267 lines
10 KiB
Python
267 lines
10 KiB
Python
from __future__ import annotations
|
|
|
|
import json
|
|
import sys
|
|
from pathlib import Path
|
|
|
|
REPO_ROOT = Path(__file__).resolve().parents[1]
|
|
if str(REPO_ROOT) not in sys.path:
|
|
sys.path.insert(0, str(REPO_ROOT))
|
|
|
|
from scripts.runtime.roles import resolve_runtime_profile
|
|
from scripts.runtime.sources import append_packet_sources, rebuild_sources_from_packets
|
|
from scripts.runtime.tasks import TaskCard
|
|
from scripts.runtime.workers import PacketWorker, build_material_context, build_route_query, build_search_context, normalize_packet_against_context
|
|
|
|
|
|
class FakeSearchProvider:
|
|
def search(self, *, query: str, route: str, num_results: int):
|
|
return [
|
|
{
|
|
"title": f"{route} result for {query}",
|
|
"url": f"https://example.com/{route}",
|
|
"snippet": "候选证据摘要",
|
|
"route": route,
|
|
}
|
|
][:num_results]
|
|
|
|
|
|
class FakeClient:
|
|
def __init__(self, response: dict) -> None:
|
|
self.response = response
|
|
self.calls: list[dict[str, object]] = []
|
|
|
|
def chat_complete(self, **kwargs) -> str:
|
|
self.calls.append(kwargs)
|
|
return json.dumps(self.response, ensure_ascii=False)
|
|
|
|
|
|
def sample_card() -> TaskCard:
|
|
return TaskCard(
|
|
task_id="ch01-literature",
|
|
chapter_ids=["ch01"],
|
|
topic_axis="literature",
|
|
questions=["围绕临床证据提炼结论。"],
|
|
search_routes=["scholar", "general"],
|
|
output_packet="phase2/packets/ch01-literature.json",
|
|
)
|
|
|
|
|
|
def test_build_search_context_assigns_stable_source_ids() -> None:
|
|
context = build_search_context(sample_card(), FakeSearchProvider(), num_results_per_route=1)
|
|
|
|
assert [source["id"] for source in context["candidate_sources"]] == [
|
|
"src_ch01_literature_001",
|
|
"src_ch01_literature_002",
|
|
]
|
|
assert context["routes_used"] == ["scholar", "general"]
|
|
|
|
|
|
def test_fda_route_query_uses_english_axis_terms_not_chinese_title() -> None:
|
|
card = TaskCard(
|
|
task_id="ch10-fda_enforcement_precedents",
|
|
chapter_ids=["ch10"],
|
|
topic_axis="fda_enforcement_precedents",
|
|
questions=["立即纠偏、体系补强、能力建设三层整改路线图必须绑定 owner、关闭证据和复核机制"],
|
|
search_routes=["fda"],
|
|
output_packet="phase2/packets/ch10-fda_enforcement_precedents.json",
|
|
chapter_title="立即纠偏、体系补强、能力建设三层整改路线图必须绑定 owner、关闭证据和复核机制",
|
|
)
|
|
|
|
query = build_route_query(card, "fda")
|
|
|
|
assert "立即纠偏" not in query
|
|
assert "CAPA" in query
|
|
assert "remediation" in query
|
|
assert "verification evidence" in query
|
|
|
|
|
|
def test_integrated_scholar_query_does_not_leak_internal_axis_or_cjk_punctuation() -> None:
|
|
card = TaskCard(
|
|
task_id="ch07-chapter_integrated",
|
|
chapter_ids=["ch07"],
|
|
topic_axis="chapter_integrated",
|
|
questions=["人员能力:培训有效性比培训记录更关键"],
|
|
search_routes=["scholar"],
|
|
output_packet="phase2/packets/ch07-chapter_integrated.json",
|
|
chapter_title="人员能力:培训有效性比培训记录更关键",
|
|
)
|
|
|
|
query = build_route_query(card, "scholar")
|
|
|
|
assert "chapter_integrated" not in query
|
|
assert "、" not in query
|
|
assert " " not in query
|
|
assert "training" in query
|
|
assert "quality" in query
|
|
assert not any("\u4e00" <= char <= "\u9fff" for char in query)
|
|
|
|
|
|
def test_evidence_route_query_is_short_english_candidate_evidence_query() -> None:
|
|
card = TaskCard(
|
|
task_id="ch08-chapter_integrated",
|
|
chapter_ids=["ch08"],
|
|
topic_axis="chapter_integrated",
|
|
questions=["运营管理需要建立跨部门节奏、问题升级、指标看板和管理层 review"],
|
|
search_routes=["evidence"],
|
|
output_packet="phase2/packets/ch08-chapter_integrated.json",
|
|
chapter_title="运营管理需要建立跨部门节奏、问题升级、指标看板和管理层 review",
|
|
)
|
|
|
|
query = build_route_query(card, "evidence")
|
|
|
|
assert "evidence" in query
|
|
assert "quality" in query
|
|
assert "operations" in query
|
|
assert "运营管理" not in query
|
|
assert not any("\u4e00" <= char <= "\u9fff" for char in query)
|
|
|
|
|
|
def test_packet_worker_includes_search_context_in_prompt() -> None:
|
|
context = build_search_context(sample_card(), FakeSearchProvider(), num_results_per_route=1)
|
|
response = {
|
|
"task_id": "ch01-literature",
|
|
"claims": [{"claim": "候选证据支持判断", "source_ids": ["src_ch01_literature_001"]}],
|
|
"evidence_items": [{"source_id": "src_ch01_literature_001", "summary": "摘要"}],
|
|
"counter_evidence": [{"claim": "仍需更多数据", "source_ids": ["src_ch01_literature_002"]}],
|
|
"source_ids": ["src_ch01_literature_001", "src_ch01_literature_002"],
|
|
"sources": context["candidate_sources"],
|
|
"source_quality_notes": ["候选来源需要后续评级"],
|
|
"open_questions": [],
|
|
"raw_quotes_or_notes": [],
|
|
}
|
|
role = resolve_runtime_profile(profile="medium").role_for_task("evidence_packet")
|
|
fake = FakeClient(response)
|
|
|
|
packet = PacketWorker(role=role, client=fake, search_provider=FakeSearchProvider()).run(sample_card())
|
|
|
|
assert packet["sources"][0]["url"] == "https://example.com/scholar"
|
|
assert "candidate_sources" in fake.calls[0]["user"]
|
|
|
|
|
|
def test_normalize_packet_fills_source_ids_and_sources_from_context() -> None:
|
|
context = {
|
|
"candidate_sources": [
|
|
{"id": "src_a", "title": "A", "url": "https://example.com/a", "tier": "Tier 2", "score": 7}
|
|
]
|
|
}
|
|
packet = {
|
|
"task_id": "ch01",
|
|
"claims": [{"claim": "判断", "source_ids": ["src_a"]}],
|
|
"evidence_items": [{"source_id": "src_a", "summary": "证据"}],
|
|
"counter_evidence": [{"claim": "反方", "source_ids": ["src_a"]}],
|
|
"source_quality_notes": [],
|
|
"open_questions": [],
|
|
"raw_quotes_or_notes": [],
|
|
}
|
|
|
|
normalized = normalize_packet_against_context(packet, context, None)
|
|
|
|
assert normalized["source_ids"] == ["src_a"]
|
|
assert normalized["sources"] == context["candidate_sources"]
|
|
|
|
|
|
def test_material_context_is_loaded_and_allowed_as_source(tmp_path: Path) -> None:
|
|
project = tmp_path / "project"
|
|
material = project / "phase0/extracted/audit.md"
|
|
material.parent.mkdir(parents=True)
|
|
material.write_text("白帆现场发现:偏差调查未闭环。", encoding="utf-8")
|
|
card = TaskCard(
|
|
task_id="ch01-chapter_integrated",
|
|
chapter_ids=["ch01"],
|
|
topic_axis="chapter_integrated",
|
|
questions=["q"],
|
|
search_routes=[],
|
|
output_packet="phase2/packets/ch01-chapter_integrated.json",
|
|
allowed_materials=["phase0/extracted/audit.md"],
|
|
)
|
|
context = build_material_context(card, project)
|
|
response = {
|
|
"task_id": "ch01-chapter_integrated",
|
|
"claims": [{"claim": "现场材料显示偏差调查需要补强", "source_ids": [context["materials"][0]["source_id"]]}],
|
|
"evidence_items": [{"source_id": context["materials"][0]["source_id"], "summary": "偏差调查未闭环。"}],
|
|
"counter_evidence": [{"claim": "需与完整审计报告交叉确认", "source_ids": [context["materials"][0]["source_id"]]}],
|
|
"source_ids": [context["materials"][0]["source_id"]],
|
|
"sources": [
|
|
{
|
|
"id": context["materials"][0]["source_id"],
|
|
"title": "audit.md",
|
|
"url": "phase0/extracted/audit.md",
|
|
"tier": "local_material",
|
|
}
|
|
],
|
|
"source_quality_notes": ["本地材料作为起点证据"],
|
|
"open_questions": [],
|
|
"raw_quotes_or_notes": ["白帆现场发现:偏差调查未闭环。"],
|
|
}
|
|
fake = FakeClient(response)
|
|
role = resolve_runtime_profile(profile="medium").role_for_task("evidence_packet")
|
|
|
|
packet = PacketWorker(role=role, client=fake, project_root=project).run(card)
|
|
|
|
assert packet["source_ids"] == [context["materials"][0]["source_id"]]
|
|
assert "白帆现场发现" in fake.calls[0]["user"]
|
|
|
|
|
|
def test_append_packet_sources_preserves_distinct_source_ids_for_same_url(tmp_path: Path) -> None:
|
|
packet = {
|
|
"sources": [
|
|
{"id": "src_a", "title": "A", "url": "https://example.com/a", "tier": "Tier 2", "score": 7},
|
|
{"id": "src_b", "title": "B", "url": "https://example.com/a", "tier": "Tier 2", "score": 7},
|
|
]
|
|
}
|
|
|
|
written = append_packet_sources(tmp_path / "sources.jsonl", packet)
|
|
|
|
assert written == 2
|
|
assert len((tmp_path / "sources.jsonl").read_text(encoding="utf-8").splitlines()) == 2
|
|
|
|
|
|
def test_rebuild_sources_from_packets_preserves_distinct_source_ids(tmp_path: Path) -> None:
|
|
project = tmp_path / "project"
|
|
packets = project / "phase2" / "packets"
|
|
packets.mkdir(parents=True)
|
|
packet = {
|
|
"sources": [
|
|
{"id": "src_001", "title": "A", "url": "https://example.com/a"},
|
|
{"id": "src_002", "title": "A duplicate", "url": "https://example.com/a"},
|
|
{"id": "src_003", "title": "Local", "url": "phase0/extracted/local.md"},
|
|
]
|
|
}
|
|
(packets / "ch01-a.json").write_text(json.dumps(packet, ensure_ascii=False), encoding="utf-8")
|
|
|
|
count = rebuild_sources_from_packets(project)
|
|
|
|
lines = (project / "phase2" / "sources.jsonl").read_text(encoding="utf-8").splitlines()
|
|
assert count == 3
|
|
assert len(lines) == 3
|
|
assert "src_001" in lines[0]
|
|
assert "src_002" in lines[1]
|
|
assert "src_003" in lines[2]
|
|
|
|
|
|
def test_rebuild_sources_preserves_cache_metadata(tmp_path: Path) -> None:
|
|
project = tmp_path / "project"
|
|
packets = project / "phase2" / "packets"
|
|
packets.mkdir(parents=True)
|
|
source = {"id": "src_001", "title": "A", "url": "https://example.com/a"}
|
|
(packets / "ch01-a.json").write_text(json.dumps({"sources": [source]}, ensure_ascii=False), encoding="utf-8")
|
|
(project / "phase2/sources.jsonl").write_text(
|
|
json.dumps(
|
|
{
|
|
**source,
|
|
"cached_text_path": "phase2/source_cache/md/src_001.md",
|
|
"cache_status": "fetched",
|
|
},
|
|
ensure_ascii=False,
|
|
)
|
|
+ "\n",
|
|
encoding="utf-8",
|
|
)
|
|
|
|
rebuild_sources_from_packets(project)
|
|
|
|
row = json.loads((project / "phase2/sources.jsonl").read_text(encoding="utf-8"))
|
|
assert row["cached_text_path"] == "phase2/source_cache/md/src_001.md"
|
|
assert row["cache_status"] == "fetched"
|