222 lines
6.1 KiB
Python
222 lines
6.1 KiB
Python
"""
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QA Agent - 测试工程师智能体
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负责测试用例创建和 TDD 实践
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"""
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from autogen import AssistantAgent
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from typing import Dict, Any, Optional
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import os
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from pathlib import Path
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from config.llm_config import get_agent_llm_config, QA_PROMPT
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class QAAgent:
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"""测试工程师 Agent，负责生成测试用例和测试脚本"""
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def __init__(self, llm_config: Optional[Dict] = None):
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"""
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初始化 QA Agent
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Args:
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llm_config: LLM 配置
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"""
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self.llm_config = llm_config or get_agent_llm_config("QA_Agent")
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self.agent = AssistantAgent(
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name="QA_Agent",
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system_message=QA_PROMPT,
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llm_config=self.llm_config,
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description="资深测试工程师，专注于自动化测试和 TDD 实践",
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human_input_mode="NEVER"
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)
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self.workspace_dir = Path("workspace")
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self.workspace_dir.mkdir(exist_ok=True)
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def generate_test_cases(self, srs_content: str) -> str:
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"""
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根据 SRS 生成测试用例
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Args:
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srs_content: SRS 文档内容
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Returns:
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生成的测试用例内容
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"""
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prompt = f"""
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请根据以下 SRS 文档生成完整的测试用例：
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{self._truncate(srs_content, 3000)}
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请生成：
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1. Pytest 测试脚本（包含完整的测试函数）
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2. BDD 风格的测试场景描述
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3. 测试数据准备
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4. 预期结果验证
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确保遵循 TDD 原则，测试先于代码存在。
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"""
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response = self.agent.generate_reply(
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messages=[{"role": "user", "content": prompt}]
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)
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test_content = response if isinstance(response, str) else str(response)
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# 保存测试文件
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test_file = self.workspace_dir / "test_battery_health.py"
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with open(test_file, 'w', encoding='utf-8') as f:
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f.write(test_content)
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print(f"✅ 测试用例已生成：{test_file}")
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return test_content
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def create_bdd_scenarios(self, srs_content: str) -> str:
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"""
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创建 BDD 风格的测试场景
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Args:
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srs_content: SRS 文档内容
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Returns:
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BDD 测试场景描述
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"""
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prompt = f"""
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请根据 SRS 创建 BDD (Behavior-Driven Development) 测试场景：
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{self._truncate(srs_content, 2000)}
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请使用 Given-When-Then 格式描述每个测试场景：
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- Feature: 功能描述
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- Scenario: 场景描述
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- Given: 前置条件
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- When: 操作
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- Then: 预期结果
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输出为 Markdown 格式。
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"""
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response = self.agent.generate_reply(
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messages=[{"role": "user", "content": prompt}]
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)
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bdd_content = response if isinstance(response, str) else str(response)
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# 保存 BDD 场景文件
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bdd_file = self.workspace_dir / "bdd_scenarios.md"
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with open(bdd_file, 'w', encoding='utf-8') as f:
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f.write(bdd_content)
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print(f"✅ BDD 场景已生成：{bdd_file}")
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return bdd_content
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def analyze_test_coverage(self, test_code: str, srs_content: str) -> Dict[str, Any]:
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"""
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分析测试覆盖率
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Args:
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test_code: 测试代码
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srs_content: SRS 文档
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Returns:
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覆盖率分析报告
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"""
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prompt = f"""
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请分析以下测试代码对 SRS 需求的覆盖情况：
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SRS 需求：
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{self._truncate(srs_content, 1500)}
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测试代码：
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{self._truncate(test_code, 2000)}
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请输出：
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1. 已覆盖的需求列表
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2. 未覆盖的需求列表
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3. 覆盖率百分比
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4. 改进建议
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"""
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response = self.agent.generate_reply(
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messages=[{"role": "user", "content": prompt}]
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)
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coverage_report = response if isinstance(response, str) else str(response)
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# 保存报告
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report_file = self.workspace_dir / "coverage_report.md"
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with open(report_file, 'w', encoding='utf-8') as f:
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f.write(coverage_report)
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return {"report": coverage_report, "file": str(report_file)}
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def _truncate(self, text: str, max_length: int) -> str:
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"""截断文本以避免超出上下文限制"""
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if len(text) <= max_length:
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return text
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return text[:max_length] + "... [内容已截断]"
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def run_tests(self, test_file_pattern: str = "test_*.py") -> Dict[str, Any]:
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"""
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执行测试（需要实际运行 pytest）
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Args:
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test_file_pattern: 测试文件模式
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Returns:
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测试结果字典
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"""
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import subprocess
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import sys
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try:
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# 使用 pytest 执行测试
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result = subprocess.run(
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[sys.executable, "-m", "pytest",
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str(self.workspace_dir / test_file_pattern),
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"-v", "--tb=short"],
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capture_output=True,
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text=True,
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timeout=60
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)
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return {
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"success": result.returncode == 0,
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"stdout": result.stdout,
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"stderr": result.stderr,
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"returncode": result.returncode
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}
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except subprocess.TimeoutExpired:
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return {
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"success": False,
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"error": "测试执行超时"
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}
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except Exception as e:
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return {
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"success": False,
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"error": str(e)
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}
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def create_qa_agent(llm_config: Optional[Dict] = None) -> AssistantAgent:
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"""
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创建 QA Agent（AutoGen 原生格式）
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Args:
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llm_config: LLM 配置
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Returns:
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AutoGen AssistantAgent 实例
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"""
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config = llm_config or get_agent_llm_config("QA_Agent")
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agent = AssistantAgent(
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name="QA_Agent",
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system_message=QA_PROMPT,
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llm_config=config,
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description="资深测试工程师",
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human_input_mode="NEVER"
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)
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return agent
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