Add FastAPI backend with agent system

backend/app/services/settings_service.py

@@ -0,0 +1,140 @@
+import logging
+from typing import Optional
+from sqlalchemy.ext.asyncio import AsyncSession
+from sqlalchemy import select
+from app.models.user import User
+from app.services.auth_service import verify_password, get_password_hash
+
+logger = logging.getLogger(__name__)
+
+
+async def get_user_settings(user_id: str, db: AsyncSession) -> dict:
+    """获取用户完整设置"""
+    result = await db.execute(select(User).where(User.id == user_id))
+    user = result.scalar_one_or_none()
+    if not user:
+        return None
+    return {
+        "profile": user,
+        "llm_config": user.llm_config or {},
+        "scheduler_config": user.scheduler_config or {}
+    }
+
+
+async def update_user_profile(
+    user_id: str,
+    db: AsyncSession,
+    full_name: Optional[str] = None,
+    password: Optional[str] = None,
+    current_password: Optional[str] = None
+) -> User:
+    """更新用户资料"""
+    result = await db.execute(select(User).where(User.id == user_id))
+    user = result.scalar_one_or_none()
+    if not user:
+        raise ValueError("用户不存在")
+
+    if password:
+        if not current_password or not verify_password(current_password, user.hashed_password):
+            raise ValueError("当前密码错误")
+        user.hashed_password = get_password_hash(password)
+
+    if full_name:
+        user.full_name = full_name
+
+    await db.commit()
+    await db.refresh(user)
+    return user
+
+
+async def update_llm_config(user_id: str, config: dict, db: AsyncSession) -> dict:
+    """更新 LLM 配置"""
+    result = await db.execute(select(User).where(User.id == user_id))
+    user = result.scalar_one_or_none()
+    if not user:
+        raise ValueError("用户不存在")
+
+    current = user.llm_config or {}
+    # 合并配置 - 直接替换整个类型配置列表
+    for key, value in config.items():
+        if value is not None:
+            if isinstance(value, list):
+                # 列表直接替换
+                current[key] = value
+            elif isinstance(value, dict):
+                # 字典合并
+                if key in current and isinstance(current[key], dict):
+                    current[key] = {**current[key], **value}
+                else:
+                    current[key] = value
+            else:
+                current[key] = value
+    user.llm_config = current
+    await db.commit()
+    return current
+
+
+async def update_scheduler_config(user_id: str, config: dict, db: AsyncSession) -> dict:
+    """更新定时任务配置"""
+    result = await db.execute(select(User).where(User.id == user_id))
+    user = result.scalar_one_or_none()
+    if not user:
+        raise ValueError("用户不存在")
+
+    current = user.scheduler_config or {}
+    for key, value in config.items():
+        if value is not None:
+            current[key] = value
+    user.scheduler_config = current
+    await db.commit()
+    return current
+
+
+async def test_llm_connection(
+    provider: str,
+    model: str,
+    base_url: str,
+    api_key: str
+) -> dict:
+    """测试 LLM 连接"""
+    try:
+        # 根据不同 provider 创建临时 LLM 实例并测试
+        if provider == "openai":
+            from langchain_openai import ChatOpenAI
+            llm = ChatOpenAI(
+                api_key=api_key,
+                model=model,
+                base_url=base_url or None,
+                timeout=30
+            )
+        elif provider == "claude":
+            from langchain_anthropic import ChatAnthropic
+            llm = ChatAnthropic(
+                api_key=api_key,
+                model=model,
+                timeout=30
+            )
+        elif provider == "ollama":
+            from langchain_ollama import ChatOllama
+            llm = ChatOllama(
+                base_url=base_url or "http://localhost:11434",
+                model=model,
+                timeout=30
+            )
+        elif provider == "deepseek":
+            from langchain_openai import ChatOpenAI
+            llm = ChatOpenAI(
+                api_key=api_key,
+                model=model,
+                base_url=base_url or "https://api.deepseek.com/v1",
+                timeout=30
+            )
+        else:
+            return {"success": False, "error": f"不支持的 provider: {provider}"}
+
+        # 简单测试调用
+        from langchain_core.messages import HumanMessage
+        response = await llm.ainvoke([HumanMessage(content="Hi")])
+        return {"success": True, "message": f"连接成功，模型响应: {response.content[:50]}..."}
+    except Exception as e:
+        return {"success": False, "error": str(e)}