刘金宝
88 lines
3.1 KiB
Python
88 lines
3.1 KiB
Python
import sys
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import os
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from pathlib import Path
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os.environ.setdefault("DATABASE_URL", "sqlite:///./storage/test_core.db")
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os.environ.setdefault("RUNTIME_MEMORY_BACKEND", "memory")
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os.environ.setdefault("LLM_MOCK_ENABLED", "true")
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sys.path.insert(0, str(Path(__file__).resolve().parents[1]))
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from app.agents.scoring_agent import ScoringAgent
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from app.agents.hint_agent import HintAgent
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from app.agents.llm_adapter import OpenAICompatibleLLMClient
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from app.core.config import settings
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from app.services.runtime_memory import InMemoryRuntimeMemoryService
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def test_runtime_memory_lifecycle() -> None:
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"""短期 memory：验证创建、写入、读取和释放流程。"""
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memory = InMemoryRuntimeMemoryService()
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memory.create("test-memory", "开场白")
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memory.add_message("test-memory", "doctor", "孩子发热几天？")
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assert memory.has_doctor_message("test-memory") is True
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assert len(memory.get_messages("test-memory")) == 2
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memory.release("test-memory")
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assert memory.get_messages("test-memory") == []
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def test_score_convert_to_five_point() -> None:
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"""评分转换：验证百分制到五分制的结构转换。"""
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agent = ScoringAgent()
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result = agent._convert_to_five_point(
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{
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"score_type": "percentage",
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"total_score": 80,
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"dimension_scores": [{"dimension": "信息获取", "score": 20, "max_score": 25, "comment": "ok"}],
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}
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)
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assert result["score_type"] == "five_point"
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assert result["total_score"] == 4.0
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assert result["dimension_scores"][0]["max_score"] == 5
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def test_public_settings() -> None:
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"""配置输出：验证 Demo 前端可读取功能开关。"""
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public = settings.as_public_dict()
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assert "score_types" in public
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assert "percentage" in public["score_types"]
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def test_reasoning_effort_disabled_when_thinking_off() -> None:
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"""LLM 参数构造：thinking 关闭时不发送 reasoning_effort，避免 reason 测试流式 400。"""
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client = OpenAICompatibleLLMClient()
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payload = client._build_payload(
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model="deepseek-v4-pro",
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messages=[{"role": "user", "content": "hello"}],
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stream=True,
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thinking_enabled=False,
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reasoning_effort="low",
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max_tokens=128,
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)
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assert "reasoning_effort" not in payload
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def test_hint_agent_invalid_json_fallback() -> None:
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"""新手提示：验证模型输出结构不匹配时使用稳定 fallback。"""
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agent = HintAgent()
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payload = {
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"case": {
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"chief_complaint": "发热、咳嗽4天，喘息1天",
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"key_exams": ["blood_routine", "chest_xray"],
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},
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"ordered_results": [],
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}
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result = agent._normalize_output({"score_type": "percentage"}, payload)
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assert result["hints"]
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assert result["next_questions"]
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assert result["recommended_orders"]
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if __name__ == "__main__":
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test_runtime_memory_lifecycle()
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test_score_convert_to_five_point()
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test_public_settings()
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test_reasoning_effort_disabled_when_thinking_off()
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test_hint_agent_invalid_json_fallback()
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print("core logic tests passed")
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