阶段F第二部分: 知识链派发——抽取智能体接入框架派发（离线7项绿+第3章真实抽取产出19条草稿，修复重派路径首次真实验证）
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#!/usr/bin/env python3
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"""抽取智能体的框架派发桥（阶段 F 第二部分）。
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职责分界（边界合同）：智能体框架负责模型事件、raw、逐回合调用，记在派发
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运行下；生产编排负责知识草稿落库与业务回执，记在生产抽取运行下。两者以
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trigger_detail.productionRunId 关联。
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与写手桥的两点不同：
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1. 全量正典正文注入任务输入——证据必须是正文逐字片段，而只读工具读正文
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会截断，注入是唯一可靠路径；工具白名单留给查重与回读核验。
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2. 单次派发（探索与产出同循环）——抽取产出是结构化 JSON，无长篇碎片化
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风险，不需要两阶段。
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机械校验、修复重派（一轮）、保守收口全部复用既有可信适配层，不新造合同。
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"""
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from __future__ import annotations
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import json
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import sys
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from pathlib import Path
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from typing import Any, Callable, Mapping
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SCRIPT_DIR = Path(__file__).resolve().parent
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DISPATCH_SCRIPTS = SCRIPT_DIR.parents[1] / "dispatch-agent-task" / "scripts"
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if str(DISPATCH_SCRIPTS) not in sys.path:
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sys.path.insert(0, str(DISPATCH_SCRIPTS))
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from extract_knowledge import ( # noqa: E402
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ACTOR,
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ExtractionContractError,
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_load_chapter,
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_propose_chapter_extract_lesson,
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normalize_extraction,
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persist_extraction,
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salvage_extraction,
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)
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from muse_llm import extract_json # noqa: E402
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from record_failed_run import record_failure # noqa: E402
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from run_registry import finish_run, new_run_id, start_run # noqa: E402
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from dispatch_agent_task import run_dispatch # noqa: E402
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from pi_runner import ExecutionPolicy # noqa: E402
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from read_tools import TOOL_REGISTRY # noqa: E402
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# 抽取探索白名单：查重与回读核验；正文本体注入任务输入，不依赖工具读取。
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EXTRACTION_TOOL_ALLOWLIST = ("read_chapter_text", "search_entities")
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# 抽取产出是结构化 JSON；严格语义由 normalize_extraction 机械校验，Schema 只做形状兜底。
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EXTRACTION_OUTPUT_SCHEMA: dict[str, Any] = {
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"$schema": "https://json-schema.org/draft/2020-12/schema",
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"type": "object",
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"required": ["entities", "relations", "state"],
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"properties": {
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"entities": {"type": "array"},
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"relations": {"type": "array"},
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"state": {"type": "object"},
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},
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}
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EXTRACTION_MAX_DURATION_SECONDS = 1800
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SESSION_ROOT = Path("/tmp/muse-agent-runs/extractor-sessions")
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class DispatchExtractionError(RuntimeError):
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"""抽取派发失败：携带稳定错误码，编排方按失败关闭处理。"""
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def __init__(self, code: str, message: str, *, details: Mapping[str, Any] | None = None):
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super().__init__(message)
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self.code = code
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self.details = dict(details or {})
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def extractor_session_paths(work_id: int, chapter_order: int) -> tuple[str, Path]:
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"""一章一个抽取智能体会话：修复重派在同一会话内接续。"""
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session_id = f"extractor-work{work_id}-ch{chapter_order}"
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return session_id, SESSION_ROOT / session_id
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def build_extraction_task_spec(
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*,
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work_id: int,
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chapter_order: int,
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title: str,
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chapter_title: str,
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existing_names: list[str],
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body: str,
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repair_reason: str | None = None,
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) -> dict[str, Any]:
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"""装配抽取任务包：全量正文进输入，合同条款进任务提示词。"""
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task_prompt = (
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f"你是抽取智能体。任务：从作品《{title}》第{chapter_order}章"
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f"《{chapter_title or ''}》的已接受正文抽取作品私有知识草稿。"
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"正文全文在冻结输入的 body 字段；证据必须是正文中的逐字连续片段，不能改写。"
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"实体类型只能使用：character、location、faction、power_system、item、event；"
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"立卡门槛：具名且有跨章复用或后续履约潜力，一次性龙套与一次性道具不列实体。"
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"不要确认知识，不要补写正文没有的事实；低置信内容保留但在 brief/fields 中标注“?”。"
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"可用只读工具核对既有实体（查重）与回读正文，但正文以输入 body 为准。"
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"只输出一个 JSON 对象：entities（每项 type/name/brief/fields/evidence）、"
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"relations（每项 source/target/type/description/evidence）、"
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"state（currentSituation/characterStates/foreshadowing/handoff）。"
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)
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if repair_reason:
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task_prompt += (
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"\n【机械校验失败，允许一次修复】失败原因："
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+ repair_reason
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+ "。只修正证据字段，使每条 evidence 都是正文中的逐字连续片段；"
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"删除无法找到逐字证据的条目，不得新增条目、事实、关系或状态。仍只输出同一 JSON 对象。"
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)
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return {
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"specVersion": "agent-task-v1",
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"role": "extractor",
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"taskPrompt": task_prompt,
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"input": {
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"workId": work_id,
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"chapterOrder": chapter_order,
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"title": title,
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"chapterTitle": chapter_title or "",
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"existingEntityNames": existing_names,
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"body": body,
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},
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"outputSchema": EXTRACTION_OUTPUT_SCHEMA,
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"outputSchemaId": "chapter-extraction-v1",
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"toolAllowlist": list(EXTRACTION_TOOL_ALLOWLIST),
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"maxDurationSeconds": EXTRACTION_MAX_DURATION_SECONDS,
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}
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def _read_dispatch_output(receipt: Mapping[str, Any], dispatch_run_id: str) -> Any:
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"""结构化输出回读派发运行目录的 output.json，不另造权威。"""
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output_file = Path(str(receipt.get("runDir") or "")) / "output.json"
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try:
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raw_text = output_file.read_text(encoding="utf-8")
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except OSError as exc:
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raise DispatchExtractionError(
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"EXTRACTION_OUTPUT_MISSING",
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f"抽取派发运行未落结构化输出：{output_file}",
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details={"dispatchRunId": dispatch_run_id},
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) from exc
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try:
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return json.loads(raw_text)
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except ValueError:
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# 模型偶尔包 markdown/解释；用既有提取器兜底，仍失败则失败关闭。
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try:
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return extract_json(raw_text)
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except Exception as exc:
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raise DispatchExtractionError(
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"EXTRACTION_OUTPUT_INVALID",
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f"抽取派发输出不是合法 JSON：{exc}",
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details={"dispatchRunId": dispatch_run_id},
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) from exc
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def run_extraction_via_dispatch(
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work_id: int,
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chapter_order: int,
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*,
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repo_root: str | Path,
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provider: str,
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model: str,
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thinking: str | None = None,
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run_id: str | None = None,
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spec_dir: str | Path | None = None,
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launcher: Callable[..., Any] | None = None,
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connect_factory: Callable[..., Any] | None = None,
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) -> dict[str, Any]:
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"""派发抽取智能体并落知识草稿；返回落库摘要。任何失败失败关闭。"""
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for name in EXTRACTION_TOOL_ALLOWLIST:
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if name not in TOOL_REGISTRY:
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raise DispatchExtractionError(
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"EXTRACTION_TOOL_UNREGISTERED", f"抽取白名单工具未登记：{name}"
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)
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active_run = run_id or new_run_id("extract-knowledge", work_id=work_id, target_chapter=chapter_order)
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start_run(
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run_id=active_run,
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work_id=work_id,
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target_chapter=chapter_order,
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trigger_detail={"stage": "chapter-after-extraction", "mode": "dispatch"},
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creator=ACTOR,
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)
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spec_root = Path(spec_dir) if spec_dir is not None else SCRIPT_DIR
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spec_root.mkdir(parents=True, exist_ok=True)
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session_id, session_dir = extractor_session_paths(work_id, chapter_order)
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session_dir.mkdir(parents=True, mode=0o700, exist_ok=True)
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policy = ExecutionPolicy(provider=provider, model=model, thinking=thinking)
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try:
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(title, chapter_id, chapter_title, _block_id, body), existing = _load_chapter(
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work_id, chapter_order
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)
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existing_names = list(existing[:200])
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def _dispatch_once(attempt: int, repair_reason: str | None) -> tuple[Any, Mapping[str, Any]]:
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spec = build_extraction_task_spec(
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work_id=work_id, chapter_order=chapter_order, title=title,
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chapter_title=chapter_title or "", existing_names=existing_names,
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body=body, repair_reason=repair_reason,
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)
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spec_file = spec_root / f"{active_run}-extractor-task-v{attempt}.json"
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spec_file.write_text(json.dumps(spec, ensure_ascii=False, indent=1), encoding="utf-8")
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dispatch_run_id = f"{active_run}-extractor-v{attempt}"
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receipt, code = run_dispatch(
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spec_file,
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repo_root=repo_root,
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policy=policy,
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run_id=dispatch_run_id,
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trigger_source="user",
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trigger_detail={"stage": "extractor-dispatch", "productionRunId": active_run},
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session_id=session_id,
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session_dir=session_dir,
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enable_read_tools=True,
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launcher=launcher,
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connect_factory=connect_factory,
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)
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if code != 0 or receipt.get("status") != "completed":
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raise DispatchExtractionError(
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str(receipt.get("errorCode") or "EXTRACTION_DISPATCH_FAILED"),
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f"抽取智能体派发未成功：{receipt.get('error') or receipt.get('errorCode')}",
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details={"dispatchRunId": dispatch_run_id, "exitCode": code},
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)
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return _read_dispatch_output(receipt, dispatch_run_id), receipt
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raw_output, receipt = _dispatch_once(1, None)
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try:
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payload = normalize_extraction(raw_output, body)
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except ExtractionContractError as first_error:
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# 只允许一轮机械修复重派（证据绑定），对齐直调链语义。
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raw_output, receipt = _dispatch_once(2, str(first_error))
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try:
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payload = normalize_extraction(raw_output, body)
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except ExtractionContractError:
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payload = salvage_extraction(raw_output, body)
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model_ids = receipt.get("actualModelIds") or []
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result = persist_extraction(
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work_id, chapter_id, chapter_order, active_run, payload,
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requested_model=f"{provider}/{model}",
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actual_model=str(model_ids[-1]) if model_ids else "",
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usage=dict(receipt.get("usage") or {}),
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)
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finish_run(active_run, "completed", creator=ACTOR,
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trigger_detail={"stage": "chapter-after-extraction", "mode": "dispatch",
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"drafts": len(result["draft_ids"])})
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lesson = _propose_chapter_extract_lesson(
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run_id=active_run, work_id=work_id, chapter_order=chapter_order,
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draft_count=len(result["draft_ids"]), state_draft_id=result.get("state_draft_id"),
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)
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return {"run_id": active_run, **result, "lesson": lesson}
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except BaseException as exc:
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finish_run(active_run, "failed", creator=ACTOR,
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trigger_detail={"stage": "chapter-after-extraction", "mode": "dispatch",
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"error_type": type(exc).__name__})
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try:
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record_failure(
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active_run,
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sample_id=f"extract-ch{chapter_order}",
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adapter_role="extractor",
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caller="extract-knowledge-dispatch",
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failure_type=type(exc).__name__,
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)
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except Exception:
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pass
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raise
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__all__ = [
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"EXTRACTION_MAX_DURATION_SECONDS",
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"EXTRACTION_OUTPUT_SCHEMA",
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"EXTRACTION_TOOL_ALLOWLIST",
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"DispatchExtractionError",
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"build_extraction_task_spec",
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"extractor_session_paths",
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"run_extraction_via_dispatch",
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]
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#!/usr/bin/env python3
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"""抽取智能体派发入口（阶段 F 第二部分）。
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真实模型调用必须显式授权并显式给出 provider/model：
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.venv/bin/python .agent/skills/extract-chapter-knowledge/scripts/extract_via_dispatch.py 12 3 \
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--provider catproxy-anthropic --model claude-opus-5 --thinking medium
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"""
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from __future__ import annotations
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import argparse
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import json
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import sys
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from pathlib import Path
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SCRIPT_DIR = Path(__file__).resolve().parent
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if str(SCRIPT_DIR) not in sys.path:
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sys.path.insert(0, str(SCRIPT_DIR))
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from dispatch_extraction_bridge import run_extraction_via_dispatch # noqa: E402
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REPO_ROOT = SCRIPT_DIR.parents[3]
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def main(argv: list[str] | None = None) -> int:
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parser = argparse.ArgumentParser(description="派发抽取智能体做章后知识抽取（知识链）")
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parser.add_argument("work_id", type=int)
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parser.add_argument("chapter_order", type=int)
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parser.add_argument("--provider", required=True)
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parser.add_argument("--model", required=True)
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parser.add_argument("--thinking", default=None)
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parser.add_argument("--run-id", default=None)
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args = parser.parse_args(argv)
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summary = run_extraction_via_dispatch(
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args.work_id,
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args.chapter_order,
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repo_root=REPO_ROOT,
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provider=args.provider,
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model=args.model,
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thinking=args.thinking,
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run_id=args.run_id,
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spec_dir=REPO_ROOT / "docs" / "write-chapter" / "artifacts",
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)
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print(json.dumps(
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{k: v for k, v in summary.items() if k != "lesson"},
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ensure_ascii=False, default=str,
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))
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print(f"RUN_ID={summary['run_id']}")
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print("知识草稿已落库（草稿态）；经经验确认通道 :8766 人审后才转正。")
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return 0
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if __name__ == "__main__":
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raise SystemExit(main())
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@ -173,6 +173,7 @@ A、B 可并行；C 依赖 A；E 依赖 D；F 依赖 E；G 依赖 D（链路透
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- 意图：评委与抽取智能体接入框架派发（评委保持圈定授权隔离）；用对照实验数据裁决直调链去留；处理写手探索冗余——生产链改为只给最小冻结输入（任务提示词 + 授权范围），由写作智能体真正自主探索取材，预组装完整上下文降为对照模式专用（2026-08-22 烟测实证：预组装下写手 0 次工具调用，探索无发生空间）。
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- 第一部分（已完成，离线绿）：两阶段写手落地——探索阶段（只读工具，产出探索清单）与生成阶段（无工具，按回放资料单次成稿）分离；`--two-phase` 旗标；详见 `docs/plans/2026-08-22-阶段F-第一部分-两阶段写手-探索与生成分离.md`。
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- 第二部分（已完成，真实派发通过）：抽取智能体接入框架派发（全量正文注入任务输入，工具白名单留给查重探索；机械校验失败一轮修复重派，仍不合法走保守收口）；候选 164 采纳后对第 3 章首次真实抽取产出 19 条草稿待人审；详见 `docs/plans/2026-08-22-阶段F-第二部分-知识链派发-抽取智能体.md`。
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- 边界：对照只在显式对照模式运行；评测候选四层强制不可接受不变；知识草稿须经人确认转正。
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- 验证：盲评隔离测试（禁看清单越权拒绝）；对照产出可比正文与成本数据；退役项零引用后删除。
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48
docs/plans/2026-08-22-阶段F-第二部分-知识链派发-抽取智能体.md
Normal file
48
docs/plans/2026-08-22-阶段F-第二部分-知识链派发-抽取智能体.md
Normal file
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# 阶段 F 第二部分：知识链派发——抽取智能体
|
||||
|
||||
日期：2026-08-23
|
||||
状态：已完成（离线绿 + 真实派发通过）
|
||||
上游事实：候选 164 经决策通道采纳（署名 qingse），第 3 章正典落库（5131 字）；接受意图 `queue_chapter_extraction`。
|
||||
|
||||
## 1. 意图
|
||||
|
||||
抽取智能体接入框架派发（边界合同：智能体框架记模型事件/raw，生产编排记知识草稿与业务回执），替代抽取直调链的生产使用；直调链保留为对照/回退，终态裁决按总 plan 用数据说话。
|
||||
|
||||
## 2. 设计
|
||||
|
||||
```text
|
||||
生产编排：注册抽取运行 → 读正典章全量正文 + 既有实体名
|
||||
↓
|
||||
派发抽取智能体（单次派发，探索与产出同一循环）：
|
||||
输入 = 全量正文（注入，不经工具——工具读取会截断）+ 既有实体名 + 抽取合同
|
||||
工具白名单 = read_chapter_text、search_entities（查重与回读核验用）
|
||||
产出 = 结构化抽取 JSON（entities/relations/state）
|
||||
↓
|
||||
机械校验：normalize_extraction（证据必须正文逐字片段）
|
||||
失败 → 一次修复重派（只纠证据绑定，不新增条目）→ 仍失败 → salvage 保守收口
|
||||
↓
|
||||
落库：persist_extraction（muse_knowledge_draft，草稿态）→ 人确认转正（:8766）
|
||||
```
|
||||
|
||||
关键取舍：
|
||||
|
||||
- 正文注入而非工具读取：`read_chapter_text` 超长截断，证据逐字绑定要求全量正文，注入是唯一可靠路径；工具留给查重探索。
|
||||
- 单次派发（非两阶段）：抽取产出是结构化 JSON，无长篇碎片化风险；探索与产出同循环。
|
||||
- 机械校验与落库全部复用既有可信适配层（`normalize_extraction`/`salvage_extraction`/`persist_extraction`），不新造合同。
|
||||
- 修复重派一轮（证据绑定是机械问题，对齐直调链既有语义）；仍不合法走 salvage；salvage 失败失败关闭。
|
||||
- 证据归属：派发运行 `{run_id}-extractor-v{N}` 记事件/raw（trigger_detail 带 productionRunId），草稿落生产抽取运行。
|
||||
|
||||
## 3. 改动台账
|
||||
|
||||
| 文件 | 动作 | 原因 |
|
||||
|---|---|---|
|
||||
| `.agent/skills/extract-chapter-knowledge/scripts/dispatch_extraction_bridge.py` | 新增 | 抽取任务包装配 + 派发编排（校验/修复/落库/收口） |
|
||||
| `.agent/skills/extract-chapter-knowledge/scripts/extract_via_dispatch.py` | 新增 | 派发入口（显式 provider/model，真实调用需授权） |
|
||||
| `tests/skills/extract-chapter-knowledge/test_dispatch_extraction_bridge.py` | 新增 | 离线测试（7 项） |
|
||||
|
||||
## 4. 验证结果
|
||||
|
||||
- 离线测试 7/7 通过。
|
||||
- 真实派发（作品 12 第 3 章，`extract-knowledge-w12-c3-20260823T150511`，catproxy-anthropic/claude-opus-5，medium）：
|
||||
- v1 派发完成但证据绑定未过 `normalize_extraction` → 桥自动触发 v2 修复重派 → 通过（修复路径首次真实验证）。
|
||||
- 18 条实体草稿 + 1 条叙事状态草稿落库（status=pending），看板与经验确认通道 :8766 可见，待人审转正。
|
||||
@ -0,0 +1,153 @@
|
||||
#!/usr/bin/env python3
|
||||
"""抽取智能体派发桥离线测试（阶段 F 第二部分）。
|
||||
|
||||
固定合同：任务包装配（正文注入/白名单/修复提示词）、单轮派发产出合法抽取、
|
||||
机械校验失败触发一轮修复重派、两轮失败走保守收口、派发失败失败关闭。
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import contextlib
|
||||
import json
|
||||
import pathlib
|
||||
import sys
|
||||
import tempfile
|
||||
import unittest
|
||||
from unittest import mock
|
||||
|
||||
PROJECT_ROOT = pathlib.Path(__file__).resolve().parents[3]
|
||||
SCRIPT_DIR = PROJECT_ROOT / ".agent" / "skills" / "extract-chapter-knowledge" / "scripts"
|
||||
for path in (SCRIPT_DIR,):
|
||||
if str(path) not in sys.path:
|
||||
sys.path.insert(0, str(path))
|
||||
|
||||
import dispatch_extraction_bridge as bridge # noqa: E402
|
||||
from dispatch_extraction_bridge import ( # noqa: E402
|
||||
DispatchExtractionError,
|
||||
build_extraction_task_spec,
|
||||
extractor_session_paths,
|
||||
run_extraction_via_dispatch,
|
||||
)
|
||||
|
||||
BODY = "第三章 波纹。茧从实验舰外舱门的裂口挤出去，金属边缘像被剥开的肋骨。林深盯着深渊方向。"
|
||||
|
||||
|
||||
def _valid_payload(evidence="茧从实验舰外舱门的裂口挤出去"):
|
||||
return {
|
||||
"entities": [
|
||||
{"type": "character", "name": "林深", "brief": "试机师", "fields": {}, "evidence": "林深盯着深渊方向"},
|
||||
{"type": "item", "name": "茧", "brief": "生物机甲", "fields": {}, "evidence": evidence},
|
||||
],
|
||||
"relations": [
|
||||
{"source": "林深", "target": "茧", "type": "神经链接", "description": "链接",
|
||||
"evidence": "茧从实验舰外舱门的裂口挤出去"},
|
||||
],
|
||||
"state": {"currentSituation": "出击", "characterStates": {}, "foreshadowing": {"埋": [], "推": [], "收": []}, "handoff": ""},
|
||||
}
|
||||
|
||||
|
||||
def _load_chapter_fake(work_id, chapter_order):
|
||||
return ("深渊机神", 301, "波纹", 901, BODY), ["林深", "茧"]
|
||||
|
||||
|
||||
class ExtractionSpecTest(unittest.TestCase):
|
||||
|
||||
def test_spec_shape(self):
|
||||
spec = build_extraction_task_spec(
|
||||
work_id=12, chapter_order=3, title="深渊机神", chapter_title="波纹",
|
||||
existing_names=["林深"], body=BODY,
|
||||
)
|
||||
self.assertEqual(spec["role"], "extractor")
|
||||
self.assertEqual(spec["input"]["body"], BODY)
|
||||
self.assertEqual(spec["input"]["existingEntityNames"], ["林深"])
|
||||
self.assertEqual(spec["toolAllowlist"], ["read_chapter_text", "search_entities"])
|
||||
self.assertIn("逐字连续片段", spec["taskPrompt"])
|
||||
self.assertNotIn("机械校验失败", spec["taskPrompt"])
|
||||
|
||||
def test_spec_repair_appends_reason(self):
|
||||
spec = build_extraction_task_spec(
|
||||
work_id=12, chapter_order=3, title="深渊机神", chapter_title="波纹",
|
||||
existing_names=[], body=BODY, repair_reason="entities[0] 证据不在正文中",
|
||||
)
|
||||
self.assertIn("机械校验失败", spec["taskPrompt"])
|
||||
self.assertIn("不得新增条目", spec["taskPrompt"])
|
||||
|
||||
def test_session_paths(self):
|
||||
sid, path = extractor_session_paths(12, 3)
|
||||
self.assertEqual(sid, "extractor-work12-ch3")
|
||||
self.assertIn("extractor-sessions", str(path))
|
||||
|
||||
|
||||
class OrchestrationTest(unittest.TestCase):
|
||||
|
||||
def setUp(self):
|
||||
self._tmp = tempfile.TemporaryDirectory()
|
||||
self.tmp = pathlib.Path(self._tmp.name)
|
||||
self.dispatches = []
|
||||
|
||||
def tearDown(self):
|
||||
self._tmp.cleanup()
|
||||
|
||||
def _fake_dispatch(self, outputs):
|
||||
"""outputs: 每次派发依次返回的 JSON（Exception 表示派发失败）。"""
|
||||
outputs = list(outputs)
|
||||
|
||||
def fake(spec_file, **kwargs):
|
||||
self.dispatches.append(kwargs["run_id"])
|
||||
run_dir = self.tmp / kwargs["run_id"]
|
||||
run_dir.mkdir(parents=True)
|
||||
out = outputs[len(self.dispatches) - 1]
|
||||
if isinstance(out, Exception):
|
||||
return {"status": "failed", "errorCode": "TIMEOUT"}, 1
|
||||
(run_dir / "output.json").write_text(json.dumps(out, ensure_ascii=False), encoding="utf-8")
|
||||
return {"status": "completed", "runDir": str(run_dir),
|
||||
"actualModelIds": ["catproxy-anthropic/claude-opus-5"],
|
||||
"usage": {"input_tokens": 10}}, 0
|
||||
|
||||
return fake
|
||||
|
||||
@contextlib.contextmanager
|
||||
def _patched(self, outputs):
|
||||
fake = self._fake_dispatch(outputs)
|
||||
with mock.patch.object(bridge, "run_dispatch", fake), \
|
||||
mock.patch.object(bridge, "_load_chapter", _load_chapter_fake), \
|
||||
mock.patch.object(bridge, "start_run", lambda **kw: {"run_id": kw["run_id"]}), \
|
||||
mock.patch.object(bridge, "finish_run", lambda *a, **kw: None), \
|
||||
mock.patch.object(bridge, "record_failure", lambda *a, **kw: None), \
|
||||
mock.patch.object(bridge, "_propose_chapter_extract_lesson", lambda **kw: None), \
|
||||
mock.patch.object(bridge, "persist_extraction",
|
||||
lambda *a, **kw: {"draft_ids": [1, 2, 3], "state_draft_id": 9}):
|
||||
yield
|
||||
|
||||
def _run(self, outputs):
|
||||
with self._patched(outputs):
|
||||
return run_extraction_via_dispatch(
|
||||
12, 3, repo_root=self.tmp, provider="catproxy-anthropic",
|
||||
model="claude-opus-5", run_id="run-extract-test", spec_dir=self.tmp,
|
||||
)
|
||||
|
||||
def test_single_dispatch_success(self):
|
||||
summary = self._run([_valid_payload()])
|
||||
self.assertEqual(summary["run_id"], "run-extract-test")
|
||||
self.assertEqual(len(summary["draft_ids"]), 3)
|
||||
self.assertEqual(self.dispatches, ["run-extract-test-extractor-v1"])
|
||||
|
||||
def test_repair_round_when_evidence_invalid(self):
|
||||
bad = _valid_payload(evidence="不在正文里的证据")
|
||||
summary = self._run([bad, _valid_payload()])
|
||||
self.assertEqual(self.dispatches, ["run-extract-test-extractor-v1", "run-extract-test-extractor-v2"])
|
||||
self.assertEqual(len(summary["draft_ids"]), 3)
|
||||
|
||||
def test_salvage_after_two_failures(self):
|
||||
bad = _valid_payload(evidence="不在正文里的证据")
|
||||
summary = self._run([bad, bad])
|
||||
# salvage：证据无效但实体名逐字在正文 → 保留并以实体名为最小证据；关系缺证据丢弃
|
||||
self.assertEqual(len(summary["draft_ids"]), 3)
|
||||
self.assertEqual(self.dispatches, ["run-extract-test-extractor-v1", "run-extract-test-extractor-v2"])
|
||||
|
||||
def test_dispatch_failure_fails_closed(self):
|
||||
with self.assertRaises(DispatchExtractionError):
|
||||
self._run([TimeoutError()])
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
unittest.main()
|
||||
Loading…
x
Reference in New Issue
Block a user