初始化提交

settings.py

@@ -0,0 +1,97 @@
+"""持久化配置管理
+
+使用 data/settings.json 存储可通过管理面板修改的设置：
+  - proxy_target_url / proxy_api_key: 可覆盖环境变量的全局配置
+  - model_mappings: Cursor 模型名 → {upstream_model, backend, target_url, api_key}
+"""
+
+import json
+import os
+import threading
+
+from config import Config
+
+# 数据目录放在项目根目录下，便于 Docker 卷挂载
+_ROOT_DIR = os.path.dirname(os.path.abspath(__file__))
+DATA_DIR = os.path.join(_ROOT_DIR, 'data')
+SETTINGS_FILE = os.path.join(DATA_DIR, 'settings.json')
+
+_lock = threading.Lock()
+_cache = None
+
+_DEFAULTS = {
+    'proxy_target_url': '',
+    'proxy_api_key': '',
+    'model_mappings': {},
+}
+
+
+def load():
+    """从文件加载配置"""
+    global _cache
+    with _lock:
+        if os.path.exists(SETTINGS_FILE):
+            try:
+                with open(SETTINGS_FILE, 'r', encoding='utf-8') as f:
+                    _cache = {**_DEFAULTS, **json.load(f)}
+            except (json.JSONDecodeError, OSError):
+                _cache = dict(_DEFAULTS)
+        else:
+            _cache = dict(_DEFAULTS)
+    return dict(_cache)
+
+
+def save(data):
+    """保存配置到文件"""
+    global _cache
+    with _lock:
+        os.makedirs(DATA_DIR, exist_ok=True)
+        _cache = {**_DEFAULTS, **data}
+        with open(SETTINGS_FILE, 'w', encoding='utf-8') as f:
+            json.dump(_cache, f, ensure_ascii=False, indent=2)
+
+
+def get():
+    """获取当前配置（优先使用缓存）"""
+    if _cache is None:
+        return load()
+    return dict(_cache)
+
+
+def get_url():
+    """获取生效的上游 URL：配置文件优先，环境变量兜底"""
+    return get().get('proxy_target_url') or Config.PROXY_TARGET_URL
+
+
+def get_key():
+    """获取生效的 API 密钥：配置文件优先，环境变量兜底"""
+    return get().get('proxy_api_key') or Config.PROXY_API_KEY
+
+
+def resolve_model(model_name):
+    """解析模型映射，返回 {upstream_model, backend, target_url, api_key}"""
+    settings = get()
+    mappings = settings.get('model_mappings', {})
+    base_url, base_key = get_url(), get_key()
+
+    if model_name in mappings:
+        m = mappings[model_name]
+        return {
+            'upstream_model': m.get('upstream_model') or model_name,
+            'backend': m.get('backend') or _auto_detect(model_name),
+            'target_url': m.get('target_url') or base_url,
+            'api_key': m.get('api_key') or base_key,
+        }
+
+    return {
+        'upstream_model': model_name,
+        'backend': _auto_detect(model_name),
+        'target_url': base_url,
+        'api_key': base_key,
+    }
+
+
+def _auto_detect(name):
+    """根据模型名自动判断后端类型"""
+    lower = (name or '').lower()
+    return 'anthropic' if ('claude' in lower or 'anthropic' in lower) else 'openai'