142 lines
5.0 KiB
Python
142 lines
5.0 KiB
Python
"""
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配置持久化：将用户在界面中设置的 API Key 等配置保存到 data/settings.json，
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服务重启后自动恢复，不再每次重启都丢失 Key。
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"""
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import json
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import os
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import logging
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logger = logging.getLogger(__name__)
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_SETTINGS_PATH: str = '' # 由 app.py 初始化时注入
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def init(settings_path: str):
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global _SETTINGS_PATH
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_SETTINGS_PATH = settings_path
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def load(cfg) -> None:
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"""从 settings.json 加载配置，覆盖 config 模块中的默认值"""
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if not _SETTINGS_PATH or not os.path.exists(_SETTINGS_PATH):
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_apply_env_overrides(cfg)
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return
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try:
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with open(_SETTINGS_PATH, 'r', encoding='utf-8') as f:
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data = json.load(f)
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_apply(cfg, data)
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_apply_env_overrides(cfg)
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logger.info(f'已从 {_SETTINGS_PATH} 恢复配置，当前 provider={cfg.MODEL_PROVIDER}')
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except Exception as e:
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logger.warning(f'加载配置文件失败: {e}')
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_apply_env_overrides(cfg)
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_ENV_API_KEYS = (
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('QWEN_API_KEY', 'QWEN_API_KEY'),
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('OPENAI_API_KEY', 'OPENAI_API_KEY'),
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('DEEPSEEK_API_KEY', 'DEEPSEEK_API_KEY'),
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('DOUBAO_API_KEY', 'DOUBAO_API_KEY'),
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('KIMI_API_KEY', 'KIMI_API_KEY'),
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)
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def _apply_env_overrides(cfg) -> None:
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"""环境变量中的 API Key 优先于 settings.json（便于 Docker / 本机 .env 注入）。"""
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mp = os.environ.get('MODEL_PROVIDER')
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if mp and isinstance(mp, str) and mp.strip():
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cfg.MODEL_PROVIDER = mp.strip()
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for env_name, attr in _ENV_API_KEYS:
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val = os.environ.get(env_name)
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if val and isinstance(val, str) and not val.startswith('sk-your'):
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setattr(cfg, attr, val.strip())
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def save(cfg) -> None:
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"""将当前 config 模块的关键配置写入 settings.json"""
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if not _SETTINGS_PATH:
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return
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data = {
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'model_provider': cfg.MODEL_PROVIDER,
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'qwen_api_key': cfg.QWEN_API_KEY,
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'qwen_model': cfg.QWEN_MODEL,
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'qwen_base_url': cfg.QWEN_BASE_URL,
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'openai_api_key': cfg.OPENAI_API_KEY,
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'openai_model': cfg.OPENAI_MODEL,
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'openai_base_url': cfg.OPENAI_BASE_URL,
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'deepseek_api_key': cfg.DEEPSEEK_API_KEY,
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'deepseek_model': cfg.DEEPSEEK_MODEL,
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'deepseek_base_url': cfg.DEEPSEEK_BASE_URL,
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'ollama_base_url': cfg.OLLAMA_BASE_URL,
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'ollama_model': cfg.OLLAMA_MODEL,
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'doubao_api_key': cfg.DOUBAO_API_KEY,
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'doubao_model': cfg.DOUBAO_MODEL,
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'doubao_base_url': cfg.DOUBAO_BASE_URL,
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'kimi_api_key': cfg.KIMI_API_KEY,
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'kimi_model': cfg.KIMI_MODEL,
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'kimi_base_url': cfg.KIMI_BASE_URL,
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'max_concurrent': cfg.MAX_CONCURRENT_SECTIONS,
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'content_volume': cfg.CONTENT_VOLUME,
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'target_pages': getattr(cfg, 'TARGET_PAGES', 0),
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'page_char_estimate': getattr(cfg, 'PAGE_CHAR_ESTIMATE', 700),
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}
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try:
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os.makedirs(os.path.dirname(_SETTINGS_PATH), exist_ok=True)
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with open(_SETTINGS_PATH, 'w', encoding='utf-8') as f:
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json.dump(data, f, ensure_ascii=False, indent=2)
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except Exception as e:
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logger.warning(f'保存配置文件失败: {e}')
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def _apply(cfg, data: dict) -> None:
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"""将 dict 中的值安全地写回 config 模块"""
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str_fields = {
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'model_provider': 'MODEL_PROVIDER',
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'qwen_api_key': 'QWEN_API_KEY',
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'qwen_model': 'QWEN_MODEL',
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'qwen_base_url': 'QWEN_BASE_URL',
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'openai_api_key': 'OPENAI_API_KEY',
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'openai_model': 'OPENAI_MODEL',
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'openai_base_url': 'OPENAI_BASE_URL',
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'deepseek_api_key': 'DEEPSEEK_API_KEY',
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'deepseek_model': 'DEEPSEEK_MODEL',
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'deepseek_base_url': 'DEEPSEEK_BASE_URL',
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'ollama_base_url': 'OLLAMA_BASE_URL',
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'ollama_model': 'OLLAMA_MODEL',
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'doubao_api_key': 'DOUBAO_API_KEY',
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'doubao_model': 'DOUBAO_MODEL',
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'doubao_base_url': 'DOUBAO_BASE_URL',
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'kimi_api_key': 'KIMI_API_KEY',
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'kimi_model': 'KIMI_MODEL',
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'kimi_base_url': 'KIMI_BASE_URL',
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}
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for key, attr in str_fields.items():
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val = data.get(key)
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if val and isinstance(val, str):
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setattr(cfg, attr, val)
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if 'max_concurrent' in data:
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try:
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v = int(data['max_concurrent'])
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cfg.MAX_CONCURRENT_SECTIONS = max(1, min(v, 20))
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except (ValueError, TypeError):
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pass
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valid_volumes = ('concise', 'standard', 'detailed', 'full')
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vol = data.get('content_volume')
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if vol and vol in valid_volumes:
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cfg.CONTENT_VOLUME = vol
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if 'target_pages' in data:
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try:
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cfg.TARGET_PAGES = max(0, int(data['target_pages']))
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except (ValueError, TypeError):
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pass
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if 'page_char_estimate' in data:
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try:
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cfg.PAGE_CHAR_ESTIMATE = max(300, min(3000, int(data['page_char_estimate'])))
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except (ValueError, TypeError):
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pass
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