712 lines
30 KiB
Python
712 lines
30 KiB
Python
import pytest
|
||
|
||
from app.services.integrations.feishu_integration_service.mixin_card_action import FeishuCardActionMixin
|
||
from app.services.integrations.feishu_integration_service.mixin_receive_routing import FeishuReceiveRoutingMixin
|
||
from app.services.integrations.feishu_integration_service.mixin_reply_templates import FeishuReplyTemplatesMixin
|
||
from app.services.integrations.feishu_integration_service.service import FeishuIntegrationService
|
||
|
||
|
||
def test_extract_card_action_payload_parses_dict_value() -> None:
|
||
payload = FeishuCardActionMixin._extract_card_action_payload(
|
||
{
|
||
"open_message_id": "om_123",
|
||
"open_chat_id": "oc_123",
|
||
"operator": {"open_id": "ou_abc", "name": "测试用户"},
|
||
"action": {
|
||
"value": {
|
||
"action": "confirm_draft",
|
||
"work_item_id": 88,
|
||
"draft_version": 3,
|
||
"revision_note": "保持现有范围",
|
||
}
|
||
},
|
||
}
|
||
)
|
||
assert payload["action"] == "confirm"
|
||
assert payload["work_item_id"] == 88
|
||
assert payload["draft_version"] == 3
|
||
assert payload["source_message_id"] == "om_123"
|
||
assert payload["chat_id"] == "oc_123"
|
||
assert payload["sender_open_id"] == "ou_abc"
|
||
|
||
|
||
def test_extract_card_action_payload_parses_json_string_value_and_aliases() -> None:
|
||
payload = FeishuCardActionMixin._extract_card_action_payload(
|
||
{
|
||
"message_id": "msg_1",
|
||
"chat_id": "chat_9",
|
||
"operator": {"user_id": "ou_user", "display_name": "张三"},
|
||
"action": {"value": '{"draft_action":"修改","workItemId":"100","version":"4","note":"改成下周上线"}'},
|
||
}
|
||
)
|
||
assert payload["action"] == "revise"
|
||
assert payload["work_item_id"] == 100
|
||
assert payload["draft_version"] == 4
|
||
assert payload["revision_note"] == "改成下周上线"
|
||
assert payload["source_message_id"] == "msg_1"
|
||
assert payload["chat_id"] == "chat_9"
|
||
|
||
|
||
def test_extract_card_action_payload_parses_plan_synthetic_text() -> None:
|
||
payload = FeishuCardActionMixin._extract_card_action_payload(
|
||
{
|
||
"message_id": "msg_plan_1",
|
||
"chat_id": "chat_plan_1",
|
||
"operator": {"open_id": "ou_plan", "name": "计划用户"},
|
||
"action": {"value": {"action": "plan_choice", "choice": "C", "synthetic_text": "C"}},
|
||
}
|
||
)
|
||
assert payload["action"] == "plan_choice"
|
||
assert payload["choice"] == "C"
|
||
assert payload["synthetic_text"] == "C"
|
||
assert payload["source_message_id"] == "msg_plan_1"
|
||
assert payload["chat_id"] == "chat_plan_1"
|
||
|
||
|
||
@pytest.mark.asyncio
|
||
async def test_handle_message_event_dispatches_card_action(monkeypatch) -> None:
|
||
service = FeishuIntegrationService(db=object())
|
||
called: dict[str, object] = {}
|
||
|
||
async def _fake_card_handler(event):
|
||
called["event_type"] = event.get("type")
|
||
return {"code": 0, "msg": "success", "data": {"handled": True}}
|
||
|
||
monkeypatch.setattr(service, "_handle_card_action_trigger", _fake_card_handler)
|
||
|
||
result = await service.handle_message_event({"type": "card.action.trigger", "event": {}})
|
||
assert result["code"] == 0
|
||
assert called["event_type"] == "card.action.trigger"
|
||
|
||
|
||
def test_build_action_card_for_draft_pending_confirm() -> None:
|
||
card = FeishuCardActionMixin._build_action_card_from_capture_result(
|
||
capture_result={
|
||
"reply_template_key": "draft_pending_confirm",
|
||
"work_item_id": 321,
|
||
"draft_version": 5,
|
||
"direct_reply_text": "📌 AI直播复盘助手\n面向跨境 DTC 团队的 AI 直播复盘工具\n\n✅ 当前判断\n可行性：待讨论\n\n⚠️ 仍需确认\n· 验收口径\n· 触发时机",
|
||
},
|
||
mention_open_id="ou_xxx",
|
||
mention_name="测试同学",
|
||
)
|
||
assert isinstance(card, dict)
|
||
assert card["header"]["title"]["content"] == "AI PMO 草稿待确认"
|
||
div_blocks = [item for item in card["elements"] if item.get("tag") == "div"]
|
||
assert len(div_blocks) >= 3
|
||
action_row = next((item for item in card["elements"] if item.get("tag") == "action"), {})
|
||
actions = action_row.get("actions") if isinstance(action_row.get("actions"), list) else []
|
||
action_names = {((btn.get("value") or {}).get("action")) for btn in actions if isinstance(btn, dict)}
|
||
assert {"confirm", "revise", "cancel"} <= action_names
|
||
|
||
|
||
def test_build_action_card_for_pending_manual_continue() -> None:
|
||
card = FeishuCardActionMixin._build_action_card_from_capture_result(
|
||
capture_result={
|
||
"reply_template_key": "pending_manual",
|
||
"results": [{"work_item_id": 99}],
|
||
"direct_reply_text": "需要继续执行。",
|
||
},
|
||
mention_open_id=None,
|
||
mention_name=None,
|
||
)
|
||
assert isinstance(card, dict)
|
||
assert card["header"]["title"]["content"] == "AI PMO 待继续执行"
|
||
action_row = next((item for item in card["elements"] if item.get("tag") == "action"), {})
|
||
actions = action_row.get("actions") if isinstance(action_row.get("actions"), list) else []
|
||
assert len(actions) == 1
|
||
assert (actions[0].get("value") or {}).get("action") == "continue"
|
||
assert (actions[0].get("value") or {}).get("work_item_id") == 99
|
||
|
||
|
||
def test_build_action_card_for_requirement_plan_followup() -> None:
|
||
card = FeishuCardActionMixin._build_action_card_from_capture_result(
|
||
capture_result={
|
||
"reply_template_key": "requirement_plan_followup",
|
||
"work_item_id": 77,
|
||
"direct_reply_text": "A. 规则引擎驱动\nB. 轻量模型辅助\nC. 混合增强路径\n\n⭐ 当前我更推荐：C",
|
||
},
|
||
mention_open_id="ou_plan_xxx",
|
||
mention_name="测试计划用户",
|
||
)
|
||
assert isinstance(card, dict)
|
||
assert card["header"]["title"]["content"] == "AI PMO 需求收敛"
|
||
action_rows = [item for item in card["elements"] if item.get("tag") == "action"]
|
||
assert len(action_rows) == 2
|
||
row_1_actions = action_rows[0].get("actions") if isinstance(action_rows[0].get("actions"), list) else []
|
||
row_2_actions = action_rows[1].get("actions") if isinstance(action_rows[1].get("actions"), list) else []
|
||
assert [((btn.get("value") or {}).get("synthetic_text")) for btn in row_1_actions] == ["A", "B", "C", "D"]
|
||
assert [((btn.get("value") or {}).get("synthetic_text")) for btn in row_2_actions] == ["继续出草稿", "重出一版"]
|
||
|
||
|
||
@pytest.mark.parametrize(
|
||
("external_recommendation", "expected_fragment"),
|
||
[
|
||
(
|
||
{
|
||
"retrieval_status": "evidence_found",
|
||
"impact_status": "indirect_only",
|
||
},
|
||
"目前更像背景相关",
|
||
),
|
||
(
|
||
{
|
||
"retrieval_status": "verifier_blocked",
|
||
"impact_status": "uncertain",
|
||
},
|
||
"校验未通过",
|
||
),
|
||
(
|
||
{
|
||
"retrieval_status": "no_relevant_results",
|
||
"impact_status": "no_direct_match",
|
||
},
|
||
"暂未找到与当前项目直接相关的公开证据",
|
||
),
|
||
(
|
||
{
|
||
"retrieval_status": "retrieval_failed",
|
||
"impact_status": "uncertain",
|
||
},
|
||
"这次外部检索失败",
|
||
),
|
||
],
|
||
)
|
||
def test_build_feishu_external_summary_line_preserves_distinct_states(
|
||
external_recommendation: dict[str, str],
|
||
expected_fragment: str,
|
||
) -> None:
|
||
line = FeishuReceiveRoutingMixin._build_feishu_external_summary_line(external_recommendation)
|
||
|
||
assert line.startswith("外部判断：")
|
||
assert expected_fragment in line
|
||
|
||
|
||
def test_should_accept_feishu_qa_natural_reply_rejects_fixed_opener_without_project_entities() -> None:
|
||
accepted = FeishuReceiveRoutingMixin._should_accept_feishu_qa_natural_reply(
|
||
"这事可以继续看，但现在还不能直接说它适合这个项目。",
|
||
selected_entity_candidates=[
|
||
"采购经理每日实时库存上报服务",
|
||
"WMS库存快照自动拉取与清洗",
|
||
"每日固定时段生成并推送结构化摘要卡片",
|
||
],
|
||
blocked_entity_candidates=[],
|
||
)
|
||
|
||
assert accepted is False
|
||
|
||
|
||
def test_should_accept_feishu_qa_natural_reply_accepts_project_entity_analysis() -> None:
|
||
accepted = FeishuReceiveRoutingMixin._should_accept_feishu_qa_natural_reply(
|
||
(
|
||
"Responses API 不适合放在 WMS库存快照自动拉取或者 TOP10缺货排序这两层，"
|
||
"更像放在每日固定时段生成并推送结构化摘要卡片之后的解释和追问层。"
|
||
),
|
||
selected_entity_candidates=[
|
||
"采购经理每日实时库存上报服务",
|
||
"WMS库存快照自动拉取与清洗",
|
||
"TOP10商品缺货排序逻辑实现（基于当前库存与安全库存差值）",
|
||
"每日固定时段生成并推送结构化摘要卡片",
|
||
],
|
||
blocked_entity_candidates=[],
|
||
)
|
||
|
||
assert accepted is True
|
||
|
||
|
||
def test_should_accept_feishu_qa_natural_reply_rejects_unplanned_project_entities() -> None:
|
||
accepted = FeishuReceiveRoutingMixin._should_accept_feishu_qa_natural_reply(
|
||
(
|
||
"Responses API 更像放在每日固定时段生成并推送结构化摘要卡片之后的解释层，"
|
||
"不适合直接放进 WMS库存快照自动拉取与清洗 主链。"
|
||
"但它和外部信号源 - WMS实时库存接口 也许也能直接打通。"
|
||
),
|
||
selected_entity_candidates=[
|
||
"WMS库存快照自动拉取与清洗",
|
||
"每日固定时段生成并推送结构化摘要卡片",
|
||
],
|
||
blocked_entity_candidates=[
|
||
"外部信号源 - WMS实时库存接口",
|
||
"TOP10商品缺货排序逻辑实现（基于当前库存与安全库存差值）",
|
||
],
|
||
)
|
||
|
||
assert accepted is False
|
||
|
||
|
||
def test_normalize_feishu_qa_analysis_plan_keeps_only_allowed_focus_entities() -> None:
|
||
plan = FeishuReceiveRoutingMixin._normalize_feishu_qa_analysis_plan(
|
||
payload={
|
||
"conclusion": "Responses API 更像摘要卡片之后的解释层。",
|
||
"focus_entities": [
|
||
{
|
||
"name": "每日固定时段生成并推送结构化摘要卡片",
|
||
"stance": "better_fit",
|
||
"why": "这里更适合承接解释和追问。",
|
||
},
|
||
{
|
||
"name": "WMS库存快照自动拉取与清洗",
|
||
"stance": "not_fit",
|
||
"why": "这是确定性取数链路，不适合塞进生成能力。",
|
||
},
|
||
{
|
||
"name": "外部并不存在的对象",
|
||
"stance": "not_fit",
|
||
"why": "这条应该被过滤掉。",
|
||
},
|
||
],
|
||
"missing_mapping": "当前没有证据说明它已接入现有信号源或主计算链。",
|
||
"next_step": "先确认它到底承担哪个节点的角色。",
|
||
},
|
||
entity_catalog=[
|
||
{
|
||
"name": "每日固定时段生成并推送结构化摘要卡片",
|
||
"kind": "task",
|
||
},
|
||
{
|
||
"name": "WMS库存快照自动拉取与清洗",
|
||
"kind": "task",
|
||
},
|
||
{
|
||
"name": "外部信号源 - WMS实时库存接口",
|
||
"kind": "signal",
|
||
},
|
||
],
|
||
fallback_next_step="继续确认它到底落在这个项目的哪一层，再决定要不要进入 plan。",
|
||
)
|
||
|
||
assert plan["conclusion"] == "Responses API 更像摘要卡片之后的解释层。"
|
||
assert [item["name"] for item in plan["focus_entities"]] == [
|
||
"每日固定时段生成并推送结构化摘要卡片",
|
||
"WMS库存快照自动拉取与清洗",
|
||
]
|
||
assert [item["stance"] for item in plan["focus_entities"]] == ["better_fit", "not_fit"]
|
||
assert all(item["name"] != "外部并不存在的对象" for item in plan["focus_entities"])
|
||
assert plan["missing_mapping"] == "当前没有证据说明它已接入现有信号源或主计算链。"
|
||
|
||
|
||
def test_build_feishu_qa_analysis_fallback_plan_prefers_presentation_and_core_chain_entities_for_indirect_only() -> None:
|
||
plan = FeishuReceiveRoutingMixin._build_feishu_qa_analysis_fallback_plan(
|
||
result={
|
||
"rag_result": {
|
||
"external_recommendation": {
|
||
"retrieval_status": "evidence_found",
|
||
"impact_status": "indirect_only",
|
||
},
|
||
"recommended_next_step": "继续确认它到底落在这个项目的哪一层，再决定要不要进入 plan。",
|
||
},
|
||
},
|
||
entity_catalog=[
|
||
{"name": "WMS库存快照自动拉取与清洗", "kind": "task"},
|
||
{"name": "TOP10商品缺货排序逻辑实现（基于当前库存与安全库存差值）", "kind": "task"},
|
||
{"name": "每日固定时段生成并推送结构化摘要卡片", "kind": "task"},
|
||
{"name": "试点小组成员接收通道配置与权限开通", "kind": "task"},
|
||
],
|
||
)
|
||
|
||
assert plan["conclusion"] == "目前还不能直接说它已经适合当前项目。"
|
||
assert [item["name"] for item in plan["focus_entities"]] == [
|
||
"每日固定时段生成并推送结构化摘要卡片",
|
||
"WMS库存快照自动拉取与清洗",
|
||
]
|
||
assert [item["stance"] for item in plan["focus_entities"]] == ["better_fit", "not_fit"]
|
||
|
||
|
||
def test_build_feishu_qa_analysis_plan_reply_text_avoids_stepwise_checklist_tone() -> None:
|
||
reply = FeishuReceiveRoutingMixin._build_feishu_qa_analysis_plan_reply_text(
|
||
{
|
||
"conclusion": "目前还不能直接说它已经适合当前项目。",
|
||
"focus_entities": [
|
||
{
|
||
"name": "每日固定时段生成并推送结构化摘要卡片",
|
||
"stance": "better_fit",
|
||
"why": "这里更像结果出来之后的解释和追问层。",
|
||
},
|
||
{
|
||
"name": "WMS库存快照自动拉取与清洗",
|
||
"stance": "not_fit",
|
||
"why": "这是稳定取数的主链，不适合直接塞进生成能力。",
|
||
},
|
||
],
|
||
"missing_mapping": "还缺它在当前项目里到底承接哪个节点的明确映射。",
|
||
"next_step": "先确认它是不是只用在摘要卡片之后。",
|
||
}
|
||
)
|
||
|
||
expected = (
|
||
"目前还不能直接说它已经适合当前项目。\n\n"
|
||
"如果放在这个项目里，它更像接在每日固定时段生成并推送结构化摘要卡片后面的解释和追问层，"
|
||
"不像 WMS库存快照自动拉取与清洗 这种要稳定取数的主链。\n\n"
|
||
"还缺它在当前项目里到底承接哪个节点的明确映射。\n\n"
|
||
"先确认它是不是只用在摘要卡片之后。"
|
||
)
|
||
assert reply == expected
|
||
|
||
|
||
def test_choose_feishu_qa_analysis_plan_prefers_fallback_when_indirect_only_plan_lacks_contrast() -> None:
|
||
chosen = FeishuReceiveRoutingMixin._choose_feishu_qa_analysis_plan(
|
||
normalized_plan={
|
||
"conclusion": "目前还不能直接说它已经适合当前项目。",
|
||
"focus_entities": [
|
||
{
|
||
"name": "WMS库存快照自动拉取与清洗",
|
||
"stance": "relevant",
|
||
"why": "该任务聚焦内部WMS数据接入。",
|
||
},
|
||
{
|
||
"name": "外部信号源 - WMS实时库存接口",
|
||
"stance": "relevant",
|
||
"why": "同为外部API调用场景。",
|
||
},
|
||
],
|
||
"missing_mapping": "缺少具体作用层映射。",
|
||
"next_step": "确认它是不是用于摘要生成环节。",
|
||
},
|
||
fallback_plan={
|
||
"conclusion": "目前还不能直接说它已经适合当前项目。",
|
||
"focus_entities": [
|
||
{
|
||
"name": "每日固定时段生成并推送结构化摘要卡片",
|
||
"stance": "better_fit",
|
||
"why": "这一步更像结果出来之后的解释和追问层。",
|
||
},
|
||
{
|
||
"name": "WMS库存快照自动拉取与清洗",
|
||
"stance": "not_fit",
|
||
"why": "这一步属于确定性取数或计算主链，不适合直接塞进生成能力。",
|
||
},
|
||
],
|
||
"missing_mapping": "还缺它在当前项目里到底承接哪个节点的明确映射。",
|
||
"next_step": "继续确认它到底落在这个项目的哪一层，再决定要不要进入 plan。",
|
||
},
|
||
retrieval_status="evidence_found",
|
||
impact_status="indirect_only",
|
||
)
|
||
|
||
assert [item["name"] for item in chosen["focus_entities"]] == [
|
||
"每日固定时段生成并推送结构化摘要卡片",
|
||
"WMS库存快照自动拉取与清洗",
|
||
]
|
||
|
||
|
||
def test_build_execution_receipt_reply_prefers_compact_multiline_summary() -> None:
|
||
reply = FeishuReplyTemplatesMixin._build_execution_receipt_reply(
|
||
message_content="请处理这条信号",
|
||
capture_result={
|
||
"status": "captured",
|
||
"signal_id": 18,
|
||
"linked_project_ids": [9],
|
||
},
|
||
)
|
||
|
||
assert reply == "✅ 已执行完成\n信号#18 已入库\n项目#9 已关联"
|
||
|
||
|
||
def test_build_action_card_for_queue_pending_confirm_returns_none() -> None:
|
||
card = FeishuCardActionMixin._build_action_card_from_capture_result(
|
||
capture_result={
|
||
"reply_template_key": "queue_pending_confirm",
|
||
"results": [{"item_id": 201, "route_status": "queued_for_decision"}],
|
||
"direct_reply_text": "需要你确认后继续执行。",
|
||
},
|
||
mention_open_id=None,
|
||
mention_name=None,
|
||
)
|
||
assert card is None
|
||
|
||
|
||
@pytest.mark.asyncio
|
||
async def test_handle_card_action_trigger_continue_dispatches_resume(monkeypatch) -> None:
|
||
called: dict[str, object] = {}
|
||
|
||
class DummyDB:
|
||
async def commit(self) -> None:
|
||
called["committed"] = True
|
||
|
||
async def rollback(self) -> None:
|
||
called["rolled_back"] = True
|
||
|
||
service = FeishuIntegrationService(db=DummyDB())
|
||
service.tenant_id = 7
|
||
|
||
async def _fake_reply_text(**kwargs):
|
||
called["reply_text"] = kwargs.get("text")
|
||
called["reply_chat"] = kwargs.get("chat_id")
|
||
|
||
monkeypatch.setattr(service, "_safe_reply_text", _fake_reply_text)
|
||
|
||
class _FakeKernel:
|
||
def __init__(self, db, tenant_id):
|
||
called["kernel_tenant_id"] = tenant_id
|
||
|
||
async def process_ingress(self, **kwargs):
|
||
called["ingress_kwargs"] = kwargs
|
||
return {
|
||
"handled": True,
|
||
"status": "captured",
|
||
"direct_reply_text": "已继续执行。",
|
||
}
|
||
|
||
monkeypatch.setattr(
|
||
"app.services.ai_pmo.ai_pmo_kernel.ai_pmo_kernel_runtime.AIPMOKernelService",
|
||
_FakeKernel,
|
||
)
|
||
|
||
result = await service._handle_card_action_trigger(
|
||
{
|
||
"open_message_id": "om_continue_1",
|
||
"open_chat_id": "oc_continue_1",
|
||
"operator": {"open_id": "ou_continue", "name": "继续用户"},
|
||
"action": {"value": {"action": "continue", "work_item_id": 55}},
|
||
}
|
||
)
|
||
|
||
assert result["code"] == 0
|
||
data = result.get("data") if isinstance(result.get("data"), dict) else {}
|
||
assert data.get("handled") is True
|
||
assert data.get("target_work_item_id") == 55
|
||
ingress_kwargs = called["ingress_kwargs"]
|
||
assert ingress_kwargs["message_text"] == "继续处理 work_item #55"
|
||
assert ingress_kwargs["source_system"] == "ai_pmo_ui"
|
||
assert called["reply_text"] == "已继续执行。"
|
||
assert called["reply_chat"] == "oc_continue_1"
|
||
|
||
|
||
@pytest.mark.asyncio
|
||
async def test_handle_card_action_trigger_plan_choice_dispatches_synthetic_ingress(monkeypatch) -> None:
|
||
called: dict[str, object] = {}
|
||
|
||
class DummyDB:
|
||
async def commit(self) -> None:
|
||
called["committed"] = True
|
||
|
||
async def rollback(self) -> None:
|
||
called["rolled_back"] = True
|
||
|
||
service = FeishuIntegrationService(db=DummyDB())
|
||
service.tenant_id = 7
|
||
|
||
async def _fake_reply_card(**kwargs):
|
||
called["reply_card"] = kwargs.get("card_content")
|
||
called["reply_chat"] = kwargs.get("chat_id")
|
||
|
||
monkeypatch.setattr(service, "_safe_reply_card", _fake_reply_card)
|
||
|
||
class _FakeKernel:
|
||
def __init__(self, db, tenant_id):
|
||
called["kernel_tenant_id"] = tenant_id
|
||
|
||
async def process_ingress(self, **kwargs):
|
||
called["ingress_kwargs"] = kwargs
|
||
return {
|
||
"handled": True,
|
||
"status": "captured",
|
||
"reply_template_key": "requirement_plan_followup",
|
||
"direct_reply_text": "C. 混合增强路径\n\n⭐ 当前我更推荐：C",
|
||
"results": [{"work_item_id": 88}],
|
||
"work_item_id": 88,
|
||
}
|
||
|
||
monkeypatch.setattr(
|
||
"app.services.ai_pmo.ai_pmo_kernel.ai_pmo_kernel_runtime.AIPMOKernelService",
|
||
_FakeKernel,
|
||
)
|
||
|
||
result = await service._handle_card_action_trigger(
|
||
{
|
||
"open_message_id": "om_plan_1",
|
||
"open_chat_id": "oc_plan_1",
|
||
"operator": {"open_id": "ou_plan", "name": "计划用户"},
|
||
"action": {"value": {"action": "plan_choice", "choice": "C", "synthetic_text": "C", "work_item_id": 88}},
|
||
}
|
||
)
|
||
|
||
assert result["code"] == 0
|
||
data = result.get("data") if isinstance(result.get("data"), dict) else {}
|
||
assert data.get("handled") is True
|
||
assert data.get("target_work_item_id") == 88
|
||
ingress_kwargs = called["ingress_kwargs"]
|
||
assert ingress_kwargs["message_text"] == "C"
|
||
assert ingress_kwargs["source_system"] == "feishu"
|
||
assert str(ingress_kwargs["source_message_id"]).startswith("feishu-card-plan-88-plan_choice-")
|
||
ingress_options = ingress_kwargs.get("ingress_options") if isinstance(ingress_kwargs.get("ingress_options"), dict) else {}
|
||
thread_context = ingress_options.get("thread_context") if isinstance(ingress_options.get("thread_context"), dict) else {}
|
||
assert thread_context["reply_to_message_id"] == "om_plan_1"
|
||
assert thread_context["root_message_id"] == "om_plan_1"
|
||
assert called["reply_chat"] == "oc_plan_1"
|
||
assert isinstance(called["reply_card"], dict)
|
||
assert called["reply_card"]["header"]["title"]["content"] == "AI PMO 需求收敛"
|
||
|
||
|
||
@pytest.mark.asyncio
|
||
async def test_handle_card_action_trigger_queue_continue_is_ignored(monkeypatch) -> None:
|
||
called: dict[str, object] = {}
|
||
|
||
class DummyDB:
|
||
async def commit(self) -> None:
|
||
called["committed"] = True
|
||
|
||
async def rollback(self) -> None:
|
||
called["rolled_back"] = True
|
||
|
||
service = FeishuIntegrationService(db=DummyDB())
|
||
service.tenant_id = 7
|
||
|
||
async def _fake_reply_text(**kwargs):
|
||
called["reply_text"] = kwargs.get("text")
|
||
|
||
monkeypatch.setattr(service, "_safe_reply_text", _fake_reply_text)
|
||
|
||
result = await service._handle_card_action_trigger(
|
||
{
|
||
"open_message_id": "om_queue_1",
|
||
"open_chat_id": "oc_queue_1",
|
||
"operator": {"open_id": "ou_queue", "name": "队列用户"},
|
||
"action": {"value": {"action": "continue", "queue_item_id": 201}},
|
||
}
|
||
)
|
||
|
||
assert result["code"] == 0
|
||
assert result["msg"] == "card_action_ignored"
|
||
data = result.get("data") if isinstance(result.get("data"), dict) else {}
|
||
assert data.get("reason") == "missing_work_item_id"
|
||
assert "reply_text" not in called
|
||
|
||
|
||
@pytest.mark.asyncio
|
||
async def test_route_scene_reply_sends_requirement_plan_followup_as_card(monkeypatch) -> None:
|
||
calls: dict[str, object] = {}
|
||
|
||
class FakeRouting(FeishuReceiveRoutingMixin):
|
||
def _build_capability_reply(self, message_content: str): # noqa: ANN001
|
||
_ = message_content
|
||
return None
|
||
|
||
def _build_action_card_from_capture_result(self, *, capture_result, mention_open_id, mention_name): # noqa: ANN001
|
||
_ = (mention_open_id, mention_name)
|
||
if str(capture_result.get("reply_template_key") or "").strip().lower() == "requirement_plan_followup":
|
||
return {
|
||
"header": {"title": {"tag": "plain_text", "content": "AI PMO 需求收敛"}},
|
||
"elements": [],
|
||
}
|
||
return None
|
||
|
||
async def _safe_reply_card(self, **kwargs): # noqa: ANN001
|
||
calls["reply_card"] = kwargs
|
||
|
||
async def _safe_reply_text(self, **kwargs): # noqa: ANN001
|
||
calls["reply_text"] = kwargs
|
||
|
||
def _emit_state_transition(self, **kwargs): # noqa: ANN001
|
||
calls["state_transition"] = kwargs
|
||
|
||
def _should_allow_group_qa_reply(self, **kwargs): # noqa: ANN001
|
||
_ = kwargs
|
||
return True
|
||
|
||
routing = FakeRouting()
|
||
result = await routing._route_scene_reply(
|
||
scene="qa",
|
||
result={
|
||
"reply_template_key": "requirement_plan_followup",
|
||
"work_item_id": 88,
|
||
"direct_reply_text": "C. 混合增强路径\n\n⭐ 当前我更推荐：C",
|
||
},
|
||
message_content="C",
|
||
chat_id="chat-plan-card",
|
||
chat_type="group",
|
||
sender_open_id="ou-plan",
|
||
sender_name="计划用户",
|
||
mentioned_bot_names=[],
|
||
thread_context=None,
|
||
trace_id="trace-plan-card",
|
||
message_id="msg-plan-card",
|
||
perf_t0=None,
|
||
)
|
||
|
||
assert result == "qa_action_card"
|
||
assert "reply_card" in calls
|
||
assert "reply_text" not in calls
|
||
card_content = calls["reply_card"]["card_content"] if isinstance(calls["reply_card"], dict) else {}
|
||
assert card_content["header"]["title"]["content"] == "AI PMO 需求收敛"
|
||
|
||
|
||
@pytest.mark.asyncio
|
||
async def test_route_scene_reply_sends_rich_qa_direct_text_for_handoff_metadata() -> None:
|
||
calls: dict[str, object] = {}
|
||
|
||
class FakeRouting(FeishuReceiveRoutingMixin):
|
||
def _build_capability_reply(self, message_content: str): # noqa: ANN001
|
||
_ = message_content
|
||
return None
|
||
|
||
def _build_action_card_from_capture_result(self, *, capture_result, mention_open_id, mention_name): # noqa: ANN001
|
||
_ = (capture_result, mention_open_id, mention_name)
|
||
return None
|
||
|
||
async def _safe_reply_text(self, **kwargs): # noqa: ANN001
|
||
calls["reply_text"] = kwargs
|
||
|
||
def _emit_state_transition(self, **kwargs): # noqa: ANN001
|
||
calls["state_transition"] = kwargs
|
||
|
||
def _should_allow_group_qa_reply(self, **kwargs): # noqa: ANN001
|
||
_ = kwargs
|
||
return True
|
||
|
||
async def _render_feishu_qa_direct_reply_text(self, *, result, message_content): # noqa: ANN001
|
||
_ = (result, message_content)
|
||
return (
|
||
"Responses API 不适合放在 WMS库存快照自动拉取或者 TOP10缺货排序这两层，"
|
||
"更像放在每日结构化摘要卡片之后的解释和追问层。\n\n"
|
||
"这个项目当前在做的是先把 WMS库存快照拉进来，再完成 TOP10缺货排序，"
|
||
"最后按固定时段推送结构化摘要卡片。前两层都属于取数和计算主链，应该保持确定、可复算，"
|
||
"不适合把 Responses API 放进去做主判断。\n\n"
|
||
"它真正更可能有价值的地方，是采购经理收到摘要卡片之后继续追问的时候。"
|
||
)
|
||
|
||
routing = FakeRouting()
|
||
result = await routing._route_scene_reply(
|
||
scene="qa",
|
||
result={
|
||
"direct_reply_required": True,
|
||
"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。",
|
||
"rag_result": {
|
||
"fit_brief": {
|
||
"project_summary": "Alpha 是一个 AI 项目管理工作台。",
|
||
"repo_summary": "当前仓库负责统一项目上下文与 AI handoff。",
|
||
},
|
||
"external_recommendation": {
|
||
"retrieval_status": "evidence_found",
|
||
"impact_status": "indirect_only",
|
||
"external_impact": "目前更像背景相关，还不能直接映射到当前正式对象。",
|
||
},
|
||
"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。",
|
||
},
|
||
},
|
||
message_content="这个适合吗",
|
||
chat_id="chat-rich-qa",
|
||
chat_type="group",
|
||
sender_open_id="ou-rich-qa",
|
||
sender_name="测试用户",
|
||
mentioned_bot_names=[],
|
||
thread_context={"reply_to_message_id": "om-rich-qa"},
|
||
trace_id="trace-rich-qa",
|
||
message_id="msg-rich-qa",
|
||
perf_t0=None,
|
||
)
|
||
|
||
assert result == "qa_direct"
|
||
reply_text = calls["reply_text"]["text"] if isinstance(calls.get("reply_text"), dict) else ""
|
||
expected = (
|
||
"Responses API 不适合放在 WMS库存快照自动拉取或者 TOP10缺货排序这两层，"
|
||
"更像放在每日结构化摘要卡片之后的解释和追问层。\n\n"
|
||
"这个项目当前在做的是先把 WMS库存快照拉进来，再完成 TOP10缺货排序，"
|
||
"最后按固定时段推送结构化摘要卡片。前两层都属于取数和计算主链，应该保持确定、可复算，"
|
||
"不适合把 Responses API 放进去做主判断。\n\n"
|
||
"它真正更可能有价值的地方，是采购经理收到摘要卡片之后继续追问的时候。"
|
||
)
|
||
assert reply_text == expected
|
||
assert "这事可以继续看" not in reply_text
|
||
assert "先说我的判断" not in reply_text
|