122 lines
3.8 KiB
Python
122 lines
3.8 KiB
Python
from datetime import UTC, datetime
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from app.models.entities import Conversation, ConversationMessage
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from app.services.conversations import ConversationService
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def test_conversation_message_data_reads_persisted_risk_result() -> None:
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message = ConversationMessage(
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id=10,
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conversation_id=3,
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role="assistant",
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content="已完成风险预估。",
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structured_data={
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"riskResult": {
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"subjectId": "软管新品",
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"score": 82,
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"level": "low",
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"modelVersion": "baseline-safety-v2",
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"factors": [],
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}
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},
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created_at=datetime.now(UTC),
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)
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result = ConversationService._message(message)
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assert result.role == "assistant"
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assert result.risk_result is not None
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assert result.risk_result.score == 82
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assert result.risk_result.level.value == "low"
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def test_conversation_data_includes_all_messages() -> None:
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conversation = Conversation(
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id=3,
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user_id=1,
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title="软管新品评估",
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created_at=datetime.now(UTC),
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updated_at=datetime.now(UTC),
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messages=[
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ConversationMessage(
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id=1,
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conversation_id=3,
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role="user",
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content="评估软管新品",
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created_at=datetime.now(UTC),
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),
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ConversationMessage(
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id=2,
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conversation_id=3,
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role="assistant",
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content="已完成分析",
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created_at=datetime.now(UTC),
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),
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],
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)
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result = ConversationService._data(conversation)
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assert result.message_count == 2
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assert [message.role for message in result.messages] == ["user", "assistant"]
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def test_only_explicit_risk_requests_generate_risk_cards() -> None:
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assert ConversationService._is_risk_request(
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"你好",
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{"intent": "greet", "risk_requested": False},
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) is False
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assert ConversationService._is_risk_request(
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"请只回复：AI 连通成功。",
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{"intent": "general", "risk_requested": False},
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) is False
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assert ConversationService._is_risk_request(
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"请评估这个产品的风险",
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{"intent": "assessment", "risk_requested": True},
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) is True
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def test_legacy_general_semantics_hide_old_risk_card() -> None:
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messages = [
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ConversationMessage(
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id=1,
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conversation_id=1,
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role="user",
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content="你好",
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created_at=datetime.now(UTC),
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),
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ConversationMessage(
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id=2,
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conversation_id=1,
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role="assistant",
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content="你好，我可以帮你做什么？",
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structured_data={
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"semantic": {"intent": "general"},
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"riskResult": {
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"subjectId": "误判",
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"score": 61,
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"level": "moderately_low",
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"modelVersion": "baseline-safety-v2",
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"factors": [],
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},
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},
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created_at=datetime.now(UTC),
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),
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]
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assert ConversationService._risk_result_for_message(messages, 1) is None
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assert ConversationService._is_risk_request(
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"我要做一款脱毛膏新品，100g，PE软管包装，加工厂准备使用瑞沣",
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{"intent": "general", "risk_requested": False},
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) is True
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def test_product_assessment_semantics_override_nlu_miss() -> None:
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normalized = ConversationService._normalize_semantics(
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"我要做一款脱毛膏新品，100g，PE软管包装，加工厂准备使用瑞沣",
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{"intent": "general", "risk_requested": False, "category": "脱毛膏"},
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)
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assert normalized["intent"] == "assessment"
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assert normalized["risk_requested"] is True
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