81 lines
2.5 KiB
Python
81 lines
2.5 KiB
Python
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import json
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import subprocess
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import sys
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from json_openai import llm_format_text, EXTRACT_OUNTLINE_SYSTEM_PROMPT
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def run_typescript_converter(markdown_content):
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"""运行TypeScript的markdownToJSON函数"""
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try:
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# 创建临时文件存储markdown内容
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with open('temp_markdown.md', 'w', encoding='utf-8') as f:
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f.write(markdown_content)
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# 运行TypeScript转换器
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result = subprocess.run([
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'node', 'dist/test_markdown.js'
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], capture_output=True, text=True, input=markdown_content)
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if result.returncode == 0:
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return result.stdout
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else:
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print(f"TypeScript转换错误: {result.stderr}")
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return None
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except Exception as e:
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print(f"运行TypeScript转换器时出错: {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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json_result = run_typescript_converter(markdown_result)
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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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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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