import logging
from contextlib import asynccontextmanager

import torch
from dotenv import load_dotenv
from fastapi import FastAPI

from src.api import fix_newlines, fix_newlines_all_models, health
from src.models.export_and_download import download_all_models
from src.pipelines.all_models_pipeline import AllModelsPipeline
from src.pipelines.one_model_pipeline import OneModelPipeline
from src.pipelines.sat_loader import load_sat

load_dotenv()
log = logging.getLogger(__name__)


@asynccontextmanager
async def lifespan(app: FastAPI):
    device = "cuda" if torch.cuda.is_available() else "cpu"
    log.info(f"Loading SAT-3L-SM on {device} ...")
    sat = load_sat(device=device)

    downloaded = download_all_models()

    # OneModelPipeline — uses bert
    bert_dir = downloaded.get("bert")
    if bert_dir and (bert_dir / "model.onnx").exists():
        log.info("Loading OneModelPipeline (bert)")
        app.state.one_model_pipeline = OneModelPipeline(
            onnx_path=bert_dir / "model.onnx",
            tokenizer_path=bert_dir,
            sat_model=sat,
            model_name="bert",
        )
    else:
        log.warning("bert not available — OneModelPipeline disabled")
        app.state.one_model_pipeline = None

    # AllModelsPipeline — uses all downloaded models
    all_pipeline = AllModelsPipeline(sat_model=sat)
    for name, local_dir in downloaded.items():
        onnx_path = local_dir / "model.onnx"
        if onnx_path.exists():
            log.info(f"Adding {name} to AllModelsPipeline")
            all_pipeline.add_model(name, onnx_path, local_dir)
        else:
            log.warning(f"Skipping {name}: model.onnx not found in {local_dir}")
    app.state.all_models_pipeline = all_pipeline

    yield


app = FastAPI(
    title="Newline Fixer API",
    description="ML service for fixing newline placement in English text",
    lifespan=lifespan,
    root_path="/api",
)

app.include_router(health.router)
app.include_router(fix_newlines.router)
app.include_router(fix_newlines_all_models.router)