#!/usr/bin/env python3
"""
gRPC server of LocalAI for NVIDIA NEMO Toolkit ASR.
"""
from concurrent import futures
import time
import argparse
import signal
import sys
import os
import backend_pb2
import backend_pb2_grpc
import torch
import nemo.collections.asr as nemo_asr

import grpc


def is_float(s):
    try:
        float(s)
        return True
    except ValueError:
        return False


def is_int(s):
    try:
        int(s)
        return True
    except ValueError:
        return False


_ONE_DAY_IN_SECONDS = 60 * 60 * 24
MAX_WORKERS = int(os.environ.get('PYTHON_GRPC_MAX_WORKERS', '1'))


class BackendServicer(backend_pb2_grpc.BackendServicer):
    def Health(self, request, context):
        return backend_pb2.Reply(message=bytes("OK", 'utf-8'))

    def LoadModel(self, request, context):
        if torch.cuda.is_available():
            device = "cuda"
        else:
            device = "cpu"
        mps_available = hasattr(torch.backends, "mps") and torch.backends.mps.is_available()
        if mps_available:
            device = "mps"
        if not torch.cuda.is_available() and request.CUDA:
            return backend_pb2.Result(success=False, message="CUDA is not available")

        self.device = device
        self.options = {}

        for opt in request.Options:
            if ":" not in opt:
                continue
            key, value = opt.split(":", 1)
            if is_float(value):
                value = float(value)
            elif is_int(value):
                value = int(value)
            elif value.lower() in ["true", "false"]:
                value = value.lower() == "true"
            self.options[key] = value

        model_name = request.Model or "nvidia/parakeet-tdt-0.6b-v3"

        try:
            print(f"Loading NEMO ASR model from {model_name}", file=sys.stderr)
            self.model = nemo_asr.models.ASRModel.from_pretrained(model_name=model_name)
            print("NEMO ASR model loaded successfully", file=sys.stderr)
        except Exception as err:
            print(f"[ERROR] LoadModel failed: {err}", file=sys.stderr)
            import traceback
            traceback.print_exc(file=sys.stderr)
            return backend_pb2.Result(success=False, message=str(err))

        return backend_pb2.Result(message="Model loaded successfully", success=True)

    def AudioTranscription(self, request, context):
        result_segments = []
        text = ""
        try:
            audio_path = request.dst
            if not audio_path or not os.path.exists(audio_path):
                print(f"Error: Audio file not found: {audio_path}", file=sys.stderr)
                return backend_pb2.TranscriptResult(segments=[], text="")

            # NEMO's transcribe method accepts a list of audio paths and returns a list of transcripts
            results = self.model.transcribe([audio_path])

            if not results or len(results) == 0:
                return backend_pb2.TranscriptResult(segments=[], text="")

            # Get the transcript text from the first result
            text = results[0]
            if text:
                # Create a single segment with the full transcription
                result_segments.append(backend_pb2.TranscriptSegment(
                    id=0, start=0, end=0, text=text
                ))

        except Exception as err:
            print(f"Error in AudioTranscription: {err}", file=sys.stderr)
            import traceback
            traceback.print_exc(file=sys.stderr)
            return backend_pb2.TranscriptResult(segments=[], text="")

        return backend_pb2.TranscriptResult(segments=result_segments, text=text)


def serve(address):
    server = grpc.server(
        futures.ThreadPoolExecutor(max_workers=MAX_WORKERS),
        options=[
            ('grpc.max_message_length', 50 * 1024 * 1024),
            ('grpc.max_send_message_length', 50 * 1024 * 1024),
            ('grpc.max_receive_message_length', 50 * 1024 * 1024),
        ])
    backend_pb2_grpc.add_BackendServicer_to_server(BackendServicer(), server)
    server.add_insecure_port(address)
    server.start()
    print("Server started. Listening on: " + address, file=sys.stderr)

    def signal_handler(sig, frame):
        print("Received termination signal. Shutting down...")
        server.stop(0)
        sys.exit(0)

    signal.signal(signal.SIGINT, signal_handler)
    signal.signal(signal.SIGTERM, signal_handler)

    try:
        while True:
            time.sleep(_ONE_DAY_IN_SECONDS)
    except KeyboardInterrupt:
        server.stop(0)


if __name__ == "__main__":
    parser = argparse.ArgumentParser(description="Run the gRPC server.")
    parser.add_argument("--addr", default="localhost:50051", help="The address to bind the server to.")
    args = parser.parse_args()
    serve(args.addr)