1136 lines
40 KiB
Python
1136 lines
40 KiB
Python
"""
|
||
设置管理 API
|
||
"""
|
||
from fastapi import APIRouter, HTTPException, Request, Depends
|
||
from sqlalchemy.ext.asyncio import AsyncSession
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||
from sqlalchemy import select
|
||
from typing import Dict, Any, List, Optional
|
||
from pathlib import Path
|
||
from pydantic import BaseModel
|
||
from datetime import datetime
|
||
import httpx
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||
import json
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||
import time
|
||
|
||
from app.database import get_db
|
||
from app.models.settings import Settings
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||
from app.services.cover_generation_service import cover_generation_service
|
||
from app.schemas.settings import (
|
||
SettingsCreate, SettingsUpdate, SettingsResponse,
|
||
APIKeyPreset, APIKeyPresetConfig, PresetCreateRequest,
|
||
PresetUpdateRequest, PresetResponse, PresetListResponse
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||
)
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||
from app.user_manager import User
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||
from app.logger import get_logger
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||
from app.config import settings as app_settings, PROJECT_ROOT
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||
from app.services.ai_service import AIService, create_user_ai_service, create_user_ai_service_with_mcp
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||
|
||
logger = get_logger(__name__)
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||
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router = APIRouter(prefix="/settings", tags=["设置管理"])
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||
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||
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||
class CoverSettingsTestRequest(BaseModel):
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cover_api_provider: str
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||
cover_api_key: str
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||
cover_api_base_url: Optional[str] = None
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||
cover_image_model: str
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||
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||
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||
def read_env_defaults() -> Dict[str, Any]:
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||
"""从.env文件读取默认配置(仅读取,不修改)"""
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||
return {
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||
"api_provider": app_settings.default_ai_provider,
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||
"api_key": app_settings.openai_api_key or app_settings.anthropic_api_key or "",
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||
"api_base_url": app_settings.openai_base_url or app_settings.anthropic_base_url or "",
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||
"llm_model": app_settings.default_model,
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||
"temperature": app_settings.default_temperature,
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||
"max_tokens": app_settings.default_max_tokens,
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||
}
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||
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||
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||
def require_login(request: Request):
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||
"""依赖:要求用户已登录"""
|
||
if not hasattr(request.state, "user") or not request.state.user:
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||
raise HTTPException(status_code=401, detail="需要登录")
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||
return request.state.user
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||
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||
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||
async def get_user_ai_service(
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||
user: User = Depends(require_login),
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||
db: AsyncSession = Depends(get_db)
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||
) -> AIService:
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||
"""
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||
依赖:获取当前用户的AI服务实例(支持MCP工具自动加载)
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||
从数据库读取用户设置并创建对应的AI服务。
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自动传递 user_id 和 db_session,使得 AIService 能够加载用户配置的MCP工具。
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根据用户的所有MCP插件状态决定是否启用MCP:如果有启用的插件则启用,否则禁用。
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"""
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from app.models.mcp_plugin import MCPPlugin
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result = await db.execute(
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select(Settings).where(Settings.user_id == user.user_id)
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)
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settings = result.scalar_one_or_none()
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if not settings:
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# 如果用户没有设置,从.env读取并保存
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env_defaults = read_env_defaults()
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settings = Settings(
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||
user_id=user.user_id,
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||
**env_defaults
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||
)
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db.add(settings)
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await db.commit()
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await db.refresh(settings)
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||
logger.info(f"用户 {user.user_id} 首次使用AI服务,已从.env同步设置到数据库")
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||
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# 查询用户的所有MCP插件状态
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mcp_result = await db.execute(
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select(MCPPlugin).where(MCPPlugin.user_id == user.user_id)
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||
)
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||
mcp_plugins = mcp_result.scalars().all()
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||
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# 检查是否有启用的MCP插件
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enable_mcp = any(plugin.enabled for plugin in mcp_plugins) if mcp_plugins else False
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||
if mcp_plugins:
|
||
enabled_count = sum(1 for p in mcp_plugins if p.enabled)
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||
logger.info(f"用户 {user.user_id} 有 {len(mcp_plugins)} 个MCP插件,{enabled_count} 个启用,{enable_mcp} 决定使用MCP")
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||
else:
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||
logger.debug(f"用户 {user.user_id} 没有配置MCP插件,禁用MCP")
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||
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||
# ✅ 使用支持MCP的工厂函数创建AI服务实例
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||
# 传递 user_id 和 db_session,使得 AIService 能够自动加载用户配置的MCP工具
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||
return create_user_ai_service_with_mcp(
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||
api_provider=settings.api_provider,
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||
api_key=settings.api_key,
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||
api_base_url=settings.api_base_url or "",
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||
model_name=settings.llm_model,
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||
temperature=settings.temperature,
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||
max_tokens=settings.max_tokens,
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||
user_id=user.user_id, # ✅ 传递 user_id
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||
db_session=db, # ✅ 传递 db_session
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||
system_prompt=settings.system_prompt,
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||
enable_mcp=enable_mcp, # 根据MCP插件状态动态决定
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||
)
|
||
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||
|
||
@router.get("", response_model=SettingsResponse)
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async def get_settings(
|
||
user: User = Depends(require_login),
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||
db: AsyncSession = Depends(get_db)
|
||
):
|
||
"""
|
||
获取当前用户的设置
|
||
如果用户没有保存过设置,自动从.env创建并保存到数据库
|
||
"""
|
||
result = await db.execute(
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||
select(Settings).where(Settings.user_id == user.user_id)
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||
)
|
||
settings = result.scalar_one_or_none()
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||
|
||
if not settings:
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||
# 如果用户没有保存过设置,从.env读取默认配置并保存到数据库
|
||
env_defaults = read_env_defaults()
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||
logger.info(f"用户 {user.user_id} 首次获取设置,自动从.env同步到数据库")
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||
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||
# 创建新设置并保存到数据库
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||
settings = Settings(
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||
user_id=user.user_id,
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||
**env_defaults
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||
)
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||
db.add(settings)
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||
await db.commit()
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||
await db.refresh(settings)
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||
logger.info(f"用户 {user.user_id} 的设置已从.env同步到数据库")
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||
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||
logger.info(f"用户 {user.user_id} 获取已保存的设置")
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||
return settings
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||
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||
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||
@router.post("/cover/test")
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||
async def test_cover_settings(
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||
data: CoverSettingsTestRequest,
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||
user: User = Depends(require_login),
|
||
):
|
||
result = await cover_generation_service.test_cover_settings(
|
||
provider=data.cover_api_provider,
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||
api_key=data.cover_api_key,
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||
api_base_url=data.cover_api_base_url,
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||
model=data.cover_image_model,
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||
)
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||
return {
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||
"success": result.success,
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||
"message": result.message,
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||
"provider": result.provider,
|
||
"model": result.model,
|
||
}
|
||
|
||
|
||
@router.post("", response_model=SettingsResponse)
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||
async def save_settings(
|
||
data: SettingsCreate,
|
||
user: User = Depends(require_login),
|
||
db: AsyncSession = Depends(get_db)
|
||
):
|
||
"""
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||
创建或更新当前用户的设置(Upsert)
|
||
如果设置已存在则更新,否则创建新设置
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||
仅保存到数据库
|
||
|
||
注意:手动保存配置后会自动取消之前激活的预设状态,
|
||
因为手动修改的配置可能与预设不一致
|
||
"""
|
||
# 查找现有设置
|
||
result = await db.execute(
|
||
select(Settings).where(Settings.user_id == user.user_id)
|
||
)
|
||
settings = result.scalar_one_or_none()
|
||
|
||
# 准备数据
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||
settings_dict = data.model_dump(exclude_unset=True)
|
||
|
||
if settings:
|
||
# 更新现有设置
|
||
for key, value in settings_dict.items():
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||
setattr(settings, key, value)
|
||
|
||
# 检查并取消预设激活状态
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||
# 因为用户手动修改了配置,可能与之前激活的预设不一致
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||
try:
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||
prefs = json.loads(settings.preferences or '{}')
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||
api_presets = prefs.get('api_presets', {'presets': [], 'version': '1.0'})
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||
presets = api_presets.get('presets', [])
|
||
|
||
# 找到激活的预设并检查是否与当前保存的配置一致
|
||
active_preset = next((p for p in presets if p.get('is_active')), None)
|
||
if active_preset:
|
||
preset_config = active_preset.get('config', {})
|
||
# 检查配置是否发生变化
|
||
config_changed = (
|
||
preset_config.get('api_provider') != settings_dict.get('api_provider', settings.api_provider) or
|
||
preset_config.get('api_key') != settings_dict.get('api_key', settings.api_key) or
|
||
preset_config.get('api_base_url') != settings_dict.get('api_base_url', settings.api_base_url) or
|
||
preset_config.get('llm_model') != settings_dict.get('llm_model', settings.llm_model) or
|
||
preset_config.get('temperature') != settings_dict.get('temperature', settings.temperature) or
|
||
preset_config.get('max_tokens') != settings_dict.get('max_tokens', settings.max_tokens)
|
||
)
|
||
|
||
if config_changed:
|
||
# 取消激活状态
|
||
active_preset['is_active'] = False
|
||
prefs['api_presets'] = api_presets
|
||
settings.preferences = json.dumps(prefs, ensure_ascii=False)
|
||
logger.info(f"用户 {user.user_id} 手动修改配置,已取消预设 {active_preset.get('name')} 的激活状态")
|
||
except (json.JSONDecodeError, TypeError) as e:
|
||
logger.warning(f"解析用户 {user.user_id} 的preferences失败: {e}")
|
||
|
||
await db.commit()
|
||
await db.refresh(settings)
|
||
logger.info(f"用户 {user.user_id} 更新设置")
|
||
else:
|
||
# 创建新设置
|
||
settings = Settings(
|
||
user_id=user.user_id,
|
||
**settings_dict
|
||
)
|
||
db.add(settings)
|
||
await db.commit()
|
||
await db.refresh(settings)
|
||
logger.info(f"用户 {user.user_id} 创建设置")
|
||
|
||
return settings
|
||
|
||
|
||
@router.put("", response_model=SettingsResponse)
|
||
async def update_settings(
|
||
data: SettingsUpdate,
|
||
user: User = Depends(require_login),
|
||
db: AsyncSession = Depends(get_db)
|
||
):
|
||
"""
|
||
更新当前用户的设置
|
||
仅保存到数据库
|
||
"""
|
||
result = await db.execute(
|
||
select(Settings).where(Settings.user_id == user.user_id)
|
||
)
|
||
settings = result.scalar_one_or_none()
|
||
|
||
if not settings:
|
||
raise HTTPException(status_code=404, detail="设置不存在,请先创建设置")
|
||
|
||
# 更新设置
|
||
update_data = data.model_dump(exclude_unset=True)
|
||
for key, value in update_data.items():
|
||
setattr(settings, key, value)
|
||
|
||
await db.commit()
|
||
await db.refresh(settings)
|
||
logger.info(f"用户 {user.user_id} 更新设置")
|
||
|
||
return settings
|
||
|
||
|
||
@router.delete("")
|
||
async def delete_settings(
|
||
user: User = Depends(require_login),
|
||
db: AsyncSession = Depends(get_db)
|
||
):
|
||
"""
|
||
删除当前用户的设置
|
||
"""
|
||
result = await db.execute(
|
||
select(Settings).where(Settings.user_id == user.user_id)
|
||
)
|
||
settings = result.scalar_one_or_none()
|
||
|
||
if not settings:
|
||
raise HTTPException(status_code=404, detail="设置不存在")
|
||
|
||
await db.delete(settings)
|
||
await db.commit()
|
||
logger.info(f"用户 {user.user_id} 删除设置")
|
||
|
||
return {"message": "设置已删除", "user_id": user.user_id}
|
||
|
||
|
||
@router.get("/models")
|
||
async def get_available_models(
|
||
api_key: str,
|
||
api_base_url: str,
|
||
provider: str = "openai"
|
||
):
|
||
"""
|
||
从配置的 API 获取可用的模型列表
|
||
|
||
Args:
|
||
api_key: API 密钥
|
||
api_base_url: API 基础 URL
|
||
provider: API 提供商 (openai, anthropic, azure, custom)
|
||
|
||
Returns:
|
||
模型列表
|
||
"""
|
||
try:
|
||
async with httpx.AsyncClient(timeout=10.0) as client:
|
||
if provider == "openai" or provider == "azure" or provider == "custom":
|
||
# OpenAI 兼容接口获取模型列表
|
||
url = f"{api_base_url.rstrip('/')}/models"
|
||
headers = {
|
||
"Authorization": f"Bearer {api_key}",
|
||
"Content-Type": "application/json"
|
||
}
|
||
|
||
logger.info(f"正在从 {url} 获取模型列表")
|
||
response = await client.get(url, headers=headers)
|
||
response.raise_for_status()
|
||
|
||
data = response.json()
|
||
models = []
|
||
|
||
if "data" in data and isinstance(data["data"], list):
|
||
for model in data["data"]:
|
||
model_id = model.get("id", "")
|
||
# 返回所有模型,不进行过滤
|
||
if model_id:
|
||
models.append({
|
||
"value": model_id,
|
||
"label": model_id,
|
||
"description": model.get("description", "") or f"Created: {model.get('created', 'N/A')}"
|
||
})
|
||
|
||
if not models:
|
||
raise HTTPException(
|
||
status_code=404,
|
||
detail="未能从 API 获取到可用的模型列表"
|
||
)
|
||
|
||
logger.info(f"成功获取 {len(models)} 个模型")
|
||
return {
|
||
"provider": provider,
|
||
"models": models,
|
||
"count": len(models)
|
||
}
|
||
|
||
elif provider == "anthropic":
|
||
# Anthropic models API
|
||
url = f"{api_base_url.rstrip('/')}/v1/models"
|
||
headers = {"x-api-key": api_key, "anthropic-version": "2023-06-01"}
|
||
response = await client.get(url, headers=headers)
|
||
response.raise_for_status()
|
||
data = response.json()
|
||
models = [{"value": m["id"], "label": m["id"], "description": m.get("display_name", "")} for m in data.get("data", [])]
|
||
return {"provider": provider, "models": models, "count": len(models)}
|
||
|
||
elif provider == "gemini":
|
||
# Gemini models API
|
||
url = f"{api_base_url.rstrip('/')}/models?key={api_key}"
|
||
response = await client.get(url)
|
||
response.raise_for_status()
|
||
data = response.json()
|
||
models = []
|
||
for m in data.get("models", []):
|
||
if "generateContent" in m.get("supportedGenerationMethods", []):
|
||
mid = m.get("name", "").replace("models/", "")
|
||
models.append({"value": mid, "label": m.get("displayName", mid), "description": ""})
|
||
return {"provider": provider, "models": models, "count": len(models)}
|
||
|
||
else:
|
||
raise HTTPException(status_code=400, detail=f"不支持的提供商: {provider}")
|
||
|
||
except httpx.HTTPStatusError as e:
|
||
logger.error(f"获取模型列表失败 (HTTP {e.response.status_code}): {e.response.text}")
|
||
if e.response.status_code == 404:
|
||
raise HTTPException(
|
||
status_code=400,
|
||
detail=f"该 API 提供商不支持模型列表查询接口 (/models 返回 404),请手动输入模型名称。当前请求地址: {api_base_url.rstrip('/')}/models"
|
||
)
|
||
raise HTTPException(
|
||
status_code=400,
|
||
detail=f"无法从 API 获取模型列表 (HTTP {e.response.status_code})"
|
||
)
|
||
except httpx.RequestError as e:
|
||
logger.error(f"请求模型列表失败: {str(e)}")
|
||
raise HTTPException(
|
||
status_code=400,
|
||
detail=f"无法连接到 API: {str(e)}"
|
||
)
|
||
except HTTPException:
|
||
raise
|
||
except Exception as e:
|
||
logger.error(f"获取模型列表时发生错误: {str(e)}")
|
||
raise HTTPException(
|
||
status_code=500,
|
||
detail=f"获取模型列表失败: {str(e)}"
|
||
)
|
||
|
||
|
||
class ApiTestRequest(BaseModel):
|
||
"""API 测试请求模型"""
|
||
api_key: str
|
||
api_base_url: str
|
||
provider: str
|
||
llm_model: str
|
||
temperature: Optional[float] = None
|
||
max_tokens: Optional[int] = None
|
||
|
||
|
||
@router.post("/check-function-calling")
|
||
async def check_function_calling_support(data: ApiTestRequest):
|
||
"""
|
||
检查模型是否支持 Function Calling(工具调用)
|
||
|
||
基于业界最佳实践的测试方法:
|
||
1. 发送包含工具定义的请求
|
||
2. 检查响应的 finish_reason 是否为 "tool_calls"
|
||
3. 验证响应中是否包含有效的 tool_calls 数据
|
||
|
||
Args:
|
||
data: 包含 API 配置的请求数据
|
||
|
||
Returns:
|
||
检测结果包含支持状态、详细信息和建议
|
||
"""
|
||
api_key = data.api_key
|
||
api_base_url = data.api_base_url
|
||
provider = data.provider
|
||
llm_model = data.llm_model
|
||
|
||
try:
|
||
start_time = time.time()
|
||
|
||
# 定义一个简单的测试工具(天气查询)
|
||
test_tools = [{
|
||
"type": "function",
|
||
"function": {
|
||
"name": "get_weather",
|
||
"description": "获取指定城市的当前天气信息",
|
||
"parameters": {
|
||
"type": "object",
|
||
"properties": {
|
||
"city": {
|
||
"type": "string",
|
||
"description": "城市名称,例如:北京、上海、深圳"
|
||
},
|
||
"unit": {
|
||
"type": "string",
|
||
"enum": ["celsius", "fahrenheit"],
|
||
"description": "温度单位"
|
||
}
|
||
},
|
||
"required": ["city"]
|
||
}
|
||
}
|
||
}]
|
||
|
||
# 测试提示:故意设计一个需要调用工具的问题
|
||
test_prompt = "请告诉我北京现在的天气情况如何?"
|
||
|
||
logger.info(f"🧪 开始检测 Function Calling 支持")
|
||
logger.info(f" - 提供商: {provider}")
|
||
logger.info(f" - 模型: {llm_model}")
|
||
logger.info(f" - 测试工具: get_weather")
|
||
|
||
# 创建临时 AI 服务实例进行测试
|
||
test_service = AIService(
|
||
api_provider=provider,
|
||
api_key=api_key,
|
||
api_base_url=api_base_url,
|
||
default_model=llm_model,
|
||
default_temperature=0.3, # 使用较低温度以获得更确定的行为
|
||
default_max_tokens=200
|
||
)
|
||
|
||
# 发送带工具的测试请求
|
||
response = await test_service.generate_text(
|
||
prompt=test_prompt,
|
||
provider=provider,
|
||
model=llm_model,
|
||
temperature=0.3,
|
||
max_tokens=200,
|
||
tools=test_tools,
|
||
tool_choice="auto", # 让模型自动决定是否使用工具
|
||
auto_mcp=False # 禁用 MCP 自动加载
|
||
)
|
||
|
||
end_time = time.time()
|
||
response_time = round((end_time - start_time) * 1000, 2)
|
||
|
||
# 分析响应以确定是否支持 Function Calling
|
||
supported = False
|
||
finish_reason = None
|
||
tool_calls = None
|
||
response_content = None
|
||
|
||
if isinstance(response, dict):
|
||
# 检查 finish_reason(OpenAI 标准)
|
||
finish_reason = response.get("finish_reason")
|
||
|
||
# 检查是否有 tool_calls
|
||
if "tool_calls" in response and response["tool_calls"]:
|
||
supported = True
|
||
tool_calls = response["tool_calls"]
|
||
logger.info(f"✅ 检测到工具调用: {len(tool_calls)} 个")
|
||
|
||
# 记录返回的内容(如果有)
|
||
if "content" in response:
|
||
response_content = response["content"]
|
||
elif isinstance(response, str):
|
||
# 如果只返回字符串,说明不支持工具调用
|
||
response_content = response
|
||
|
||
logger.info(f" - 响应时间: {response_time}ms")
|
||
logger.info(f" - finish_reason: {finish_reason}")
|
||
logger.info(f" - 支持状态: {'✅ 支持' if supported else '❌ 不支持'}")
|
||
|
||
# 构建详细的返回信息
|
||
result = {
|
||
"success": True,
|
||
"supported": supported,
|
||
"message": "✅ 模型支持 Function Calling" if supported else "❌ 模型不支持 Function Calling",
|
||
"response_time_ms": response_time,
|
||
"provider": provider,
|
||
"model": llm_model,
|
||
"details": {
|
||
"finish_reason": finish_reason,
|
||
"has_tool_calls": bool(tool_calls),
|
||
"tool_call_count": len(tool_calls) if tool_calls else 0,
|
||
"test_tool": "get_weather",
|
||
"test_prompt": test_prompt,
|
||
"response_type": "tool_calls" if supported else "text"
|
||
}
|
||
}
|
||
|
||
# 添加工具调用详情
|
||
if tool_calls:
|
||
result["tool_calls"] = tool_calls
|
||
result["suggestions"] = [
|
||
"✅ 该模型支持 Function Calling,可以正常使用 MCP 插件",
|
||
"建议:启用需要的 MCP 插件以扩展 AI 能力",
|
||
"提示:测试成功检测到工具调用,模型能够正确解析和使用外部工具"
|
||
]
|
||
else:
|
||
result["response_preview"] = response_content[:200] if response_content else None
|
||
result["suggestions"] = [
|
||
"❌ 该模型不支持 Function Calling,无法使用 MCP 插件功能",
|
||
"建议:更换支持工具调用的模型",
|
||
"推荐模型:GPT-4 系列、GPT-4-turbo、Claude 3 Opus/Sonnet、Gemini 1.5 Pro 等",
|
||
"说明:模型返回了文本回复而非工具调用,表明不支持该功能"
|
||
]
|
||
|
||
return result
|
||
|
||
except ValueError as e:
|
||
error_msg = str(e)
|
||
logger.error(f"❌ Function Calling 检测配置错误: {error_msg}")
|
||
return {
|
||
"success": False,
|
||
"supported": False,
|
||
"message": "配置错误",
|
||
"error": error_msg,
|
||
"error_type": "ConfigurationError",
|
||
"suggestions": [
|
||
"请检查 API Key 是否正确",
|
||
"请确认 API Base URL 格式是否正确",
|
||
"请验证所选提供商与配置是否匹配"
|
||
]
|
||
}
|
||
|
||
except TimeoutError as e:
|
||
error_msg = str(e)
|
||
logger.error(f"❌ Function Calling 检测超时: {error_msg}")
|
||
return {
|
||
"success": False,
|
||
"supported": None,
|
||
"message": "检测超时",
|
||
"error": error_msg,
|
||
"error_type": "TimeoutError",
|
||
"suggestions": [
|
||
"请检查网络连接是否正常",
|
||
"请确认 API 服务是否可访问",
|
||
"建议:稍后重试或使用其他网络环境"
|
||
]
|
||
}
|
||
|
||
except Exception as e:
|
||
error_msg = str(e)
|
||
error_type = type(e).__name__
|
||
|
||
logger.error(f"❌ Function Calling 检测失败: {error_msg}")
|
||
logger.error(f" - 错误类型: {error_type}")
|
||
|
||
# 智能分析错误原因
|
||
suggestions = []
|
||
if "tool" in error_msg.lower() or "function" in error_msg.lower():
|
||
suggestions = [
|
||
"该模型可能不支持 Function Calling 功能",
|
||
"API 返回了与工具调用相关的错误",
|
||
"建议:更换支持工具调用的模型或联系 API 提供商"
|
||
]
|
||
elif "unauthorized" in error_msg.lower() or "401" in error_msg:
|
||
suggestions = [
|
||
"API Key 认证失败",
|
||
"请检查 API Key 是否正确且有效",
|
||
"请确认 API Key 是否有足够的权限"
|
||
]
|
||
elif "not found" in error_msg.lower() or "404" in error_msg:
|
||
suggestions = [
|
||
"模型不存在或不可用",
|
||
"请检查模型名称是否正确",
|
||
"请确认该模型在当前 API 中是否可用"
|
||
]
|
||
else:
|
||
suggestions = [
|
||
"检测过程中遇到未知错误",
|
||
"建议:检查所有配置参数是否正确",
|
||
"提示:查看详细错误信息以获取更多线索"
|
||
]
|
||
|
||
return {
|
||
"success": False,
|
||
"supported": False,
|
||
"message": "Function Calling 检测失败",
|
||
"error": error_msg,
|
||
"error_type": error_type,
|
||
"suggestions": suggestions
|
||
}
|
||
|
||
|
||
@router.post("/test")
|
||
async def test_api_connection(data: ApiTestRequest):
|
||
"""
|
||
测试 API 连接和配置是否正确
|
||
|
||
Args:
|
||
data: 包含 API 配置的请求数据(包括 temperature 和 max_tokens)
|
||
|
||
Returns:
|
||
测试结果包含状态、响应时间和详细信息
|
||
"""
|
||
api_key = data.api_key
|
||
api_base_url = data.api_base_url
|
||
provider = data.provider
|
||
llm_model = data.llm_model
|
||
# 使用前端传递的参数,如果未传递则使用默认值
|
||
temperature = data.temperature if data.temperature is not None else 0.7
|
||
max_tokens = data.max_tokens if data.max_tokens is not None else 2000
|
||
import time
|
||
|
||
try:
|
||
start_time = time.time()
|
||
|
||
# 创建临时 AI 服务实例,使用前端传递的参数
|
||
test_service = AIService(
|
||
api_provider=provider,
|
||
api_key=api_key,
|
||
api_base_url=api_base_url,
|
||
default_model=llm_model,
|
||
default_temperature=temperature,
|
||
default_max_tokens=max_tokens
|
||
)
|
||
|
||
# 发送简单的测试请求
|
||
test_prompt = "请用一句话回复:测试成功"
|
||
|
||
logger.info(f"🧪 开始测试 API 连接")
|
||
logger.info(f" - 提供商: {provider}")
|
||
logger.info(f" - 模型: {llm_model}")
|
||
logger.info(f" - Base URL: {api_base_url}")
|
||
logger.info(f" - Temperature: {temperature}")
|
||
logger.info(f" - Max Tokens: {max_tokens}")
|
||
|
||
response = await test_service.generate_text(
|
||
prompt=test_prompt,
|
||
provider=provider,
|
||
model=llm_model,
|
||
temperature=temperature,
|
||
max_tokens=max_tokens,
|
||
auto_mcp=False # 测试时不加载MCP工具
|
||
)
|
||
|
||
end_time = time.time()
|
||
response_time = round((end_time - start_time) * 1000, 2) # 转换为毫秒
|
||
|
||
logger.info(f"✅ API 测试成功")
|
||
logger.info(f" - 响应时间: {response_time}ms")
|
||
|
||
# 安全地处理响应内容(确保是字符串)
|
||
response_str = str(response) if response else 'N/A'
|
||
logger.info(f" - 响应内容: {response_str[:100]}")
|
||
|
||
return {
|
||
"success": True,
|
||
"message": "API 连接测试成功",
|
||
"response_time_ms": response_time,
|
||
"provider": provider,
|
||
"model": llm_model,
|
||
"response_preview": response_str[:100] if len(response_str) > 100 else response_str,
|
||
"details": {
|
||
"api_available": True,
|
||
"model_accessible": True,
|
||
"response_valid": bool(response),
|
||
"temperature": temperature,
|
||
"max_tokens": max_tokens
|
||
}
|
||
}
|
||
|
||
except ValueError as e:
|
||
# 配置错误
|
||
error_msg = str(e)
|
||
logger.error(f"❌ API 配置错误: {error_msg}")
|
||
return {
|
||
"success": False,
|
||
"message": "API 配置错误",
|
||
"error": error_msg,
|
||
"error_type": "ConfigurationError",
|
||
"suggestions": [
|
||
"请检查 API Key 是否正确",
|
||
"请确认 API Base URL 格式正确",
|
||
"请验证所选提供商是否匹配"
|
||
]
|
||
}
|
||
|
||
except TimeoutError as e:
|
||
# 超时错误
|
||
error_msg = str(e)
|
||
logger.error(f"❌ API 请求超时: {error_msg}")
|
||
return {
|
||
"success": False,
|
||
"message": "API 请求超时",
|
||
"error": error_msg,
|
||
"error_type": "TimeoutError",
|
||
"suggestions": [
|
||
"请检查网络连接",
|
||
"请确认 API Base URL 是否可访问",
|
||
"如果使用代理,请检查代理设置"
|
||
]
|
||
}
|
||
|
||
except Exception as e:
|
||
# 其他错误
|
||
error_msg = str(e)
|
||
error_type = type(e).__name__
|
||
|
||
logger.error(f"❌ API 测试失败: {error_msg}")
|
||
logger.error(f" - 错误类型: {error_type}")
|
||
|
||
# 分析错误原因并提供建议
|
||
suggestions = []
|
||
if "blocked" in error_msg.lower():
|
||
suggestions = [
|
||
"请求被 API 提供商阻止",
|
||
"可能原因:API Key 被限制或地区限制",
|
||
"建议:检查 API Key 状态和账户余额",
|
||
"建议:尝试更换 API Base URL 或使用代理"
|
||
]
|
||
elif "unauthorized" in error_msg.lower() or "401" in error_msg:
|
||
suggestions = [
|
||
"API Key 认证失败",
|
||
"建议:检查 API Key 是否正确",
|
||
"建议:确认 API Key 是否过期"
|
||
]
|
||
elif "not found" in error_msg.lower() or "404" in error_msg:
|
||
suggestions = [
|
||
"API 端点不存在或模型不可用",
|
||
"建议:检查 API Base URL 是否正确",
|
||
"建议:确认模型名称是否正确"
|
||
]
|
||
elif "rate limit" in error_msg.lower() or "429" in error_msg:
|
||
suggestions = [
|
||
"API 请求频率超限",
|
||
"建议:稍后重试",
|
||
"建议:升级 API 套餐"
|
||
]
|
||
elif "insufficient" in error_msg.lower() or "quota" in error_msg.lower():
|
||
suggestions = [
|
||
"API 配额不足",
|
||
"建议:检查账户余额",
|
||
"建议:充值或升级套餐"
|
||
]
|
||
else:
|
||
suggestions = [
|
||
"请检查所有配置参数是否正确",
|
||
"请确认网络连接正常",
|
||
"请查看详细错误信息"
|
||
]
|
||
|
||
return {
|
||
"success": False,
|
||
"message": "API 测试失败",
|
||
"error": error_msg,
|
||
"error_type": error_type,
|
||
"suggestions": suggestions
|
||
}
|
||
|
||
|
||
# ========== API配置预设管理(零数据库改动方案)==========
|
||
|
||
async def get_user_settings(user_id: str, db: AsyncSession) -> Settings:
|
||
"""获取用户settings,如果不存在则创建"""
|
||
result = await db.execute(
|
||
select(Settings).where(Settings.user_id == user_id)
|
||
)
|
||
settings = result.scalar_one_or_none()
|
||
|
||
if not settings:
|
||
# 创建默认设置
|
||
env_defaults = read_env_defaults()
|
||
settings = Settings(
|
||
user_id=user_id,
|
||
**env_defaults,
|
||
preferences='{}' # 初始化为空JSON
|
||
)
|
||
db.add(settings)
|
||
await db.commit()
|
||
await db.refresh(settings)
|
||
logger.info(f"用户 {user_id} 首次访问,已创建默认设置")
|
||
|
||
return settings
|
||
|
||
|
||
@router.get("/presets", response_model=PresetListResponse)
|
||
async def get_presets(
|
||
user: User = Depends(require_login),
|
||
db: AsyncSession = Depends(get_db)
|
||
):
|
||
"""
|
||
获取所有API配置预设
|
||
|
||
从preferences字段读取预设列表
|
||
"""
|
||
settings = await get_user_settings(user.user_id, db)
|
||
|
||
# 解析preferences
|
||
try:
|
||
prefs = json.loads(settings.preferences or '{}')
|
||
except json.JSONDecodeError:
|
||
logger.warning(f"用户 {user.user_id} 的preferences字段JSON格式错误,重置为空")
|
||
prefs = {}
|
||
|
||
api_presets = prefs.get('api_presets', {'presets': [], 'version': '1.0'})
|
||
presets = api_presets.get('presets', [])
|
||
|
||
# 找到激活的预设
|
||
active_preset_id = next(
|
||
(p['id'] for p in presets if p.get('is_active')),
|
||
None
|
||
)
|
||
|
||
logger.info(f"用户 {user.user_id} 获取预设列表,共 {len(presets)} 个")
|
||
|
||
return {
|
||
"presets": presets,
|
||
"total": len(presets),
|
||
"active_preset_id": active_preset_id
|
||
}
|
||
|
||
|
||
@router.post("/presets", response_model=PresetResponse)
|
||
async def create_preset(
|
||
data: PresetCreateRequest,
|
||
user: User = Depends(require_login),
|
||
db: AsyncSession = Depends(get_db)
|
||
):
|
||
"""
|
||
创建新预设
|
||
|
||
将预设添加到preferences字段的JSON中
|
||
"""
|
||
settings = await get_user_settings(user.user_id, db)
|
||
|
||
# 解析preferences
|
||
try:
|
||
prefs = json.loads(settings.preferences or '{}')
|
||
except json.JSONDecodeError:
|
||
prefs = {}
|
||
|
||
api_presets = prefs.get('api_presets', {'presets': [], 'version': '1.0'})
|
||
presets = api_presets.get('presets', [])
|
||
|
||
# 创建新预设
|
||
new_preset = {
|
||
"id": f"preset_{int(datetime.now().timestamp() * 1000)}",
|
||
"name": data.name,
|
||
"description": data.description,
|
||
"is_active": False,
|
||
"created_at": datetime.now().isoformat(),
|
||
"config": data.config.model_dump()
|
||
}
|
||
|
||
presets.append(new_preset)
|
||
|
||
# 保存回preferences
|
||
api_presets['presets'] = presets
|
||
prefs['api_presets'] = api_presets
|
||
settings.preferences = json.dumps(prefs, ensure_ascii=False)
|
||
|
||
await db.commit()
|
||
|
||
logger.info(f"用户 {user.user_id} 创建预设: {data.name}")
|
||
return new_preset
|
||
|
||
|
||
@router.put("/presets/{preset_id}", response_model=PresetResponse)
|
||
async def update_preset(
|
||
preset_id: str,
|
||
data: PresetUpdateRequest,
|
||
user: User = Depends(require_login),
|
||
db: AsyncSession = Depends(get_db)
|
||
):
|
||
"""
|
||
更新预设
|
||
|
||
在preferences字段的JSON中更新指定预设
|
||
"""
|
||
settings = await get_user_settings(user.user_id, db)
|
||
|
||
# 解析preferences
|
||
try:
|
||
prefs = json.loads(settings.preferences or '{}')
|
||
except json.JSONDecodeError:
|
||
raise HTTPException(status_code=500, detail="配置数据格式错误")
|
||
|
||
api_presets = prefs.get('api_presets', {'presets': [], 'version': '1.0'})
|
||
presets = api_presets.get('presets', [])
|
||
|
||
# 找到并更新预设
|
||
target_preset = next((p for p in presets if p['id'] == preset_id), None)
|
||
if not target_preset:
|
||
raise HTTPException(status_code=404, detail="预设不存在")
|
||
|
||
# 更新字段
|
||
if data.name is not None:
|
||
target_preset['name'] = data.name
|
||
if data.description is not None:
|
||
target_preset['description'] = data.description
|
||
if data.config is not None:
|
||
target_preset['config'] = data.config.model_dump()
|
||
|
||
# 保存回preferences
|
||
prefs['api_presets'] = api_presets
|
||
settings.preferences = json.dumps(prefs, ensure_ascii=False)
|
||
|
||
await db.commit()
|
||
|
||
logger.info(f"用户 {user.user_id} 更新预设: {preset_id}")
|
||
return target_preset
|
||
|
||
|
||
@router.delete("/presets/{preset_id}")
|
||
async def delete_preset(
|
||
preset_id: str,
|
||
user: User = Depends(require_login),
|
||
db: AsyncSession = Depends(get_db)
|
||
):
|
||
"""
|
||
删除预设
|
||
|
||
从preferences字段的JSON中删除指定预设
|
||
"""
|
||
settings = await get_user_settings(user.user_id, db)
|
||
|
||
# 解析preferences
|
||
try:
|
||
prefs = json.loads(settings.preferences or '{}')
|
||
except json.JSONDecodeError:
|
||
raise HTTPException(status_code=500, detail="配置数据格式错误")
|
||
|
||
api_presets = prefs.get('api_presets', {'presets': [], 'version': '1.0'})
|
||
presets = api_presets.get('presets', [])
|
||
|
||
# 找到预设
|
||
target_preset = next((p for p in presets if p['id'] == preset_id), None)
|
||
if not target_preset:
|
||
raise HTTPException(status_code=404, detail="预设不存在")
|
||
|
||
# 检查是否是激活的预设
|
||
if target_preset.get('is_active'):
|
||
raise HTTPException(status_code=400, detail="无法删除激活中的预设,请先激活其他预设")
|
||
|
||
# 删除预设
|
||
presets = [p for p in presets if p['id'] != preset_id]
|
||
|
||
# 保存回preferences
|
||
api_presets['presets'] = presets
|
||
prefs['api_presets'] = api_presets
|
||
settings.preferences = json.dumps(prefs, ensure_ascii=False)
|
||
|
||
await db.commit()
|
||
|
||
logger.info(f"用户 {user.user_id} 删除预设: {preset_id}")
|
||
return {"message": "预设已删除", "preset_id": preset_id}
|
||
|
||
|
||
@router.post("/presets/{preset_id}/activate")
|
||
async def activate_preset(
|
||
preset_id: str,
|
||
user: User = Depends(require_login),
|
||
db: AsyncSession = Depends(get_db)
|
||
):
|
||
"""
|
||
激活预设
|
||
|
||
将预设的配置应用到Settings主字段
|
||
"""
|
||
settings = await get_user_settings(user.user_id, db)
|
||
|
||
# 解析preferences
|
||
try:
|
||
prefs = json.loads(settings.preferences or '{}')
|
||
except json.JSONDecodeError:
|
||
raise HTTPException(status_code=500, detail="配置数据格式错误")
|
||
|
||
api_presets = prefs.get('api_presets', {'presets': [], 'version': '1.0'})
|
||
presets = api_presets.get('presets', [])
|
||
|
||
# 找到目标预设
|
||
target_preset = next((p for p in presets if p['id'] == preset_id), None)
|
||
if not target_preset:
|
||
raise HTTPException(status_code=404, detail="预设不存在")
|
||
|
||
# 应用配置到Settings主字段
|
||
config = target_preset['config']
|
||
settings.api_provider = config['api_provider']
|
||
settings.api_key = config['api_key']
|
||
settings.api_base_url = config.get('api_base_url')
|
||
settings.llm_model = config['llm_model']
|
||
settings.temperature = config['temperature']
|
||
settings.max_tokens = config['max_tokens']
|
||
settings.system_prompt = config.get('system_prompt')
|
||
|
||
# 更新所有预设的is_active状态
|
||
for preset in presets:
|
||
preset['is_active'] = (preset['id'] == preset_id)
|
||
|
||
# 保存回preferences
|
||
prefs['api_presets'] = api_presets
|
||
settings.preferences = json.dumps(prefs, ensure_ascii=False)
|
||
|
||
await db.commit()
|
||
|
||
logger.info(f"用户 {user.user_id} 激活预设: {target_preset['name']}")
|
||
return {
|
||
"message": "预设已激活",
|
||
"preset_id": preset_id,
|
||
"preset_name": target_preset['name']
|
||
}
|
||
|
||
|
||
@router.post("/presets/{preset_id}/test")
|
||
async def test_preset(
|
||
preset_id: str,
|
||
user: User = Depends(require_login),
|
||
db: AsyncSession = Depends(get_db)
|
||
):
|
||
"""
|
||
测试预设的API连接
|
||
"""
|
||
settings = await get_user_settings(user.user_id, db)
|
||
|
||
# 解析preferences
|
||
try:
|
||
prefs = json.loads(settings.preferences or '{}')
|
||
except json.JSONDecodeError:
|
||
raise HTTPException(status_code=500, detail="配置数据格式错误")
|
||
|
||
api_presets = prefs.get('api_presets', {'presets': [], 'version': '1.0'})
|
||
presets = api_presets.get('presets', [])
|
||
|
||
# 找到预设
|
||
target_preset = next((p for p in presets if p['id'] == preset_id), None)
|
||
if not target_preset:
|
||
raise HTTPException(status_code=404, detail="预设不存在")
|
||
|
||
# 使用现有的test_api_connection逻辑
|
||
# 确保传递完整参数,与当前配置测试保持一致
|
||
config = target_preset['config']
|
||
test_request = ApiTestRequest(
|
||
api_key=config['api_key'],
|
||
api_base_url=config.get('api_base_url', ''),
|
||
provider=config['api_provider'],
|
||
llm_model=config['llm_model'],
|
||
temperature=config.get('temperature'), # 使用预设中的温度参数
|
||
max_tokens=config.get('max_tokens') # 使用预设中的最大tokens参数
|
||
)
|
||
|
||
logger.info(f"用户 {user.user_id} 测试预设: {target_preset['name']}")
|
||
return await test_api_connection(test_request)
|
||
|
||
|
||
@router.post("/presets/from-current", response_model=PresetResponse)
|
||
async def create_preset_from_current(
|
||
name: str,
|
||
description: Optional[str] = None,
|
||
user: User = Depends(require_login),
|
||
db: AsyncSession = Depends(get_db)
|
||
):
|
||
"""
|
||
从当前配置创建新预设
|
||
|
||
快捷方式:将当前激活的配置保存为新预设
|
||
"""
|
||
settings = await get_user_settings(user.user_id, db)
|
||
|
||
# 从当前Settings主字段读取配置
|
||
current_config = APIKeyPresetConfig(
|
||
api_provider=settings.api_provider,
|
||
api_key=settings.api_key,
|
||
api_base_url=settings.api_base_url,
|
||
llm_model=settings.llm_model,
|
||
temperature=settings.temperature,
|
||
max_tokens=settings.max_tokens,
|
||
system_prompt=settings.system_prompt
|
||
)
|
||
|
||
# 创建预设
|
||
create_request = PresetCreateRequest(
|
||
name=name,
|
||
description=description,
|
||
config=current_config
|
||
)
|
||
|
||
logger.info(f"用户 {user.user_id} 从当前配置创建预设: {name}")
|
||
return await create_preset(create_request, user, db) |