import numpy as np
import cv2
import base64
import requests
from io import BytesIO

from starlette.requests import Request
from starlette.responses import JSONResponse
from ray import serve
from ray.serve.handle import DeploymentHandle

from texteller.api import load_model, load_tokenizer, img2latex
from texteller.utils import get_device
from texteller.globals import Globals
from typing import Literal


@serve.deployment(
    num_replicas=Globals().num_replicas,
    ray_actor_options={
        "num_cpus": Globals().ncpu_per_replica,
        "num_gpus": Globals().ngpu_per_replica * 1.0 / 2,
    },
)
class TexTellerServer:
    def __init__(
        self,
        checkpoint_dir: str,
        tokenizer_dir: str,
        use_onnx: bool = False,
        out_format: Literal["latex", "katex"] = "katex",
        keep_style: bool = False,
        num_beams: int = 1,
    ) -> None:
        self.model = load_model(
            model_dir=checkpoint_dir,
            use_onnx=use_onnx,
        )
        self.tokenizer = load_tokenizer(tokenizer_dir=tokenizer_dir)
        self.num_beams = num_beams
        self.out_format = out_format
        self.keep_style = keep_style

        if not use_onnx:
            self.model = self.model.to(get_device())

    def predict(self, image_nparray: np.ndarray) -> str:
        return img2latex(
            model=self.model,
            tokenizer=self.tokenizer,
            images=[image_nparray],
            device=get_device(),
            out_format=self.out_format,
            keep_style=self.keep_style,
            num_beams=self.num_beams,
        )[0]


@serve.deployment()
class Ingress:
    def __init__(self, rec_server: DeploymentHandle) -> None:
        self.texteller_server = rec_server

    async def __call__(self, request: Request):
        try:
            # Parse JSON body
            body = await request.json()

            # Get image data from either base64 or URL
            if "image_base64" in body:
                # Decode base64 image
                image_data = body["image_base64"]
                # Remove data URL prefix if present (e.g., "data:image/png;base64,")
                if "," in image_data:
                    image_data = image_data.split(",", 1)[1]
                img_bytes = base64.b64decode(image_data)
                img_nparray = np.frombuffer(img_bytes, np.uint8)

            elif "image_url" in body:
                # Download image from URL
                image_url = body["image_url"]
                response = requests.get(image_url, timeout=30)
                response.raise_for_status()
                img_bytes = response.content
                img_nparray = np.frombuffer(img_bytes, np.uint8)

            else:
                return JSONResponse({"error": "Either 'image_base64' or 'image_url' must be provided"}, status_code=400)

            # Decode and convert image
            img_nparray = cv2.imdecode(img_nparray, cv2.IMREAD_COLOR)
            if img_nparray is None:
                return JSONResponse({"error": "Failed to decode image"}, status_code=400)
            img_nparray = cv2.cvtColor(img_nparray, cv2.COLOR_BGR2RGB)

            # Get prediction
            pred = await self.texteller_server.predict.remote(img_nparray)

            return JSONResponse({"result": pred})

        except Exception as e:
            return JSONResponse({"error": str(e)}, status_code=500)