#!/usr/bin/env python3
"""
配置加载器 - 从nanobot主配置读取模型设置
这样当nanobot配置更改时，项目会自动跟随
"""

import json
import os
from pathlib import Path

class ConfigLoader:
    """配置加载器 - 优先从nanobot主配置读取"""
    
    def __init__(self):
        self.nanobot_config_path = Path.home() / ".nanobot" / "config.json"
        self.project_config_path = Path("/home/ubuntu/nanocode/it_automation_enhanced/config/config.json")
        
    def load_nanobot_config(self):
        """加载nanobot主配置"""
        try:
            if self.nanobot_config_path.exists():
                with open(self.nanobot_config_path, 'r', encoding='utf-8') as f:
                    return json.load(f)
        except Exception as e:
            print(f"警告: 无法加载nanobot配置: {e}")
        return {}
    
    def load_project_config(self):
        """加载项目配置"""
        try:
            if self.project_config_path.exists():
                with open(self.project_config_path, 'r', encoding='utf-8') as f:
                    return json.load(f)
        except Exception as e:
            print(f"警告: 无法加载项目配置: {e}")
        return {}
    
    def get_model_config(self):
        """
        获取模型配置
        优先从nanobot配置读取，如果不存在则使用项目配置
        """
        nanobot_config = self.load_nanobot_config()
        project_config = self.load_project_config()
        
        # 从nanobot配置读取默认模型设置
        nanobot_defaults = nanobot_config.get('agents', {}).get('defaults', {})
        nanobot_providers = nanobot_config.get('providers', {})
        
        provider_name = nanobot_defaults.get('provider', 'moonshot')
        model_name = nanobot_defaults.get('model', 'kimi-k2.5')
        
        # 获取该提供商的API配置
        provider_config = nanobot_providers.get(provider_name, {})
        api_key = provider_config.get('apiKey', '')
        api_base = provider_config.get('apiBase', '')
        
        # 构建配置字典
        config = {
            'provider': provider_name,
            'model': model_name,
            'api_key': api_key,
            'api_base': api_base,
            'max_tokens': nanobot_defaults.get('maxTokens', 8192),
            'context_window': nanobot_defaults.get('contextWindowTokens', 65536),
            'temperature': nanobot_defaults.get('temperature', 0.7),
            # 从项目配置读取提示词模板
            'translation_prompt': project_config.get(provider_name, {}).get('translation_prompt', 
                "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}"),
            'summarization_prompt': project_config.get(provider_name, {}).get('summarization_prompt',
                "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}")
        }
        
        return config
    
    def get_api_endpoint(self, provider=None):
        """获取API端点"""
        if provider is None:
            config = self.get_model_config()
            provider = config['provider']
        
        # 默认端点
        endpoints = {
            'moonshot': 'https://api.moonshot.cn/v1/chat/completions',
            'deepseek': 'https://api.deepseek.com/chat/completions',
            'openai': 'https://api.openai.com/v1/chat/completions',
            'azureOpenai': None,  # 需要从配置读取
        }
        
        return endpoints.get(provider, endpoints['moonshot'])

# 全局配置加载器实例
_config_loader = None

def get_config_loader():
    """获取全局配置加载器实例"""
    global _config_loader
    if _config_loader is None:
        _config_loader = ConfigLoader()
    return _config_loader

def get_current_model_config():
    """获取当前模型配置的便捷函数"""
    return get_config_loader().get_model_config()

if __name__ == "__main__":
    # 测试配置加载
    print("=== 配置加载器测试 ===")
    loader = ConfigLoader()
    config = loader.get_model_config()
    
    print(f"\n当前模型配置:")
    print(f"  提供商: {config['provider']}")
    print(f"  模型: {config['model']}")
    print(f"  API密钥: {config['api_key'][:20]}..." if config['api_key'] else "  API密钥: 未配置")
    print(f"  API端点: {config['api_base']}")
    print(f"  最大Token: {config['max_tokens']}")
    print(f"  上下文窗口: {config['context_window']}")
    
    print(f"\nAPI调用端点: {loader.get_api_endpoint()}")