448 lines
19 KiB
Python
448 lines
19 KiB
Python
from types import SimpleNamespace
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import pytest
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from fastapi import FastAPI
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from httpx import ASGITransport, AsyncClient
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from app.api.router import api_router
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from app.api.ai_pmo_api import routes_core
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from app.api.rag_api import routes_query
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from app.core.database import get_db
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from app.dependencies.auth import get_current_user
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from app.dependencies.tenant import get_tenant_id
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def _build_test_app() -> FastAPI:
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app = FastAPI()
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app.include_router(routes_query.router)
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app.include_router(routes_core.router)
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async def _fake_get_db():
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yield object()
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app.dependency_overrides[get_db] = _fake_get_db
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app.dependency_overrides[get_tenant_id] = lambda: 9
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app.dependency_overrides[get_current_user] = lambda: SimpleNamespace(
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id=101,
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tenant_id=9,
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name="测试用户",
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username="tester",
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)
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return app
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@pytest.mark.asyncio
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async def test_http_rag_ask_readonly_mainline_contract(monkeypatch) -> None:
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captured: dict[str, object] = {}
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class FakeKernel:
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def __init__(self, db, tenant_id: int):
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_ = db
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captured["tenant_id"] = tenant_id
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async def process_ingress(self, **kwargs):
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captured["ingress_kwargs"] = kwargs
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return {
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"handled": True,
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"status": "answered",
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"intent": "query.read_only",
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"direct_reply_required": True,
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"direct_reply_text": "当前主链状态正常。",
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"rag_result": {
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"answer": "当前主链状态正常。",
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"processing_stage": "qa",
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"route_decision": {
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"route_mode": "internal",
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"effective_source_policy": "internal",
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"decision_origin": "reply_anchor",
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},
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"clarification_code": None,
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"clarification_candidates": [],
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"answer_mode": "fast_path",
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"grounding_status": "grounded",
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"policy_version": "retrieval-v2.1|routing:v3|prompt:deterministic",
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"citations": [],
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"sources_used": [],
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"evidence_pack": {
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"summary": {
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"conclusion": "当前主链状态正常。",
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"evidence": [],
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"uncertainties": [],
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},
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"tool_trace": [],
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},
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},
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}
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monkeypatch.setattr(routes_query, "AIPMOKernelService", FakeKernel)
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app = _build_test_app()
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transport = ASGITransport(app=app)
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async with AsyncClient(transport=transport, base_url="http://test") as client:
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response = await client.post(
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"/rag/ask",
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json={
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"question": "当前主链状态？",
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"asked_via": "pmflow_manual",
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"action_mode": "read",
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},
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)
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assert response.status_code == 200
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payload = response.json()
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assert payload["code"] == 0
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assert "当前主链状态正常" in str((payload.get("data") or {}).get("answer") or "")
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assert payload["data"]["route_decision"]["effective_source_policy"] == "internal"
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assert payload["data"]["clarification_code"] is None
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assert payload["data"]["clarification_candidates"] == []
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assert payload["data"]["answer_mode"] == "fast_path"
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assert payload["data"]["grounding_status"] == "grounded"
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assert payload["data"]["policy_version"] == "retrieval-v2.1|routing:v3|prompt:deterministic"
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assert payload["data"]["citations"] == []
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assert payload["data"]["sources_used"] == []
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assert payload["data"]["evidence_pack"]["summary"]["conclusion"] == "当前主链状态正常。"
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ingress_kwargs = captured["ingress_kwargs"]
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assert isinstance(ingress_kwargs, dict)
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assert ingress_kwargs["source_system"] == "pmflow_manual"
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rag_request_context = ingress_kwargs["ingress_options"]["rag_request_context"]
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assert rag_request_context["asked_via"] == "pmflow_manual"
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assert rag_request_context["action_mode"] == "read"
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assert rag_request_context["message_intent"] is None
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@pytest.mark.asyncio
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async def test_http_rag_ask_mixed_mainline_contract(monkeypatch) -> None:
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captured: dict[str, object] = {}
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class FakeKernel:
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def __init__(self, db, tenant_id: int):
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_ = db
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captured["tenant_id"] = tenant_id
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async def process_ingress(self, **kwargs):
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captured["ingress_kwargs"] = kwargs
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return {
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"handled": True,
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"status": "answered",
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"intent": "query.read_only",
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"direct_reply_required": True,
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"direct_reply_text": "[回答] 进展稳定\n[已收到需求] 新增任务确认流",
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"rag_result": {"answer": "[回答] 进展稳定\n[已收到需求] 新增任务确认流"},
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}
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monkeypatch.setattr(routes_query, "AIPMOKernelService", FakeKernel)
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app = _build_test_app()
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transport = ASGITransport(app=app)
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async with AsyncClient(transport=transport, base_url="http://test") as client:
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response = await client.post(
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"/rag/ask",
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json={
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"question": "顺便问进展并新增任务确认流",
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"asked_via": "pmflow_manual",
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"action_mode": "read",
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"message_intent": "mixed",
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"mixed_signal_part": "新增任务确认流",
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},
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)
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assert response.status_code == 200
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payload = response.json()
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assert payload["code"] == 0
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assert "[回答]" in str((payload.get("data") or {}).get("answer") or "")
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ingress_kwargs = captured["ingress_kwargs"]
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assert isinstance(ingress_kwargs, dict)
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rag_request_context = ingress_kwargs["ingress_options"]["rag_request_context"]
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assert rag_request_context["message_intent"] == "mixed"
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assert rag_request_context["mixed_signal_part"] == "新增任务确认流"
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@pytest.mark.asyncio
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async def test_http_rag_ask_should_attach_project_operating_context_for_current_project(monkeypatch) -> None:
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captured: dict[str, object] = {}
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class FakeKernel:
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def __init__(self, db, tenant_id: int):
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_ = db
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captured["tenant_id"] = tenant_id
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async def process_ingress(self, **kwargs):
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captured["ingress_kwargs"] = kwargs
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return {
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"handled": True,
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"status": "answered",
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"intent": "query.read_only",
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"direct_reply_required": True,
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"direct_reply_text": "先给判断，再给下一步。",
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"rag_result": {
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"answer": "先给判断，再给下一步。",
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"route_decision": {
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"route_mode": "external",
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"effective_source_policy": "external",
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"decision_origin": "query_route_gateway",
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},
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},
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}
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monkeypatch.setattr(routes_query, "AIPMOKernelService", FakeKernel)
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app = _build_test_app()
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transport = ASGITransport(app=app)
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async with AsyncClient(transport=transport, base_url="http://test") as client:
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response = await client.post(
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"/rag/ask",
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json={
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"question": "OpenAI Docs 这种能力适不适合我们当前项目？",
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"asked_via": "feishu",
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"project_id": 12,
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"source_chat_id": "chat-12",
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"action_mode": "read",
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},
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)
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assert response.status_code == 200
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ingress_options = captured["ingress_kwargs"]["ingress_options"]
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packet = ingress_options["project_operating_context"]
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assert packet["current_project_id"] == 12
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assert packet["current_repo_scope"]
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assert packet["fit_scope"] == "current_project_and_repo"
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assert packet["decision_strategy"] == "answer_then_offer_plan"
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@pytest.mark.asyncio
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async def test_http_rag_ask_returns_offer_after_answer_handoff_metadata_for_current_project_fit_question(
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monkeypatch,
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) -> None:
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class FakeKernel:
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def __init__(self, db, tenant_id: int):
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_ = (db, tenant_id)
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async def process_ingress(self, **kwargs):
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_ = kwargs
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return {
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"handled": True,
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"status": "answered",
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"intent": "query.read_only",
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"direct_reply_required": True,
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"direct_reply_text": "外部实时查询：目前证据不足，建议先明确要查融资还是招聘动态。",
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"rag_result": {
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"answer": "外部实时查询：目前证据不足，建议先明确要查融资还是招聘动态。",
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"route_decision": {
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"route_mode": "external",
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"effective_source_policy": "external",
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"decision_origin": "query_route_gateway",
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},
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"project_operating_context": {
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"context_version": "v1",
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"current_project_id": 12,
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"current_repo_scope": "alpha-repo",
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"page_anchor": {"type": "project_board", "ref": "project:12"},
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"thread_anchor": {"source": "pmflow"},
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"fit_scope": "current_project_and_repo",
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"decision_strategy": "answer_then_offer_plan",
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},
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"execution_recipe": {
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"primary_lane": "external",
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"fit_brief_required": True,
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"external_evidence_required": True,
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"plan_handoff_mode": "offer_after_answer",
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},
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"fit_brief": {
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"project_summary": "Alpha 是一个 AI 项目管理工作台。",
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"repo_summary": "当前仓库负责统一项目上下文与 AI handoff。",
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},
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"external_recommendation": {
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"retrieval_status": "evidence_found",
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"impact_status": "indirect_only",
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"external_impact": "目前更像背景相关，还不能直接映射到当前正式对象。",
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},
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"analysis_packet": {
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"packet_version": "v1",
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"packet_type": "project_fit_analysis",
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"conclusion": "放到采购经理每日实时库存上报服务里，Responses API 更像接在摘要卡片后面的解释层，不像主计算链。",
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"focus_objects": [
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{
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"name": "每日固定时段生成并推送结构化摘要卡片",
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"kind": "task",
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"stance": "better_fit",
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"reason": "这一步更接近结果出来之后的解释和追问层。",
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},
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{
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"name": "WMS库存快照自动拉取与清洗",
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"kind": "task",
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"stance": "not_fit",
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"reason": "这一步属于确定性取数或计算主链。",
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},
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],
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"fit_verdict": "fit_later",
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"current_subject": "采购经理每日实时库存上报服务",
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"candidate_position": "每日固定时段生成并推送结构化摘要卡片",
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"rejected_position": "WMS库存快照自动拉取与清洗",
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"preferred_layer": "每日固定时段生成并推送结构化摘要卡片",
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"rejected_layer": "WMS库存快照自动拉取与清洗",
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"reason_chain": [
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"WMS库存快照自动拉取与清洗这一步属于确定性取数或计算主链，结果要稳定、可复算。",
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"每日固定时段生成并推送结构化摘要卡片更接近结果出来之后的解释和追问层，更适合承接这类能力。",
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],
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"missing_mapping": "还缺它在每日固定时段生成并推送结构化摘要卡片这一步到底承担解释、问答还是编排角色的明确映射。",
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"next_step": "先确认它是不是只用在摘要卡片之后。",
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},
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"handoff_mode": "offer_after_answer",
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"can_enter_plan": True,
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"recommended_next_step": "如果你要，我可以基于当前结论进入 plan，继续把需求范围和下一步收清楚。",
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},
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}
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monkeypatch.setattr(routes_query, "AIPMOKernelService", FakeKernel)
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app = _build_test_app()
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transport = ASGITransport(app=app)
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async with AsyncClient(transport=transport, base_url="http://test") as client:
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response = await client.post(
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"/rag/ask",
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json={
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"question": "OpenAI Responses API 放到当前库存上报项目里，适合放在哪一层？",
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"asked_via": "pmflow_manual",
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"project_id": 12,
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"source_chat_id": "chat-12",
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"action_mode": "read",
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},
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)
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assert response.status_code == 200
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payload = response.json()
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assert payload["code"] == 0
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data = payload["data"]
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assert data["route_decision"]["route_mode"] == "external"
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assert data["project_operating_context"]["current_project_id"] == 12
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assert data["execution_recipe"]["plan_handoff_mode"] == "offer_after_answer"
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assert data["fit_brief"]["project_summary"] == "Alpha 是一个 AI 项目管理工作台。"
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assert data["external_recommendation"]["impact_status"] == "indirect_only"
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assert data["analysis_packet"]["packet_type"] == "project_fit_analysis"
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assert data["analysis_packet"]["current_subject"] == "采购经理每日实时库存上报服务"
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assert data["analysis_packet"]["candidate_position"] == "每日固定时段生成并推送结构化摘要卡片"
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assert data["analysis_packet"]["rejected_position"] == "WMS库存快照自动拉取与清洗"
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assert len(data["analysis_packet"]["reason_chain"]) == 2
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assert data["analysis_packet"]["fit_verdict"] == "fit_later"
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assert data["handoff_mode"] == "offer_after_answer"
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assert data["can_enter_plan"] is True
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assert "进入 plan" in data["recommended_next_step"]
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@pytest.mark.asyncio
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async def test_http_ai_pmo_process_text_draft_pending_confirm_mainline(monkeypatch) -> None:
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captured: dict[str, object] = {}
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class FakeKernel:
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def __init__(self, db, tenant_id: int):
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_ = db
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captured["tenant_id"] = tenant_id
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async def process_ingress(self, **kwargs):
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captured["ingress_kwargs"] = kwargs
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return {
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"handled": True,
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"status": "draft_pending_confirm",
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"classification": "command",
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"direct_reply_required": True,
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"direct_reply_text": "草稿已生成，请确认。",
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"draft_version": 2,
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}
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monkeypatch.setattr(routes_core, "AIPMOKernelService", FakeKernel)
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app = _build_test_app()
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transport = ASGITransport(app=app)
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async with AsyncClient(transport=transport, base_url="http://test") as client:
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response = await client.post(
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"/ai-pmo/process-text",
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json={
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"message_text": "请创建任务并先给草稿",
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"sender": "产品经理A",
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"source_message_id": "manual-msg-100",
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"project_id": 12,
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},
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)
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assert response.status_code == 200
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payload = response.json()
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assert payload["code"] == 0
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data = payload["data"]
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assert data["status"] == "draft_pending_confirm"
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kwargs = captured["ingress_kwargs"]
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assert isinstance(kwargs, dict)
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assert kwargs["source_system"] == "pmflow_manual"
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assert kwargs["message_text"] == "请创建任务并先给草稿"
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assert kwargs["project_hint_id"] == 12
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@pytest.mark.asyncio
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async def test_http_ai_pmo_process_text_should_attach_project_operating_context(monkeypatch) -> None:
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captured: dict[str, object] = {}
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class FakeKernel:
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def __init__(self, db, tenant_id: int):
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_ = db
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captured["tenant_id"] = tenant_id
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async def process_ingress(self, **kwargs):
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captured["ingress_kwargs"] = kwargs
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return {
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"handled": True,
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"status": "answered",
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"classification": "query",
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"direct_reply_required": True,
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"direct_reply_text": "这个方向先判断，再决定是否进入计划。",
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}
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monkeypatch.setattr(routes_core, "AIPMOKernelService", FakeKernel)
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app = _build_test_app()
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transport = ASGITransport(app=app)
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async with AsyncClient(transport=transport, base_url="http://test") as client:
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response = await client.post(
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"/ai-pmo/process-text",
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json={
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"message_text": "这个方案适不适合我们当前项目？",
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"sender": "产品经理A",
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"source_message_id": "manual-msg-200",
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"project_id": 12,
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},
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)
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assert response.status_code == 200
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ingress_options = captured["ingress_kwargs"]["ingress_options"]
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packet = ingress_options["project_operating_context"]
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assert packet["current_project_id"] == 12
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assert packet["fit_scope"] == "current_project_and_repo"
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assert packet["decision_strategy"] == "answer_then_offer_plan"
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@pytest.mark.asyncio
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async def test_http_ai_pmo_work_items_list_smoke(monkeypatch) -> None:
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class FakeResult:
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def all(self):
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return []
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class FakeDB:
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async def execute(self, *_args, **_kwargs):
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return FakeResult()
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async def _fake_get_db():
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yield FakeDB()
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app = _build_test_app()
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app.dependency_overrides[get_db] = _fake_get_db
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transport = ASGITransport(app=app)
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async with AsyncClient(transport=transport, base_url="http://test") as client:
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response = await client.get("/ai-pmo/work-items", params={"limit": 18})
|
||
|
||
assert response.status_code == 200
|
||
payload = response.json()
|
||
assert payload["code"] == 0
|
||
assert payload["data"]["items"] == []
|
||
|
||
|
||
def test_ai_pmo_api_router_uses_single_prefix() -> None:
|
||
route_paths = {str(getattr(route, "path", "")).strip() for route in api_router.routes}
|
||
|
||
assert "/ai-pmo/work-items" in route_paths
|
||
assert "/ai-pmo/process-text" in route_paths
|
||
assert "/ai-pmo/ai-pmo/work-items" not in route_paths
|
||
assert "/ai-pmo/ai-pmo/process-text" not in route_paths
|