73 lines
2.1 KiB
Python
73 lines
2.1 KiB
Python
#!/usr/bin/env python3
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"""
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QwenPaw 调用 MetaGPT 干活 — 集成示例
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使用时确保已安装：pip install metagpt
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"""
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import subprocess
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# ============================================
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# 方式一：Shell 调用（最简单）
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# ============================================
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def call_metagpt_cli(requirement: str):
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"""QwenPaw 通过 Shell 直接调 MetaGPT CLI"""
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cmd = f'metagpt "{requirement}"'
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print(f"🚀 QwenPaw → MetaGPT: {cmd}")
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result = subprocess.run(cmd, shell=True, capture_output=True, text=True, timeout=300)
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print(f"✅ 输出:\n{result.stdout[:500]}")
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return result
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# ============================================
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# 方式二：Python SDK 调用（更灵活）
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# ============================================
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def call_metagpt_sdk(requirement: str):
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"""QwenPaw 通过 Python SDK 调 MetaGPT，拿到结构化结果"""
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from metagpt.software_company import generate_repo
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print(f"🚀 QwenPaw → MetaGPT SDK: {requirement}")
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repo = generate_repo(requirement)
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print(f"✅ 项目生成成功! 仓库: {repo}")
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return repo
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# ============================================
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# 方式三：QwenPaw + MetaGPT + ECC 全套流水线
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# ============================================
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def full_pipeline(requirement: str):
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"""
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QwenPaw 编排完整流水线:
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1. MetaGPT 从需求生成项目
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2. ECC 代码审查
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3. ECC 安全扫描
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4. ECC 测试
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5. ECC 部署
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"""
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print("=" * 60)
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print("🔥 QwenPaw 编排完整开发流水线")
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print("=" * 60)
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print("\n[1/5] MetaGPT 生成项目...")
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# repo = call_metagpt_sdk(requirement)
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print("\n[2/5] ECC 代码审查...")
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# ecc_code_review(...)
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print("\n[3/5] ECC 安全扫描...")
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# ecc_security_scan(...)
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print("\n[4/5] ECC 自动化测试...")
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# ecc_test(...)
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print("\n[5/5] ECC 部署上线...")
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# ecc_deploy(...)
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print("\n✅ 流水线完成!")
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if __name__ == "__main__":
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requirement = "用 Python 创建一个命令行 TODO 应用，支持增删改查，数据存 JSON"
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print(f"📝 需求: {requirement}\n")
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call_metagpt_cli(requirement)
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