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import gradio as gr
from subtitle import subtitle_maker,LANGUAGE_CODE
source_lang_list = ['Automatic', "English", "Hindi", "Bengali"]
available_language = LANGUAGE_CODE.keys()
source_lang_list.extend(available_language)
target_lang_list = ["English", "Hindi", "Bengali"]
target_lang_list.extend(available_language)
def update_target_lang(selected_src):
"""Update target language automatically when source changes."""
if selected_src == "Automatic":
return "English"
else:
return selected_src
def ui1():
with gr.Blocks() as demo:
gr.HTML("""
<div style="text-align: center; margin: 20px auto; max-width: 800px;">
<h1 style="font-size: 2.5em; margin-bottom: 10px;">π¬ Auto Subtitle Generator</h1>
<p style="font-size: 1.2em; color: #555; margin-bottom: 15px;">If you have a large video, upload the audio instead, it's much faster to upload.</p>
<a href="https://github.com/NeuralFalconYT/Auto-Subtitle-Generator-Free" target="_blank" style="display: inline-block; padding: 10px 20px; background-color: #4285F4; color: white; border-radius: 6px; text-decoration: none; font-size: 1em;">π Run on Google Colab</a>
</div>
""")
with gr.Row():
with gr.Column():
upload_media = gr.File(label="Upload Audio or Video File")
input_lang = gr.Dropdown(label="Source Language", choices=source_lang_list, value="English")
generate_btn = gr.Button("π Generate Subtitle", variant="primary")
with gr.Accordion("βοΈ Translation using Google Translator", open=False):
output_lang = gr.Dropdown(label="Translate Into", choices=target_lang_list, value="English")
with gr.Column():
default_srt = gr.File(label="π― Original Subtitles (Default Generated by whisper)")
customized_srt = gr.File(label="π Readable Subtitles (Multi-line)")
word_level_srt = gr.File(label="π Word-by-Word Subtitles")
with gr.Accordion("π Other Subtitle Formats", open=False):
translated_srt = gr.File(label="π Translated Subtitles")
shorts_srt = gr.File(label="π± Shorts/Reels Subtitles")
transcript_txt = gr.File(label="π Full Transcript (Text File)")
subtitle_json= gr.File(label="π Full Transcript (JSON File) To make .ass file")
word_json= gr.File(label="π Shorts Transcript (JSON File) To make .ass file")
transcript_box = gr.Textbox(label="ποΈ Transcript Preview", lines=4,show_copy_button=True)
generate_btn.click(
fn=subtitle_maker,
inputs=[upload_media, input_lang, output_lang],
outputs=[default_srt, translated_srt, customized_srt, word_level_srt, shorts_srt, transcript_txt, subtitle_json,word_json,transcript_box]
)
input_lang.change(
fn=update_target_lang,
inputs=input_lang,
outputs=output_lang
)
# Add example runs (optional)
# gr.Examples(
# examples=[
# ["sample.mp3", "English", "English"],
# ["sample.wav", "English", "Hindi"],
# ],
# inputs=[upload_media, input_lang, output_lang]
# )
return demo
def prompt_translation(language):
"""
Generates a dubbing-friendly translation prompt for an .srt subtitle file.
Tailored for natural speech and timing accuracy.
"""
prompt = f"""
-------------- You are a professional subtitle translator for **video dubbing**.
Translate the following `.srt` subtitle file into **{language}** while preserving timing, meaning, and emotional tone.
Output in JSON format exactly like this:
```json
{{
"subtitle sequence number": {{
"timestamp": "original timestamp",
"actual subtitle text": "original English subtitle line",
"dubbing": "natural, dubbing-friendly {language} translation"
}}
}}
```
**Guidelines for Translation:**
1. **Understand the full context** before translating β read the entire subtitle file first.
2. Translate into **natural, conversational {language}**, not a direct word-for-word translation.
6. Keep translations **roughly similar in length** to the original so lip movements sync naturally.
"""
return prompt
def prompt_fix_grammar(language="English"):
"""
Generates a dubbing-friendly grammar correction prompt for an .srt subtitle file.
Tailored for natural speech and timing accuracy.
"""
prompt = f"""
-------------- You are a professional subtitle editor for **video dubbing**.
Fix the grammar, spelling, and awkward phrasing in the following `.srt` subtitle file while preserving timing, meaning, and emotional tone. Β
Do NOT translate β keep everything in {language}.
Output in JSON format exactly like this:
```json
{{
"subtitle sequence number": {{
"timestamp": "original timestamp",
"actual subtitle text": "original {language} subtitle line",
"dubbing": "natural, dubbing-friendly corrected {language} line"
}}
}}
```
**Guidelines for Grammar Fixing:**
1. **Understand the full context** before editing β read the entire subtitle file first.
2. Correct grammar, spelling, and phrasing errors while keeping the same meaning.
4. Keep corrections **roughly similar in length** to the original so lip movements sync naturally.
"""
return prompt
def prompt_srt_to_romanized(language="Hindi"):
"""
Generates a prompt for converting a .srt subtitle file
from any language to a Romanized (Latin letters) version,
preserving timing, meaning, punctuation, and formatting.
"""
prompt = f"""
-------------- You are a professional subtitle editor tasked with converting subtitles to Romanized text.
Your task is to convert a `.srt` subtitle file from {language} to **Romanized {language}**,
keeping everything exactly the same except using Latin letters for all words.
**Instructions:**
1. Preserve the original timestamp of each subtitle.
2. Keep the original meaning, punctuation, and formatting intact.
3. Convert **only the original subtitle text** to Roman letters, word by word.
4. Do not add, remove, or change any words.
5. Output in strict JSON format exactly like this:
```json
{{
"subtitle sequence number": {{
"timestamp": "original timestamp",
"original subtitle text": "original {language} subtitle line",
"dubbing": "Romanized, {language} line of original subtitle text"
}}
}}
````
Focus entirely on **accurate Romanization**; do not modify anything else.
"""
return prompt
import pysrt
def prompt_maker(srt_path, target_language, task="Translation"):
txt_path = srt_path.replace(".srt", ".txt")
subs = pysrt.open(srt_path, encoding='utf-8')
with open(txt_path, 'w', encoding='utf-8') as f:
for sub in subs:
f.write(f"{sub.index}\n")
f.write(f"{sub.start} --> {sub.end}\n")
f.write(f"{sub.text}\n\n")
if task == "Translation":
f.write(prompt_translation(target_language))
if task=="Romanization":
f.write(prompt_srt_to_romanized(target_language))
else:
f.write(prompt_fix_grammar(target_language))
with open(txt_path, 'r', encoding='utf-8') as f:
content = f.read()
# return both prompt text and original path
return content, srt_path
import pysrt
import json
import os
def json_to_srt(json_script, srt_path):
"""
Convert dubbing-friendly JSON back into .srt
Uses original srt_path to name output <name>_dubbing.srt
"""
os.makedirs("./dubbing_srt", exist_ok=True)
base_name = os.path.basename(srt_path)
name_no_ext, _ = os.path.splitext(base_name)
output_srt_path = os.path.join("./dubbing_srt", f"{name_no_ext}_dubbing.srt")
# Load JSON
if isinstance(json_script, str):
json_object = json.loads(json_script)
else:
json_object = json_script
# Write to file
with open(output_srt_path, "w", encoding="utf-8") as f:
for i, (key, value) in enumerate(json_object.items(), start=1):
f.write(f"{i}\n")
f.write(f"{value['timestamp']}\n")
f.write(f"{value['dubbing']}\n\n")
return output_srt_path
def ui2():
with gr.Blocks() as demo:
gr.Markdown("<center><h1 style='font-size: 32px;'>π¬ Subtitle Translation Using LLM</h1></center>")
# hidden state to keep original srt path
srt_state = gr.State("")
with gr.Row():
with gr.Column():
gr.Markdown("### Step 1: Generate Prompt")
srt_file = gr.File(label="Upload .srt file generated by Whisper", file_types=[".srt"])
task = gr.Dropdown(
["Translation","Romanization","Fix Grammar [English to English for dubbing]"],
label="Select Task",
value="Translation",
)
language = gr.Dropdown(target_lang_list, label="Select the language you want to translate into", value="English")
generate_btn = gr.Button("Generate Prompt")
output_prompt = gr.Textbox(
label="Copy & Paste this prompt in https://aistudio.google.com/",
lines=20,
show_copy_button=True
)
with gr.Column():
gr.Markdown("### Step 2: Paste JSON & Convert Back to SRT")
json_input = gr.Textbox(
label="Paste JSON script from https://aistudio.google.com/ ",
lines=20,
placeholder="Paste the JSON output here..."
)
convert_btn = gr.Button("Convert JSON β SRT")
srt_file_out = gr.File(label="Download new .srt")
# Button actions
generate_btn.click(
fn=prompt_maker,
inputs=[srt_file, language, task],
outputs=[output_prompt, srt_state],
)
convert_btn.click(
fn=json_to_srt,
inputs=[json_input, srt_state],
outputs=srt_file_out,
)
return demo
import click
@click.command()
@click.option("--debug", is_flag=True, default=False, help="Enable debug mode.")
@click.option("--share", is_flag=True, default=False, help="Enable sharing of the interface.")
def main(share,debug):
# def main(debug=True, share=True):
demo1 = ui1()
demo2 = ui2()
custom_css = """.gradio-container { font-family: 'SF Pro Display', -apple-system, BlinkMacSystemFont, sans-serif; }"""
demo = gr.TabbedInterface([demo1, demo2], ["Generate SRT File", "SRT Translation"], title="",theme=gr.themes.Soft(),css=custom_css)
demo.queue().launch(share=share,debug=debug)
if __name__ == "__main__":
main() |