began))
|
||
text = message_text(response)
|
||
if snippet := leaked_markup(text):
|
||
# 写成了一段工具调用标记：纠正一次，还这样就判失败，别把标记当报告往下游送
|
||
if nudged:
|
||
raise NodeError(ctx.node.id, MARKUP_ERROR)
|
||
nudged = True
|
||
ctx.emit(EventType.LOG, level="warn", code="tool_markup_leak",
|
||
message=f"{markup_warning(snippet)}，已要求模型重试一次")
|
||
return await draft([*payload, response, HumanMessage(content=MARKUP_NUDGE)])
|
||
if not text and thinking_text(response):
|
||
ctx.emit(EventType.LOG, level="warn", code="empty_completion",
|
||
message="模型只输出了思考内容，报告正文为空。请调大「最大输出 token」，或关闭「思考模式」。")
|
||
return response, text
|
||
|
||
entities = report_entities(spec, ctx.node) == "link"
|
||
|
||
def compose(raw: str) -> dict[str, Any]:
|
||
return compose_doc(raw, catalog, node_id=ctx.node.id, run_id=ctx.run.run_id, allow_numbers=allow,
|
||
cells_allowed=cells, entities=entities)
|
||
|
||
response, raw = await draft(messages)
|
||
doc = compose(raw)
|
||
repairs = 0
|
||
while (blocking := _blocking(doc["violations"], numbers)) and repairs < max_repairs:
|
||
repairs += 1
|
||
ctx.emit(EventType.LOG, level="warn", code="report_repair",
|
||
message=f"报告有 {len(blocking)} 处未通过核对（{_named(blocking)}），"
|
||
f"已要求模型重写（第 {repairs} 次）")
|
||
messages = [*messages, response, HumanMessage(content=_repair_request(blocking))]
|
||
response, raw = await draft(messages)
|
||
doc = compose(raw)
|
||
|
||
judgement: dict[str, Any] | None = None
|
||
if claims == CLAIMS_JUDGE:
|
||
judge_cfg = report_judge(spec, ctx.node)
|
||
if await _run_class(ctx.run.run_id) != "formal":
|
||
# 探索运行默认按需裁判：点开哪句才判哪句，节点里不花这笔钱
|
||
judgement = judging.on_demand(doc, on_unsupported=judge_cfg["on_unsupported"],
|
||
rewrite_once=judge_cfg["rewrite_once"], writer_model=model_id)
|
||
elif not (blocking and on_violation == "fail"):
|
||
# 反正要判失败的报告不值得再花钱判（节点紧接着就报错）
|
||
doc, response, blocking, judgement, usages = await _judge_inline(
|
||
ctx, doc, catalog, judge_cfg, model_id=model_id, messages=[*messages, response],
|
||
draft=draft, compose=compose, numbers=numbers, blocking=blocking)
|
||
spent.extend(usages)
|
||
|
||
doc_artifact = await _store(doc, ctx)
|
||
ctx.emit(EventType.REPORT_CHECKED, doc_artifact=doc_artifact, ok=not doc["violations"],
|
||
stats=doc["stats"], violations=doc["violations"][:20], repairs=repairs,
|
||
on_violation=on_violation, failed=bool(blocking) and on_violation == "fail",
|
||
**({"claims": claims} if evidence_on else {}),
|
||
**({"judge": judgement} if judgement is not None else {}))
|
||
if blocking and on_violation == "fail":
|
||
head = "；".join(v["message"] for v in blocking[:5])
|
||
more = f"；…另有 {len(blocking) - 5} 处" if len(blocking) > 5 else ""
|
||
raise NodeError(
|
||
ctx.node.id,
|
||
f"报告有 {len(blocking)} 处未通过核对（已要求重写 {repairs} 次）：{head}{more}。"
|
||
f"请换用指令遵循能力更强的模型，或先将「{field_label('on_violation')}」设为"
|
||
f"「{option_label('on_violation', 'flag')}」，查看标注后再调整",
|
||
)
|
||
|
||
usage = {key: sum(one[key] for one in spent) for key in spent[0]}
|
||
usage["cost_usd"] = round(usage["cost_usd"], 6)
|
||
text = doc["markdown"]
|
||
result = {
|
||
"text": text,
|
||
"doc_artifact": doc_artifact,
|
||
"stats": doc["stats"],
|
||
"violations": doc["violations"][:20],
|
||
"repairs": repairs,
|
||
"model": model_id,
|
||
"duration_ms": int((time.perf_counter() - started) * 1000),
|
||
**({"claims": claims} if evidence_on else {}),
|
||
**({"judge": judgement} if judgement is not None else {}),
|
||
}
|
||
updates: dict[str, Any] = {"nodes": {ctx.node.id: result}, "usage": usage}
|
||
if ctx.cfg("emit_message", True):
|
||
updates["messages"] = [AIMessage(content=text or "（空）")]
|
||
var_name = ctx.cfg("assign_to", "")
|
||
if var_name:
|
||
updates["vars"] = {var_name: text}
|
||
return updates
|
||
|
||
|
||
# --------------------------------------------------------------------------
|
||
# claims: judge——正式运行在节点里裁判
|
||
# --------------------------------------------------------------------------
|
||
|
||
|
||
def _rewrite_request(sentences: list[tuple[str, str]]) -> str:
|
||
listed = "\n".join(f"{i}.「{text}」——{why or '证据不支持这句话'}" for i, (text, why) in enumerate(sentences, 1))
|
||
return (
|
||
"另一个模型按证据逐句核对了你的报告，下面这几句它认为证据不支持（和证据相矛盾，或者证据不足）：\n"
|
||
f"{listed}\n\n"
|
||
"请只改这几句：补上证据目录里真有的依据 [[see:…]]，或者把说法收窄到证据能支持的程度，或者删掉；"
|
||
"其余部分一字不改。数字仍然只能用引用标记写。不要解释改了什么，只输出改好的整篇报告正文。"
|
||
)
|
||
|
||
|
||
def _rewrite_reason(verdict: dict[str, Any]) -> str:
|
||
"""交回写作者的理由：裁判的理由，证据不足的再写上缺的是什么。"""
|
||
why = str(verdict.get("rationale") or "")
|
||
if verdict.get("status") == "insufficient" and verdict.get("missing"):
|
||
why = f"{why}（缺少：{verdict['missing']}）" if why else f"证据不足，缺少：{verdict['missing']}"
|
||
return why
|
||
|
||
|
||
def _merge(first: dict[str, Any], second: dict[str, Any], budget: judging.Budget) -> dict[str, Any]:
|
||
"""改写前后两轮裁判合成一份：判定、句数、缺口按改写后这一稿，花费、调用、用时两轮相加。"""
|
||
merged = dict(second)
|
||
for key in ("cost_usd", "estimated_usd"):
|
||
merged[key] = round(first[key] + second[key], 6)
|
||
for key in ("calls", "duration_ms"):
|
||
merged[key] = first[key] + second[key]
|
||
merged["notes"] = list(dict.fromkeys([*first["notes"], *second["notes"]]))
|
||
merged["budget"] = budget.as_dict()
|
||
merged["model"] = second.get("model") or first.get("model")
|
||
merged["priced"] = first.get("priced")
|
||
return merged
|
||
|
||
|
||
async def _judge_inline(ctx: NodeContext, doc: dict[str, Any], catalog: dict[str, Any], judge_cfg: dict[str, Any], *,
|
||
model_id: str, messages: list[BaseMessage], draft: Any, compose: Any, numbers: str,
|
||
blocking: list[dict[str, Any]]
|
||
) -> tuple[dict[str, Any], BaseMessage, list[dict[str, Any]], dict[str, Any], list[dict[str, Any]]]:
|
||
"""写完、核对完之后请裁判判一遍，判定写进文档。返回 (文档, 写作者最后一稿, 要拦的违规, 裁判摘要, 用量)。
|
||
|
||
messages 是写作的对话、最后一条是写作者这一稿。rewrite_once 时把证据不支持的句子交回去只改这几句，
|
||
再判一次（没改的句子直接用第一次的判定），最多一轮；改写稿冒出原稿没有的违规就不采用，保留原稿。
|
||
|
||
摘要里的 rewrite = {units, sentences, applied, reason, changed}：
|
||
- sentences：交回去的句子（原稿里的原文）
|
||
- units：这几句在封存文档里的编号。没采用时封存的是原稿，就是原稿的编号；采用了封存的是改写稿，
|
||
编号按改写稿重排，按原文认：原句原样留在改写稿里的给新编号，改掉了的是 null
|
||
- changed：采用时改写稿里新出来的句子（原稿里没有这段原文）在封存文档里的编号；没采用是 []
|
||
"""
|
||
from app.engine.replay import _in_graph
|
||
|
||
async with SessionLocal() as session:
|
||
settings = await judging.judge_settings(session)
|
||
judge_spec = await judging.judge_model_spec(session, judge_cfg, settings=settings)
|
||
budget = judging.report_budget(settings, judge_cfg)
|
||
masks = await judging.source_masks(catalog)
|
||
|
||
@task
|
||
async def judge_step(request: judging.JudgeRequest, key: str, limits: judging.Budget, known: dict[str, Any],
|
||
first: bool) -> dict[str, Any]:
|
||
# 裁判进 checkpoint：「接着跑」时直接取这里的判定，不再调用、不再计费（每日计数也记在这里面）。
|
||
# 事件都在这里面发：取缓存时不会再发一遍。第二轮 limits 是剩下的钱和时间，说给人看的仍是配置的上限
|
||
outcome = await judging.run_request(request, spec=judge_spec, budget=limits, known=known, emit=ctx.emit,
|
||
shown=budget)
|
||
if first and outcome.get("model") and outcome["model"] == model_id:
|
||
outcome["same_model"] = True
|
||
ctx.emit(EventType.LOG, level="warn", code="judge_same_model",
|
||
message=f"裁判模型与写作模型相同（「{model_id}」），难以发现写作模型自身的错误。"
|
||
"请在「设置 → 偏好设置 → 证据裁判」中选择另一个模型，"
|
||
f"或在节点的「{field_label('judge')}」中指定裁判模型")
|
||
return {**outcome, "key": key}
|
||
|
||
async def judge_round(round_doc: dict[str, Any], limits: judging.Budget, known: dict[str, Any],
|
||
first: bool) -> dict[str, Any]:
|
||
request = judging.prepare(round_doc, catalog, masked=masks)
|
||
key = judging.request_key(request, judge_spec, limits, known)
|
||
if _in_graph():
|
||
# 写作不进 checkpoint，接着跑时写作者会重写一稿：缓存里先前那一稿的判定对不上指纹，往后翻
|
||
for _ in range(_STALE_LIMIT):
|
||
outcome = await judge_step(request, key, limits, known, first)
|
||
if outcome.get("key") == key:
|
||
return outcome
|
||
return await judging.run_request(request, spec=judge_spec, budget=limits, known=known, emit=ctx.emit,
|
||
shown=budget)
|
||
|
||
outcome = await judge_round(doc, budget, {}, True)
|
||
same_model = bool(outcome.get("same_model"))
|
||
usages = [outcome["usage"]]
|
||
response = messages[-1]
|
||
rewrite: dict[str, Any] | None = None
|
||
# 交回改写的：证据相矛盾的（含旧取值 unsupported）和证据不足的——两样原来都判作「证据不支持」
|
||
bad = [uid for uid, v in outcome["verdicts"].items() if v["status"] in (*judging.CONTRADICTED, "insufficient")]
|
||
if judge_cfg["rewrite_once"] and bad:
|
||
texts = judging.unit_texts(doc)
|
||
sentences = [(texts.get(uid, ""), _rewrite_reason(outcome["verdicts"][uid])) for uid in bad]
|
||
ctx.emit(EventType.LOG, level="warn", code="report_rewrite",
|
||
message=f"裁判认为 {len(bad)} 句结论证据不支持（{_named([{'text': t} for t, _ in sentences])}），"
|
||
"已退回写作模型仅修改这几句")
|
||
again, raw = await draft([*messages, HumanMessage(content=_rewrite_request(sentences))])
|
||
rewritten = compose(raw)
|
||
worse = _blocking(rewritten["violations"], numbers)
|
||
fresh = _new_violations(doc["violations"], rewritten["violations"])
|
||
rewrite = {"units": bad, "sentences": [t for t, _ in sentences], "applied": False, "reason": None,
|
||
"changed": []}
|
||
if fresh:
|
||
rewrite["reason"] = (f"改写稿新增了 {len(fresh)} 处原稿没有的问题（{_named(fresh)}），未予采用，"
|
||
"已保留原稿及原有判定")
|
||
ctx.emit(EventType.LOG, level="warn", code="report_rewrite_rejected", message=rewrite["reason"])
|
||
else:
|
||
known = {outcome["keys"][u]: v for u, v in outcome["verdicts"].items() if v["status"] in judging.JUDGED}
|
||
# 第二轮用第一轮剩下的钱和时间：每份报告的上限管的是整份报告
|
||
left = judging.Budget(
|
||
max_claims=budget.max_claims,
|
||
max_cost_usd=None if budget.max_cost_usd is None else max(0.0, budget.max_cost_usd - outcome["cost_usd"]),
|
||
timeout_s=None if budget.timeout_s is None else max(0.0, budget.timeout_s - outcome["duration_ms"] / 1000),
|
||
daily_max_usd=budget.daily_max_usd)
|
||
second = await judge_round(rewritten, left, known, False)
|
||
usages.append(second["usage"])
|
||
outcome = _merge(outcome, second, budget)
|
||
doc, response, blocking = rewritten, again, worse
|
||
# 封存的是改写稿，编号按它重排：按原文认回去，改掉了的句子在改写稿里没有编号
|
||
now = judging.unit_texts(rewritten)
|
||
at: dict[str, str] = {}
|
||
for uid, text in now.items():
|
||
at.setdefault(text, uid)
|
||
before = set(texts.values())
|
||
rewrite.update(applied=True, units=[at.get(texts.get(uid, "")) for uid in bad],
|
||
changed=[uid for uid, text in now.items() if text not in before])
|
||
summary = judging.summarize(outcome, mode="inline", on_unsupported=judge_cfg["on_unsupported"],
|
||
rewrite_once=judge_cfg["rewrite_once"], same_model=same_model, rewrite=rewrite,
|
||
writer_model=model_id)
|
||
judging.apply_judgement(doc, outcome, summary)
|
||
return doc, response, blocking, summary, usages
|
||
|