#!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# Copyright 2016-2099 Ailemon.net
#
# This file is part of ASRT Speech Recognition Tool.
#
# ASRT is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# ASRT is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with ASRT.  If not, see <https://www.gnu.org/licenses/>.
# ============================================================================

"""
@author: nl8590687
ASRT语音识别基于HTTP协议的API服务器程序
"""

import base64
import json
from flask import Flask, Response, request

from speech_model import ModelSpeech
from speech_model_zoo import SpeechModel251
from speech_features import Spectrogram
from LanguageModel2 import ModelLanguage
from utils.ops import decode_wav_bytes

API_STATUS_CODE_OK = 200000 # OK
API_STATUS_CODE_CLIENT_ERROR = 400000
API_STATUS_CODE_CLIENT_ERROR_FORMAT = 400001 # 请求数据格式错误
API_STATUS_CODE_CLIENT_ERROR_FORMAT = 400002 # 请求数据配置不支持
API_STATUS_CODE_SERVER_ERROR = 500000
API_STATUS_CODE_SERVER_ERROR_RUNNING = 500001 # 服务器运行中出错

app = Flask("ASRT API Service")

AUDIO_LENGTH = 1600
AUDIO_FEATURE_LENGTH = 200
CHANNELS = 1
# 默认输出的拼音的表示大小是1428，即1427个拼音+1个空白块
OUTPUT_SIZE = 1428
sm251 = SpeechModel251(
    input_shape=(AUDIO_LENGTH, AUDIO_FEATURE_LENGTH, CHANNELS),
    output_size=OUTPUT_SIZE
    )
feat = Spectrogram()
ms = ModelSpeech(sm251, feat, max_label_length=64)
ms.load_model('save_models/' + sm251.get_model_name() + '.model.h5')

ml = ModelLanguage('model_language')
ml.LoadModel()


class AsrtApiResponse:
    '''
    ASRT语音识别基于HTTP协议的API接口响应类
    '''
    def __init__(self, status_code, status_message='', result=''):
        self.status_code = status_code
        self.status_message = status_message
        self.result = result
    def to_json(self):
        '''
        类转json
        '''
        return json.dumps(self, default=lambda o: o.__dict__,
            sort_keys=True)

# api接口根url:GET
@app.route('/', methods=["GET"])
def index_get():
    '''
    根路径handle GET方法
    '''
    buffer = ''
    with open('assets/default.html', 'r', encoding='utf-8') as file_handle:
        buffer = file_handle.read()
    return Response(buffer, mimetype='text/html; charset=utf-8')

# api接口根url:POST
@app.route('/', methods=["POST"])
def index_post():
    '''
    根路径handle POST方法
    '''
    json_data = AsrtApiResponse(API_STATUS_CODE_OK, 'ok')
    buffer = json_data.to_json()
    return Response(buffer, mimetype='application/json')

# 获取分类列表
@app.route('/<level>', methods=["POST"])
def recognition_post(level):
    '''
    其他路径 POST方法
    '''
    #读取json文件内容
    try:
        if level == 'speech':
            request_data = request.get_json()
            samples = request_data['samples']
            wavdata_bytes = base64.urlsafe_b64decode(bytes(samples,encoding='utf-8'))
            sample_rate = request_data['sample_rate']
            channels = request_data['channels']
            byte_width = request_data['byte_width']

            wavdata = decode_wav_bytes(samples_data=wavdata_bytes,
                                    channels=channels, byte_width=byte_width)
            result = ms.recognize_speech(wavdata, sample_rate)

            json_data = AsrtApiResponse(API_STATUS_CODE_OK, 'speech level')
            json_data.result = result
            buffer = json_data.to_json()
            print('output:', buffer)
            return Response(buffer, mimetype='application/json')
        elif level == 'language':
            request_data = request.get_json()

            seq_pinyin = request_data['sequence_pinyin']

            result = ml.SpeechToText(seq_pinyin)

            json_data = AsrtApiResponse(API_STATUS_CODE_OK, 'language level')
            json_data.result = result
            buffer = json_data.to_json()
            print('output:', buffer)
            return Response(buffer, mimetype='application/json')
        elif level == 'all':
            request_data = request.get_json()

            samples = request_data['samples']
            wavdata_bytes = base64.urlsafe_b64decode(samples)
            sample_rate = request_data['sample_rate']
            channels = request_data['channels']
            byte_width = request_data['byte_width']

            wavdata = decode_wav_bytes(samples_data=wavdata_bytes,
                                        channels=channels, byte_width=byte_width)
            result_speech = ms.recognize_speech(wavdata, sample_rate)
            result = ml.SpeechToText(result_speech)

            json_data = AsrtApiResponse(API_STATUS_CODE_OK, 'all level')
            json_data.result = result
            buffer = json_data.to_json()
            print('output:', buffer)
            return Response(buffer, mimetype='application/json')
        else:
            request_data = request.get_json()
            print('input:', request_data)
            json_data = AsrtApiResponse(API_STATUS_CODE_CLIENT_ERROR, '')
            buffer = json_data.to_json()
            print('output:', buffer)
            return Response(buffer, mimetype='application/json')
    except Exception as except_general:
        request_data = request.get_json()
        #print(request_data['sample_rate'], request_data['channels'],
        # request_data['byte_width'], len(request_data['samples']),
        # request_data['samples'][-100:])
        json_data = AsrtApiResponse(API_STATUS_CODE_SERVER_ERROR, str(except_general))
        buffer = json_data.to_json()
        return Response(buffer, mimetype='application/json')


if __name__ == '__main__':
    # for development env
    #app.run(host='0.0.0.0', port=20001)
    # for production env
    import waitress
    waitress.serve(app, host='0.0.0.0', port=20001)