feat：添加模型列表获取API路由

src/webui/model_routes.py

@@ -0,0 +1,242 @@
+"""
+模型列表获取API路由
+
+提供从各个 AI 厂商 API 获取可用模型列表的代理接口
+"""
+
+import os
+import httpx
+from fastapi import APIRouter, HTTPException, Query
+from typing import Optional
+import tomlkit
+
+from src.common.logger import get_logger
+from src.config.config import CONFIG_DIR
+
+logger = get_logger("webui")
+
+router = APIRouter(prefix="/models", tags=["models"])
+
+
+# 模型获取器配置
+MODEL_FETCHER_CONFIG = {
+    # OpenAI 兼容格式的提供商
+    "openai": {
+        "endpoint": "/models",
+        "parser": "openai",
+    },
+    # Gemini 格式
+    "gemini": {
+        "endpoint": "/models",
+        "parser": "gemini",
+    },
+}
+
+
+def _normalize_url(url: str) -> str:
+    """规范化 URL（去掉尾部斜杠）"""
+    if not url:
+        return ""
+    return url.rstrip("/")
+
+
+def _parse_openai_response(data: dict) -> list[dict]:
+    """
+    解析 OpenAI 格式的模型列表响应
+    
+    格式: { "data": [{ "id": "gpt-4", "object": "model", ... }] }
+    """
+    models = []
+    if "data" in data and isinstance(data["data"], list):
+        for model in data["data"]:
+            if isinstance(model, dict) and "id" in model:
+                models.append({
+                    "id": model["id"],
+                    "name": model.get("name") or model["id"],
+                    "owned_by": model.get("owned_by", ""),
+                })
+    return models
+
+
+def _parse_gemini_response(data: dict) -> list[dict]:
+    """
+    解析 Gemini 格式的模型列表响应
+    
+    格式: { "models": [{ "name": "models/gemini-pro", "displayName": "Gemini Pro", ... }] }
+    """
+    models = []
+    if "models" in data and isinstance(data["models"], list):
+        for model in data["models"]:
+            if isinstance(model, dict) and "name" in model:
+                # Gemini 的 name 格式是 "models/gemini-pro"，我们只取后面部分
+                model_id = model["name"]
+                if model_id.startswith("models/"):
+                    model_id = model_id[7:]  # 去掉 "models/" 前缀
+                models.append({
+                    "id": model_id,
+                    "name": model.get("displayName") or model_id,
+                    "owned_by": "google",
+                })
+    return models
+
+
+async def _fetch_models_from_provider(
+    base_url: str,
+    api_key: str,
+    endpoint: str,
+    parser: str,
+    client_type: str = "openai",
+) -> list[dict]:
+    """
+    从提供商 API 获取模型列表
+    
+    Args:
+        base_url: 提供商的基础 URL
+        api_key: API 密钥
+        endpoint: 获取模型列表的端点
+        parser: 响应解析器类型 ('openai' | 'gemini')
+        client_type: 客户端类型 ('openai' | 'gemini')
+    
+    Returns:
+        模型列表
+    """
+    url = f"{_normalize_url(base_url)}{endpoint}"
+    
+    # 根据客户端类型设置请求头
+    headers = {}
+    params = {}
+    
+    if client_type == "gemini":
+        # Gemini 使用 URL 参数传递 API Key
+        params["key"] = api_key
+    else:
+        # OpenAI 兼容格式使用 Authorization 头
+        headers["Authorization"] = f"Bearer {api_key}"
+    
+    try:
+        async with httpx.AsyncClient(timeout=30.0) as client:
+            response = await client.get(url, headers=headers, params=params)
+            response.raise_for_status()
+            data = response.json()
+    except httpx.TimeoutException:
+        raise HTTPException(status_code=504, detail="请求超时，请稍后重试")
+    except httpx.HTTPStatusError as e:
+        if e.response.status_code == 401:
+            raise HTTPException(status_code=401, detail="API Key 无效或已过期")
+        elif e.response.status_code == 403:
+            raise HTTPException(status_code=403, detail="没有权限访问模型列表")
+        elif e.response.status_code == 404:
+            raise HTTPException(status_code=404, detail="该提供商不支持获取模型列表")
+        else:
+            raise HTTPException(
+                status_code=e.response.status_code, 
+                detail=f"请求失败: {e.response.text}"
+            )
+    except Exception as e:
+        logger.error(f"获取模型列表失败: {e}")
+        raise HTTPException(status_code=500, detail=f"获取模型列表失败: {str(e)}")
+    
+    # 根据解析器类型解析响应
+    if parser == "openai":
+        return _parse_openai_response(data)
+    elif parser == "gemini":
+        return _parse_gemini_response(data)
+    else:
+        raise HTTPException(status_code=400, detail=f"不支持的解析器类型: {parser}")
+
+
+def _get_provider_config(provider_name: str) -> Optional[dict]:
+    """
+    从 model_config.toml 获取指定提供商的配置
+    
+    Args:
+        provider_name: 提供商名称
+    
+    Returns:
+        提供商配置，如果未找到则返回 None
+    """
+    config_path = os.path.join(CONFIG_DIR, "model_config.toml")
+    if not os.path.exists(config_path):
+        return None
+    
+    try:
+        with open(config_path, "r", encoding="utf-8") as f:
+            config_data = tomlkit.load(f)
+        
+        providers = config_data.get("api_providers", [])
+        for provider in providers:
+            if provider.get("name") == provider_name:
+                return dict(provider)
+        
+        return None
+    except Exception as e:
+        logger.error(f"读取提供商配置失败: {e}")
+        return None
+
+
+@router.get("/list")
+async def get_provider_models(
+    provider_name: str = Query(..., description="提供商名称"),
+    parser: str = Query("openai", description="响应解析器类型 (openai | gemini)"),
+    endpoint: str = Query("/models", description="获取模型列表的端点"),
+):
+    """
+    获取指定提供商的可用模型列表
+    
+    通过提供商名称查找配置，然后请求对应的模型列表端点
+    """
+    # 获取提供商配置
+    provider_config = _get_provider_config(provider_name)
+    if not provider_config:
+        raise HTTPException(status_code=404, detail=f"未找到提供商: {provider_name}")
+    
+    base_url = provider_config.get("base_url")
+    api_key = provider_config.get("api_key")
+    client_type = provider_config.get("client_type", "openai")
+    
+    if not base_url:
+        raise HTTPException(status_code=400, detail="提供商配置缺少 base_url")
+    if not api_key:
+        raise HTTPException(status_code=400, detail="提供商配置缺少 api_key")
+    
+    # 获取模型列表
+    models = await _fetch_models_from_provider(
+        base_url=base_url,
+        api_key=api_key,
+        endpoint=endpoint,
+        parser=parser,
+        client_type=client_type,
+    )
+    
+    return {
+        "success": True,
+        "models": models,
+        "provider": provider_name,
+        "count": len(models),
+    }
+
+
+@router.get("/list-by-url")
+async def get_models_by_url(
+    base_url: str = Query(..., description="提供商的基础 URL"),
+    api_key: str = Query(..., description="API Key"),
+    parser: str = Query("openai", description="响应解析器类型 (openai | gemini)"),
+    endpoint: str = Query("/models", description="获取模型列表的端点"),
+    client_type: str = Query("openai", description="客户端类型 (openai | gemini)"),
+):
+    """
+    通过 URL 直接获取模型列表（用于自定义提供商）
+    """
+    models = await _fetch_models_from_provider(
+        base_url=base_url,
+        api_key=api_key,
+        endpoint=endpoint,
+        parser=parser,
+        client_type=client_type,
+    )
+    
+    return {
+        "success": True,
+        "models": models,
+        "count": len(models),
+    }

src/webui/routes.py

@@ -13,6 +13,7 @@ from .emoji_routes import router as emoji_router
 from .plugin_routes import router as plugin_router
 from .plugin_progress_ws import get_progress_router
 from .routers.system import router as system_router
+from .model_routes import router as model_router
 
 logger = get_logger("webui.api")
 
@@ -35,6 +36,8 @@ router.include_router(plugin_router)
 router.include_router(get_progress_router())
 # 注册系统控制路由
 router.include_router(system_router)
+# 注册模型列表获取路由
+router.include_router(model_router)
 
 
 class TokenVerifyRequest(BaseModel):