121 lines
3.7 KiB
Python
121 lines
3.7 KiB
Python
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import json
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import subprocess
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import tempfile
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import os
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from json_openai import llm_format_text, EXTRACT_OUNTLINE_SYSTEM_PROMPT
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def create_temp_test_file(markdown_content):
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"""创建临时的TypeScript测试文件"""
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test_content = f'''import {{ markdownToJSON }} from './markdownToJSON.js';
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// AI生成的Markdown内容
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const markdown = `{markdown_content}`;
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// 转换并输出结果
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const result = markdownToJSON(markdown);
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console.log('转换结果:');
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console.log(JSON.stringify(result, null, 2));
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'''
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with open('temp_test_markdown.ts', 'w', encoding='utf-8') as f:
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f.write(test_content)
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return 'temp_test_markdown.ts'
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def run_typescript_converter(test_file):
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"""编译并运行TypeScript测试文件"""
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try:
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# 编译TypeScript文件
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compile_result = subprocess.run([
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'npx', 'tsc', test_file, '--outDir', 'dist', '--target', 'ES2020', '--module', 'ES2020'
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], capture_output=True, text=True)
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if compile_result.returncode != 0:
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print(f"编译错误: {compile_result.stderr}")
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return None
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# 运行编译后的JavaScript文件
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js_file = test_file.replace('.ts', '.js').replace('./', 'dist/')
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run_result = subprocess.run([
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'node', js_file
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], capture_output=True, text=True)
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if run_result.returncode == 0:
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return run_result.stdout
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else:
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print(f"运行错误: {run_result.stderr}")
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return None
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except Exception as e:
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print(f"执行TypeScript转换时出错: {e}")
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return None
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def main():
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# 测试配置
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model = "glm-4.5"
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base_url = "https://open.bigmodel.cn/api/paas/v4/"
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api_key = "ce39bdd4fcf34ec0aec75072bc9ff988.hAp7HZTVUwy7vImn"
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# 测试内容
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test_content = """
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人工智能的发展历程
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早期发展
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人工智能的概念最早可以追溯到1950年代。图灵测试的提出标志着AI研究的开始。
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图灵测试
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图灵测试是判断机器是否具有智能的重要标准。
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现代发展
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近年来，深度学习技术的突破推动了AI的快速发展。
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深度学习
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深度学习通过神经网络模拟人脑的工作方式。
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"""
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# 构建消息
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messages = [
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{"role": "system", "content": EXTRACT_OUNTLINE_SYSTEM_PROMPT},
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{"role": "user", "content": f"请分析以下文章内容并转换为Markdown格式：\n\n{test_content}"}
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]
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print("=== 第一步：AI处理生成Markdown ===")
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try:
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markdown_result = llm_format_text(model, base_url, api_key, messages, 2000)
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print("AI生成的Markdown:")
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print(markdown_result)
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print("\n" + "="*50 + "\n")
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print("=== 第二步：Markdown转换为JSON ===")
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# 创建临时测试文件
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test_file = create_temp_test_file(markdown_result)
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# 运行TypeScript转换
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json_result = run_typescript_converter(test_file)
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if json_result:
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print("转换后的JSON结构:")
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print(json_result)
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else:
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print("转换失败")
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# 清理临时文件
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try:
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os.remove(test_file)
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js_file = test_file.replace('.ts', '.js').replace('./', 'dist/')
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if os.path.exists(js_file):
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os.remove(js_file)
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except:
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pass
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except Exception as e:
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print(f"处理失败: {e}")
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print("可能的原因:")
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print("1. API密钥无效或过期")
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print("2. 网络连接问题")
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print("3. API服务不可用")
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print("4. 模型名称不正确")
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if __name__ == "__main__":
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main()
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