import voicerss_tts
import json
from speech_tools import format_filename

def generate_voice(phrase):
    voice = voicerss_tts.speech({
        'key': '0ae89d82aa78460691c99a4ac8c0f9ec',
        'hl': 'en-us',
        'src': phrase,
        'r': '0',
        'c': 'mp3',
        'f': '22khz_16bit_mono',
        'ssml': 'false',
        'b64': 'false'
    })
    if not voice['error']:
        return voice[b'response']
    return None


def generate_test_audio_for_stories():
    story_file = './inputs/all_stories_hs.json'
    # story_file = './inputs/all_stories.json'
    stories_data = json.load(open(story_file))
    text_list_dup = [t[0] for i in stories_data.values() for t in i]
    text_list = sorted(list(set(text_list_dup)))[:10]
    for t in text_list:
        v = generate_voice(t)
        if v:
            f_name = format_filename(t)
            tf = open('inputs/voicerss/'+f_name+'.mp3','wb')
            tf.write(v)
            tf.close()

# def generate_test_audio_for(records_file,audio_group='audio'):
#     # audio_group='audio';model_file = 'siamese_speech_model-305-epoch-0.20-acc.h5'
#     # records_file  = os.path.join('./outputs',eval_group+'.train.tfrecords')
#     const_file = os.path.join('./models/'+audio_group+'/','constants.pkl')
#     (n_spec,n_features,n_records) = pickle.load(open(const_file,'rb'))
#     print('evaluating {}...'.format(records_file))
#     record_iterator,records_count = record_generator_count(records_file)
#     all_results = []
#     for (i,string_record) in tqdm(enumerate(record_iterator),total=records_count):
#         total+=1
#         example = tf.train.Example()
#         example.ParseFromString(string_record)
#         word = example.features.feature['word'].bytes_list.value[0].decode()

# audio = generate_voice('hello world')
# audio