333 lines
12 KiB
Python
333 lines
12 KiB
Python
from fastapi import APIRouter, Depends, status, Query
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from langchain_core.messages import HumanMessage, SystemMessage
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from langchain_core.prompts import ChatPromptTemplate
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from sqlalchemy.orm import Session
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from typing import List, Optional
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import uuid
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from app.core.models import RedBearLLM
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from app.core.models.base import RedBearModelConfig
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from app.db import get_db
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from app.dependencies import get_current_user
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from app.models.models_model import ModelProvider, ModelType
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from app.models.user_model import User
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from app.schemas import model_schema
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from app.core.response_utils import success
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from app.schemas.response_schema import ApiResponse, PageData
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from app.services.model_service import ModelConfigService, ModelApiKeyService
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from app.core.logging_config import get_api_logger
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# 获取API专用日志器
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api_logger = get_api_logger()
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router = APIRouter(
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prefix="/models",
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tags=["Models"],
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)
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@router.get("/type", response_model=ApiResponse)
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def get_model_types():
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return success(msg="获取模型类型成功", data=list(ModelType))
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@router.get("/provider", response_model=ApiResponse)
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def get_model_providers():
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return success(msg="获取模型提供商成功", data=list(ModelProvider))
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@router.get("", response_model=ApiResponse)
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def get_model_list(
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type: Optional[List[model_schema.ModelType]] = Query(None, description="模型类型筛选(支持多个,如 ?type=LLM&type=EMBEDDING)"),
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provider: Optional[model_schema.ModelProvider] = Query(None, description="提供商筛选(基于API Key)"),
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is_active: Optional[bool] = Query(None, description="激活状态筛选"),
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is_public: Optional[bool] = Query(None, description="公开状态筛选"),
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search: Optional[str] = Query(None, description="搜索关键词"),
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page: int = Query(1, ge=1, description="页码"),
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pagesize: int = Query(10, ge=1, le=100, description="每页数量"),
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db: Session = Depends(get_db)
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):
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"""
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获取模型配置列表
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支持多个 type 参数:
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- 单个:?type=LLM
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- 多个:?type=LLM&type=EMBEDDING
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"""
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api_logger.info(f"获取模型配置列表请求: type={type}, provider={provider}, page={page}, pagesize={pagesize}")
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try:
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query = model_schema.ModelConfigQuery(
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type=type,
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provider=provider,
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is_active=is_active,
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is_public=is_public,
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search=search,
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page=page,
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pagesize=pagesize
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)
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api_logger.debug(f"开始获取模型配置列表: {query.dict()}")
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result_orm = ModelConfigService.get_model_list(db=db, query=query)
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result = PageData.model_validate(result_orm)
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api_logger.info(f"模型配置列表获取成功: 总数={result.page.total}, 当前页={len(result.items)}")
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return success(data=result, msg="模型配置列表获取成功")
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except Exception as e:
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api_logger.error(f"获取模型配置列表失败: {str(e)}")
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raise
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@router.get("/{model_id}", response_model=ApiResponse)
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def get_model_by_id(
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model_id: uuid.UUID,
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db: Session = Depends(get_db)
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):
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"""
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根据ID获取模型配置
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"""
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api_logger.info(f"获取模型配置请求: model_id={model_id}")
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try:
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api_logger.debug(f"开始获取模型配置: model_id={model_id}")
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result_orm = ModelConfigService.get_model_by_id(db=db, model_id=model_id)
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api_logger.info(f"模型配置获取成功: {result_orm.name}")
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# 将ORM对象转换为Pydantic模型
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result_pydantic = model_schema.ModelConfig.model_validate(result_orm)
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return success(data=result_pydantic, msg="模型配置获取成功")
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except Exception as e:
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api_logger.error(f"获取模型配置失败: model_id={model_id} - {str(e)}")
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raise
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@router.post("", response_model=ApiResponse)
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async def create_model(
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model_data: model_schema.ModelConfigCreate,
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db: Session = Depends(get_db),
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current_user: User = Depends(get_current_user)
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):
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"""
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创建模型配置
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- 创建模型配置基础信息
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- 如果包含 API Key,会先验证配置有效性,然后创建
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- 验证失败时会抛出异常,不会创建配置
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- 可通过 skip_validation=true 跳过验证
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"""
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api_logger.info(f"创建模型配置请求: {model_data.name}, 用户: {current_user.username}")
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try:
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api_logger.debug(f"开始创建模型配置: {model_data.name}")
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result_orm = await ModelConfigService.create_model(db=db, model_data=model_data)
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api_logger.info(f"模型配置创建成功: {result_orm.name} (ID: {result_orm.id})")
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# 将ORM对象转换为Pydantic模型
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result = model_schema.ModelConfig.model_validate(result_orm)
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return success(data=result, msg="模型配置创建成功")
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except Exception as e:
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api_logger.error(f"创建模型配置失败: {model_data.name} - {str(e)}")
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raise
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@router.put("/{model_id}", response_model=ApiResponse)
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def update_model(
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model_id: uuid.UUID,
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model_data: model_schema.ModelConfigUpdate,
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db: Session = Depends(get_db),
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current_user: User = Depends(get_current_user)
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):
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"""
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更新模型配置
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"""
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api_logger.info(f"更新模型配置请求: model_id={model_id}, 用户: {current_user.username}")
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try:
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api_logger.debug(f"开始更新模型配置: model_id={model_id}")
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result_orm = ModelConfigService.update_model(db=db, model_id=model_id, model_data=model_data)
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api_logger.info(f"模型配置更新成功: {result_orm.name} (ID: {model_id})")
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# 将ORM对象转换为Pydantic模型
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result_pydantic = model_schema.ModelConfig.model_validate(result_orm)
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return success(data=result_pydantic, msg="模型配置更新成功")
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except Exception as e:
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api_logger.error(f"更新模型配置失败: model_id={model_id} - {str(e)}")
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raise
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@router.delete("/{model_id}", response_model=ApiResponse)
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def delete_model(
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model_id: uuid.UUID,
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db: Session = Depends(get_db),
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current_user: User = Depends(get_current_user)
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):
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"""
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删除模型配置
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"""
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api_logger.info(f"删除模型配置请求: model_id={model_id}, 用户: {current_user.username}")
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try:
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api_logger.debug(f"开始删除模型配置: model_id={model_id}")
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ModelConfigService.delete_model(db=db, model_id=model_id)
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api_logger.info(f"模型配置删除成功: model_id={model_id}")
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return success(msg="模型配置删除成功")
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except Exception as e:
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api_logger.error(f"删除模型配置失败: model_id={model_id} - {str(e)}")
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raise
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# API Key 相关接口
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@router.get("/{model_id}/apikeys", response_model=ApiResponse)
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def get_model_api_keys(
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model_id: uuid.UUID,
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is_active: bool = Query(True, description="是否只获取活跃的API Key"),
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db: Session = Depends(get_db),
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current_user: User = Depends(get_current_user)
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):
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"""
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获取模型的API Key列表
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"""
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api_logger.info(f"获取模型API Key列表请求: model_id={model_id}, 用户: {current_user.username}")
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try:
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api_logger.debug(f"开始获取模型API Key列表: model_id={model_id}")
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result_orm = ModelApiKeyService.get_api_keys_by_model(
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db=db, model_config_id=model_id, is_active=is_active
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)
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# 将ORM对象列表转换为Pydantic模型列表
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result_pydantic = [model_schema.ModelApiKey.model_validate(item) for item in result_orm]
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api_logger.info(f"模型API Key列表获取成功: 数量={len(result_pydantic)}")
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return success(data=result_pydantic, msg="模型API Key列表获取成功")
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except Exception as e:
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api_logger.error(f"获取模型API Key列表失败: model_id={model_id} - {str(e)}")
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raise
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@router.post("/{model_id}/apikeys", response_model=ApiResponse, status_code=status.HTTP_201_CREATED)
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async def create_model_api_key(
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model_id: uuid.UUID,
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api_key_data: model_schema.ModelApiKeyCreate,
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db: Session = Depends(get_db),
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current_user: User = Depends(get_current_user)
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):
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"""
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为模型创建API Key
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"""
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api_logger.info(f"创建模型API Key请求: model_id={model_id}, model_name={api_key_data.model_name}, 用户: {current_user.username}")
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try:
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# 设置模型配置ID
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api_key_data.model_config_id = model_id
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api_logger.debug(f"开始创建模型API Key: {api_key_data.model_name}")
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result = await ModelApiKeyService.create_api_key(db=db, api_key_data=api_key_data)
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api_logger.info(f"模型API Key创建成功: {result.model_name} (ID: {result.id})")
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return success(data=result, msg="模型API Key创建成功")
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except Exception as e:
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api_logger.error(f"创建模型API Key失败: {api_key_data.model_name} - {str(e)}")
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raise
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@router.get("/apikeys/{api_key_id}", response_model=ApiResponse)
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def get_api_key_by_id(
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api_key_id: uuid.UUID,
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db: Session = Depends(get_db),
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current_user: User = Depends(get_current_user)
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):
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"""
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根据ID获取API Key
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"""
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api_logger.info(f"获取API Key请求: api_key_id={api_key_id}, 用户: {current_user.username}")
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try:
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api_logger.debug(f"开始获取API Key: api_key_id={api_key_id}")
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result = ModelApiKeyService.get_api_key_by_id(db=db, api_key_id=api_key_id)
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api_logger.info(f"API Key获取成功: {result.model_name}")
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return success(data=result, msg="API Key获取成功")
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except Exception as e:
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api_logger.error(f"获取API Key失败: api_key_id={api_key_id} - {str(e)}")
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raise
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@router.put("/apikeys/{api_key_id}", response_model=ApiResponse)
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async def update_api_key(
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api_key_id: uuid.UUID,
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api_key_data: model_schema.ModelApiKeyUpdate,
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db: Session = Depends(get_db),
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current_user: User = Depends(get_current_user)
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):
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"""
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更新API Key
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"""
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api_logger.info(f"更新API Key请求: api_key_id={api_key_id}, 用户: {current_user.username}")
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try:
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api_logger.debug(f"开始更新API Key: api_key_id={api_key_id}")
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result = await ModelApiKeyService.update_api_key(db=db, api_key_id=api_key_id, api_key_data=api_key_data)
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api_logger.info(f"API Key更新成功: {result.model_name} (ID: {api_key_id})")
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result_pydantic = model_schema.ModelApiKey.model_validate(result)
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return success(data=result_pydantic, msg="API Key更新成功")
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except Exception as e:
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api_logger.error(f"更新API Key失败: api_key_id={api_key_id} - {str(e)}")
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raise
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@router.delete("/apikeys/{api_key_id}", response_model=ApiResponse)
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def delete_api_key(
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api_key_id: uuid.UUID,
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db: Session = Depends(get_db),
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current_user: User = Depends(get_current_user)
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):
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"""
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删除API Key
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"""
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api_logger.info(f"删除API Key请求: api_key_id={api_key_id}, 用户: {current_user.username}")
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try:
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api_logger.debug(f"开始删除API Key: api_key_id={api_key_id}")
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ModelApiKeyService.delete_api_key(db=db, api_key_id=api_key_id)
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api_logger.info(f"API Key删除成功: api_key_id={api_key_id}")
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return success(msg="API Key删除成功")
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except Exception as e:
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api_logger.error(f"删除API Key失败: api_key_id={api_key_id} - {str(e)}")
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raise
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@router.post("/validate", response_model=ApiResponse)
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async def validate_model_config(
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validate_data: model_schema.ModelValidateRequest,
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db: Session = Depends(get_db),
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current_user: User = Depends(get_current_user)
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):
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"""
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验证模型配置是否有效
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支持验证不同类型的模型:
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- llm: 大语言模型
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- chat: 对话模型
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- embedding: 向量模型
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- rerank: 重排序模型
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"""
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api_logger.info(f"验证模型配置请求: {validate_data.model_name} ({validate_data.model_type}), 用户: {current_user.username}")
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result = await ModelConfigService.validate_model_config(
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db=db,
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model_name=validate_data.model_name,
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provider=validate_data.provider,
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api_key=validate_data.api_key,
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api_base=validate_data.api_base,
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model_type=validate_data.model_type,
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test_message=validate_data.test_message
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)
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return success(data=model_schema.ModelValidateResponse(**result), msg="验证完成")
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