把 21 个内置 agent 的 system_prompt 从 specs.py 的 Python 常量外置为 prompts/<spec.name>.md,import 期由 load_prompt 确定性加载;建立 SPECS 名册 + SCHEMA_CATALOG(Pydantic 类型留 Python)+ 统一只读解析入口 SpecResolver。 纯重构、零功能/schema 变更,缓存断点前块字节级不变(不变量 #9)。 @llm packages/agents(步骤1-3) - spec_model.py:抽出 AgentSpec(frozen,字段不变) - prompt_loader.py:load_prompt = utf-8-sig 去BOM → LF 归一 → NFC → rstrip尾LF, 内存缓存 + fail-fast(PromptNotFoundError),import 期确定性 - schema_catalog.py:SCHEMA_CATALOG[name]→output type 唯一真相源(refiner=None) - prompts/*.md ×21:取常量「运行时值」程序化外迁(反斜杠折行已塌缩, 物理换行≡运行时换行);文件名按 spec.name 连字符(style.md/character-gen.md 等) - specs.py:删 21 常量 + AgentSpec 类;system_prompt=load_prompt(name)、 output_schema=SCHEMA_CATALOG[name];建 SPECS + REVIEW_RESERVED_NAMES; *_spec 兼容期保留且 SPECS[name] is *_spec(同一实例)。804→337 行 - __init__.py:显式 __all__ 重导出(避 F401) @backend packages/skills(步骤4-5) - SpecResolver:内置 SPECS(纯内存、零 DB)+ 用户 SkillRegistry 统一 get; 内置 name 永不触发 DB;output_schema_for 精确匹配 - skill_registry:保留命名空间守卫前移至入库校验,拒同名内置 → VALIDATION - toolbox_registry:GeneratorTool.spec 改走 SPECS[...],删 12 个 *_spec 直接 import @devops repo-root - .gitattributes:prompts/*.md text eol=lf(修正:须用完整嵌套路径才匹配) - packages/agents/pyproject:hatchling artifacts 纳入 prompts/*.md 随 wheel/sdist 分发 - ci.yml:新增 build wheel → 裸装 → import ww_agents.SPECS 冒烟 TDD 全程 mock 网关;门禁绿:ruff/format clean · mypy 209 files · pytest 744 passed (含金标准 sha256 回归 / md↔spec↔catalog 一一对应 / fail-fast / BOM+NFC / 内置守卫 / 同一实例 / 编排器无回归 / apps/api import-smoke / 打包冒烟)
250 lines
8.4 KiB
Python
250 lines
8.4 KiB
Python
"""T6 创作工具箱 · 生成器注册表(`TOOLBOX`:把每个生成器声明成一条 `GeneratorTool`)。
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「加一个生成器」= 在本表加一份声明(descriptor 在代码、不进 DB——保 Pydantic schema
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为真类,避免迁移;DB `skills` 表与只读注册表/权限故事不变)。
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两类形态:
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- **legacy**(已上架的 世界观/人设/大纲):`spec=None`,带 `legacy_route` 指向现有更丰富的
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入库/冲突页面,前端据 `legacy_route` 直接跳页,不回归既测代码(通用 generate/ingest
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端点对它们返 404/422);
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- **新工具**(8 个):带 `spec`(§5.1 声明)+ `output_schema`(结构化产物真类)+
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`context_strategy`(注入策略)+ `input_fields`(声明式表单),走通用执行器;声明 `ingest`
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者可经通用 ingest 端点入库(复用既有 continuity 预检 + 白名单 gate,不变量 #3)。
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不变量 #2(只声明 tier,spec 已守)/ #3(AI 产出入库必经验收 gate,预览不写库)。
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"""
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from __future__ import annotations
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from ww_agents import SPECS
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from ww_agents.schemas import (
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BlurbResult,
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BookTeardownResult,
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ContinuationResult,
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DeAiResult,
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DetailedOutlineResult,
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GlossaryResult,
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GoldenFingerResult,
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IdeaListResult,
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NameListResult,
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OpeningResult,
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PolishResult,
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TitleListResult,
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)
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from ww_skills.toolbox import GeneratorTool, IngestSpec, InputField
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# 复用的常见输入字段(DRY:每个生成器都有「一句话需求」textarea)。
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_BRIEF_FIELD = InputField(
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name="brief",
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label="一句话需求",
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type="textarea",
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required=False,
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help="描述创作方向/约束;留空则按作品设定与题材自由发散",
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)
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def _chapter_no_field() -> InputField:
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"""按章展开的生成器(开篇/细纲)所需的章号输入。"""
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return InputField(
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name="chapter_no",
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label="章号",
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type="number",
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required=True,
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default="1",
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help="要生成/展开的章节号(读取该章大纲节拍)",
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)
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# 原文输入(扩写/降AI率/拆书样本所需的大段正文)。
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_SOURCE_TEXT_FIELD = InputField(
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name="text",
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label="原文",
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type="textarea",
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required=True,
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help="待处理的正文/样本片段(扩写/降AI 的原文;拆书的章节样本)",
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)
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# 创作工具箱注册表:key → 描述符。legacy 3 + 新 8 = 11 条。
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TOOLBOX: dict[str, GeneratorTool] = {
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# ---- legacy(spec=None,前端走 legacy_route 跳现有页面)----
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"worldbuilding": GeneratorTool(
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key="worldbuilding",
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title="世界观生成器",
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subtitle="构建内部自洽的世界观与硬规则",
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spec=None,
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output_schema=None,
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context_strategy="with_project",
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input_fields=[],
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legacy_route="/projects/{id}/codex?gen=world",
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),
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"character": GeneratorTool(
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key="character",
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title="人设生成器",
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subtitle="群像防雷同的结构化角色卡",
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spec=None,
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output_schema=None,
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context_strategy="with_world",
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input_fields=[],
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legacy_route="/projects/{id}/codex?gen=character",
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),
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"outline": GeneratorTool(
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key="outline",
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title="大纲生成器",
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subtitle="分卷分章 + 伏笔回收窗口",
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spec=None,
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output_schema=None,
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context_strategy="with_project",
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input_fields=[],
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legacy_route="/projects/{id}/outline",
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),
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# ---- 新工具(走通用执行器)----
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"brainstorm": GeneratorTool(
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key="brainstorm",
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title="脑洞生成器",
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subtitle="突破想象,脑洞大开",
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spec=SPECS["brainstorm"],
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output_schema=IdeaListResult,
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context_strategy="brief_only",
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input_fields=[_BRIEF_FIELD],
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),
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"book-title": GeneratorTool(
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key="book-title",
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title="书名生成器",
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subtitle="一秒生成抓人书名",
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spec=SPECS["book-title"],
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output_schema=TitleListResult,
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context_strategy="brief_only",
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input_fields=[_BRIEF_FIELD],
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),
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"blurb": GeneratorTool(
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key="blurb",
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title="简介生成器",
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subtitle="多版差异化书页文案",
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spec=SPECS["blurb"],
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output_schema=BlurbResult,
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context_strategy="with_project",
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input_fields=[_BRIEF_FIELD],
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),
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"name": GeneratorTool(
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key="name",
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title="名字生成器",
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subtitle="契合世界观的人/物/地命名",
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spec=SPECS["name"],
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output_schema=NameListResult,
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context_strategy="with_world",
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input_fields=[
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_BRIEF_FIELD,
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InputField(
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name="kind",
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label="命名对象",
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type="text",
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required=False,
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help="人物 / 势力 / 地点 / 功法 / 物品 等",
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),
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],
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),
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"golden-finger": GeneratorTool(
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key="golden-finger",
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title="金手指生成器",
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subtitle="自洽机制 + 成长 + 限制代价",
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spec=SPECS["golden-finger"],
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output_schema=GoldenFingerResult,
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context_strategy="with_world",
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input_fields=[_BRIEF_FIELD],
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ingest=IngestSpec(table="world_entities"),
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),
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"glossary": GeneratorTool(
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key="glossary",
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title="词条生成器",
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subtitle="带硬规则的世界观术语表",
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spec=SPECS["glossary"],
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output_schema=GlossaryResult,
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context_strategy="with_world",
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input_fields=[_BRIEF_FIELD],
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ingest=IngestSpec(table="world_entities"),
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),
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"opening": GeneratorTool(
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key="opening",
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title="黄金开篇生成器",
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subtitle="多版高代入感开篇正文",
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spec=SPECS["opening"],
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output_schema=OpeningResult,
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context_strategy="with_outline_chapter",
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input_fields=[_chapter_no_field(), _BRIEF_FIELD],
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),
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"fine-outline": GeneratorTool(
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key="fine-outline",
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title="细纲生成器",
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subtitle="把章节粗节拍展开为场景序列",
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spec=SPECS["fine-outline"],
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output_schema=DetailedOutlineResult,
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context_strategy="with_outline_chapter",
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input_fields=[_chapter_no_field(), _BRIEF_FIELD],
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ingest=IngestSpec(table="outline"),
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),
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# ---- 竞品快赢(Scope B):续写/扩写/降AI率 preview-only;拆书 F1 可落库 rules ----
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"continue": GeneratorTool(
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key="continue",
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title="续写生成器",
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subtitle="承接前文,无缝续写下文",
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spec=SPECS["continue"],
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output_schema=ContinuationResult,
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context_strategy="with_prior_chapter",
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input_fields=[
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InputField(
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name="chapter_no",
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label="续写章号",
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type="number",
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required=False,
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help="续写的目标章号(读取该章已写正文承接;缺则按设定起笔)",
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),
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_BRIEF_FIELD,
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],
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),
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"expand": GeneratorTool(
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key="expand",
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title="扩写生成器",
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subtitle="在原文基础上丰富细节铺陈",
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spec=SPECS["expand"],
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output_schema=PolishResult,
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context_strategy="text_input",
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input_fields=[_SOURCE_TEXT_FIELD, _BRIEF_FIELD],
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),
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"de-ai": GeneratorTool(
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key="de-ai",
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title="降 AI 率生成器",
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subtitle="去机翻腔,更自然的人写质感",
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spec=SPECS["de-ai"],
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output_schema=DeAiResult,
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context_strategy="text_input",
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input_fields=[_SOURCE_TEXT_FIELD, _BRIEF_FIELD],
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),
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"teardown": GeneratorTool(
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key="teardown",
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title="拆书生成器",
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subtitle="拆解主题/原型/结构/钩子套路",
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spec=SPECS["teardown"],
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output_schema=BookTeardownResult,
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context_strategy="text_input",
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input_fields=[
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InputField(
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name="kind",
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label="书名",
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type="text",
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required=False,
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help="待拆解作品的书名(供拆解对照)",
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),
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_SOURCE_TEXT_FIELD,
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_BRIEF_FIELD,
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],
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ingest=IngestSpec(table="rules"), # F1:拆书结论拍平为项目 rules 条目落库
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),
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}
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def get_tool(key: str) -> GeneratorTool | None:
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"""按 key 取生成器描述符;未知 key → None(端点据此返 404)。"""
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return TOOLBOX.get(key)
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