Ubuntu
120 lines
4.5 KiB
Python
120 lines
4.5 KiB
Python
#!/usr/bin/env python3
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"""
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配置加载器 - 从nanobot主配置读取模型设置
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这样当nanobot配置更改时，项目会自动跟随
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"""
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import json
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import os
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from pathlib import Path
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class ConfigLoader:
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"""配置加载器 - 优先从nanobot主配置读取"""
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def __init__(self):
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self.nanobot_config_path = Path.home() / ".nanobot" / "config.json"
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self.project_config_path = Path("/home/ubuntu/nanocode/it_automation_enhanced/config/config.json")
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def load_nanobot_config(self):
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"""加载nanobot主配置"""
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try:
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if self.nanobot_config_path.exists():
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with open(self.nanobot_config_path, 'r', encoding='utf-8') as f:
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return json.load(f)
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except Exception as e:
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print(f"警告: 无法加载nanobot配置: {e}")
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return {}
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def load_project_config(self):
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"""加载项目配置"""
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try:
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if self.project_config_path.exists():
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with open(self.project_config_path, 'r', encoding='utf-8') as f:
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return json.load(f)
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except Exception as e:
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print(f"警告: 无法加载项目配置: {e}")
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return {}
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def get_model_config(self):
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"""
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获取模型配置
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优先从nanobot配置读取，如果不存在则使用项目配置
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"""
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nanobot_config = self.load_nanobot_config()
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project_config = self.load_project_config()
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# 从nanobot配置读取默认模型设置
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nanobot_defaults = nanobot_config.get('agents', {}).get('defaults', {})
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nanobot_providers = nanobot_config.get('providers', {})
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provider_name = nanobot_defaults.get('provider', 'moonshot')
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model_name = nanobot_defaults.get('model', 'kimi-k2.5')
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# 获取该提供商的API配置
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provider_config = nanobot_providers.get(provider_name, {})
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api_key = provider_config.get('apiKey', '')
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api_base = provider_config.get('apiBase', '')
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# 构建配置字典
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config = {
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'provider': provider_name,
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'model': model_name,
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'api_key': api_key,
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'api_base': api_base,
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'max_tokens': nanobot_defaults.get('maxTokens', 8192),
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'context_window': nanobot_defaults.get('contextWindowTokens', 65536),
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'temperature': nanobot_defaults.get('temperature', 0.7),
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# 从项目配置读取提示词模板
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'translation_prompt': project_config.get(provider_name, {}).get('translation_prompt',
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"请将以下英文技术文章翻译成中文，保持技术准确性，语言自然流畅：\n\n{content}"),
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'summarization_prompt': project_config.get(provider_name, {}).get('summarization_prompt',
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"请用中文总结以下技术文章的核心内容，突出技术要点和创新点：\n\n{content}")
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}
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return config
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def get_api_endpoint(self, provider=None):
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"""获取API端点"""
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if provider is None:
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config = self.get_model_config()
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provider = config['provider']
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# 默认端点
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endpoints = {
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'moonshot': 'https://api.moonshot.cn/v1/chat/completions',
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'deepseek': 'https://api.deepseek.com/chat/completions',
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'openai': 'https://api.openai.com/v1/chat/completions',
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'azureOpenai': None, # 需要从配置读取
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}
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return endpoints.get(provider, endpoints['moonshot'])
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# 全局配置加载器实例
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_config_loader = None
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def get_config_loader():
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"""获取全局配置加载器实例"""
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global _config_loader
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if _config_loader is None:
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_config_loader = ConfigLoader()
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return _config_loader
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def get_current_model_config():
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"""获取当前模型配置的便捷函数"""
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return get_config_loader().get_model_config()
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if __name__ == "__main__":
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# 测试配置加载
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print("=== 配置加载器测试 ===")
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loader = ConfigLoader()
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config = loader.get_model_config()
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print(f"\n当前模型配置:")
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print(f" 提供商: {config['provider']}")
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print(f" 模型: {config['model']}")
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print(f" API密钥: {config['api_key'][:20]}..." if config['api_key'] else " API密钥: 未配置")
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print(f" API端点: {config['api_base']}")
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print(f" 最大Token: {config['max_tokens']}")
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print(f" 上下文窗口: {config['context_window']}")
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print(f"\nAPI调用端点: {loader.get_api_endpoint()}") |