Medical Calculator MCP Service

import asyncio import json import sys import os from fastmcp import Client sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) from config import MCP_SERVER_URL async def test_ldl_cholesterol_calculator(client): """测试 LDL 胆固醇计算器的各种功能和单位转换""" def print_header(): print("\n" + "=" * 60) print("LDL 胆固醇计算器测试套件") print("=" * 60) def print_test_case(i, test_case): print(f"\n测试 {i:2d} | {test_case['name']}") print(f"- {test_case['description']}") print(f"- 输入参数: {test_case['params']}") def print_validation_result(expected, actual, errors=None, warnings=None): if expected == actual: status = "✅ 通过" else: status = "❌ 失败" expected_text = "有效" if expected else "无效" actual_text = "有效" if actual else "无效" print(f"- 验证结果: {status} (期望: {expected_text}, 实际: {actual_text})") if errors: print(f"- ⚠️ 错误: {errors}") if warnings: print(f"- ⚠️ 警告: {warnings}") def print_calculation_result(data, expected_value=None, lower_limit=None, upper_limit=None): """打印完整的计算结果""" ldl_value = data.get("value", "N/A") unit = data.get("unit", "") explanation = data.get("explanation", "") metadata = data.get("metadata", {}) warnings = data.get("warnings", []) # 基本结果 print(f"- LDL 值: {ldl_value} {unit}") # 期望值和范围检查 if expected_value is not None: print(f"- 期望值: {expected_value} {unit}") if lower_limit is not None and upper_limit is not None: print(f"- 期望范围: {lower_limit} - {upper_limit} {unit}") if isinstance(ldl_value, (int, float)) and lower_limit <= ldl_value <= upper_limit: print("- ✅ 结果在期望范围内") else: print("- ❌ 结果超出期望范围") # 元数据 if metadata: total_cholesterol = metadata.get("total_cholesterol") hdl_cholesterol = metadata.get("hdl_cholesterol") triglycerides = metadata.get("triglycerides") clinical_note = metadata.get("clinical_note", "N/A") if total_cholesterol: print(f"- 总胆固醇: {total_cholesterol} mg/dL") if hdl_cholesterol: print(f"- HDL胆固醇: {hdl_cholesterol} mg/dL") if triglycerides: print(f"- 甘油三酯: {triglycerides} mg/dL") if clinical_note: print(f"- 临床意义: {clinical_note}") # 警告信息 if warnings: for warning in warnings: print(f"- ⚠️ 警告: {warning}") # 详细解释（截取前几行显示） if explanation: lines = explanation.split('\n')[:3] print(f"- 解释: {' '.join(lines)}") def print_test_result(i, passed, error_msg=None): if passed: status = "✅ 通过" else: status = "❌ 失败" print(f"- 测试结果: {status}") if error_msg: print(f"- 错误信息: {error_msg}") print("-" * 60) def print_summary(total, passed, failed): print(f"\n测试总结:") print(f" 总测试数: {total}") print(f" 通过数: {passed}") print(f" 失败数: {failed}") print(f" 成功率: {(passed/total*100):.1f}%") if failed == 0: print("\n✅ 所有测试都通过了！LDL 胆固醇计算器工作正常。") else: print(f"\n❌ {failed} 个测试失败，请检查实现。") print("\n测试覆盖范围:") features = [ "Friedewald 公式计算", "多种单位支持 (mg/dL, mmol/L)", "参数验证", "临床分类", "错误处理", "边界测试", "甘油三酯高值警告", ] for feature in features: print(f" - {feature}") def convert_mmol_to_mgdl(value, cholesterol_type): """将 mmol/L 转换为 mg/dL - 使用更精确的转换系数""" if cholesterol_type == "cholesterol": # 胆固醇: 1 mmol/L = 38.66 mg/dL (更接近标准值) return value * 38.66 elif cholesterol_type == "triglycerides": # 甘油三酯: 1 mmol/L = 88.50 mg/dL (调整后的系数) return value * 88.50 return value def map_parameters(params): """映射数据文件中的参数名到计算器期望的参数名，保持原始单位""" mapped_params = {} for key, value in params.items(): if key == "Total cholesterol": mapped_params["total_cholesterol"] = value elif key == "high-density lipoprotein cholesterol": mapped_params["hdl_cholesterol"] = value elif key == "Triglycerides": mapped_params["triglycerides"] = value return mapped_params # Test statistics total_tests = 0 passed_tests = 0 # Test cases from data file - 真实测试数据 test_cases_from_data = [ { "name": "Standard case 1", "params": {"Total cholesterol": [170.0, "mg/dL"], "high-density lipoprotein cholesterol": [51.0, "mg/dL"], "Triglycerides": [98.0, "mg/dL"]}, "expected_valid": True, "expected_value": 99.4, "lower_limit": 94.43, "upper_limit": 104.37, "description": "标准案例 1 - 来自数据文件", }, { "name": "Standard case 2", "params": {"high-density lipoprotein cholesterol": [32.0, "mg/dL"], "Triglycerides": [88.0, "mg/dL"], "Total cholesterol": [145.0, "mg/dL"]}, "expected_valid": True, "expected_value": 95.4, "lower_limit": 90.63, "upper_limit": 100.17, "description": "标准案例 2 - 来自数据文件", }, { "name": "mmol/L units case", "params": {"Total cholesterol": [4.6, "mmol/L"], "high-density lipoprotein cholesterol": [0.8, "mmol/L"], "Triglycerides": [3.9, "mmol/L"]}, "expected_valid": True, "expected_value": 93.5, "lower_limit": 88.825, "upper_limit": 98.175, "description": "mmol/L 单位测试 - 来自数据文件", }, { "name": "Normal LDL case", "params": {"Total cholesterol": [167.0, "mg/dL"], "high-density lipoprotein cholesterol": [42.0, "mg/dL"], "Triglycerides": [77.0, "mg/dL"]}, "expected_valid": True, "expected_value": 109.6, "lower_limit": 104.12, "upper_limit": 115.08, "description": "正常 LDL 案例 - 来自数据文件", }, { "name": "Low LDL case", "params": {"high-density lipoprotein cholesterol": [0.57, "mmol/L"], "Triglycerides": [2.28, "mmol/L"], "Total cholesterol": [2.86, "mmol/L"]}, "expected_valid": True, "expected_value": 59.54, "lower_limit": 56.563, "upper_limit": 62.517, "description": "低 LDL 案例 (mmol/L) - 来自数据文件", }, { "name": "Very low LDL case", "params": {"high-density lipoprotein cholesterol": [37.44, "mg/dL"], "Triglycerides": [20.7, "mg/dL"], "Total cholesterol": [92.16, "mg/dL"]}, "expected_valid": True, "expected_value": 50.58, "lower_limit": 48.051, "upper_limit": 53.109, "description": "极低 LDL 案例 - 来自数据文件", }, { "name": "High LDL case", "params": {"high-density lipoprotein cholesterol": [55.0, "mg/dL"], "Triglycerides": [100.0, "mg/dL"], "Total cholesterol": [315.0, "mg/dL"]}, "expected_valid": True, "expected_value": 240.0, "lower_limit": 228.0, "upper_limit": 252.0, "description": "高 LDL 案例 - 来自数据文件", }, { "name": "High triglycerides case", "params": {"Total cholesterol": [208.0, "mg/dL"], "Triglycerides": [207.0, "mg/dL"], "high-density lipoprotein cholesterol": [46.0, "mg/dL"]}, "expected_valid": True, "expected_value": 120.6, "lower_limit": 114.57, "upper_limit": 126.63, "description": "高甘油三酯案例 - 来自数据文件", }, { "name": "Moderate triglycerides case", "params": {"high-density lipoprotein cholesterol": [36.0, "mg/dL"], "Triglycerides": [197.0, "mg/dL"], "Total cholesterol": [121.0, "mg/dL"]}, "expected_valid": True, "expected_value": 45.6, "lower_limit": 43.32, "upper_limit": 47.88, "description": "中等甘油三酯案例 - 来自数据文件", }, { "name": "Very high LDL case", "params": {"Total cholesterol": [335.0, "mg/dL"], "high-density lipoprotein cholesterol": [45.0, "mg/dL"], "Triglycerides": [211.0, "mg/dL"]}, "expected_valid": True, "expected_value": 247.8, "lower_limit": 235.41, "upper_limit": 260.19, "description": "极高 LDL 案例 - 来自数据文件", } ] # Additional validation test cases additional_test_cases = [ { "name": "Very low total cholesterol (edge case)", "params": {"total_cholesterol": 30, "hdl_cholesterol": 40, "triglycerides": 100}, "expected_valid": False, "description": "总胆固醇过低（边界外）", }, { "name": "Very low HDL cholesterol (edge case)", "params": {"total_cholesterol": 200, "hdl_cholesterol": 5, "triglycerides": 100}, "expected_valid": False, "description": "HDL胆固醇过低（边界外）", }, { "name": "Invalid triglycerides (too high)", "params": {"total_cholesterol": 200, "hdl_cholesterol": 40, "triglycerides": 1200}, "expected_valid": False, "description": "无效甘油三酯（过高）", }, { "name": "High triglycerides with warning", "params": {"total_cholesterol": 250, "hdl_cholesterol": 45, "triglycerides": 450}, "expected_valid": True, "description": "高甘油三酯警告案例（>400，应该计算但带警告）", } ] print_header() # Execute test cases from data all_test_cases = test_cases_from_data + additional_test_cases for i, test_case in enumerate(all_test_cases, 1): total_tests += 1 test_passed = True error_msg = None print_test_case(i, test_case) # 映射参数（如果需要） if "params" in test_case and any(isinstance(v, list) for v in test_case["params"].values()): # 来自数据文件的测试案例，需要映射参数名 mapped_params = map_parameters(test_case["params"]) else: # 额外的验证测试案例，直接使用 mapped_params = test_case["params"] # Calculation test try: calc_result = await client.call_tool( "calculate", { "calculator_id": 44, "parameters": mapped_params, }, ) # 使用 structured_content 或 data 属性获取实际数据 calc_data = calc_result.structured_content or calc_result.data or {} if isinstance(calc_data, dict) and calc_data.get("success") and "result" in calc_data: # 成功计算 data = calc_data["result"] expected_value = test_case.get("expected_value") lower_limit = test_case.get("lower_limit") upper_limit = test_case.get("upper_limit") print_calculation_result(data, expected_value, lower_limit, upper_limit) # 检查是否符合预期 if not test_case["expected_valid"]: error_msg = "预期失败但计算成功" test_passed = False elif expected_value is not None and lower_limit is not None and upper_limit is not None: # 检查结果是否在期望范围内 ldl_value = data.get("value") if not isinstance(ldl_value, (int, float)) or not (lower_limit <= ldl_value <= upper_limit): error_msg = f"结果 {ldl_value} 不在期望范围 [{lower_limit}, {upper_limit}] 内" test_passed = False else: # 计算失败（可能是参数验证失败） error_msg_from_calc = calc_data.get("error", "未知错误") if isinstance(calc_data, dict) else str(calc_data) print(f"- 计算失败: {error_msg_from_calc}") # 检查是否符合预期 if test_case["expected_valid"]: error_msg = f"预期成功但计算失败: {error_msg_from_calc}" test_passed = False except Exception as e: error_msg = f"计算错误: {e}" print(f"- 计算错误: {e}") # 检查是否符合预期 if test_case["expected_valid"]: test_passed = False # Update statistics if test_passed: passed_tests += 1 print_test_result(i, test_passed, error_msg) print_summary(total_tests, passed_tests, total_tests - passed_tests) return passed_tests, total_tests - passed_tests async def main(): def print_header(): print("LDL 胆固醇计算器 MCP 测试") print("=" * 60) def print_connection_status(success, error=None): if success: print("✅ 成功连接到 MCP 服务器") else: print(f"❌ 连接失败: {error}") def print_overall_results(total_passed, total_failed): total_tests = total_passed + total_failed if total_tests == 0: return print("\n" + "=" * 60) print("LDL 胆固醇计算器测试结果") print("=" * 60) print(f"总测试数: {total_tests}") print(f"通过数: {total_passed}") print(f"失败数: {total_failed}") print(f"成功率: {(total_passed/total_tests*100):.1f}%") if total_failed == 0: print("\n✅ LDL 胆固醇计算器所有测试都通过了！") else: print(f"\n❌ {total_failed} 个测试失败，请检查 LDL 胆固醇计算器实现。") print_header() try: async with Client(MCP_SERVER_URL) as client: print_connection_status(True) passed, failed = await test_ldl_cholesterol_calculator(client) print_overall_results(passed, failed) except Exception as e: print_connection_status(False, str(e)) import traceback traceback.print_exc() return print("\n" + "=" * 60) print("✅ LDL 胆固醇计算器测试完成") if __name__ == "__main__": asyncio.run(main())