Medical Calculator MCP Service

# -*- coding: utf-8 -*- import asyncio import json import sys import os from fastmcp import Client # Set UTF-8 encoding for output import io sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding='utf-8') sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) from config import MCP_SERVER_URL async def test_cardiac_risk_index_calculator(client): """测试 Revised Cardiac Risk Index 计算器的各种功能""" def print_header(): print("\n" + "=" * 60) print("Revised Cardiac Risk Index 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_calculation_result(data): """打印完整的计算结果""" score = 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"- RCRI 分数: {score} {unit}") # 风险分类 if metadata: risk_category = metadata.get("risk_category", "N/A") criteria_met = metadata.get("criteria_met", {}) print(f"- 风险分类: {risk_category}") # 显示满足的标准 print("- 满足的标准:") for criterion, met in criteria_met.items(): status = "是" if met else "否" print(f" - {criterion}: {status}") # 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: explanation_lines = explanation.split('\n')[:5] print(f"- 解释: {explanation_lines[0][:100]}..." if len(explanation_lines[0]) > 100 else explanation_lines[0]) def print_test_result(i, passed): if passed: status = "✅ 通过" else: status = "❌ 失败" print(f"- 测试结果: {status}") 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！Revised Cardiac Risk Index 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 = [ "不同风险因子组合", "肌酐水平变化", "边界值测试", "参数验证", "风险分层", "错误处理", ] for feature in features: print(f" - {feature}") # Test statistics total_tests = 0 passed_tests = 0 # Test cases test_cases = [ { "name": "最低风险 (无风险因子)", "params": { "elevated_risk_surgery": False, "ischemic_heart_disease": False, "congestive_heart_failure": False, "cerebrovascular_disease": False, "pre_operative_insulin_treatment": False, "pre_operative_creatinine": 1.0 }, "expected_valid": True, "expected_score": 0, "description": "所有风险因子为假，肌酐正常", }, { "name": "单一风险因子 - 高风险手术", "params": { "elevated_risk_surgery": True, "ischemic_heart_disease": False, "congestive_heart_failure": False, "cerebrovascular_disease": False, "pre_operative_insulin_treatment": False, "pre_operative_creatinine": 1.5 }, "expected_valid": True, "expected_score": 1, "description": "仅高风险手术为真", }, { "name": "单一风险因子 - 肌酐升高", "params": { "elevated_risk_surgery": False, "ischemic_heart_disease": False, "congestive_heart_failure": False, "cerebrovascular_disease": False, "pre_operative_insulin_treatment": False, "pre_operative_creatinine": 2.5 }, "expected_valid": True, "expected_score": 1, "description": "仅肌酐>2.0 mg/dL", }, { "name": "多个风险因子", "params": { "elevated_risk_surgery": True, "ischemic_heart_disease": True, "congestive_heart_failure": False, "cerebrovascular_disease": True, "pre_operative_insulin_treatment": False, "pre_operative_creatinine": 1.8 }, "expected_valid": True, "expected_score": 3, "description": "3个风险因子为真", }, { "name": "所有风险因子", "params": { "elevated_risk_surgery": True, "ischemic_heart_disease": True, "congestive_heart_failure": True, "cerebrovascular_disease": True, "pre_operative_insulin_treatment": True, "pre_operative_creatinine": 3.0 }, "expected_valid": True, "expected_score": 6, "description": "所有风险因子为真", }, { "name": "肌酐边界值 - 正好2.0", "params": { "elevated_risk_surgery": False, "ischemic_heart_disease": False, "congestive_heart_failure": False, "cerebrovascular_disease": False, "pre_operative_insulin_treatment": False, "pre_operative_creatinine": 2.0 }, "expected_valid": True, "expected_score": 0, "description": "肌酐正好2.0 mg/dL (不应加分)", }, { "name": "肌酐边界值 - 刚超过2.0", "params": { "elevated_risk_surgery": False, "ischemic_heart_disease": False, "congestive_heart_failure": False, "cerebrovascular_disease": False, "pre_operative_insulin_treatment": False, "pre_operative_creatinine": 2.1 }, "expected_valid": True, "expected_score": 1, "description": "肌酐2.1 mg/dL (应加分)", }, { "name": "无效肌酐 - 负值", "params": { "elevated_risk_surgery": False, "ischemic_heart_disease": False, "congestive_heart_failure": False, "cerebrovascular_disease": False, "pre_operative_insulin_treatment": False, "pre_operative_creatinine": -1.0 }, "expected_valid": False, "description": "肌酐为负值 (应失败)", }, { "name": "无效肌酐 - 过高", "params": { "elevated_risk_surgery": False, "ischemic_heart_disease": False, "congestive_heart_failure": False, "cerebrovascular_disease": False, "pre_operative_insulin_treatment": False, "pre_operative_creatinine": 25.0 }, "expected_valid": False, "description": "肌酐过高 (应失败)", }, { "name": "极值测试 - 最高肌酐", "params": { "elevated_risk_surgery": True, "ischemic_heart_disease": False, "congestive_heart_failure": False, "cerebrovascular_disease": False, "pre_operative_insulin_treatment": False, "pre_operative_creatinine": 20.0 }, "expected_valid": True, "expected_score": 2, "description": "最高允许肌酐值", }, ] print_header() # Execute test cases for i, test_case in enumerate(test_cases, 1): total_tests += 1 test_passed = True print_test_case(i, test_case) # Calculation test try: calc_result = await client.call_tool( "calculate", { "calculator_id": 17, "parameters": test_case["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"] print_calculation_result(data) # 检查是否符合预期 if not test_case["expected_valid"]: print("- 错误: 预期失败但计算成功") test_passed = False elif "expected_score" in test_case: actual_score = data.get("value") expected_score = test_case["expected_score"] if actual_score != expected_score: print(f"- 错误: 分数不匹配 (期望: {expected_score}, 实际: {actual_score})") test_passed = False else: # 计算失败（可能是参数验证失败） error_msg = 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}") # 检查是否符合预期 if test_case["expected_valid"]: print("- 错误: 预期成功但计算失败") test_passed = False except Exception as 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) print_summary(total_tests, passed_tests, total_tests - passed_tests) return passed_tests, total_tests - passed_tests async def main(): def print_header(): print("Revised Cardiac Risk Index 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("Revised Cardiac Risk Index 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✅ Revised Cardiac Risk Index 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 Revised Cardiac Risk Index 计算器实现。") print_header() try: async with Client(MCP_SERVER_URL) as client: print_connection_status(True) passed, failed = await test_cardiac_risk_index_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("✅ Revised Cardiac Risk Index 计算器测试完成") if __name__ == "__main__": asyncio.run(main())