src/api/main.py

from contextlib import asynccontextmanager

import mlflow
from fastapi import FastAPI
from fastapi.responses import RedirectResponse

from src.config import (
    MLFLOW_TRACKING_URI,
    MODEL_SOURCE,
    FINAL_MODEL_PATH,
    HF_MODEL_REPO,
    HF_TOKEN,
)

from src.recommendations.loader import load_model
from src.api.monitoring.metadata import load_crops_by_area_from_db

from src.api.routes.prediction import router as prediction_router
from src.api.routes.recommendation import router as recommendation_router
from src.api.routes.metadata import router as metadata_router
from src.api.monitoring.routes import router as monitoring_router


@asynccontextmanager
async def lifespan(app: FastAPI):
    mlflow.set_tracking_uri(MLFLOW_TRACKING_URI)
    mlflow.set_registry_uri(MLFLOW_TRACKING_URI)

    app.state.model = load_model(
        model_source=MODEL_SOURCE,
        local_path=FINAL_MODEL_PATH,
        hf_repo=HF_MODEL_REPO,
        hf_token=HF_TOKEN,
    )

    app.state.crops_by_area = load_crops_by_area_from_db()

    yield


app = FastAPI(
    title="API de Prédiction de Rendement et Recommandation de Cultures",
    lifespan=lifespan,
)


@app.get("/")
def root():
    return RedirectResponse(url="/docs")


@app.get("/health", tags=["Health"])
def health():
    return {"status": "ok"}


app.include_router(prediction_router)
app.include_router(recommendation_router)
app.include_router(metadata_router)
app.include_router(monitoring_router)