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ThearchyHelios
2f90f0eb3a
- QueryCore 固定执行（K09）：按已发布的不可变口径跑一次，交回类型化标量、发布/manifest 引用与逐查询证据 - 依赖闭包（K08）：按选中的指标算出要拷的取数节点、要的入口字段，接进 derive / compose / metrics - SQL 模板参数完整性（K01）：试跑、组合问数、派生图、运行时取数共用一套语义，缺参数在渲染前就拒 - 受限字段变更服务（K03）与口径领域边界（K01）：改动打在整图深拷贝上，身份与证据归属不可改 - 版本化受控模板绑定（K04）：业务口径按显式绑定落到 SQL，对不上就报 unsupported / needs_update - 验证记录（K05）与最小审阅：样例匹配不等于正式批准，审批人只从服务端身份取 - 发布依据清单（K07）：发布时按不可变图物化内容寻址清单，正式用途按它判 - 增量重导入（K11）与 B/L/R 三方合并、受限自然语言修改提案（K12）：只产候选，落图仍走既有写路径 - 接口与前端：口径草稿页接上字段变更、绑定状态、验证与重导入，新增 caliber-drafts / studio 检查脚本 验证：前端 tsc -b 通过。
434 lines
24 KiB
Python
434 lines
24 KiB
Python
"""K05 的来源侧前置切片：提取时把来源存成不可篡改的工件，引用只认实际进提示的材料。
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这份文件盯住几件 K05 明确要求、而其它测试没覆盖的事：
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1. **快照可还原，不只是哈希。** 提取时把逐份原文、逐段原文、目录文本按内容寻址存进工件库；草稿 payload 只记引用。
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读的时候按 id 回读，原文一模一样，哈希对得上（app/core/artifact_store.load 会复验）。
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2. **chunk id 换了，快照照旧读得回来。** 文档被重新切块、段落 id 换了一批，旧草稿记的引用仍指向当初那一份材料。
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3. **可见的引用才核得上。** 材料超限时 fit_material 从后往前丢段落；被丢掉的段落不在提示里，模型引用它也核不上。
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同一段话在「全量 chunks」下核得上、在「实际进提示的可见 chunks」下核不上。
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4. **每次提示的可见范围有记录。** payload.prompts 逐次记下 visible_chunk_ids、提示词/解析版本、模型、截断情况。
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5. **checkpoint 只是任务恢复，不冒充 B。** checkpoint 里只有「哪些组起草好了」，把它当 payload 读，来源基线仍
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是 baseline_unknown；来源的还原只走工件。
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6. **旧草稿标记 baseline_unknown。** 没有快照的老草稿不拿当前内容伪造历史基线。
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模型一律注入假模型（monkeypatch resolve_draft_model），试跑换成假的，测试不发真实请求、不连真实业务库。
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"""
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from __future__ import annotations
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import copy
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import json
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import uuid
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import pytest
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from sqlalchemy import delete, select
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from app.core.artifact_store import canonical_json, content_hash, load
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from app.db.base import SessionLocal
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from app.db.models import CaliberDraft, Chunk, Document, Workflow, WorkflowVersion
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from app.ledger import authoring, docdraft, draftplan
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from tests.test_ledger_docdraft_api import client, datasource, fake_model, fake_trial # noqa: F401 (fixtures)
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SMALL_ONE = "退款率按已支付订单统计，退款订单不计入。"
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SMALL_TWO = "门店维度只保留已支付订单，未支付不进分子分母。"
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@pytest.fixture(autouse=True)
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def _fake_trial(fake_trial):
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"""本模块的草稿都走接口起草：试跑必须换成假的，不然会去打夹具里不存在的库。
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（fake_trial 是从别的模块 import 进来的普通夹具，它自带的 autouse 在本模块不生效；这里替本模块的每个用例把它拉起来。）"""
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return fake_trial
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# ==========================================================================
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# 夹具：可自定义段落的文档 + 收尾清理
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# ==========================================================================
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@pytest.fixture
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async def docs():
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"""按给定的分段建一份文档；收尾删掉它、它的段落、以及测试期间建的草稿/工作流/运行。"""
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made: list[str] = []
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async def make(doc_id: str, chunks: list[tuple[int, str]], *, title: str = "口径.md") -> str:
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async with SessionLocal() as session:
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session.add(Document(id=doc_id, collection="default", title=title, source=title,
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content="".join(content for _, content in chunks), chunk_count=len(chunks)))
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for ordinal, content in chunks:
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session.add(Chunk(id=f"{doc_id}-{ordinal}", document_id=doc_id, ordinal=ordinal,
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content=content))
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await session.commit()
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made.append(doc_id)
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return doc_id
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yield make
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async with SessionLocal() as session:
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drafts = (await session.execute(select(CaliberDraft))).scalars().all()
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workflow_ids = [draft.workflow_id for draft in drafts if draft.workflow_id]
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workflow_ids += [draft.payload.get("workflow_id") for draft in drafts
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if isinstance(draft.payload, dict) and draft.payload.get("workflow_id")]
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workflow_ids = list(dict.fromkeys(wid for wid in workflow_ids if wid))
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for draft in drafts:
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await session.delete(draft)
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if workflow_ids:
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await session.execute(delete(WorkflowVersion).where(WorkflowVersion.workflow_id.in_(workflow_ids)))
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await session.execute(delete(Workflow).where(Workflow.id.in_(workflow_ids)))
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for doc_id in made:
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await session.execute(delete(Chunk).where(Chunk.document_id == doc_id))
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row = await session.get(Document, doc_id)
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if row is not None:
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await session.delete(row)
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await session.commit()
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async def _extract(client, doc: str, source_id: str, **extra) -> dict:
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body = (await client.post("/api/ledger/drafts/extract",
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json={"documents": [doc], "datasource_id": source_id, **extra})).json()
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return body
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async def _draft(client, draft_id: str) -> dict:
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return (await client.get(f"/api/ledger/drafts/{draft_id}")).json()
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def _reply(chunk_id: str, *, quote: str, name: str = "退款率", sql: str | None = None) -> dict:
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"""一条指标的回复：引用逐字抄原文。"""
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return {
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"entry_fields": [],
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"sql": sql or "SELECT COUNT(*) AS refund_rate FROM orders",
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"metrics": [{
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"id": "m1", "name": name, "synonyms": [], "unit": "%", "decimals": 2,
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"expression": "cell(nodes.fetch, 0, 'refund_rate')",
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"definition": {"text": "已支付订单里发生退款的比例",
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"citations": [{"chunk": chunk_id, "quote": quote}]},
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"open_questions": [],
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}],
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"open_questions": [],
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}
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# ==========================================================================
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# 1. 快照可还原、不可变
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# ==========================================================================
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async def test_the_first_extraction_persists_a_restorable_source_snapshot(client, docs, datasource,
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monkeypatch):
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"""提取时把原文存进工件库：payload 只有引用，按引用回读，逐份、逐段原文一模一样，哈希对得上。"""
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doc = await docs("snap-1", [(0, SMALL_ONE), (1, SMALL_TWO)], title="退款口径.md")
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source_id = await datasource()
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fake_model(monkeypatch, json.dumps(_reply(f"{doc}-0", quote="退款率按已支付订单统计"), ensure_ascii=False))
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made = await _draft(client, (await _extract(client, doc, source_id))["draft_id"])
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ref = made["source_snapshot"]
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assert ref["version"] == docdraft.SNAPSHOT_VERSION and ref["kind"] == docdraft.SNAPSHOT_KIND
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assert ref["chunk_ids"] == [f"{doc}-0", f"{doc}-1"] and ref["documents"] == [doc]
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# 引用里的 id 就是规范化内容的 sha256：内容不变，id 不变；内容变了，读的时候复验哈希会当场报错
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assert ref["content_hash"] == ref["artifact_id"]
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snapshot = load(ref["artifact_id"])
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assert snapshot is not None
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assert content_hash(canonical_json(snapshot)) == ref["artifact_id"]
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assert snapshot["chunks"][f"{doc}-0"]["content"] == SMALL_ONE
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assert snapshot["chunks"][f"{doc}-1"]["content"] == SMALL_TWO
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assert snapshot["documents"][0]["content"] == SMALL_ONE + SMALL_TWO
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assert snapshot["documents"][0]["content_hash"] == content_hash(SMALL_ONE + SMALL_TWO)
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assert snapshot["catalog"].strip(), "目录文本也要存：它改了，模型看到的材料和写出的 SQL 就变了"
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# 基线状态：有可还原快照 → known（只说明材料还原得出来，不等于字段基线，更不等于业务验证通过）
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assert made["source_baseline"] == {"status": "known", "readable": True, "artifact_id": ref["artifact_id"],
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"version": docdraft.SNAPSHOT_VERSION,
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"chunk_ids": [f"{doc}-0", f"{doc}-1"]}
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assert docdraft.source_baseline(made) == made["source_baseline"]
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async def test_the_snapshot_still_reads_after_the_document_is_rechunked(client, docs, datasource,
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monkeypatch):
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"""重导入会重新切块、换一批 chunk id；旧草稿记的引用仍指向当初那一份材料（按内容寻址，不按名字）。"""
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doc = await docs("snap-2", [(0, SMALL_ONE), (1, SMALL_TWO)])
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source_id = await datasource()
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fake_model(monkeypatch, json.dumps(_reply(f"{doc}-0", quote="退款率按已支付订单统计"), ensure_ascii=False))
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made = await _draft(client, (await _extract(client, doc, source_id))["draft_id"])
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artifact_id = made["source_snapshot"]["artifact_id"]
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# 文档被重新切块：旧段落删掉，换成三个新 id、顺序和内容也变了
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async with SessionLocal() as session:
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await session.execute(delete(Chunk).where(Chunk.document_id == doc))
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for ordinal, content in enumerate([SMALL_TWO, "新加的一段说明。", SMALL_ONE]):
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session.add(Chunk(id=f"re-{doc}-{ordinal}", document_id=doc, ordinal=ordinal, content=content))
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await session.commit()
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snapshot = load(artifact_id)
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assert snapshot is not None, "旧引用必须还读得回来"
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assert set(snapshot["chunks"]) == {f"{doc}-0", f"{doc}-1"}, "当初收进去的段落一个都不能少"
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assert snapshot["chunks"][f"{doc}-0"]["content"] == SMALL_ONE
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assert snapshot["chunks"][f"{doc}-1"]["content"] == SMALL_TWO
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# 草稿里那条指标仍指着当初的段落 id 和原文，不受重新切块影响
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assert made["metrics"][0]["definition"]["citations"][0]["chunk"] == f"{doc}-0"
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# ==========================================================================
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# 2. 引用核对只认实际可见的材料
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# ==========================================================================
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async def test_a_citation_to_a_truncated_away_chunk_is_not_accepted(client, docs, datasource, monkeypatch):
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"""材料超限时从后往前丢段落：被丢掉的段落没进提示，模型引用它也核不上，只留能核对的那条指标。"""
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tail = "这一段很长，超限时会被整段丢掉。" * 3000 # 六万字，稳稳超过一次提示的上限
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doc = await docs("snap-3", [(0, SMALL_ONE), (1, tail)])
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source_id = await datasource()
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reply = _reply(f"{doc}-0", quote="退款率按已支付订单统计", name="退款率")
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reply["metrics"].append({**reply["metrics"][0], "id": "m2", "name": "长文里的指标",
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"definition": {"text": "引用被丢段的原文",
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"citations": [{"chunk": f"{doc}-1",
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"quote": "这一段很长，超限时会被整段丢掉"}]}})
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fake_model(monkeypatch, json.dumps(reply, ensure_ascii=False))
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made = await _draft(client, (await _extract(client, doc, source_id))["draft_id"])
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assert made["doc_truncated"] is True
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assert [m["name"] for m in made["metrics"]] == ["退款率"], "引用不到可见材料的指标不该留下"
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assert any(item["name"] == "长文里的指标" and "引用" in item["reason"] for item in made["dropped"])
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# 提示记录里也如实写着：只看得见第一段
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[trace] = [t for t in made["prompts"] if t["purpose"] == "plan"]
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assert trace["visible_chunk_ids"] == [f"{doc}-0"]
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assert trace["doc_truncated"] is True
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assert set(trace["visible_chars"]) == {f"{doc}-0"}
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def test_normalize_plan_checks_citations_only_against_what_the_model_saw():
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"""同一段话：在「全量 chunks」下核得上，在「实际进提示的可见 chunks」下核不上——引用核对以可见范围为准。"""
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full = {"c1": {"ordinal": 0, "content": "退款率按已支付订单统计", "document_id": "d"},
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"c2": {"ordinal": 1, "content": "门店维度只保留已支付订单", "document_id": "d"}}
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visible = {"c1": full["c1"]} # c2 被截断丢掉了
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raw = {"entry_fields": [], "sql": "SELECT COUNT(*) AS n FROM orders",
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"metrics": [{"id": "m1", "name": "退款率", "expression": "cell(nodes.fetch, 0, 'n')",
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"definition": {"text": "口径", "citations": [{"chunk": "c2",
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"quote": "门店维度只保留已支付订单"}]}}],
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"open_questions": []}
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with_visibility, dropped = draftplan.normalize_plan(raw, visible, allowed_tables={"orders"})
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assert with_visibility["metrics"] == [] and dropped and "引用" in dropped[0]["reason"]
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without_visibility, dropped = draftplan.normalize_plan(raw, full, allowed_tables={"orders"})
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assert dropped == [] and [m["name"] for m in without_visibility["metrics"]] == ["退款率"]
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async def test_plan_groups_reports_the_same_visible_chunks_it_sends_to_the_model():
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"""draftplan 自己算材料时，报出来的 visible_chunk_ids 就是真正进提示的那几段（与提示文本一致）。"""
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from types import SimpleNamespace
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class Model:
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model_name = "visible-model"
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def __init__(self) -> None:
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self.messages: list = []
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async def ainvoke(self, messages):
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self.messages = messages
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return SimpleNamespace(content='{"groups": [], "open_questions": [], "uncovered": []}')
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first = "第一段：" + "退款率按已支付订单统计。" * 3000
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second = "第二段：" + "门店维度只保留已支付订单。" * 3000
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chunks = {"c1": {"ordinal": 0, "content": first, "document_id": "d"},
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"c2": {"ordinal": 1, "content": second, "document_id": "d"}}
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model = Model()
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result = await draftplan.plan_groups(None, docs=[], chunks=chunks, tables_text="表 orders", model=model)
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sent = "\n".join(str(getattr(message, "content", "")) for message in model.messages)
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assert result["visible_chunk_ids"] == ["c1"] and result["doc_truncated"] is True
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assert "第一段" in sent and "第二段" not in sent
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assert result["prompt_version"] == draftplan.PROMPT_VERSION
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assert result["parse_version"] == docdraft.PARSE_VERSION
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# ==========================================================================
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# 3. 提示记录
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# ==========================================================================
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async def test_every_model_prompt_records_what_it_saw_and_which_versions(client, docs, datasource,
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monkeypatch):
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"""payload.prompts 逐次记下 visible_chunk_ids、模型、提示词/解析版本：历史结果才知道是按哪一版抽的。"""
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doc = await docs("snap-4", [(0, SMALL_ONE), (1, SMALL_TWO)])
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source_id = await datasource()
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fake_model(monkeypatch, json.dumps(_reply(f"{doc}-0", quote="退款率按已支付订单统计"), ensure_ascii=False))
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made = await _draft(client, (await _extract(client, doc, source_id))["draft_id"])
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[trace] = made["prompts"]
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assert trace["purpose"] == "plan" and trace["round"] == 1
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assert trace["visible_chunk_ids"] == [f"{doc}-0", f"{doc}-1"]
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assert trace["model_id"] == "fake-model"
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assert trace["prompt_version"] == draftplan.PROMPT_VERSION
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assert trace["parse_version"] == docdraft.PARSE_VERSION
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assert trace["doc_truncated"] is False and trace["catalog_truncated"] is False
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assert trace["visible_chars"][f"{doc}-0"] == len(SMALL_ONE)
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async def test_the_auxiliary_extract_path_reports_visibility_and_versions():
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"""docdraft.extract（辅助路径）也交回可见段落与版本，和主路径一套说法。"""
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from types import SimpleNamespace
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class Model:
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model_name = "aux-model"
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async def ainvoke(self, _messages):
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return SimpleNamespace(content=json.dumps(
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{"metrics": [{"name": "退款率", "definition": {"text": "口径", "citations": [
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{"chunk": "c1", "quote": "退款率按已支付订单统计"}]}}]}, ensure_ascii=False))
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result = await docdraft.extract(None, docs=[{"document_id": "d", "title": "口径.md"}],
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chunks={"c1": {"ordinal": 0, "content": SMALL_ONE, "document_id": "d"}},
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model=Model())
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assert result["visible_chunk_ids"] == ["c1"]
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assert result["prompt_version"] == docdraft.PROMPT_VERSION
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assert result["parse_version"] == docdraft.PARSE_VERSION
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assert [m["name"] for m in result["metrics"]] == ["退款率"]
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# ==========================================================================
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# 4. checkpoint 只是任务恢复，不冒充 B
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# ==========================================================================
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async def _run_extract(draft_id: str) -> dict:
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"""直接调后台起草，试跑换成不启动引擎的桩（不经 HTTP、不建任务）。"""
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trial: dict = {}
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async def run_trial(**_kwargs):
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return {"run_id": "", "status": "succeeded", "error": ""}
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async def save_trial(_draft_id, value):
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trial.update(value or {})
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def binding(*_args):
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return {}
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|
||
await authoring.extract(draft_id, run_trial=run_trial, save_trial=save_trial, trial_binding=binding)
|
||
return trial
|
||
|
||
|
||
async def test_the_checkpoint_is_recovery_only_and_never_masquerades_as_a_baseline(client, docs, datasource,
|
||
monkeypatch):
|
||
"""材料指纹相同的重试接续 checkpoint；checkpoint 只记「哪些组起草好了」，把它当 payload 读仍是 baseline_unknown。"""
|
||
doc = await docs("snap-5", [(0, SMALL_ONE), (1, SMALL_TWO)])
|
||
source_id = await datasource()
|
||
group = _reply(f"{doc}-0", quote="退款率按已支付订单统计")
|
||
calls: list[list[str]] = []
|
||
|
||
async def interrupted(_session, **kwargs):
|
||
calls.append(list(kwargs["covered"]))
|
||
if len(calls) == 1:
|
||
return {"groups": [group], "uncovered": ["门店数"]}
|
||
raise RuntimeError("这一轮被打断")
|
||
|
||
monkeypatch.setattr(draftplan, "plan_groups", interrupted)
|
||
extracted = await _extract(client, doc, source_id)
|
||
draft_id = extracted["draft_id"]
|
||
await _run_extract(draft_id)
|
||
|
||
async with SessionLocal() as session:
|
||
row = await session.get(CaliberDraft, draft_id)
|
||
payload = copy.deepcopy(row.payload)
|
||
# 被打断的那一轮之前，第一组和来源快照都已经写下来了
|
||
assert payload["checkpoint"]["groups"][0]["metrics"][0]["name"] == "退款率"
|
||
assert payload["source_snapshot"]["artifact_id"] and payload["source_baseline"]["status"] == "known"
|
||
# checkpoint 里只有恢复用的东西：把它当成一份 payload 去读来源基线，只会得到 baseline_unknown
|
||
assert set(payload["checkpoint"]) == {"groups"}
|
||
assert docdraft.source_baseline(payload["checkpoint"])["status"] == "baseline_unknown"
|
||
assert "source_snapshot" not in payload["checkpoint"]
|
||
|
||
# 重试：材料没变，checkpoint 里的组接续下去；来源快照仍从这次读到的材料现取（不来自 checkpoint）
|
||
second = copy.deepcopy(group)
|
||
second["metrics"][0].update(id="m2", name="门店数")
|
||
|
||
async def resume(_session, **kwargs):
|
||
assert kwargs["covered"] == ["退款率"], "重试要接着上次起草过的地方，不重头再来"
|
||
return {"groups": [second], "uncovered": []}
|
||
|
||
monkeypatch.setattr(draftplan, "plan_groups", resume)
|
||
async with SessionLocal() as session: # 重试会先把草稿置回 drafting（api/ledger 的 retry 就是这样）
|
||
row = await session.get(CaliberDraft, draft_id)
|
||
row.status = "drafting"
|
||
await session.commit()
|
||
await _run_extract(draft_id)
|
||
async with SessionLocal() as session:
|
||
row = await session.get(CaliberDraft, draft_id)
|
||
resumed = copy.deepcopy(row.payload)
|
||
assert [m["name"] for m in resumed["metrics"]] == ["退款率", "门店数"]
|
||
assert resumed["source_snapshot"]["artifact_id"] == payload["source_snapshot"]["artifact_id"]
|
||
assert load(resumed["source_snapshot"]["artifact_id"])["chunks"][f"{doc}-1"]["content"] == SMALL_TWO
|
||
|
||
|
||
# ==========================================================================
|
||
# 5. 旧草稿：baseline_unknown，不拿当前值伪造历史
|
||
# ==========================================================================
|
||
|
||
|
||
async def test_an_old_draft_without_a_snapshot_reads_as_baseline_unknown(client, docs):
|
||
"""保存来源快照之前起草的草稿没有引用：如实标记 baseline_unknown，不能拿它现在的内容当历史基线。"""
|
||
draft_id = f"old-{uuid.uuid4().hex[:10]}"
|
||
old_payload = {"metrics": [{"id": "m1", "name": "旧指标", "expression": "cell(nodes.fetch, 0, 'n')"}],
|
||
"sql": "SELECT 1 AS n", "version": 1, "workflow_id": None}
|
||
async with SessionLocal() as session:
|
||
session.add(CaliberDraft(id=draft_id, title="老草稿", status="path_pending",
|
||
payload=copy.deepcopy(old_payload)))
|
||
await session.commit()
|
||
|
||
async with SessionLocal() as session:
|
||
stored = (await session.get(CaliberDraft, draft_id)).payload
|
||
baseline = docdraft.source_baseline(stored)
|
||
assert baseline["status"] == "baseline_unknown" and "无法还原" in baseline["reason"]
|
||
assert "artifact_id" not in baseline
|
||
|
||
body = await _draft(client, draft_id)
|
||
assert body["status"] == "path_pending" and body["metrics"][0]["name"] == "旧指标"
|
||
# 老草稿里根本没有快照，也没有凭空补一条：当前内容照旧显示，但它不是「上次被接受的导入值」。
|
||
# 读接口如实给出 baseline_unknown（没有快照本身就是要说的话，不能让客户端从「缺字段」去猜）
|
||
assert "source_snapshot" not in body
|
||
assert body["source_baseline"]["status"] == "baseline_unknown"
|
||
assert "无法还原" in body["source_baseline"]["reason"] and "artifact_id" not in body["source_baseline"]
|
||
assert docdraft.source_baseline(body)["status"] == "baseline_unknown"
|
||
|
||
|
||
async def test_a_snapshot_is_not_invented_for_a_draft_without_one(client, docs, datasource, monkeypatch):
|
||
"""新草稿照常记快照；同一批材料被再次读取时快照不变（按内容寻址，同一份材料只存一份、id 相同）。"""
|
||
doc = await docs("snap-6", [(0, SMALL_ONE)])
|
||
source_id = await datasource()
|
||
fake_model(monkeypatch, json.dumps(_reply(f"{doc}-0", quote="退款率按已支付订单统计"), ensure_ascii=False))
|
||
first = await _draft(client, (await _extract(client, doc, source_id))["draft_id"])
|
||
|
||
fake_model(monkeypatch, json.dumps(_reply(f"{doc}-0", quote="退款率按已支付订单统计",
|
||
name="退款率（第二份）"), ensure_ascii=False))
|
||
second = await _draft(client, (await _extract(client, doc, source_id))["draft_id"])
|
||
|
||
assert first["source_snapshot"]["artifact_id"] == second["source_snapshot"]["artifact_id"]
|
||
assert docdraft.source_baseline(second)["status"] == "known"
|
||
|
||
|
||
# ==========================================================================
|
||
# 6. 装快照失败时如实说「没有基线」，不假装有
|
||
# ==========================================================================
|
||
|
||
|
||
async def test_a_snapshot_that_cannot_be_stored_is_reported_as_baseline_unknown(client, docs, datasource,
|
||
monkeypatch):
|
||
"""落工件失败（磁盘/库出错）不让整份草稿失败，但也绝不假装有基线：source_snapshot 为空、状态 unknown。"""
|
||
import app.core.artifact_store as store
|
||
|
||
doc = await docs("snap-7", [(0, SMALL_ONE)])
|
||
source_id = await datasource()
|
||
fake_model(monkeypatch, json.dumps(_reply(f"{doc}-0", quote="退款率按已支付订单统计"), ensure_ascii=False))
|
||
|
||
async def broken(*_args, **_kwargs):
|
||
raise OSError("磁盘满了")
|
||
|
||
# _capture_source 在函数里 `from app.core.artifact_store import put_json`，换掉模块属性就换掉了它
|
||
monkeypatch.setattr(store, "put_json", broken)
|
||
|
||
made = await _draft(client, (await _extract(client, doc, source_id))["draft_id"])
|
||
assert made["status"] in ("ready", "questions_open"), made.get("error")
|
||
assert made["workflow_id"], "快照存不下不该把草稿判死：图和试跑照旧"
|
||
assert made["source_snapshot"] is None
|
||
assert made["source_baseline"]["status"] == "baseline_unknown"
|