348 lines
12 KiB
Python
348 lines
12 KiB
Python
import pytest
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from app.config.ai_prompts import (
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PROMPT_EXTERNAL_TREND_QA,
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PROMPT_FEISHU_DIRECT_QA,
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PROMPT_FEISHU_MIXED_QA,
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PROMPT_PROJECT_STATUS_QA,
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)
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from app.services.ai_pmo.draft_confirm_handler import DraftConfirmHandler
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from app.services.ai_pmo.ai_pmo_kernel_ingress_flow import mixin_auto
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from app.services.adaptive_rag_service.mixin_deep_guard_answer import AdaptiveRAGDeepGuardAnswerMixin
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from app.services.integrations.feishu_integration_service.mixin_reply_llm_core import (
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FeishuReplyLLMCoreMixin,
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)
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def test_parse_action_confirm() -> None:
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action, note = DraftConfirmHandler.parse_action_from_text(message_text="确认")
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assert action == "confirm"
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assert note == ""
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def test_parse_action_revise_with_note() -> None:
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action, note = DraftConfirmHandler.parse_action_from_text(message_text="修改 改成每周跟进")
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assert action == "revise"
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assert note == "改成每周跟进"
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def test_parse_action_cancel() -> None:
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action, note = DraftConfirmHandler.parse_action_from_text(message_text="取消")
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assert action == "cancel"
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assert note == ""
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def test_parse_action_yes_as_confirm() -> None:
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action, note = DraftConfirmHandler.parse_action_from_text(message_text="yes")
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assert action == "confirm"
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assert note == ""
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def test_draft_confirm_handler_thread_anchor_match() -> None:
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ingest = type(
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"Ingest",
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(),
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{
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"payload": {
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"thread_id": "th_1",
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"root_message_id": "root_1",
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"reply_to_message_id": "reply_1",
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},
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"source_message_id": "src_1",
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},
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)()
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work_item = type("WorkItem", (), {"source_message_id": "wi_1"})()
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assert DraftConfirmHandler._matches_thread_anchor(
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work_item=work_item,
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ingest=ingest,
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anchor_context={"reply_to_message_id": "reply_1"},
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) is True
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assert DraftConfirmHandler._matches_thread_anchor(
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work_item=work_item,
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ingest=ingest,
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anchor_context={"reply_to_message_id": "missing"},
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) is False
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assert DraftConfirmHandler._normalize_thread_context(
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{"thread_id": "th_1", "root_message_id": "root_1", "reply_to_message_id": "reply_1"}
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) == {
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"thread_id": "th_1",
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"root_message_id": "root_1",
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"reply_to_message_id": "reply_1",
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}
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def test_draft_confirm_handler_thread_anchor_matches_draft_reply_message_id() -> None:
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ingest = type(
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"Ingest",
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(),
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{
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"payload": {
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"thread_id": "th_1",
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"root_message_id": "draft_msg_1",
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"reply_to_message_id": "draft_msg_1",
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},
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"source_message_id": "original_msg_1",
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},
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)()
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work_item = type("WorkItem", (), {"source_message_id": "original_msg_1"})()
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assert DraftConfirmHandler._matches_thread_anchor(
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work_item=work_item,
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ingest=ingest,
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anchor_context={"root_message_id": "draft_msg_1"},
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draft_reply_message_id="draft_msg_1",
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) is True
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def test_reply_outbox_extract_sent_message_id() -> None:
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from app.services.integrations.feishu_integration_service.mixin_reply_outbox import FeishuReplyOutboxMixin
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assert FeishuReplyOutboxMixin._extract_sent_message_id({"data": {"message_id": "msg_123"}}) == "msg_123"
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assert FeishuReplyOutboxMixin._extract_sent_message_id({"message_id": "msg_456"}) == "msg_456"
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@pytest.mark.asyncio
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async def test_draft_confirm_handler_ignores_non_draft_reply_without_target(monkeypatch) -> None:
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kernel = type("Kernel", (), {"db": object(), "tenant_id": 1})()
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handler = DraftConfirmHandler(kernel)
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async def _fake_resolve_pending_draft(**kwargs):
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_ = kwargs
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return None
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monkeypatch.setattr(handler, "_resolve_pending_draft", _fake_resolve_pending_draft)
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result = await handler.handle_text_reply(
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message_text="创建时间是多少？",
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sender="林宇航",
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source_system="feishu",
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source_message_id="msg-1",
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channel_ref="chat-1",
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source_sender_open_id="ou_xxx",
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thread_context={"reply_to_message_id": "reply-1"},
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)
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assert result["handled"] is False
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assert result["status"] == "ignored"
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assert result["followup_reply"] == ""
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def test_kernel_ingress_mixin_auto_safe_int_regression() -> None:
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assert callable(mixin_auto._safe_int)
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assert mixin_auto._safe_int("123") == 123
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assert mixin_auto._safe_int("") is None
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assert mixin_auto._safe_int(None) is None
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def test_adaptive_rag_process_entry_and_mixed_format() -> None:
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mixin = AdaptiveRAGDeepGuardAnswerMixin()
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assert mixin._is_ai_pmo_process_entry("pmflow_manual") is True
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assert mixin._is_ai_pmo_process_entry("feishu") is False
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mixed = mixin._format_mixed_two_block_output(
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answer_text="[回答] 接口契约已对齐\n[已收到需求] 新增任务创建确认流",
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question_part="现在进展怎么样",
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signal_part="补齐任务确认",
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)
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assert mixed.startswith("[回答] ")
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assert "\n[已收到需求] " in mixed
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assert mixed.endswith("，已入库处理")
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def test_adaptive_rag_select_scene_prompt_prefers_mixed() -> None:
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mixin = AdaptiveRAGDeepGuardAnswerMixin()
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scene_key, prompt = mixin._select_scene_prompt(
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question="现在进展怎么样？",
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project_id=7,
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asked_via="pmflow_manual",
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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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conversation_text="无",
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context_blocks_text="无",
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system_snapshot={},
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user_snapshot={},
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system_snapshot_text="{}",
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user_snapshot_text="{}",
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relevance_max=0.0,
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)
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assert scene_key == "mixed"
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assert "现在进展怎么样" in prompt
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assert "新增任务确认流" in prompt
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def test_adaptive_rag_select_scene_prompt_ai_pmo_manual_entry() -> None:
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mixin = AdaptiveRAGDeepGuardAnswerMixin()
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scene_key, prompt = mixin._select_scene_prompt(
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question="帮我总结这个项目",
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project_id=9,
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asked_via="pmflow_manual",
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message_intent=None,
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mixed_signal_part=None,
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conversation_text="无",
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context_blocks_text="无",
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system_snapshot={},
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user_snapshot={},
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system_snapshot_text="{}",
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user_snapshot_text="{}",
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relevance_max=0.0,
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)
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assert scene_key == "ai_pmo"
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assert "帮我总结这个项目" in prompt
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def test_adaptive_rag_select_scene_prompt_prefers_decision_choice() -> None:
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mixin = AdaptiveRAGDeepGuardAnswerMixin()
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scene_key, prompt = mixin._select_scene_prompt(
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question="如果 AI 助手第一次上线只允许一种提醒，你会把它做成桌面通知还是飞书消息？为什么？",
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project_id=None,
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asked_via="feishu",
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message_intent=None,
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mixed_signal_part=None,
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conversation_text="无",
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context_blocks_text="无",
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system_snapshot={},
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user_snapshot={},
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system_snapshot_text="{}",
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user_snapshot_text="{}",
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relevance_max=0.0,
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)
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assert scene_key == "decision_choice"
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assert "明确选择" in prompt
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assert "飞书消息" in prompt
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def test_adaptive_rag_select_scene_prompt_prefers_industry_trend_without_project_context() -> None:
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mixin = AdaptiveRAGDeepGuardAnswerMixin()
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scene_key, prompt = mixin._select_scene_prompt(
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question="帮我看看宠物行业最新动态",
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project_id=None,
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asked_via="feishu",
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message_intent=None,
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mixed_signal_part=None,
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conversation_text="无",
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context_blocks_text="无",
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system_snapshot={"assistant_profile": {"name": "PMFlow"}},
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user_snapshot={"projects": [{"id": 1}]},
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system_snapshot_text="{}",
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user_snapshot_text="{}",
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relevance_max=0.0,
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)
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assert scene_key == "industry_trend"
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assert "当前未接入实时数据" in prompt
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assert "project_context" not in prompt
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def test_adaptive_rag_select_scene_prompt_filters_member_context_noise() -> None:
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mixin = AdaptiveRAGDeepGuardAnswerMixin()
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scene_key, prompt = mixin._select_scene_prompt(
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question="杨宇现在负载情况如何？",
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project_id=None,
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asked_via="feishu",
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message_intent=None,
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mixed_signal_part=None,
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conversation_text="无",
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context_blocks_text=(
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"[1] 来源: project\n相关度: 0.991\n内容: Enterprise Knowledge Base 项目列表\n"
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"[2] 来源: workload\n相关度: 0.884\n内容: 杨宇 当前负载 265.56% 超载\n"
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),
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system_snapshot={"team_members": []},
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user_snapshot={"projects": [{"id": 1}]},
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system_snapshot_text="{\"team_members\": []}",
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user_snapshot_text="{\"projects\": [{\"id\": 1}]}",
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relevance_max=0.0,
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)
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assert scene_key == "member_workload"
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assert "Enterprise Knowledge Base 项目列表" not in prompt
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assert "杨宇 当前负载 265.56% 超载" in prompt
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assert '"projects"' not in prompt
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def test_adaptive_rag_select_scene_prompt_ignores_negated_project_context_for_trend() -> None:
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mixin = AdaptiveRAGDeepGuardAnswerMixin()
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scene_key, prompt = mixin._select_scene_prompt(
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question="帮我看看宠物行业最新动态，重点只说消费侧和产品侧的变化，不要提项目。",
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project_id=7,
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asked_via="feishu",
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message_intent=None,
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mixed_signal_part=None,
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conversation_text="无",
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context_blocks_text="无",
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system_snapshot={"assistant_profile": {"name": "PMFlow"}},
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user_snapshot={"projects": [{"id": 1}]},
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system_snapshot_text="{}",
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user_snapshot_text="{}",
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relevance_max=0.0,
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)
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assert scene_key == "industry_trend"
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assert "当前未接入实时数据" in prompt
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assert "project_context" not in prompt
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def test_adaptive_rag_select_scene_prompt_uses_project_trend_when_project_context_explicit() -> None:
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mixin = AdaptiveRAGDeepGuardAnswerMixin()
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scene_key, prompt = mixin._select_scene_prompt(
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question="这个项目所在行业最新动态怎么样？",
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project_id=7,
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asked_via="feishu",
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message_intent=None,
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mixed_signal_part=None,
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conversation_text="无",
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context_blocks_text="无",
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system_snapshot={"assistant_profile": {"name": "PMFlow"}},
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user_snapshot={"projects": [{"id": 1}]},
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system_snapshot_text="{}",
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user_snapshot_text="{}",
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relevance_max=0.0,
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)
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assert scene_key == "external_trend"
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assert "项目上下文" in prompt
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assert "外部搜索结果" in prompt
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def test_adaptive_rag_select_scene_prompt_prefers_project_status_for_progress_questions() -> None:
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mixin = AdaptiveRAGDeepGuardAnswerMixin()
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scene_key, prompt = mixin._select_scene_prompt(
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question="这个项目最新进展怎么样？",
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project_id=7,
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asked_via="feishu",
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message_intent=None,
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mixed_signal_part=None,
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conversation_text="无",
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context_blocks_text="无",
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system_snapshot={"assistant_profile": {"name": "PMFlow"}},
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user_snapshot={"projects": [{"id": 1}]},
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system_snapshot_text="{}",
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user_snapshot_text="{}",
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relevance_max=0.0,
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query_type="status",
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)
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assert scene_key == "project_status"
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assert "项目状态分析助手" in prompt
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assert "完成率" in prompt
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assert "当前阶段" in prompt
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def test_feishu_qa_prompts_prefer_professional_answer_style() -> None:
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assert "先给结论" in PROMPT_FEISHU_DIRECT_QA
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assert "信息不足，缺少" in PROMPT_FEISHU_DIRECT_QA
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assert "适合飞书消息阅读" in PROMPT_FEISHU_DIRECT_QA
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assert "先回答问题部分" in PROMPT_FEISHU_MIXED_QA
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assert "[已收到需求]" in PROMPT_FEISHU_MIXED_QA
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assert "专业" in PROMPT_FEISHU_MIXED_QA
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assert "XXXX年" not in PROMPT_EXTERNAL_TREND_QA
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assert "通用行业认知" in PROMPT_EXTERNAL_TREND_QA
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assert "项目状态分析助手" in PROMPT_PROJECT_STATUS_QA
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def test_feishu_reply_llm_fallback_is_failure_oriented() -> None:
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reply_text = FeishuReplyLLMCoreMixin._fallback_reply_text(
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{
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"status": "captured",
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"classification": "project",
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}
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)
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assert "当前回复" in reply_text
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assert "已收到需求并完成初步识别" not in reply_text
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assert "已入库处理" not in reply_text
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