Update app.py

app.py

@@ -1,102 +1,55 @@
 import gradio as gr
 import os
 import subprocess
-import logging
 from datetime import datetime
-
-# Import Departments
 from denoiser import Denoiser
 from transcriber import Transcriber
 from translator import Translator
 
-logging.basicConfig(level=logging.INFO)
-logger = logging.getLogger(__name__)
-
-# Initialize
 denoiser = Denoiser()
 transcriber = Transcriber()
 translator = Translator()
 
 def run_pipeline(audio_input, remove_fillers, remove_stutters, remove_silences, remove_breaths, remove_mouth, target_lang):
-    if not audio_input:
-        return None, "No audio detected. Please upload a file.", ""
-
-    # Create job directory
-    job_id = datetime.now().strftime("%Y%m%d_%H%M%S")
-    output_dir = f"outputs/{job_id}"
-    os.makedirs(output_dir, exist_ok=True)
+    if not audio_input: return None, "No audio detected.", ""
+    
+    out_dir = f"outputs/{datetime.now().strftime('%H%M%S')}"
+    os.makedirs(out_dir, exist_ok=True)
     
     try:
-        # 1. DENOISE & CLEAN (Handles WhatsApp/Any format)
-        logger.info("[Pipeline] Step 1: Denoising & Studio Processing...")
-        res = denoiser.process(
-            audio_input, output_dir,
-            fillers=remove_fillers, stutters=remove_stutters,
-            long_silences=remove_silences, breath=remove_breaths,
-            mouth_sounds=remove_mouth
-        )
+        # 1. Clean (Supports WhatsApp/Any via Denoiser pre-process)
+        res = denoiser.process(audio_input, out_dir, fillers=remove_fillers, stutters=remove_stutters)
         
-        # 2. TRANSCRIBE (Using the clean internal WAV)
-        logger.info("[Pipeline] Step 2: Transcribing...")
-        transcript_data = transcriber.transcribe(res['audio_path'])
-        text = transcript_data['text']
-        
-        # Clean text fillers locally if requested
+        # 2. Transcribe & Translate
+        text = transcriber.transcribe(res['audio_path'])['text']
         if remove_fillers:
             text = denoiser.clean_transcript_fillers(text)
-            
-        # 3. TRANSLATE
-        logger.info(f"[Pipeline] Step 3: Translating to {target_lang}...")
         translated = translator.translate(text, target_lang)
 
-        # 4. FINAL EXPORT: Conversion to MP3
-        final_mp3 = os.path.join(output_dir, "ClearWave_Studio_Final.mp3")
+        # 3. Final MP3 Export
+        final_mp3 = os.path.join(out_dir, "ClearWave_Result.mp3")
         subprocess.run([
             "ffmpeg", "-y", "-i", res['audio_path'],
             "-codec:a", "libmp3lame", "-qscale:a", "2", final_mp3
         ], check=True)
 
         return final_mp3, text, translated
-
     except Exception as e:
-        logger.error(f"Pipeline Error: {e}")
-        return None, f"Error: {str(e)}", ""
+        return None, f"Error: {e}", ""
 
-# ══════════════════════════════════════════════════════════════════
-# GRADIO UI (Gradio 6.0)
-# ══════════════════════════════════════════════════════════════════
-with gr.Blocks(title="ClearWave AI Studio") as demo:
-    gr.Markdown("# 🎙️ ClearWave AI: WhatsApp to Studio MP3")
-    gr.Markdown("Upload any audio (WhatsApp Voice Notes, M4A, WAV) and get a professional MP3.")
-    
+with gr.Blocks() as demo:
+    gr.Markdown("# 🎙️ ClearWave: Any Format ➔ Studio MP3")
     with gr.Row():
         with gr.Column():
-            audio_in = gr.Audio(label="Input Audio File", type="filepath")
-            with gr.Group():
-                gr.Markdown("### Processing Filters")
-                f = gr.Checkbox(label="Remove Fillers", value=True)
-                s = gr.Checkbox(label="Remove Stutters", value=True)
-                z = gr.Checkbox(label="Remove Long Silences", value=True)
-                b = gr.Checkbox(label="Remove Breaths", value=True)
-                m = gr.Checkbox(label="Remove Mouth Noises", value=True)
-            
-            lang = gr.Dropdown(
-                choices=["Hindi", "Telugu", "Spanish", "French", "German"], 
-                value="Hindi", 
-                label="Translation Language"
-            )
-            btn = gr.Button("✨ Generate Studio MP3", variant="primary")
-        
+            audio_in = gr.Audio(label="Input (WhatsApp/WAV/AAC)", type="filepath")
+            f = gr.Checkbox(label="Remove Fillers", value=True)
+            lang = gr.Dropdown(choices=["Hindi", "Telugu", "Spanish"], value="Telugu", label="Translate to")
+            btn = gr.Button("Generate Professional MP3", variant="primary")
         with gr.Column():
-            audio_out = gr.Audio(label="Final Clean MP3", type="filepath")
-            t_out = gr.Textbox(label="Transcript", lines=8)
-            tr_out = gr.Textbox(label="Translation", lines=8)
+            audio_out = gr.Audio(label="Studio MP3 Output")
+            t_out = gr.Textbox(label="Transcript")
+            tr_out = gr.Textbox(label="Translation")
 
-    btn.click(
-        fn=run_pipeline, 
-        inputs=[audio_in, f, s, z, b, m, lang], 
-        outputs=[audio_out, t_out, tr_out]
-    )
+    btn.click(run_pipeline, [audio_in, f, f, f, f, f, lang], [audio_out, t_out, tr_out])
 
-if __name__ == "__main__":
-    demo.launch(theme=gr.themes.Soft())
+demo.launch(theme=gr.themes.Soft())