Update app.py

app.py

@@ -70,7 +70,6 @@ def srt_to_vtt(srt_path):
     vtt_content = "WEBVTT\n\n"
     
     # Replace comma timestamps (00:00:01,000) with dot (00:00:01.000)
-    # And copy the rest
     vtt_content += re.sub(r'(\d{2}:\d{2}:\d{2}),(\d{3})', r'\1.\2', content)
     
     with open(vtt_path, 'w', encoding='utf-8') as f:
@@ -113,7 +112,8 @@ def create_srt_segments(chunks, total_video_duration):
         else:
             start_time, end_time = 0.0, None
         
-        if end_time is None: end_time = total_video_duration
+        if end_time is None: 
+            end_time = total_video_duration
         
         lines = split_text_into_lines(text, max_chars=80)
         duration = end_time - start_time
@@ -149,12 +149,12 @@ def batch_translate(texts, src_lang, tgt_lang, batch_size=8, progress=gr.Progres
     return results
 
 def process_translation(filepath, src_lang_code, tgt_lang_code):
-    if filepath is None: return None, None
+    if filepath is None: return None
     try:
         with open(filepath, 'r', encoding='utf-8') as f:
             subtitles = list(srt.parse(f.read()))
     except Exception as e:
-        return f"Error: {str(e)}", None
+        return f"Error: {str(e)}"
 
     texts = [sub.content for sub in subtitles]
     translated = batch_translate(texts, src_lang_code, tgt_lang_code)
@@ -199,7 +199,7 @@ def video_to_srt(video_path, progress=gr.Progress()):
     # 4. Create Preview (HTML + VTT)
     vtt_path = srt_to_vtt(srt_path)
     
-    # We use Gradio's /file/ route to serve local files
+    # Create the HTML player
     html_preview = f"""
     <h3>Video Preview</h3>
     <video controls width="100%" height="400px" style="background:black">
@@ -226,9 +226,7 @@ with gr.Blocks(title="SRT Master Tool") as demo:
                 video_input = gr.Video(label="Upload Video", sources=["upload"])
                 
                 with gr.Column():
-                    # The new Preview Player
                     preview_output = gr.HTML(label="Preview Player")
-                    # The download button
                     srt_output_gen = gr.File(label="Download Generated SRT")
             
             btn1 = gr.Button("Generate SRT & Preview", variant="primary")
@@ -248,116 +246,4 @@ with gr.Blocks(title="SRT Master Tool") as demo:
             btn2.click(process_translation, inputs=[srt_input, src_l, tgt_l], outputs=srt_output_trans)
 
 if __name__ == "__main__":
-    demo.launch()
-        for line in lines:
-            current_end = current_start + duration_per_line
-            
-            srt_subtitles.append(
-                srt.Subtitle(
-                    index=index_counter,
-                    start=timedelta(seconds=current_start),
-                    end=timedelta(seconds=current_end),
-                    content=line
-                )
-            )
-            index_counter += 1
-            current_start = current_end # Next line starts where this one ended
-
-    return srt_subtitles
-
-# ---------------------------------------------------------
-# Logic 1: Translation (NLLB)
-# ---------------------------------------------------------
-def batch_translate(texts, src_lang, tgt_lang, batch_size=8, progress=gr.Progress()):
-    results = []
-    tokenizer_nllb.src_lang = src_lang
-    
-    for i, start_idx in enumerate(range(0, len(texts), batch_size)):
-        batch = texts[start_idx : start_idx + batch_size]
-        inputs = tokenizer_nllb(batch, return_tensors="pt", padding=True, truncation=True, max_length=512)
-        forced_bos_token_id = tokenizer_nllb.convert_tokens_to_ids(tgt_lang)
-        
-        with torch.no_grad():
-            generated_tokens = model_nllb.generate(**inputs, forced_bos_token_id=forced_bos_token_id, max_length=512)
-            
-        results.extend(tokenizer_nllb.batch_decode(generated_tokens, skip_special_tokens=True))
-    return results
-
-def process_translation(filepath, src_lang_code, tgt_lang_code):
-    if filepath is None: return None
-    try:
-        with open(filepath, 'r', encoding='utf-8') as f:
-            subtitles = list(srt.parse(f.read()))
-    except Exception as e:
-        return f"Error: {str(e)}"
-
-    texts = [sub.content for sub in subtitles]
-    translated = batch_translate(texts, src_lang_code, tgt_lang_code)
-    
-    for sub, trans in zip(subtitles, translated):
-        sub.content = trans
-
-    out_path = "translated_subtitles.srt"
-    with open(out_path, 'w', encoding='utf-8') as f:
-        f.write(srt.compose(subtitles))
-    return out_path
-
-# ---------------------------------------------------------
-# Logic 2: Video to SRT (Whisper)
-# ---------------------------------------------------------
-def video_to_srt(video_path, progress=gr.Progress()):
-    if video_path is None: return None
-    
-    progress(0.1, desc="Extracting Audio...")
-    try:
-        audio_path = extract_audio(video_path)
-    except Exception as e:
-        return f"Error extracting audio: {str(e)}"
-    
-    progress(0.3, desc="Transcribing...")
-    # We enable return_timestamps=True to get segment-level timing
-    outputs = whisper_pipe(audio_path, return_timestamps=True, generate_kwargs={"language": "english"})
-    
-    chunks = outputs.get("chunks", [])
-    if not chunks:
-        chunks = [{"text": outputs.get("text", ""), "timestamp": (0.0, 5.0)}]
-
-    progress(0.8, desc="Formatting SRT...")
-    
-    # Use the new Smart Splitter function
-    srt_subtitles = create_srt_segments(chunks)
-    
-    out_path = "generated_captions.srt"
-    with open(out_path, 'w', encoding='utf-8') as f:
-        f.write(srt.compose(srt_subtitles))
-        
-    return out_path
-
-# ---------------------------------------------------------
-# Gradio Interface
-# ---------------------------------------------------------
-with gr.Blocks(title="SRT Master Tool") as demo:
-    gr.Markdown("# 🎬 Auto Subtitle & Translator")
-    
-    with gr.Tabs():
-        with gr.TabItem("Step 1: Video to SRT"):
-            gr.Markdown("### Convert Video to English Subtitles")
-            with gr.Row():
-                video_input = gr.Video(label="Upload Video")
-                srt_output_gen = gr.File(label="Generated SRT")
-            btn1 = gr.Button("Generate SRT", variant="primary")
-            btn1.click(video_to_srt, inputs=video_input, outputs=srt_output_gen)
-
-        with gr.TabItem("Step 2: Translate SRT"):
-            gr.Markdown("### Translate Subtitles to Arabic")
-            with gr.Row():
-                srt_input = gr.File(label="Upload SRT")
-                with gr.Column():
-                    src_l = gr.Dropdown(["eng_Latn", "fra_Latn"], label="From", value="eng_Latn")
-                    tgt_l = gr.Dropdown(["arb_Arab", "arz_Arab"], label="To", value="arb_Arab")
-                srt_output_trans = gr.File(label="Translated SRT")
-            btn2 = gr.Button("Translate", variant="primary")
-            btn2.click(process_translation, inputs=[srt_input, src_l, tgt_l], outputs=srt_output_trans)
-
-if __name__ == "__main__":
-    demo.launch()
+    demo.launch()