import uvicorn
from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
import gradio as gr
from config import get_settings
from models.text_classification import TextClassificationModel
from api.models import router as models_router, registry

app = FastAPI(
    title=get_settings().app_name,
    description="API for managing and running ML models",
    version="1.0.0",
    docs_url="/docs",
    redoc_url="/redoc",
)

# Configure CORS
app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],  # Modify this in production
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

# Register models
text_classifier = TextClassificationModel()
registry.register_model(
    "text-classification",
    text_classifier,
    "/gradio/text-classification"
)

# Mount the models API router
app.include_router(
    models_router,
    prefix="/api/models",
    tags=["models"]
)

# Mount Gradio interface
app = gr.mount_gradio_app(
    app, 
    text_classifier.create_interface(), 
    path="/gradio/text-classification"
)

@app.get("/")
async def root():
    """Root endpoint returning basic API information."""
    return {
        "name": get_settings().app_name,
        "version": "1.0.0",
        "status": "running"
    }

if __name__ == "__main__":
    # Initialize settings
    settings = get_settings()
    
    uvicorn.run(
        "main:app",
        host=settings.host,
        port=settings.port,
        reload=settings.debug
    )