225 lines
8.5 KiB
Python
225 lines
8.5 KiB
Python
"""Task 5（D3 强端到端）：服务层 RAG 接线验证。
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真实驱动完整链路：上传 → 解压 → index_dir → retrieve → LLM prompt（RAG 注入），
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不 mock 任何环节。验证上传即索引（D1）与 use_rag 默认关闭的向后兼容。
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"""
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from __future__ import annotations
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import asyncio
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import glob
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import io
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import json
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import zipfile
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from pathlib import Path
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import pytest
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from fastapi.testclient import TestClient
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from genesis.server.app import create_app
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from genesis.impact.impact_agent import _RAG_CONTEXT_TITLE
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from genesis.rag.embeddings import FakeEmbedder
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from genesis.rag.impact_rag import ImpactRAG
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from genesis.rag.store import RagStore
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from genesis.server.service import GenesisService
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from genesis.server.store import SessionStore
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_REPO = Path(__file__).resolve().parents[1]
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def _sample_req() -> bytes:
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hits = glob.glob(str(_REPO / "sample" / "requirements_*.xlsx"))
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assert hits, "sample 下未找到 requirements xlsx"
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return Path(hits[0]).read_bytes()
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def _sample_tpl() -> bytes:
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hits = glob.glob(str(_REPO / "sample" / "template_*.docx"))
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assert hits, "sample 下未找到 template docx"
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return Path(hits[0]).read_bytes()
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def _make_existing_zip() -> bytes:
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"""构造含已知源码的既有系统 zip（src/KnownOrder.java 含『订单创建调用 MyBatis』）。"""
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buf = io.BytesIO()
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with zipfile.ZipFile(buf, "w") as zf:
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zf.writestr(
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"src/KnownOrder.java",
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"package demo;\n"
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"public class KnownOrder {\n"
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" // 订单创建调用 MyBatis\n"
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" public void createOrder() { /* ... */ }\n}\n",
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)
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return buf.getvalue()
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class FakeEngine:
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"""异步确定性引擎：捕获 LLM 收到的 prompt。"""
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def __init__(self) -> None:
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self.captured: str | None = None
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async def chat_structured(self, *, session_id, prompt, variables, schema, retry_count=2):
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from types import SimpleNamespace
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self.captured = prompt
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return SimpleNamespace(
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data={"title": variables.get("title", "x"), "blocks": []},
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raw_text=prompt,
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status="ok",
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)
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@pytest.fixture
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def svc(tmp_path):
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store = SessionStore(db_path=str(tmp_path / "s.db"))
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rag = ImpactRAG(RagStore(str(tmp_path / "rag.db")), FakeEmbedder())
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return GenesisService(
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store=store,
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data_root=str(tmp_path / "data"),
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engine=FakeEngine(),
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rag=rag,
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use_rag=False, # 默认关闭，由 run_impact 显参开启
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)
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def test_rag_e2e_upload_then_impact_injects_source(tmp_path):
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"""D3 强验证：上传源码被 RAG 检索并注入 LLM prompt。"""
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store = SessionStore(db_path=str(tmp_path / "s.db"))
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engine = FakeEngine()
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rag = ImpactRAG(RagStore(str(tmp_path / "rag.db")), FakeEmbedder())
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svc = GenesisService(
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store=store,
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data_root=str(tmp_path / "data"),
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engine=engine,
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rag=rag,
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use_rag=False,
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)
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sid = svc.create_session("u1").session_id
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svc.upload_file(sid, "requirements", "requirements_newdev.xlsx", _sample_req())
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svc.upload_file(sid, "template", "template_design_ja.docx", _sample_tpl())
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# 上传即索引（D1）
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svc.upload_file(sid, "existing_system", "existing.zip", _make_existing_zip())
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# 上传后直接检索应命中非空
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hits = rag.retrieve(sid, "订单创建", k=1)
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assert hits, "上传即索引后应能检索到源码片段"
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assert "KnownOrder" in hits[0]
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svc.run_parse(sid)
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svc.confirm_parse(sid)
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assert svc.get_session(sid).status == "impact_running"
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# 真实驱动 RAG 路径
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rec = asyncio.run(svc.run_impact(sid, use_rag=True))
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assert rec.status == "awaiting_impact_confirm"
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# 核心断言：RAG 检索片段（含 KnownOrder）注入 LLM prompt
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assert engine.captured is not None
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assert "KnownOrder" in engine.captured
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# 摘要标记 rag_enabled
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import json
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assert json.loads(rec.impact_summary).get("rag_enabled") is True
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def test_rag_e2e_use_rag_false_backward_compat(tmp_path):
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"""向后兼容：rag=None 且 use_rag 默认关闭时，不调用 LLM、无 RAG 小节。"""
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store = SessionStore(db_path=str(tmp_path / "s.db"))
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engine = FakeEngine()
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svc = GenesisService(
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store=store,
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data_root=str(tmp_path / "data"),
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engine=engine,
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rag=None, # 不启用 RAG
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use_rag=False,
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)
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sid = svc.create_session("u1").session_id
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svc.upload_file(sid, "requirements", "requirements_newdev.xlsx", _sample_req())
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svc.upload_file(sid, "template", "template_design_ja.docx", _sample_tpl())
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svc.upload_file(sid, "existing_system", "existing.zip", _make_existing_zip())
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svc.run_parse(sid)
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svc.confirm_parse(sid)
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rec = asyncio.run(svc.run_impact(sid)) # 默认 use_rag=None → 走确定性路径
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assert rec.status == "awaiting_impact_confirm"
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# 向后兼容：确定性路径不调用 LLM（captured 保持 None），prompt 不含 RAG 小节
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assert engine.captured is None
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assert _RAG_CONTEXT_TITLE not in (engine.captured or "")
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# 确定性报告存在
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assert rec.impact_report_path and Path(rec.impact_report_path).exists()
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def test_service_rag_lazy_engine_build(tmp_path, monkeypatch):
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"""覆盖 service.py:233-236：构造未传 engine 且 run_impact(use_rag=True) 时懒构建引擎。"""
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store = SessionStore(db_path=str(tmp_path / "s.db"))
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rag = ImpactRAG(RagStore(str(tmp_path / "rag.db")), FakeEmbedder())
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# 注入的懒构建产物：一个会捕获 prompt 的 FakeEngine
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injected_engine = FakeEngine()
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monkeypatch.setattr(
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"genesis.inference.factory.build_inference_engine", lambda: injected_engine
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)
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svc = GenesisService(
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store=store,
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data_root=str(tmp_path / "data"),
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rag=rag,
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use_rag=False, # 构造时不传 engine、RAG 默认关闭
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)
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assert svc.engine is None # 尚未构建
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sid = svc.create_session("u1").session_id
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svc.upload_file(sid, "requirements", "requirements_newdev.xlsx", _sample_req())
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svc.upload_file(sid, "template", "template_design_ja.docx", _sample_tpl())
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# 上传即索引（D1），existing_system 含 KnownOrder 源码
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svc.upload_file(sid, "existing_system", "existing.zip", _make_existing_zip())
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svc.run_parse(sid)
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svc.confirm_parse(sid)
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assert svc.get_session(sid).status == "impact_running"
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# 显参开启 RAG → 触发 engine 为 None 的懒构建分支
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rec = asyncio.run(svc.run_impact(sid, use_rag=True))
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assert rec.status == "awaiting_impact_confirm"
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# 懒构建的引擎被注入并实际使用
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assert svc.engine is injected_engine
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summary = json.loads(rec.impact_summary)
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assert summary.get("rag_enabled") is True
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# 引擎捕获的 prompt 含 RAG 检索注入的 KnownOrder 片段
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assert injected_engine.captured is not None
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assert "KnownOrder" in injected_engine.captured
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def test_http_start_impact_use_rag_e2e(tmp_path):
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"""覆盖 app.py start_impact 异步端点 + _FakeEngine.chat_structured（RAG 路径，HTTP 级）。"""
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store = SessionStore(db_path=str(tmp_path / "s.db"))
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rag = ImpactRAG(RagStore(str(tmp_path / "rag.db")), FakeEmbedder())
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app = create_app(
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store=store,
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data_root=str(tmp_path / "data"),
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engine="fake", # 触发内部 _FakeEngine（异步 chat_structured）
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rag=rag,
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)
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client = TestClient(app)
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sid = client.post("/api/sessions", json={"user_id": "u1"}).json()["session_id"]
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# multipart 上传：要件/模板/既有系统
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client.post(f"/api/sessions/{sid}/files",
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data={"file_type": "requirements"},
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files={"file": ("requirements_newdev.xlsx", _sample_req())})
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client.post(f"/api/sessions/{sid}/files",
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data={"file_type": "template"},
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files={"file": ("template_design_ja.docx", _sample_tpl())})
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client.post(f"/api/sessions/{sid}/files",
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data={"file_type": "existing_system"},
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files={"file": ("existing.zip", _make_existing_zip())})
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assert client.post(f"/api/sessions/{sid}/start-parse").status_code == 200
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# 有既有系统 → impact_running
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assert client.post(f"/api/sessions/{sid}/confirm-parse").json()["status"] == "impact_running"
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# 异步端点：start-impact?use_rag=True（显参开启 RAG）
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r = client.post(f"/api/sessions/{sid}/start-impact?use_rag=True")
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assert r.status_code == 200
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ir = client.get(f"/api/sessions/{sid}/impact-result").json()
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# 经 HTTP 真实走到 RAG 路径，摘要标记 rag_enabled
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assert ir.get("rag_enabled") is True
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