Update denoiser.py

denoiser.py

@@ -13,42 +13,70 @@ class Denoiser:
     def __init__(self):
         self.api_key = os.environ.get("CLEANVOICE_API_KEY", "")
         if self.api_key:
-            print("[Denoiser] ☁️ Cleanvoice API Ready")
+            print("[Denoiser] ☁️ Cleanvoice API Ready (WhatsApp Support Active)")
+        else:
+            print("[Denoiser] ⚠️ No CLEANVOICE_API_KEY found — will use preprocessed WAV only")
 
     def process(self, audio_path: str, out_dir: str, **kwargs) -> dict:
+        # Step A: Pre-convert to standard WAV (Handles .opus, .aac, .m4a)
         standard_input = os.path.join(out_dir, "input_converted.wav")
-        subprocess.run([
-            "ffmpeg", "-y", "-i", audio_path,
-            "-ar", "16000", "-ac", "1", "-acodec", "pcm_s16le",
-            standard_input
+        result = subprocess.run([
+            "ffmpeg", "-y", "-i", audio_path, 
+            "-ar", "16000", "-ac", "1", standard_input
         ], capture_output=True)
 
+        # Fallback to original if FFmpeg fails
+        if result.returncode != 0 or not os.path.exists(standard_input):
+            logger.warning("[Denoiser] FFmpeg conversion failed — using original file")
+            standard_input = audio_path
+
         try:
+            from cleanvoice import Cleanvoice
             cv = Cleanvoice({'api_key': self.api_key})
-            supported_kwargs = {k: v for k, v in kwargs.items() 
-                              if k in ["fillers", "stutters", "long_silences"]}
             
+            # Step B: Process via Cleanvoice API
+            supported_kwargs = {k: v for k, v in kwargs.items() if k in ["fillers", "stutters", "long_silences"]}
             result = cv.process(
-                standard_input,
-                remove_noise=True,
-                studio_sound=True,
+                standard_input, 
+                remove_noise=True, 
+                studio_sound=True, 
                 **supported_kwargs
             )
-
+            
+            # Step C: Download the processed WAV file
             audio_data = requests.get(result.audio.url, timeout=60).content
-            final_wav = os.path.join(out_dir, "clean_output.wav")
-            with open(final_wav, "wb") as f:
+            wav_output = os.path.join(out_dir, "clean_output.wav")
+            with open(wav_output, "wb") as f:
                 f.write(audio_data)
-            return {'audio_path': final_wav}
-
+            
+            # ✅ NEW: Convert WAV → MP3 (high quality)
+            mp3_output = os.path.join(out_dir, "clean_output.mp3")
+            subprocess.run([
+                "ffmpeg", "-y", "-i", wav_output,
+                "-codec:a", "libmp3lame", "-b:a", "192k",
+                "-ar", "44100", "-ac", "2",
+                mp3_output
+            ], capture_output=True)
+            
+            return {'audio_path': mp3_output}  # Returns MP3!
+            
         except Exception as e:
-            logger.error(f"Cleanvoice failed: {e}")
-            return {'audio_path': standard_input}
+            logger.error(f"Denoiser error: {e}")
+            
+            # Fallback: Convert original to MP3
+            fallback_mp3 = os.path.join(out_dir, "fallback.mp3")
+            subprocess.run([
+                "ffmpeg", "-y", "-i", audio_path,
+                "-codec:a", "libmp3lame", "-b:a", "192k",
+                fallback_mp3
+            ], capture_output=True)
+            return {'audio_path': fallback_mp3}
 
     def clean_transcript_fillers(self, transcript: str) -> str:
         fillers = {"um", "umm", "uh", "basically", "like", "ante", "ane"}
         words = transcript.split()
         return " ".join([w for w in words if re.sub(r'[^a-z]', '', w.lower()) not in fillers])
 
+    # Important: Dummy methods to prevent "AttributeError" in app.py
     def _remove_fillers(self, audio, sr, segments): return audio, 0
     def _remove_stutters(self, audio, sr, segments): return audio, 0