#!/usr/bin/env python3 """ Cidadão.AI Models - HuggingFace Spaces Entry Point FastAPI server for ML model inference optimized for HuggingFace Spaces deployment. """ import os import sys import logging from contextlib import asynccontextmanager import uvicorn from fastapi import FastAPI, HTTPException from fastapi.middleware.cors import CORSMiddleware from fastapi.responses import JSONResponse, HTMLResponse # Configure logging for HuggingFace logging.basicConfig( level=logging.INFO, format="%(asctime)s - %(name)s - %(levelname)s - %(message)s", handlers=[logging.StreamHandler(sys.stdout)] ) logger = logging.getLogger(__name__) # Import our API server try: from src.inference.api_server import app as models_app MODELS_AVAILABLE = True logger.info("✅ Models API successfully imported") except Exception as e: logger.error(f"❌ Failed to import models API: {e}") MODELS_AVAILABLE = False @asynccontextmanager async def lifespan(app: FastAPI): """Application lifespan manager for HuggingFace Spaces.""" logger.info("🚀 Starting Cidadão.AI Models on HuggingFace Spaces") logger.info(f"🔧 Environment: {os.getenv('SPACE_ID', 'local')}") logger.info(f"🌐 Port: {os.getenv('PORT', '8001')}") yield logger.info("🛑 Shutting down Cidadão.AI Models") if MODELS_AVAILABLE: # Use the imported models app app = models_app logger.info("Using full models API") else: # Fallback minimal app app = FastAPI( title="🤖 Cidadão.AI Models (Fallback)", description="Minimal fallback API when models are not available", version="1.0.0", lifespan=lifespan ) app.add_middleware( CORSMiddleware, allow_origins=["*"], allow_credentials=True, allow_methods=["*"], allow_headers=["*"], ) @app.get("/", response_class=HTMLResponse) async def fallback_root(): """Fallback root with information about the service.""" return """ Cidadão.AI Models

🤖 Cidadão.AI Models

Sistema de ML para Transparência Pública Brasileira

📊 Status do Sistema

⚠️ Modo Fallback - Modelos ML não disponíveis

🔧 Para funcionalidade completa, verifique as dependências

🔗 Endpoints Disponíveis

GET /health - Health check
GET /docs - Documentação da API
GET / - Esta página

🏛️ Sobre o Cidadão.AI

Sistema multi-agente de IA para análise de transparência pública, especializado em detectar anomalias e padrões suspeitos em dados governamentais brasileiros.

📚 Ver Documentação da API

""" @app.get("/health") async def fallback_health(): """Fallback health check.""" return { "status": "limited", "mode": "fallback", "models_loaded": False, "message": "Models not available, running in fallback mode" } logger.info("Using fallback minimal API") # Add HuggingFace Spaces specific routes @app.get("/spaces-info") async def spaces_info(): """HuggingFace Spaces specific information.""" return { "platform": "HuggingFace Spaces", "space_id": os.getenv("SPACE_ID", "unknown"), "space_author": os.getenv("SPACE_AUTHOR", "cidadao-ai"), "space_title": os.getenv("SPACE_TITLE", "Cidadão.AI Models"), "sdk": "docker", "port": int(os.getenv("PORT", "8001")), "models_available": MODELS_AVAILABLE } if __name__ == "__main__": # Configuration for HuggingFace Spaces port = int(os.getenv("PORT", "8001")) host = os.getenv("HOST", "0.0.0.0") logger.info(f"🚀 Starting server on {host}:{port}") logger.info(f"📊 Models available: {MODELS_AVAILABLE}") try: # Use uvicorn with optimized settings for HuggingFace uvicorn.run( app, host=host, port=port, log_level="info", access_log=True, workers=1, # Single worker for HuggingFace Spaces loop="asyncio" ) except Exception as e: logger.error(f"❌ Failed to start server: {str(e)}") sys.exit(1)