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ThearchyHelios
1cd9cab7b4
文档里叫「月活」，卡上指标叫「月度活跃买家」；同义词丢了，以后按名字找这份口径就永远对不上。 合并时带上（大小写与空白不算新说法），并让口径描述把它交出去。
231 lines
10 KiB
Python
231 lines
10 KiB
Python
"""口径草稿的纯逻辑（app/ledger/docdraft.py）。
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- 引用定位：跨行、连续空格、全角空格都能还原到原文下标，找不到就是 None；
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- 指标归一化：缺名、没有可核对的引用、带 SQL 痕迹整条丢弃；引用太短、chunk 不存在逐条丢弃；顺手删掉取数字段；
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- 回复解析：围栏、前后废话、尾随逗号都认，截断的抛 ValueError；
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- 对齐：new / duplicate / conflict（单位或定义不同）；
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- 合并定义：同名或同义词命中，不动 expression / id，匹配不上进 warnings；
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- extract：注入假模型（不调真模型），输入超限按 chunk 边界截断。
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"""
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from __future__ import annotations
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from types import SimpleNamespace
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from app.ledger import docdraft
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CHUNK = ("本季度销售额按订单创建时间统计，退款订单不计入销售额。"
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"订单数按已支付订单统计，一个订单算一单。")
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CHUNKS = {"c1": {"ordinal": 0, "content": CHUNK, "document_id": "doc-1"}}
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def metric(name="销售额", quote="销售额按订单创建时间统计", **extra):
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item = {
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"name": name,
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"synonyms": ["营业额"],
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"unit": "元",
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"definition": {"text": "按订单创建时间统计", "citations": [{"chunk": "c1", "quote": quote}]},
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}
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item.update(extra)
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return item
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# ==========================================================================
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# verify_quote
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# ==========================================================================
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def test_verify_quote_restores_original_span_across_lines_and_spaces():
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text = "口径说明：\n销售额\u3000按订单创建时间统计，\n\n退款不计入。\n"
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span = docdraft.verify_quote(text, "销售额 按订单创建时间统计， 退款")
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assert span is not None
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start, end = span
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assert text[start:end] == "销售额\u3000按订单创建时间统计，\n\n退款"
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def test_verify_quote_ignores_extra_spaces():
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text = "订单 数"
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assert docdraft.verify_quote(text, "订单 数") == (0, 6)
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assert docdraft.verify_quote(text, " 订单\t数 ") == (0, 6)
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def test_verify_quote_handles_full_width_space_and_missing_quote():
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text = "销售额\u3000合计"
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assert docdraft.verify_quote(text, "销售额 合计") == (0, 6)
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assert docdraft.verify_quote(text, "毛利率") is None
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assert docdraft.verify_quote(text, " ") is None
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# ==========================================================================
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# normalize_metrics
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# ==========================================================================
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def test_normalize_metrics_keeps_a_verified_metric_and_hands_over_span():
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good, dropped = docdraft.normalize_metrics({"metrics": [metric()]}, CHUNKS)
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assert dropped == []
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[item] = good
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[citation] = item["citations"]
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assert citation["document_id"] == "doc-1"
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assert citation["chunk"] == "c1"
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assert CHUNK[citation["span"][0]:citation["span"][1]] == "销售额按订单创建时间统计"
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assert item["definition"]["citations"] == item["citations"]
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def test_normalize_metrics_drops_a_metric_without_a_name():
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good, dropped = docdraft.normalize_metrics({"metrics": [metric(name=" ")]}, CHUNKS)
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assert good == []
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assert dropped[0]["reason"] == "缺少指标名称"
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def test_normalize_metrics_drops_short_quotes_and_unknown_chunks_per_citation():
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item = metric(quote="销售额")
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item["definition"]["citations"].append({"chunk": "missing", "quote": "退款订单不计入销售额"})
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good, dropped = docdraft.normalize_metrics({"metrics": [item]}, CHUNKS)
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# 两条引用都不可用：一条太短，一条 chunk 不存在
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assert good == []
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assert "引用" in dropped[0]["reason"]
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# 一条可用、一条不可用：只丢不可用的那条
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item = metric()
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item["definition"]["citations"] += [{"chunk": "missing", "quote": "退款订单不计入销售额"}]
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good, dropped = docdraft.normalize_metrics({"metrics": [item]}, CHUNKS)
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assert dropped == []
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assert len(good[0]["citations"]) == 1
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def test_normalize_metrics_drops_sql_traces_and_strips_forbidden_fields():
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traced = metric(notes="select sum(amount) from orders")
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good, dropped = docdraft.normalize_metrics({"metrics": [traced]}, CHUNKS)
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assert good == []
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assert "SQL" in dropped[0]["reason"]
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templated = metric(notes="{{ input.period }}")
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good, dropped = docdraft.normalize_metrics({"metrics": [templated]}, CHUNKS)
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assert good == []
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assert "SQL" in dropped[0]["reason"]
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clean = metric(table="orders", column="amount", sql="", filter={"tables": ["orders"]})
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# sql 是空串，没有 select … from，按字段删除处理而不是整条丢弃
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good, dropped = docdraft.normalize_metrics({"metrics": [clean]}, CHUNKS)
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assert dropped == []
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assert set(good[0]) & set(docdraft.FORBIDDEN_FIELDS) == set()
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assert good[0]["filter"] == {}
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# ==========================================================================
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# parse_reply
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# ==========================================================================
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def test_parse_reply_accepts_fences_chatter_and_trailing_commas():
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text = '好的，结果如下：\n```json\n{"metrics": [{"name": "销售额",},],}\n```\n以上。'
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assert docdraft.parse_reply(text) == {"metrics": [{"name": "销售额"}]}
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def test_parse_reply_rejects_a_truncated_object():
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try:
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docdraft.parse_reply('{"metrics": [{"name": "销售额"')
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except ValueError as e:
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assert "不完整" in str(e) or "没有" in str(e)
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else: # pragma: no cover - 只有实现走样时才会到这里
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raise AssertionError("截断的 JSON 应当抛 ValueError")
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# ==========================================================================
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# alignment
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# ==========================================================================
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EXISTING = [
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{"workflow_id": "wf-1", "version": 3, "node_id": "card", "name": "销售额",
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"synonyms": ["GMV"], "unit": "元", "definition_text": "按订单创建时间统计"},
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{"workflow_id": "wf-2", "version": 1, "node_id": "card", "name": "订单数",
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"synonyms": [], "unit": "单", "definition_text": "按已支付订单统计"},
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]
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def test_alignment_reports_new_duplicate_and_conflict():
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draft = [
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{"name": "成交额", "synonyms": ["gmv "], "unit": "元", "definition": {"text": "按订单创建时间统计"}},
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{"name": "订单数 ", "unit": "万元", "definition": {"text": "按已支付订单统计"}},
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{"name": "客单价", "unit": "元", "definition": {"text": "销售额除以订单数"}},
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]
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result = docdraft.alignment(draft, EXISTING)
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assert result["new"] == ["客单价"]
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assert result["duplicate"] == [{"name": "成交额", "workflow_id": "wf-1", "version": 3, "node_id": "card"}]
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[conflict] = result["conflict"]
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assert conflict["name"] == "订单数"
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assert conflict["workflow_id"] == "wf-2"
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assert "单位不同" in conflict["reason"]
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def test_alignment_conflicts_when_only_the_definition_differs():
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draft = [{"name": "销售额", "unit": "元", "definition": {"text": "按发货时间统计"}}]
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[conflict] = docdraft.alignment(draft, EXISTING)["conflict"]
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assert conflict["reason"] == "定义说明不同"
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# ==========================================================================
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# merge_definition
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# ==========================================================================
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def test_merge_definition_matches_by_synonym_and_keeps_expression():
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cards = [{"id": "gmv", "name": "销售额", "synonyms": ["GMV"], "expression": "cell(nodes.q, 0, '金额')",
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"definition": {"text": "旧说明", "owner": "财务"}}]
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drafts = [
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{"name": "成交额", "synonyms": ["gmv"], "definition": {"text": "新说明", "scope": "全渠道"}},
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{"name": "客单价", "definition": {"text": "销售额除以订单数"}},
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]
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merged, warnings = docdraft.merge_definition(cards, drafts)
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[card] = merged
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assert card["id"] == "gmv"
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assert card["expression"] == "cell(nodes.q, 0, '金额')"
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assert card["definition"] == {"text": "新说明", "owner": "财务", "scope": "全渠道"}
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# 文档里的叫法要留在卡上：以后按同义词找这份口径，「成交额」才对得上
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assert card["synonyms"] == ["GMV"]
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assert len(warnings) == 1 and "客单价" in warnings[0]
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# ==========================================================================
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# extract
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# ==========================================================================
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class FakeModel:
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model_name = "fake-model"
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def __init__(self, text: str) -> None:
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self.text = text
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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=self.text)
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async def test_extract_uses_the_injected_model_and_normalizes_its_reply():
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reply = """```json
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{"metrics": [{"name": "销售额", "unit": "元",
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"definition": {"text": "按订单创建时间统计",
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"citations": [{"chunk": "c1", "quote": "销售额按订单创建时间统计"}]}}],
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"open_questions": ["退款订单是否算销售额？"]}
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```"""
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model = FakeModel(reply)
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result = await docdraft.extract(None, docs=[{"document_id": "doc-1", "title": "口径说明"}],
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chunks=CHUNKS, model=model)
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assert result["model_id"] == "fake-model"
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assert result["truncated"] is False
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assert result["open_questions"] == ["退款订单是否算销售额？"]
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[item] = result["metrics"]
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assert item["citations"][0]["document_id"] == "doc-1"
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async def test_extract_truncates_at_chunk_boundaries_and_flags_it():
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first = "第一段：" + "销售额按订单创建时间统计。" * 2000
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second = "第二段：" + "退款订单不计入销售额。" * 2000
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chunks = {
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"c1": {"ordinal": 0, "content": first, "document_id": "doc-1"},
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"c2": {"ordinal": 1, "content": second, "document_id": "doc-1"},
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}
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model = FakeModel('{"metrics": [], "open_questions": []}')
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result = await docdraft.extract(None, docs=[], chunks=chunks, model=model)
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assert result["truncated"] is True
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sent = "\n".join(str(getattr(m, "content", "")) for m in model.messages)
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assert "第二段" not in sent
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assert len(sent) <= docdraft.MAX_INPUT_CHARS
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