app.py

import os
import subprocess
import json
from datetime import timedelta
import tempfile
import re
import yt_dlp
import gradio as gr
import groq
from groq import Groq


# setup groq 

client = Groq(api_key=os.environ.get("Groq_Api_Key"))

def handle_groq_error(e, model_name):
 error_data = e.args[0]

 if isinstance(error_data, str):
 # Use regex to extract the JSON part of the string
 json_match = re.search(r'(\{.*\})', error_data)
 if json_match:
 json_str = json_match.group(1)
 # Ensure the JSON string is well-formed
 json_str = json_str.replace("'", '"') # Replace single quotes with double quotes
 error_data = json.loads(json_str)

 if isinstance(e, groq.AuthenticationError):
 if isinstance(error_data, dict) and 'error' in error_data and 'message' in error_data['error']:
 error_message = error_data['error']['message']
 raise gr.Error(error_message)
 elif isinstance(e, groq.RateLimitError):
 if isinstance(error_data, dict) and 'error' in error_data and 'message' in error_data['error']:
 error_message = error_data['error']['message']
 error_message = re.sub(r'org_[a-zA-Z0-9]+', 'org_(censored)', error_message) # censor org
 raise gr.Error(error_message)
 else:
 raise gr.Error(f"Error during Groq API call: {e}")


# language codes for subtitle maker

LANGUAGE_CODES = {
 "English": "en",
 "Chinese": "zh",
 "German": "de",
 "Spanish": "es",
 "Russian": "ru",
 "Korean": "ko",
 "French": "fr",
 "Japanese": "ja",
 "Portuguese": "pt",
 "Turkish": "tr",
 "Polish": "pl",
 "Catalan": "ca",
 "Dutch": "nl",
 "Arabic": "ar",
 "Swedish": "sv",
 "Italian": "it",
 "Indonesian": "id",
 "Hindi": "hi",
 "Finnish": "fi",
 "Vietnamese": "vi",
 "Hebrew": "he",
 "Ukrainian": "uk",
 "Greek": "el",
 "Malay": "ms",
 "Czech": "cs",
 "Romanian": "ro",
 "Danish": "da",
 "Hungarian": "hu",
 "Tamil": "ta",
 "Norwegian": "no",
 "Thai": "th",
 "Urdu": "ur",
 "Croatian": "hr",
 "Bulgarian": "bg",
 "Lithuanian": "lt",
 "Latin": "la",
 "Māori": "mi",
 "Malayalam": "ml",
 "Welsh": "cy",
 "Slovak": "sk",
 "Telugu": "te",
 "Persian": "fa",
 "Latvian": "lv",
 "Bengali": "bn",
 "Serbian": "sr",
 "Azerbaijani": "az",
 "Slovenian": "sl",
 "Kannada": "kn",
 "Estonian": "et",
 "Macedonian": "mk",
 "Breton": "br",
 "Basque": "eu",
 "Icelandic": "is",
 "Armenian": "hy",
 "Nepali": "ne",
 "Mongolian": "mn",
 "Bosnian": "bs",
 "Kazakh": "kk",
 "Albanian": "sq",
 "Swahili": "sw",
 "Galician": "gl",
 "Marathi": "mr",
 "Panjabi": "pa",
 "Sinhala": "si",
 "Khmer": "km",
 "Shona": "sn",
 "Yoruba": "yo",
 "Somali": "so",
 "Afrikaans": "af",
 "Occitan": "oc",
 "Georgian": "ka",
 "Belarusian": "be",
 "Tajik": "tg",
 "Sindhi": "sd",
 "Gujarati": "gu",
 "Amharic": "am",
 "Yiddish": "yi",
 "Lao": "lo",
 "Uzbek": "uz",
 "Faroese": "fo",
 "Haitian": "ht",
 "Pashto": "ps",
 "Turkmen": "tk",
 "Norwegian Nynorsk": "nn",
 "Maltese": "mt",
 "Sanskrit": "sa",
 "Luxembourgish": "lb",
 "Burmese": "my",
 "Tibetan": "bo",
 "Tagalog": "tl",
 "Malagasy": "mg",
 "Assamese": "as",
 "Tatar": "tt",
 "Hawaiian": "haw",
 "Lingala": "ln",
 "Hausa": "ha",
 "Bashkir": "ba",
 "jw": "jw",
 "Sundanese": "su",
}


# download link input 
def yt_dlp_download(link):
 try:
 ydl_opts = {
 'format': 'bestvideo+bestaudio/best', # Download best video and audio or best available
 'outtmpl': '%(title)s.%(ext)s',
 'nocheckcertificate': True,
 'ignoreerrors': False,
 'no_warnings': True,
 'quiet': True,
 }

 with yt_dlp.YoutubeDL(ydl_opts) as ydl:
 ydl.download([link])
 result = ydl.extract_info(link, download=False)
 download_path = ydl.prepare_filename(result)

 return download_path
 except yt_dlp.utils.DownloadError as e:
 raise gr.Error(f"Download Error: {e}")
 except ValueError as e:
 raise gr.Error(f"Invalid Link or Format Error: {e}")
 except Exception as e:
 raise gr.Error(f"An unexpected error occurred: {e}")


# helper functions

def split_audio(input_file_path, chunk_size_mb):
 chunk_size = chunk_size_mb * 1024 * 1024 # Convert MB to bytes
 file_number = 1
 chunks = []
 with open(input_file_path, 'rb') as f:
 chunk = f.read(chunk_size)
 while chunk:
 chunk_name = f"{os.path.splitext(input_file_path)[0]}_part{file_number:03}.mp3" # Pad file number for correct ordering
 with open(chunk_name, 'wb') as chunk_file:
 chunk_file.write(chunk)
 chunks.append(chunk_name)
 file_number += 1
 chunk = f.read(chunk_size)
 return chunks

def merge_audio(chunks, output_file_path):
 with open("temp_list.txt", "w") as f:
 for file in chunks:
 f.write(f"file '{file}'\n")
 try:
 subprocess.run(
 [
 "ffmpeg",
 "-f",
 "concat",
 "-safe", "0",
 "-i",
 "temp_list.txt",
 "-c",
 "copy",
 "-y",
 output_file_path
 ],
 check=True
 )
 os.remove("temp_list.txt")
 for chunk in chunks:
 os.remove(chunk)
 except subprocess.CalledProcessError as e:
 raise gr.Error(f"Error during audio merging: {e}")


# Checks file extension, size, and downsamples or splits if needed.

ALLOWED_FILE_EXTENSIONS = ["mp3", "mp4", "mpeg", "mpga", "m4a", "wav", "webm"]
MAX_FILE_SIZE_MB = 25
CHUNK_SIZE_MB = 25

def check_file(input_file_path):
 if not input_file_path:
 raise gr.Error("Please upload an audio/video file.")

 file_size_mb = os.path.getsize(input_file_path) / (1024 * 1024)
 file_extension = input_file_path.split(".")[-1].lower()

 if file_extension not in ALLOWED_FILE_EXTENSIONS:
 raise gr.Error(f"Invalid file type (.{file_extension}). Allowed types: {', '.join(ALLOWED_FILE_EXTENSIONS)}")

 if file_size_mb > MAX_FILE_SIZE_MB:
 gr.Warning(
 f"File size too large ({file_size_mb:.2f} MB). Attempting to downsample to 16kHz MP3 128kbps. Maximum size allowed: {MAX_FILE_SIZE_MB} MB"
 )

 output_file_path = os.path.splitext(input_file_path)[0] + "_downsampled.mp3"
 try:
 subprocess.run(
 [
 "ffmpeg",
 "-i",
 input_file_path,
 "-ar",
 "16000",
 "-ab",
 "128k",
 "-ac",
 "1",
 "-f",
 "mp3",
 "-y",
 output_file_path,
 ],
 check=True
 )

 # Check size after downsampling
 downsampled_size_mb = os.path.getsize(output_file_path) / (1024 * 1024)
 if downsampled_size_mb > MAX_FILE_SIZE_MB:
 gr.Warning(f"File still too large after downsampling ({downsampled_size_mb:.2f} MB). Splitting into {CHUNK_SIZE_MB} MB chunks.")
 return split_audio(output_file_path, CHUNK_SIZE_MB), "split"

 return output_file_path, None
 except subprocess.CalledProcessError as e:
 raise gr.Error(f"Error during downsampling: {e}")
 return input_file_path, None


# subtitle maker

def format_time(seconds):
 hours = int(seconds // 3600)
 minutes = int((seconds % 3600) // 60)
 seconds = int(seconds % 60)
 milliseconds = int((seconds % 1) * 1000)

 return f"{hours:02}:{minutes:02}:{seconds:02},{milliseconds:03}"

def json_to_srt(transcription_json):
 srt_lines = []

 for segment in transcription_json:
 start_time = format_time(segment['start'])
 end_time = format_time(segment['end'])
 text = segment['text']

 srt_line = f"{segment['id']+1}\n{start_time} --> {end_time}\n{text}\n"
 srt_lines.append(srt_line)

 return '\n'.join(srt_lines)


def generate_subtitles(input_mode, input_file, link_input, prompt, language, auto_detect_language, model, include_video, font_selection, font_file, font_color, font_size, outline_thickness, outline_color):
 if input_mode == "Upload Video/Audio File":
 input_file_path = input_file
 elif input_mode == "Link Video/Audio":
 input_file_path = yt_dlp_download(link_input)
 
 processed_path, split_status = check_file(input_file_path)
 full_srt_content = ""
 total_duration = 0
 segment_id_offset = 0

 if split_status == "split":
 srt_chunks = []
 video_chunks = []
 for i, chunk_path in enumerate(processed_path):
 try:
 with open(chunk_path, "rb") as file:
 transcription_json_response = client.audio.transcriptions.create(
 file=(os.path.basename(chunk_path), file.read()),
 model=model,
 prompt=prompt,
 response_format="verbose_json",
 language=None if auto_detect_language else language,
 temperature=0.0,
 )
 transcription_json = transcription_json_response.segments

 # Adjust timestamps and segment IDs
 for segment in transcription_json:
 segment['start'] += total_duration
 segment['end'] += total_duration
 segment['id'] += segment_id_offset
 segment_id_offset += len(transcription_json)
 total_duration += transcription_json[-1]['end'] # Update total duration

 srt_content = json_to_srt(transcription_json)
 full_srt_content += srt_content
 temp_srt_path = f"{os.path.splitext(chunk_path)[0]}.srt"
 with open(temp_srt_path, "w", encoding="utf-8") as temp_srt_file:
 temp_srt_file.write(srt_content)
 temp_srt_file.write("\n") # add a new line at the end of the srt chunk file to fix format when merged
 srt_chunks.append(temp_srt_path)

 if include_video and input_file_path.lower().endswith((".mp4", ".webm")):
 try:
 output_file_path = chunk_path.replace(os.path.splitext(chunk_path)[1], "_with_subs" + os.path.splitext(chunk_path)[1])
 # Handle font selection
 if font_selection == "Custom Font File" and font_file:
 font_name = os.path.splitext(os.path.basename(font_file.name))[0] # Get font filename without extension
 font_dir = os.path.dirname(font_file.name) # Get font directory path
 elif font_selection == "Custom Font File" and not font_file:
 font_name = None # Let FFmpeg use its default Arial
 font_dir = None # No font directory
 gr.Warning(f"You want to use a Custom Font File, but uploaded none. Using the default Arial font.")
 elif font_selection == "Arial":
 font_name = None # Let FFmpeg use its default Arial
 font_dir = None # No font directory
 
 # FFmpeg command
 subprocess.run(
 [
 "ffmpeg",
 "-y",
 "-i",
 chunk_path,
 "-vf",
 f"subtitles={temp_srt_path}:fontsdir={font_dir}:force_style='Fontname={font_name},Fontsize={int(font_size)},PrimaryColour=&H{font_color[1:]}&,OutlineColour=&H{outline_color[1:]}&,BorderStyle={int(outline_thickness)},Outline=1'",
 "-preset", "fast",
 output_file_path,
 ],
 check=True,
 )
 video_chunks.append(output_file_path) 
 except subprocess.CalledProcessError as e:
 raise gr.Error(f"Error during subtitle addition: {e}") 
 elif include_video and not input_file_path.lower().endswith((".mp4", ".webm")):
 gr.Warning(f"You have checked on the 'Include Video with Subtitles', but the input file {input_file_path} isn't a video (.mp4 or .webm). Returning only the SRT File.", duration=15)
 except groq.AuthenticationError as e:
 handle_groq_error(e, model)
 except groq.RateLimitError as e:
 handle_groq_error(e, model)
 gr.Warning(f"API limit reached during chunk {i+1}. Returning processed chunks only.")
 if srt_chunks and video_chunks:
 merge_audio(video_chunks, 'merged_output_video.mp4')
 with open('merged_output.srt', 'w', encoding="utf-8") as outfile:
 for chunk_srt in srt_chunks:
 with open(chunk_srt, 'r', encoding="utf-8") as infile:
 outfile.write(infile.read())
 return 'merged_output.srt', 'merged_output_video.mp4'
 else:
 raise gr.Error("Subtitle generation failed due to API limits.")

 # Merge SRT chunks
 final_srt_path = os.path.splitext(input_file_path)[0] + "_final.srt"
 with open(final_srt_path, 'w', encoding="utf-8") as outfile:
 for chunk_srt in srt_chunks:
 with open(chunk_srt, 'r', encoding="utf-8") as infile:
 outfile.write(infile.read())

 # Merge video chunks
 if video_chunks:
 merge_audio(video_chunks, 'merged_output_video.mp4')
 return final_srt_path, 'merged_output_video.mp4'
 else:
 return final_srt_path, None

 else: # Single file processing (no splitting)
 try:
 with open(processed_path, "rb") as file:
 transcription_json_response = client.audio.transcriptions.create(
 file=(os.path.basename(processed_path), file.read()),
 model=model,
 prompt=prompt,
 response_format="verbose_json",
 language=None if auto_detect_language else language,
 temperature=0.0,
 )
 transcription_json = transcription_json_response.segments

 srt_content = json_to_srt(transcription_json)
 temp_srt_path = os.path.splitext(input_file_path)[0] + ".srt"
 with open(temp_srt_path, "w", encoding="utf-8") as temp_srt_file:
 temp_srt_file.write(srt_content)

 if include_video and input_file_path.lower().endswith((".mp4", ".webm")):
 try:
 output_file_path = input_file_path.replace(
 os.path.splitext(input_file_path)[1], "_with_subs" + os.path.splitext(input_file_path)[1]
 )
 # Handle font selection
 if font_selection == "Custom Font File" and font_file:
 font_name = os.path.splitext(os.path.basename(font_file.name))[0] # Get font filename without extension
 font_dir = os.path.dirname(font_file.name) # Get font directory path
 elif font_selection == "Custom Font File" and not font_file:
 font_name = None # Let FFmpeg use its default Arial
 font_dir = None # No font directory
 gr.Warning(f"You want to use a Custom Font File, but uploaded none. Using the default Arial font.")
 elif font_selection == "Arial":
 font_name = None # Let FFmpeg use its default Arial
 font_dir = None # No font directory

 # FFmpeg command
 subprocess.run(
 [
 "ffmpeg",
 "-y",
 "-i",
 input_file_path,
 "-vf",
 f"subtitles={temp_srt_path}:fontsdir={font_dir}:force_style='FontName={font_name},Fontsize={int(font_size)},PrimaryColour=&H{font_color[1:]}&,OutlineColour=&H{outline_color[1:]}&,BorderStyle={int(outline_thickness)},Outline=1'",
 "-preset", "fast",
 output_file_path,
 ],
 check=True,
 )
 return temp_srt_path, output_file_path
 except subprocess.CalledProcessError as e:
 raise gr.Error(f"Error during subtitle addition: {e}")
 elif include_video and not input_file_path.lower().endswith((".mp4", ".webm")):
 gr.Warning(f"You have checked on the 'Include Video with Subtitles', but the input file {input_file_path} isn't a video (.mp4 or .webm). Returning only the SRT File.", duration=15)
 
 return temp_srt_path, None
 except groq.AuthenticationError as e:
 handle_groq_error(e, model)
 except groq.RateLimitError as e:
 handle_groq_error(e, model)
 except ValueError as e:
 raise gr.Error(f"Error creating SRT file: {e}")


theme = gr.themes.Soft(
 primary_hue="sky",
 secondary_hue="blue",
 neutral_hue="neutral"
).set(
 border_color_primary='*neutral_300',
 block_border_width='1px',
 block_border_width_dark='1px',
 block_title_border_color='*secondary_100',
 block_title_border_color_dark='*secondary_200',
 input_background_fill_focus='*secondary_300',
 input_border_color='*border_color_primary',
 input_border_color_focus='*secondary_500',
 input_border_width='1px',
 input_border_width_dark='1px',
 slider_color='*secondary_500',
 slider_color_dark='*secondary_600'
)

css = """
.gradio-container{max-width: 1400px !important}
h1{text-align:center}
.extra-option {
 display: none;
}
.extra-option.visible {
 display: block;
}
"""



with gr.Blocks(theme=theme, css=css) as interface:
 gr.Markdown(
 """
 # Fast Subtitle Maker
 Inference by Groq API 
 If you are having API Rate Limit issues, you can retry later based on the [rate limits](https://console.groq.com/docs/rate-limits) or <a href="https://huggingface.co/spaces/Nick088/Fast-Subtitle-Maker?duplicate=true" style="display: inline-block;margin-top: .5em;margin-right: .25em;" target="_blank"> <img style="margin-bottom: 0em;display: inline;margin-top: -.25em;" src="https://img.shields.io/badge/-Duplicate%20Space-blue?labelColor=white&style=flat&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAAXNSR0IArs4c6QAAAP5JREFUOE+lk7FqAkEURY+ltunEgFXS2sZGIbXfEPdLlnxJyDdYB62sbbUKpLbVNhyYFzbrrA74YJlh9r079973psed0cvUD4A+4HoCjsA85X0Dfn/RBLBgBDxnQPfAEJgBY+A9gALA4tcbamSzS4xq4FOQAJgCDwV2CPKV8tZAJcAjMMkUe1vX+U+SMhfAJEHasQIWmXNN3abzDwHUrgcRGmYcgKe0bxrblHEB4E/pndMazNpSZGcsZdBlYJcEL9Afo75molJyM2FxmPgmgPqlWNLGfwZGG6UiyEvLzHYDmoPkDDiNm9JR9uboiONcBXrpY1qmgs21x1QwyZcpvxt9NS09PlsPAAAAAElFTkSuQmCC&logoWidth=14" alt="Duplicate Space"></a> with <a href=https://console.groq.com/keys>your own API Key</a> </p>
 Hugging Face Space by [Nick088](https://linktr.ee/Nick088) 
 <br> <a href="https://discord.gg/osai"> <img src="https://img.shields.io/discord/1198701940511617164?color=%23738ADB&label=Discord&style=for-the-badge" alt="Discord"> </a> 
 """
 )

 with gr.Column():
 # Input mode selection
 input_mode = gr.Dropdown(choices=["Upload Video/Audio File", "Link Video/Audio"], value="Upload Video/Audio File", label="Input Mode")
 # Input components
 input_file = gr.File(label="Upload Audio/Video", file_types=[f".{ext}" for ext in ALLOWED_FILE_EXTENSIONS], visible=True)
 link_input_info = gr.Markdown("Using yt-dlp to download Youtube Video Links + other platform's ones. Check [all supported sites](https://github.com/yt-dlp/yt-dlp/blob/master/supportedsites.md)!", visible=False)
 link_input = gr.Textbox(label="Enter Video/Audio Link", visible=False)

 # Model and options
 model_choice_subtitles = gr.Dropdown(choices=["whisper-large-v3", "distil-whisper-large-v3-en"], value="whisper-large-v3", label="Audio Speech Recogition (ASR) Model")
 transcribe_prompt_subtitles = gr.Textbox(label="Prompt (Optional)", info="Specify any context or spelling corrections.")
 with gr.Row():
 language_subtitles = gr.Dropdown(choices=[(lang, code) for lang, code in LANGUAGE_CODES.items()], value="en", label="Language")
 auto_detect_language_subtitles = gr.Checkbox(label="Auto Detect Language")

 # Generate button
 transcribe_button_subtitles = gr.Button("Generate Subtitles")

 # Output and settings
 include_video_option = gr.Checkbox(label="Include Video with Subtitles")
 gr.Markdown("The SubText Rip (SRT) File, contains the subtitles, you can upload this to any video editing app for adding the subs to your video and also modify/stilyze them")
 srt_output = gr.File(label="SRT Output File")
 show_subtitle_settings = gr.Checkbox(label="Show Subtitle Video Settings", visible=False)
 with gr.Row(visible=False) as subtitle_video_settings:
 with gr.Column():
 font_selection = gr.Radio(["Arial", "Custom Font File"], value="Arial", label="Font Selection", info="Select what font to use")
 font_file = gr.File(label="Upload Font File (TTF or OTF)", file_types=[".ttf", ".otf"], visible=False)
 font_color = gr.ColorPicker(label="Font Color", value="#FFFFFF")
 font_size = gr.Slider(label="Font Size (in pixels)", minimum=10, maximum=60, value=24, step=1)
 outline_thickness = gr.Slider(label="Outline Thickness", minimum=0, maximum=5, value=1, step=1)
 outline_color = gr.ColorPicker(label="Outline Color", value="#000000")

 
 video_output = gr.Video(label="Output Video with Subtitles", visible=False)


 # Event bindings

 # input mode
 def toggle_input(mode):
 if mode == "Upload Video/Audio File":
 return gr.update(visible=True), gr.update(visible=False), gr.update(visible=False)
 else:
 return gr.update(visible=False), gr.update(visible=True), gr.update(visible=True)

 input_mode.change(fn=toggle_input, inputs=[input_mode], outputs=[input_file, link_input_info, link_input])

 # show video output
 include_video_option.change(lambda include_video: gr.update(visible=include_video), inputs=[include_video_option], outputs=[video_output])
 # show video output subs settings checkbox
 include_video_option.change(lambda include_video: gr.update(visible=include_video), inputs=[include_video_option], outputs=[show_subtitle_settings])
 # show video output subs settings
 show_subtitle_settings.change(lambda show: gr.update(visible=show), inputs=[show_subtitle_settings], outputs=[subtitle_video_settings])
 # uncheck show subtitle settings checkbox if include video is unchecked (to make the output subs settings not visible)
 show_subtitle_settings.change(lambda show, include_video: gr.update(visible=show and include_video), inputs=[show_subtitle_settings, include_video_option], outputs=[show_subtitle_settings])
 # show custom font file selection
 font_selection.change(lambda font_selection: gr.update(visible=font_selection == "Custom Font File"), inputs=[font_selection], outputs=[font_file])
 
 # Update language dropdown based on model selection
 def update_language_options(model):
 if model == "distil-whisper-large-v3-en":
 return gr.update(choices=[("English", "en")], value="en", interactive=False)
 else:
 return gr.update(choices=[(lang, code) for lang, code in LANGUAGE_CODES.items()], value="en", interactive=True)

 model_choice_subtitles.change(fn=update_language_options, inputs=[model_choice_subtitles], outputs=[language_subtitles])

 # Modified generate subtitles event
 transcribe_button_subtitles.click(
 fn=generate_subtitles,
 inputs=[
 input_mode,
 input_file,
 link_input,
 transcribe_prompt_subtitles,
 language_subtitles,
 auto_detect_language_subtitles,
 model_choice_subtitles,
 include_video_option,
 font_selection,
 font_file,
 font_color,
 font_size,
 outline_thickness,
 outline_color,
 ],
 outputs=[srt_output, video_output],
 )

interface.launch(share=True)