NeuralFalcon
commited on
Update app.py
Browse files
app.py
CHANGED
@@ -137,6 +137,78 @@ def combine_word_segments(words_timestamp, max_words_per_subtitle=8, min_silence
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return before_translate
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def convert_time_to_srt_format(seconds):
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""" Convert seconds to SRT time format (HH:MM:SS,ms) """
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@@ -162,15 +234,20 @@ def write_subtitles_to_file(subtitles, filename="subtitles.srt"):
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# Write the text and speaker information
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f.write(f"{entry['text']}\n\n")
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-
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with open(srt_path, 'w', encoding='utf-8') as srt_file:
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for i, word_info in enumerate(words_timestamp, start=1):
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start_time = convert_time_to_srt_format(word_info['start'])
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end_time = convert_time_to_srt_format(word_info['end'])
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word=word_info['word']
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word =
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srt_file.write(f"{i}\n{start_time} --> {end_time}\n{word}\n\n")
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def generate_srt_from_sentences(sentence_timestamp, srt_path="default_subtitle.srt"):
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with open(srt_path, 'w', encoding='utf-8') as srt_file:
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for index, sentence in enumerate(sentence_timestamp):
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@@ -214,9 +291,9 @@ def whisper_subtitle(uploaded_file,Source_Language,max_words_per_subtitle=8):
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del faster_whisper_model
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gc.collect()
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torch.cuda.empty_cache()
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-
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word_segments=combine_word_segments(words_timestamp, max_words_per_subtitle=max_words_per_subtitle, min_silence_between_words=0.5)
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-
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#setup srt file names
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base_name = os.path.basename(uploaded_file).rsplit('.', 1)[0][:30]
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save_name = f"{subtitle_folder}/{base_name}_{src_lang}.srt"
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@@ -224,22 +301,24 @@ def whisper_subtitle(uploaded_file,Source_Language,max_words_per_subtitle=8):
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original_txt_name=original_srt_name.replace(".srt",".txt")
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word_level_srt_name=original_srt_name.replace(".srt","_word_level.srt")
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customize_srt_name=original_srt_name.replace(".srt","_customize.srt")
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generate_srt_from_sentences(sentence_timestamp, srt_path=original_srt_name)
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word_level_srt(words_timestamp, srt_path=word_level_srt_name)
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write_subtitles_to_file(word_segments, filename=customize_srt_name)
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with open(original_txt_name, 'w', encoding='utf-8') as f1:
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f1.write(text)
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return original_srt_name,customize_srt_name,word_level_srt_name,original_txt_name
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#@title Using Gradio Interface
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def subtitle_maker(Audio_or_Video_File,Source_Language,max_words_per_subtitle):
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try:
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default_srt_path,customize_srt_path,word_level_srt_path,text_path=whisper_subtitle(Audio_or_Video_File,Source_Language,max_words_per_subtitle=max_words_per_subtitle)
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except Exception as e:
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print(f"Error in whisper_subtitle: {e}")
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default_srt_path,customize_srt_path,word_level_srt_path,text_path=None,None,None,None
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return default_srt_path,customize_srt_path,word_level_srt_path,text_path
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@@ -262,6 +341,7 @@ available_language=language_dict.keys()
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source_lang_list.extend(available_language)
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@click.command()
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@click.option("--debug", is_flag=True, default=False, help="Enable debug mode.")
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@click.option("--share", is_flag=True, default=False, help="Enable sharing of the interface.")
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@@ -279,6 +359,7 @@ def main(debug, share):
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gr.File(label="Default SRT File", show_label=True),
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gr.File(label="Customize SRT File", show_label=True),
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gr.File(label="Word Level SRT File", show_label=True),
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gr.File(label="Text File", show_label=True)
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]
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@@ -288,4 +369,4 @@ def main(debug, share):
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# Launch Gradio with command-line options
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demo.queue().launch(debug=debug, share=share)
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if __name__ == "__main__":
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main()
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return before_translate
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def custom_word_segments(words_timestamp, min_silence_between_words=0.3, max_characters_per_subtitle=17):
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before_translate = []
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id = 1
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text = ""
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start = None
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end = None
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last_end_time = None
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i = 0
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while i < len(words_timestamp):
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word = words_timestamp[i]['word']
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word_start = words_timestamp[i]['start']
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word_end = words_timestamp[i]['end']
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# Look ahead to check if the next word (i+1) starts with a hyphen
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if i + 1 < len(words_timestamp) and words_timestamp[i + 1]['word'].startswith("-"):
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# Combine the current word and the next word (i, i+1) if next word starts with a hyphen
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combined_text = word + words_timestamp[i + 1]['word'][:] # Skip the hyphen and combine
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combined_start_time = word_start
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combined_end_time = words_timestamp[i + 1]['end']
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i += 1 # Skip the next word (i+1) since it has been combined
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# Look ahead for the next non-hyphenated word, check further if needed (i+2, i+3, etc.)
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while i + 1 < len(words_timestamp) and words_timestamp[i + 1]['word'].startswith("-"):
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combined_text += words_timestamp[i + 1]['word'][:] # Add word excluding hyphen
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combined_end_time = words_timestamp[i + 1]['end']
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i += 1 # Skip the next hyphenated word
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else:
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# No hyphen at the next word, just take the current word
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combined_text = word
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combined_start_time = word_start
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combined_end_time = word_end
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# Check if the combined text exceeds the maximum character limit
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if len(text) + len(combined_text) > max_characters_per_subtitle:
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# If accumulated text is non-empty, store it as a subtitle
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if text:
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before_translate.append({
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"word": text.strip(),
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"start": start,
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"end": end
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})
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id += 1
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# Start a new subtitle with the combined text
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text = combined_text
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start = combined_start_time
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else:
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# Accumulate text
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if not text:
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start = combined_start_time
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text += " " + combined_text
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# Update the end timestamp
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end = combined_end_time
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last_end_time = end
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# Move to the next word
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i += 1
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# Add the final subtitle segment if text is not empty
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if text:
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before_translate.append({
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"word": text.strip(),
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"start": start,
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"end": end
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})
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return before_translate
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def convert_time_to_srt_format(seconds):
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""" Convert seconds to SRT time format (HH:MM:SS,ms) """
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# Write the text and speaker information
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f.write(f"{entry['text']}\n\n")
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def word_level_srt(words_timestamp, srt_path="world_level_subtitle.srt",shorts=False):
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punctuation_pattern = re.compile(r'[.,!?;:"\–—_~^+*|]')
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with open(srt_path, 'w', encoding='utf-8') as srt_file:
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for i, word_info in enumerate(words_timestamp, start=1):
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start_time = convert_time_to_srt_format(word_info['start'])
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end_time = convert_time_to_srt_format(word_info['end'])
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word=word_info['word']
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word =re.sub(punctuation_pattern, '', word)
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if shorts==False:
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word=word.replace("-","")
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srt_file.write(f"{i}\n{start_time} --> {end_time}\n{word}\n\n")
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def generate_srt_from_sentences(sentence_timestamp, srt_path="default_subtitle.srt"):
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with open(srt_path, 'w', encoding='utf-8') as srt_file:
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for index, sentence in enumerate(sentence_timestamp):
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del faster_whisper_model
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gc.collect()
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torch.cuda.empty_cache()
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word_segments=combine_word_segments(words_timestamp, max_words_per_subtitle=max_words_per_subtitle, min_silence_between_words=0.5)
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shorts_segments=custom_word_segments(words_timestamp, min_silence_between_words=0.3, max_characters_per_subtitle=17)
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#setup srt file names
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base_name = os.path.basename(uploaded_file).rsplit('.', 1)[0][:30]
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save_name = f"{subtitle_folder}/{base_name}_{src_lang}.srt"
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original_txt_name=original_srt_name.replace(".srt",".txt")
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word_level_srt_name=original_srt_name.replace(".srt","_word_level.srt")
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customize_srt_name=original_srt_name.replace(".srt","_customize.srt")
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shorts_srt_name=original_srt_name.replace(".srt","_shorts.srt")
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generate_srt_from_sentences(sentence_timestamp, srt_path=original_srt_name)
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word_level_srt(words_timestamp, srt_path=word_level_srt_name)
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word_level_srt(shorts_segments, srt_path=shorts_srt_name,shorts=True)
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write_subtitles_to_file(word_segments, filename=customize_srt_name)
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with open(original_txt_name, 'w', encoding='utf-8') as f1:
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f1.write(text)
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return original_srt_name,customize_srt_name,word_level_srt_name,shorts_srt_name,original_txt_name
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#@title Using Gradio Interface
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def subtitle_maker(Audio_or_Video_File,Source_Language,max_words_per_subtitle):
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try:
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default_srt_path,customize_srt_path,word_level_srt_path,shorts_srt_name,text_path=whisper_subtitle(Audio_or_Video_File,Source_Language,max_words_per_subtitle=max_words_per_subtitle)
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except Exception as e:
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print(f"Error in whisper_subtitle: {e}")
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default_srt_path,customize_srt_path,word_level_srt_path,shorts_srt_name,text_path=None,None,None,None,None
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return default_srt_path,customize_srt_path,word_level_srt_path,shorts_srt_name,text_path
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source_lang_list.extend(available_language)
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@click.command()
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@click.option("--debug", is_flag=True, default=False, help="Enable debug mode.")
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@click.option("--share", is_flag=True, default=False, help="Enable sharing of the interface.")
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gr.File(label="Default SRT File", show_label=True),
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gr.File(label="Customize SRT File", show_label=True),
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gr.File(label="Word Level SRT File", show_label=True),
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gr.File(label="SRT File For Shorts", show_label=True),
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gr.File(label="Text File", show_label=True)
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]
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# Launch Gradio with command-line options
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demo.queue().launch(debug=debug, share=share)
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if __name__ == "__main__":
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main()
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