feat: M4 文风 + M5 生成/多provider/Skill + Kimi Code 订阅接入 + 本地联调修复
M4（文风）: style-auditor 双轨（提取指纹/漂移第四审）+ jobs 长任务框架(zombie reaper) + 回炉 refine + GET /style read-back。 M5（生成+扩展）: worldbuilder/character-gen（入库 continuity 409 gate + partition_writes 白名单 + schema→JSONB 形变）； 网关多 provider 回退链/熔断/能力降级（Anthropic/Gemini 适配器）；Skill registry + 表权限沙箱 + 规则； 前端 角色生成器/世界观/Codex/规则页/技能库/⌘K 命令面板。 K1（Kimi Code 订阅接入）: OAuth device-flow（kimi-code）+ 静态 Console key（kimi-code-key）两路径； coding 端点 KimiCLI 伪造头（实测 UA allow-list 门禁，缺则 403）+ JSON 模式结构化（thinking ⊥ tool_choice）。 本地联调修复: CORS 中间件；assemble 注入 premise+「写第N章」指令（修空 prompt 400）； GET /outline·/draft read-back + 大纲/工作台/审稿页重载；写页 client/server 常量边界 + notFound 健壮化； 字数 toLocaleString locale 水合；审稿页终稿从已存草稿 seed（修 accept 422）。 门禁: backend ruff/mypy(157)/alembic 无漂移/pytest 451 · frontend lint/tsc/vitest/build。 Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
This commit is contained in:
Yaojia Wang
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tests/test_m4_e2e.py
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tests/test_m4_e2e.py
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"""M4 端到端：学文风(指纹+证据,版本化) + 漂移打分(第四审) + 回炉（真实 DB，零 token）。
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证明 M4 闭环（DoD：学文风指纹+证据；漂移打分作第四审真持久化；回炉返新旧 diff）：
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用例 1 · 学文风闭环（jobs 异步长任务，M4-c）
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`POST /projects` → `POST .../style`(samples) → **202 `{job_id}`**（写一行 job 返回）；
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BackgroundTask 经 `run_job` 自建独立 session 跑 `run_style_extraction`(analyst 假适配器
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产 `StyleFingerprintResult`)→拆指纹→`SqlStyleFingerprintWriteRepo.append`(真落 pg)。
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ASGITransport 下 `await client.post` 等 background task 跑完（同 M3 时序坑）；override
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`get_session_factory`→`e2e_sm`(真 sessionmaker/同测试 engine/loop)，并 monkeypatch
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`style.build_gateway_for_tier`→真 Gateway 包假适配器(用 background task 的真 session 记账)。
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→ `GET /jobs/{id}` status=done(result.version/dims_count) → 断言 `style_fingerprint` 真有行
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(dimensions_json/evidence_json/version)。再 `mode="update"` 学一次 → version+1。
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用例 2 · 写章第四审（drift scoring）
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学文风后 `assemble` 的 `stable_core` 含指纹 → 第四审能在 review_context 拿指纹对照。
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`POST .../chapters/N/review`(SSE) → 断言 `section{name:"style"}` 帧 + `style{score,segments}`
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帧真发；`GET .../reviews` 留痕行 `style`(dict) 已填；DB 真源 `chapter_reviews.style` 真落库
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(score + segments)。四审齐（continuity/foreshadow/pace/style）无 error。
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用例 3 · 回炉（refine，非持久 / 不变量 #3）
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`POST .../chapters/N/refine` → 200 `{original, refined}`；断言 `refined != original`
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（writer 假适配器据 `req.output_schema is None` 返改写串）+ 不写库。
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确定性 & 零成本（同 M1/M2/M3）：真实 `Gateway` + 多档位假适配器（据 `req.output_schema`
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分支返回固定 `parsed`/`text`，绝不联网）+ 真实 `SqlAlchemyLedgerSink`。无 pg → skip。
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坑（见 memory/gotchas）：
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- 学文风 BackgroundTask 在 `run_job` 自建独立 session 上**自造网关**(`build_gateway_for_tier`,
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从凭据建真 OpenAI 适配器) → E2E 无真凭据，须 monkeypatch `style.build_gateway_for_tier`
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返真 `Gateway`(包假适配器, ledger 绑入参 session)；写侧 `SqlStyleFingerprintWriteRepo` 保持
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真实 → 指纹真落 pg。`run_job` 默认 `repo_factory`→真 `SqlJobRepo`（落真 pg job 行），不动。
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- `get_session_factory` 必 override → `e2e_sm`（真 sessionmaker，同测试 engine/loop），否则
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默认 `get_sessionmaker()` 另建 engine 绑别的 loop（跨 loop 坑）。
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- `get_sessionmaker` engine 绑首个 loop → 每 DB 测试清缓存重建、结束 dispose（同 M3）。
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- ASGITransport 默认 `raise_app_exceptions=True`；SSE 解析 `event:`/`data:` 块；snake_case。
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"""
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from __future__ import annotations
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import json
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import uuid
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from collections.abc import AsyncIterator, Callable
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from typing import Annotated
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import httpx
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import pytest
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from asgi_lifespan import LifespanManager
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from fastapi import Depends
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from sqlalchemy import delete, select
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from sqlalchemy.ext.asyncio import AsyncSession, async_sessionmaker
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from ww_agents import (
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ContinuityReview,
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ForeshadowReview,
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ForeshadowSuggestion,
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PaceIssue,
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PaceReview,
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StyleDimension,
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StyleDriftReview,
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StyleDriftSegment,
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StyleFingerprintResult,
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)
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from ww_api.services.digest_extraction import ChapterDigestFacts
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from ww_db import get_session, get_sessionmaker
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from ww_db.models import (
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Chapter,
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ChapterDigest,
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ChapterReview,
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Foreshadow,
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Job,
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Outline,
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Project,
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StyleFingerprint,
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UsageLedger,
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)
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from ww_llm_gateway import (
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Gateway,
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SqlAlchemyLedgerSink,
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resolve_route,
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)
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from ww_llm_gateway.adapters.base import (
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Capabilities,
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ProviderResult,
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ProviderUsage,
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StreamChunk,
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)
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from ww_llm_gateway.types import LlmRequest
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# 三档位（writer/analyst/light）默认都路由到 deepseek（config.tier_defaults）。
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_PROVIDER = "deepseek"
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# 确定性流式写章 token。
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_TOKENS = ["第", "一", "章", "：", "文风漂移之时。"]
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# 学文风假产物：两维指纹，每维带原文证据（StyleFingerprintResult 提取轨）。
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_FINGERPRINT = StyleFingerprintResult(
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dimensions=[
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StyleDimension(name="句长节奏", value="短句为主", evidence=["他来了。", "她走了。"]),
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StyleDimension(name="叙事人称", value="第三人称", evidence=["他看着远方的山。"]),
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]
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)
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# 第四审（文风漂移）假产物：整体相似度 + 一个低相似段。
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_STYLE_DRIFT = StyleDriftReview(
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score=72,
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segments=[StyleDriftSegment(idx=2, score=40, label="机翻腔")],
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)
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# 三审固定产物（与 M3 一致，让四审图跑通）。
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_FORESHADOW_REVIEW = ForeshadowReview(
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planted=[ForeshadowSuggestion(code="F9", title="新埋：山门禁制", where="第2段")],
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resolved=[],
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)
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_PACE_REVIEW = PaceReview(
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water=[PaceIssue(where="第3段", reason="信息密度低")],
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hook=True,
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beat_map=[1, 3, 5, 2],
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)
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# 回炉改写标记（writer 纯文本返回）：保证 refined != original。
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_REFINE_PREFIX = "【已回炉】"
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# 各档位假用量（喂记账；证明各档位调用各自落库）。
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_USAGE = {
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"writer": ProviderUsage(input_tokens=11, output_tokens=5),
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"analyst": ProviderUsage(input_tokens=23, output_tokens=7),
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"light": ProviderUsage(input_tokens=17, output_tokens=9),
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}
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def _req_text(req: LlmRequest) -> str:
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"""把 `LlmRequest.input`（str | list[Block]）压成纯文本（供回炉改写引用原文）。"""
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if isinstance(req.input, str):
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return req.input
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return "\n".join(block.text for block in req.input)
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class _FakeMultiTierAdapter:
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"""实现 `ProviderAdapter` Protocol：按 `req.output_schema` 分支返回 parsed/text，绝不联网。
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- `complete()`：据 `req.output_schema` 路由：
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`StyleFingerprintResult`→学文风提取（analyst）；四审 schema
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（`ContinuityReview`/`ForeshadowReview`/`PaceReview`/`StyleDriftReview`）→各审；
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`output_schema is None`→**回炉纯文本**（writer，返改写串，保证 refined≠original）；
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其余视作 digest 提炼（light）。
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- `stream()`：吐固定写章 token（writer/draft），末尾喂 writer 用量。
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每路带 `ProviderUsage` → 网关据此各落一条 usage_ledger。
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"""
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provider = _PROVIDER
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def capabilities(self) -> Capabilities:
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return Capabilities(structured_output=True)
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async def complete(self, req: LlmRequest, model: str) -> ProviderResult:
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schema = req.output_schema
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if schema is None:
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# 回炉：writer 纯文本重写选中段（保证 refined != original）。
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return ProviderResult(
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text=_REFINE_PREFIX + _req_text(req),
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parsed=None,
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usage=_USAGE["writer"],
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)
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if schema is StyleFingerprintResult:
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return ProviderResult(
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text=_FINGERPRINT.model_dump_json(),
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parsed=_FINGERPRINT,
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usage=_USAGE["analyst"],
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)
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if schema is StyleDriftReview:
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return ProviderResult(
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text=_STYLE_DRIFT.model_dump_json(),
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parsed=_STYLE_DRIFT,
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usage=_USAGE["light"],
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)
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if schema is ContinuityReview:
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review = ContinuityReview(conflicts=[]) # 零冲突
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return ProviderResult(
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text=review.model_dump_json(), parsed=review, usage=_USAGE["analyst"]
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)
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if schema is ForeshadowReview:
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return ProviderResult(
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text=_FORESHADOW_REVIEW.model_dump_json(),
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parsed=_FORESHADOW_REVIEW,
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usage=_USAGE["analyst"],
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)
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if schema is PaceReview:
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return ProviderResult(
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text=_PACE_REVIEW.model_dump_json(), parsed=_PACE_REVIEW, usage=_USAGE["light"]
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)
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# 否则视为 digest 提炼（ChapterDigestFacts）。
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facts = ChapterDigestFacts(summary="终稿摘要", events=["事件"], locations=["地点"])
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return ProviderResult(text=facts.model_dump_json(), parsed=facts, usage=_USAGE["light"])
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async def stream(self, req: LlmRequest, model: str) -> AsyncIterator[StreamChunk]:
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for token in _TOKENS:
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yield StreamChunk(text=token)
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yield StreamChunk(usage=_USAGE["writer"])
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@pytest.fixture
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async def e2e_sm() -> AsyncIterator[async_sessionmaker[AsyncSession]]:
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"""真实 DB session 工厂；无 pg 时跳过（每测试清缓存重建 engine、结束 dispose）。"""
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get_sessionmaker.cache_clear()
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maker = get_sessionmaker()
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try:
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async with maker() as probe:
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await probe.execute(select(1))
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except Exception:
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pytest.skip("postgres not reachable")
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yield maker
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await maker.kw["bind"].dispose()
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get_sessionmaker.cache_clear()
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def _parse_sse(raw: str) -> list[tuple[str, str]]:
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"""把 text/event-stream 原文解析为 `(event, data)` 帧列表。"""
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frames: list[tuple[str, str]] = []
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event: str | None = None
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data: str | None = None
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for line in raw.splitlines():
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if line.startswith("event:"):
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event = line[len("event:") :].strip()
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elif line.startswith("data:"):
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data = line[len("data:") :].strip()
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elif line == "":
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if event is not None and data is not None:
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frames.append((event, data))
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event, data = None, None
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if event is not None and data is not None:
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frames.append((event, data))
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return frames
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def _gateway_override_factory(
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adapter: _FakeMultiTierAdapter,
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) -> Callable[[AsyncSession], Gateway]:
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"""构造依赖覆盖：真实 Gateway + 给定假适配器 + 真实 ledger（请求 session）。"""
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def _override(session: Annotated[AsyncSession, Depends(get_session)]) -> Gateway:
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return Gateway(
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adapters={_PROVIDER: adapter},
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ledger=SqlAlchemyLedgerSink(session),
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resolver=resolve_route,
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)
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return _override
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def _patched_build_gateway(
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adapter: _FakeMultiTierAdapter,
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) -> Callable[..., object]:
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"""构造 monkeypatch 替身：`style.build_gateway_for_tier`→真 Gateway 包假适配器。
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学文风 BackgroundTask 在 `run_job` 自建的独立 session 上自造网关（从凭据建真 OpenAI
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适配器）——E2E 无真凭据，故替换成返真 `Gateway`(包假适配器, ledger 绑 background task
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的真 session)。写侧 `SqlStyleFingerprintWriteRepo` + `run_job` 默认 `SqlJobRepo` 保持
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真实 → 指纹/job 真落 pg。
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"""
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async def _build(session: AsyncSession, store: object, tier: str) -> Gateway:
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return Gateway(
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adapters={_PROVIDER: adapter},
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ledger=SqlAlchemyLedgerSink(session),
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resolver=resolve_route,
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)
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return _build
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async def _cleanup(e2e_sm: async_sessionmaker[AsyncSession], project_uuid: uuid.UUID) -> None:
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"""按 FK 顺序清理（多数子表经 FK CASCADE；显式删可独立行）。"""
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async with e2e_sm() as cleanup:
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await cleanup.execute(delete(UsageLedger).where(UsageLedger.project_id == project_uuid))
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await cleanup.execute(delete(Job).where(Job.project_id == project_uuid))
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await cleanup.execute(
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delete(StyleFingerprint).where(StyleFingerprint.project_id == project_uuid)
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)
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await cleanup.execute(delete(ChapterDigest).where(ChapterDigest.project_id == project_uuid))
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await cleanup.execute(delete(ChapterReview).where(ChapterReview.project_id == project_uuid))
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await cleanup.execute(delete(Outline).where(Outline.project_id == project_uuid))
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await cleanup.execute(delete(Foreshadow).where(Foreshadow.project_id == project_uuid))
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await cleanup.execute(delete(Chapter).where(Chapter.project_id == project_uuid))
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await cleanup.execute(delete(Project).where(Project.id == project_uuid))
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await cleanup.commit()
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async def test_m4_learn_style_job_done_and_fingerprint_persisted(
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e2e_sm: async_sessionmaker[AsyncSession],
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monkeypatch: pytest.MonkeyPatch,
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) -> None:
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"""用例 1：学文风闭环 → 202 job → 后台跑完 → job done → 指纹真落 pg（含 update version+1）。"""
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import ww_api.routers.style as style_mod
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from ww_api.main import create_app
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from ww_api.services.project_deps import (
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get_session_factory,
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get_style_extract_gateway,
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)
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adapter = _FakeMultiTierAdapter()
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override = _gateway_override_factory(adapter)
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app = create_app()
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# 凭据探测（请求阶段）→ 注假网关，绕过无凭据 503。
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app.dependency_overrides[get_style_extract_gateway] = override
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# BackgroundTask 独立 session 工厂 → 真 sessionmaker（同测试 engine/loop）。
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app.dependency_overrides[get_session_factory] = lambda: e2e_sm
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# BackgroundTask 自造网关 → 替成真 Gateway 包假适配器（写侧 repo + SqlJobRepo 保持真）。
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monkeypatch.setattr(style_mod, "build_gateway_for_tier", _patched_build_gateway(adapter))
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transport = httpx.ASGITransport(app=app)
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project_uuid: uuid.UUID | None = None
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try:
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async with LifespanManager(app):
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async with httpx.AsyncClient(transport=transport, base_url="http://test") as client:
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create_resp = await client.post(
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"/projects", json={"title": "M4 学文风验证作品", "genre": "玄幻"}
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)
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assert create_resp.status_code == 201
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project_id = create_resp.json()["id"]
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project_uuid = uuid.UUID(project_id)
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# 1) 学文风（首学）→ 202 {job_id}（ASGITransport 等 background task 跑完）。
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learn_resp = await client.post(
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f"/projects/{project_id}/style",
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json={"samples": ["他来了。她走了。", "他看着远方的山。"], "mode": "create"},
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)
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assert learn_resp.status_code == 202
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job_id = learn_resp.json()["job_id"]
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# 2) 轮询 job → done，result 含 version/dims_count。
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job_resp = await client.get(f"/jobs/{job_id}")
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assert job_resp.status_code == 200
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job = job_resp.json()
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assert job["status"] == "done"
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assert job["kind"] == "style_learn"
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assert job["result"]["version"] == 1
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assert job["result"]["dims_count"] == 2
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|
||||
# 3) GET /style → 最新指纹（完整维度 + 证据 + 版本）。
|
||||
style_resp = await client.get(f"/projects/{project_id}/style")
|
||||
assert style_resp.status_code == 200
|
||||
fp = style_resp.json()
|
||||
assert fp["version"] == 1
|
||||
assert fp["dimensions"]["句长节奏"] == "短句为主"
|
||||
assert fp["evidence"]["句长节奏"] == ["他来了。", "她走了。"]
|
||||
|
||||
# 4) mode="update" 再学一次 → version+1。
|
||||
update_resp = await client.post(
|
||||
f"/projects/{project_id}/style",
|
||||
json={"samples": ["新样本正文。"], "mode": "update"},
|
||||
)
|
||||
assert update_resp.status_code == 202
|
||||
update_job = (await client.get(f"/jobs/{update_resp.json()['job_id']}")).json()
|
||||
assert update_job["status"] == "done"
|
||||
assert update_job["result"]["version"] == 2
|
||||
|
||||
# DB 真源断言。
|
||||
assert project_uuid is not None
|
||||
async with e2e_sm() as verify:
|
||||
fp_rows = (
|
||||
(
|
||||
await verify.execute(
|
||||
select(StyleFingerprint)
|
||||
.where(StyleFingerprint.project_id == project_uuid)
|
||||
.order_by(StyleFingerprint.version)
|
||||
)
|
||||
)
|
||||
.scalars()
|
||||
.all()
|
||||
)
|
||||
# 两次学文风 → 两行（版本化 INSERT，不覆盖历史）。
|
||||
assert [r.version for r in fp_rows] == [1, 2]
|
||||
first = fp_rows[0]
|
||||
assert first.dimensions_json == {"句长节奏": "短句为主", "叙事人称": "第三人称"}
|
||||
assert first.evidence_json["句长节奏"] == ["他来了。", "她走了。"]
|
||||
|
||||
# job 真落 pg：两行 done。
|
||||
job_rows = (
|
||||
(await verify.execute(select(Job).where(Job.project_id == project_uuid)))
|
||||
.scalars()
|
||||
.all()
|
||||
)
|
||||
assert len(job_rows) == 2
|
||||
assert all(r.status == "done" and r.kind == "style_learn" for r in job_rows)
|
||||
finally:
|
||||
if project_uuid is not None:
|
||||
await _cleanup(e2e_sm, project_uuid)
|
||||
|
||||
|
||||
async def test_m4_review_fourth_style_audit_sse_and_trace(
|
||||
e2e_sm: async_sessionmaker[AsyncSession],
|
||||
monkeypatch: pytest.MonkeyPatch,
|
||||
) -> None:
|
||||
"""用例 2：写章第四审（drift）→ SSE section{style} + style{score,segments} + style 列真填。
|
||||
|
||||
先学文风 → `assemble` 的 stable_core 含指纹 → 第四审能在 review_context 拿指纹对照打分。
|
||||
四审齐（continuity/foreshadow/pace/style）无 error。
|
||||
"""
|
||||
import ww_api.routers.style as style_mod
|
||||
from ww_api.main import create_app
|
||||
from ww_api.services.project_deps import (
|
||||
get_review_gateway,
|
||||
get_session_factory,
|
||||
get_style_extract_gateway,
|
||||
get_writer_gateway,
|
||||
)
|
||||
|
||||
adapter = _FakeMultiTierAdapter()
|
||||
override = _gateway_override_factory(adapter)
|
||||
|
||||
app = create_app()
|
||||
app.dependency_overrides[get_writer_gateway] = override
|
||||
app.dependency_overrides[get_review_gateway] = override
|
||||
app.dependency_overrides[get_style_extract_gateway] = override
|
||||
app.dependency_overrides[get_session_factory] = lambda: e2e_sm
|
||||
monkeypatch.setattr(style_mod, "build_gateway_for_tier", _patched_build_gateway(adapter))
|
||||
|
||||
transport = httpx.ASGITransport(app=app)
|
||||
project_uuid: uuid.UUID | None = None
|
||||
try:
|
||||
async with LifespanManager(app):
|
||||
async with httpx.AsyncClient(transport=transport, base_url="http://test") as client:
|
||||
create_resp = await client.post("/projects", json={"title": "M4 第四审验证作品"})
|
||||
assert create_resp.status_code == 201
|
||||
project_id = create_resp.json()["id"]
|
||||
project_uuid = uuid.UUID(project_id)
|
||||
|
||||
# 1) 学文风 → 指纹入库（供 assemble 注入第四审做对照）。
|
||||
learn_resp = await client.post(
|
||||
f"/projects/{project_id}/style",
|
||||
json={"samples": ["他来了。她走了。"], "mode": "create"},
|
||||
)
|
||||
assert learn_resp.status_code == 202
|
||||
assert (await client.get(f"/jobs/{learn_resp.json()['job_id']}")).json()[
|
||||
"status"
|
||||
] == "done"
|
||||
|
||||
# 2) 写第1章草稿 + 自动保存（供续审）。
|
||||
draft_resp = await client.post(f"/projects/{project_id}/chapters/1/draft")
|
||||
draft_text = "".join(
|
||||
json.loads(d)["text"]
|
||||
for (ev, d) in _parse_sse(draft_resp.text)
|
||||
if ev == "token"
|
||||
)
|
||||
await client.put(
|
||||
f"/projects/{project_id}/chapters/1/draft",
|
||||
json={"text": draft_text},
|
||||
)
|
||||
|
||||
# 3) 续审（SSE）：四审齐 + section{style} + style{score,segments}，无 error。
|
||||
review_resp = await client.post(
|
||||
f"/projects/{project_id}/chapters/1/review",
|
||||
json={"draft": draft_text},
|
||||
)
|
||||
assert review_resp.status_code == 200
|
||||
assert review_resp.headers["content-type"].startswith("text/event-stream")
|
||||
rframes = _parse_sse(review_resp.text)
|
||||
assert [d for (ev, d) in rframes if ev == "error"] == []
|
||||
section_names = {
|
||||
json.loads(d).get("name") for (ev, d) in rframes if ev == "section"
|
||||
}
|
||||
assert {"continuity", "foreshadow", "pace", "style"} <= section_names
|
||||
style_events = [json.loads(d) for (ev, d) in rframes if ev == "style"]
|
||||
assert len(style_events) == 1
|
||||
style_ev = style_events[0]
|
||||
assert style_ev["score"] == 72
|
||||
assert style_ev["segments"][0]["idx"] == 2
|
||||
assert style_ev["segments"][0]["score"] == 40
|
||||
assert style_ev["segments"][0]["label"] == "机翻腔"
|
||||
|
||||
# 4) GET 历史：留痕行 style(dict) 已填。
|
||||
hist_resp = await client.get(f"/projects/{project_id}/chapters/1/reviews")
|
||||
assert hist_resp.status_code == 200
|
||||
latest = hist_resp.json()["reviews"][0]
|
||||
assert isinstance(latest["style"], dict)
|
||||
assert latest["style"]["score"] == 72
|
||||
|
||||
# DB 真源断言：chapter_reviews.style 列真填。
|
||||
assert project_uuid is not None
|
||||
async with e2e_sm() as verify:
|
||||
review_rows = (
|
||||
(
|
||||
await verify.execute(
|
||||
select(ChapterReview).where(ChapterReview.project_id == project_uuid)
|
||||
)
|
||||
)
|
||||
.scalars()
|
||||
.all()
|
||||
)
|
||||
assert len(review_rows) == 1
|
||||
row = review_rows[0]
|
||||
assert isinstance(row.style, dict)
|
||||
assert row.style["score"] == 72
|
||||
assert row.style["segments"][0]["idx"] == 2
|
||||
assert row.style["segments"][0]["label"] == "机翻腔"
|
||||
finally:
|
||||
if project_uuid is not None:
|
||||
await _cleanup(e2e_sm, project_uuid)
|
||||
|
||||
|
||||
async def test_m4_refine_returns_diff_without_persisting(
|
||||
e2e_sm: async_sessionmaker[AsyncSession],
|
||||
) -> None:
|
||||
"""用例 3：回炉 → 200 {original, refined}；refined != original；不写库（不变量 #3）。"""
|
||||
from ww_api.main import create_app
|
||||
from ww_api.services.project_deps import get_refine_gateway
|
||||
|
||||
adapter = _FakeMultiTierAdapter()
|
||||
override = _gateway_override_factory(adapter)
|
||||
|
||||
app = create_app()
|
||||
app.dependency_overrides[get_refine_gateway] = override
|
||||
|
||||
transport = httpx.ASGITransport(app=app)
|
||||
project_uuid: uuid.UUID | None = None
|
||||
try:
|
||||
async with LifespanManager(app):
|
||||
async with httpx.AsyncClient(transport=transport, base_url="http://test") as client:
|
||||
create_resp = await client.post("/projects", json={"title": "M4 回炉验证作品"})
|
||||
assert create_resp.status_code == 201
|
||||
project_id = create_resp.json()["id"]
|
||||
project_uuid = uuid.UUID(project_id)
|
||||
|
||||
segment = "他緩緩走進房間。"
|
||||
refine_resp = await client.post(
|
||||
f"/projects/{project_id}/chapters/1/refine",
|
||||
json={"segment": segment, "instruction": "去掉机翻腔"},
|
||||
)
|
||||
assert refine_resp.status_code == 200
|
||||
body = refine_resp.json()
|
||||
assert body["original"] == segment
|
||||
# writer 假适配器返改写串（前缀），保证 refined != original。
|
||||
assert body["refined"] != body["original"]
|
||||
assert body["refined"].startswith(_REFINE_PREFIX)
|
||||
# 指令进了输入文本（writer 据 output_schema is None 走纯文本路径）。
|
||||
assert "去掉机翻腔" in body["refined"]
|
||||
|
||||
# DB 真源断言：回炉不写库 → 无 chapter/chapter_review 行（不变量 #3）。
|
||||
assert project_uuid is not None
|
||||
async with e2e_sm() as verify:
|
||||
chapter_rows = (
|
||||
(await verify.execute(select(Chapter).where(Chapter.project_id == project_uuid)))
|
||||
.scalars()
|
||||
.all()
|
||||
)
|
||||
assert chapter_rows == []
|
||||
review_rows = (
|
||||
(
|
||||
await verify.execute(
|
||||
select(ChapterReview).where(ChapterReview.project_id == project_uuid)
|
||||
)
|
||||
)
|
||||
.scalars()
|
||||
.all()
|
||||
)
|
||||
assert review_rows == []
|
||||
# 但回炉记账落库（writer 网关 ledger，端点末尾 commit）。
|
||||
ledger_rows = (
|
||||
(
|
||||
await verify.execute(
|
||||
select(UsageLedger).where(UsageLedger.project_id == project_uuid)
|
||||
)
|
||||
)
|
||||
.scalars()
|
||||
.all()
|
||||
)
|
||||
assert len(ledger_rows) == 1
|
||||
assert ledger_rows[0].input_tokens == _USAGE["writer"].input_tokens
|
||||
finally:
|
||||
if project_uuid is not None:
|
||||
await _cleanup(e2e_sm, project_uuid)
|
||||
Reference in New Issue
Block a user