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from fastapi import FastAPI, Depends, APIRouter, HTTPException
from fastapi.security import HTTPBearer
from fastapi.middleware.cors import CORSMiddleware
import asyncio
# from fastapi.responses import JSONResponse # Not used
# import os # Not used
# Local module imports
from app.vertex.auth import get_api_key, validate_api_key
from app.vertex.credentials_manager import CredentialManager
from app.vertex.vertex_ai_init import init_vertex_ai
from app.utils.logging import vertex_log
from app.config import settings
# import config as app_config # Not directly used in main.py
# Routers
from app.vertex.routes import models_api
from app.vertex.routes import chat_api
app = FastAPI(title="OpenAI to Gemini Adapter")
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
credential_manager = CredentialManager()
app.state.credential_manager = credential_manager # Store manager on app state
# Include API routers
app.include_router(models_api.router)
app.include_router(chat_api.router)
# Create router
vertex_router = APIRouter(prefix="/vertex")
# Security scheme
security = HTTPBearer()
# Include vertex_router in the app
app.include_router(vertex_router)
@app.on_event("startup")
async def startup_event():
try:
# 检查是否有Google Credentials JSON
if hasattr(settings, 'GOOGLE_CREDENTIALS_JSON') and settings.GOOGLE_CREDENTIALS_JSON:
vertex_log('info', "检测到持久化的Google Credentials JSON，准备加载")
from app.vertex.credentials_manager import parse_multiple_json_credentials
parsed_json_objects = parse_multiple_json_credentials(settings.GOOGLE_CREDENTIALS_JSON)
if parsed_json_objects:
loaded_count = credential_manager.load_credentials_from_json_list(parsed_json_objects)
vertex_log('info', f"从持久化的Google Credentials JSON中加载了{loaded_count}个凭据")
# 检查是否有Vertex Express API Key
if hasattr(settings, 'VERTEX_EXPRESS_API_KEY') and settings.VERTEX_EXPRESS_API_KEY:
vertex_log('info', "检测到持久化的Vertex Express API Key")
# 初始化Vertex AI
if await init_vertex_ai(credential_manager):
vertex_log('info', "Vertex AI credential and model config initialization check completed successfully.")
# 刷新模型配置缓存
from app.vertex.model_loader import refresh_models_config_cache
refresh_success = await refresh_models_config_cache()
if refresh_success:
vertex_log('info', "成功刷新模型配置缓存")
else:
vertex_log('warning', "刷新模型配置缓存失败")
else:
vertex_log('error', "Failed to initialize a fallback Vertex AI client. API will likely fail.")
except Exception as e:
vertex_log('error', f"启动时初始化Vertex AI服务出错: {str(e)}")
@app.get("/")
async def root():
return {
"status": "ok",
"message": "OpenAI to Gemini Adapter is running."
}
@vertex_router.get("/health")
async def health_check(credentials: HTTPAuthorizationCredentials = Depends(security)):
"""
Simple health check endpoint for the Vertex AI integration.
"""
# Validate API key
api_key = validate_api_key(credentials)
if not api_key:
raise HTTPException(status_code=401, detail="Invalid API key")
# If we get here, API key is valid
vertex_log('info', "Health check passed with valid API key")
return {"status": "ok", "message": "Vertex AI integration is operational"}
@vertex_router.get("/status")
async def status():
"""
Public status endpoint (no auth required)
"""
vertex_log('info', "Status check requested")
return {
"status": "online",
"version": "1.0.0",
"endpoints_available": [
"/vertex/health",
"/vertex/predict",
"/vertex/generate",
"/vertex/admin/config",
"/vertex/models/list"
]
}
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