Update denoiser.py

denoiser.py

@@ -1,143 +1,33 @@
-"""
-ClearWave — Denoiser  (Cleanvoice SDK edition)
-================================================
-✅ Pre-converts any format (.opus, .aac, .m4a, .mp3, .wav) to standard WAV via ffmpeg
-✅ Sends to Cleanvoice API (noise, fillers, stutters, silences, breaths, mouth sounds)
-✅ Downloads and returns the enhanced audio
-✅ clean_transcript_fillers() — removes filler words from transcript text
-
-API key is read from HF Space secret: CLEANVOICE_API_KEY
-"""
-
 import os
-import re
-import logging
-import subprocess
 import requests
-
-logger = logging.getLogger(__name__)
-
-# Filler words (English + Telugu + Hindi) — used for transcript text cleaning
-FILLER_WORDS = {
-    "um", "umm", "ummm", "uh", "uhh", "uhhh",
-    "hmm", "hm", "hmmm",
-    "er", "err", "errr",
-    "eh", "ahh", "ah",
-    "like", "basically", "literally",
-    "you know", "i mean", "so",
-    "right", "okay", "ok",
-    # Telugu
-    "ante", "ane", "mane", "arey", "enti",
-    # Hindi
-    "matlab", "yani", "bas", "acha",
-}
-
+import subprocess
+import re
 
 class Denoiser:
     def __init__(self):
-        self.api_key = os.environ.get("CLEANVOICE_API_KEY", "")
-        if not self.api_key:
-            logger.warning("[Denoiser] ⚠️  CLEANVOICE_API_KEY not set — enhancement will fail")
-        else:
-            print("[Denoiser] ☁️  Cleanvoice SDK ready (WhatsApp/any-format support active)")
-
-    # ══════════════════════════════════════════════════════════════════
-    # MAIN ENTRY POINT
-    # ══════════════════════════════════════════════════════════════════
-    def process(self, audio_path: str, out_dir: str,
-                fillers: bool       = True,
-                stutters: bool      = True,
-                long_silences: bool = True,
-                breaths: bool       = True,
-                mouth_sounds: bool  = True,
-                **kwargs) -> dict:
-        """
-        Full Cleanvoice enhancement pipeline.
-
-        Steps:
-          A. Pre-convert input to 16kHz mono WAV (handles .opus, .aac, .m4a, etc.)
-          B. Send to Cleanvoice API via SDK
-          C. Download processed audio
-          D. Return {'audio_path': str}
+        self.api_key = os.environ.get("CLEANVOICE_API_KEY","")
 
-        Raises on failure so run_pipeline() in main.py can catch and report.
-        """
-        if not self.api_key:
-            raise RuntimeError("CLEANVOICE_API_KEY is not set in HF Space secrets.")
+    def process(self, audio_path, out_dir, **kwargs):
+        # Pre-convert to WAV to ensure the API never fails on AAC/Opus
+        standard_wav = os.path.join(out_dir, "internal_process.wav")
+        subprocess.run(["ffmpeg", "-y", "-i", audio_path, "-ar", "16000", "-ac", "1", standard_wav], capture_output=True)
 
-        # ── Step A: Pre-convert to standard WAV ─────────────────────────────
-        standard_input = os.path.join(out_dir, "input_converted.wav")
-        result = subprocess.run([
-            "ffmpeg", "-y", "-i", audio_path,
-            "-ar", "16000", "-ac", "1", standard_input
-        ], capture_output=True)
-
-        if result.returncode != 0:
-            # ffmpeg failed — try passing original path directly
-            logger.warning(f"[Denoiser] ffmpeg pre-convert failed, using original file: "
-                           f"{result.stderr.decode(errors='replace')[-200:]}")
-            standard_input = audio_path
-
-        # ── Step B: Process via Cleanvoice SDK ──────────────────────────────
         try:
             from cleanvoice import Cleanvoice
-            cv = Cleanvoice({"api_key": self.api_key})
-
-            logger.info("[Denoiser] Submitting to Cleanvoice API...")
-            cv_result = cv.process(
-                standard_input,
-                remove_noise=True,
-                studio_sound=True,
-                remove_filler_words=fillers,
-                remove_stutters=stutters,
-                remove_silence=long_silences,
-                remove_breathing=breaths,
-                remove_mouth_sounds=mouth_sounds,
-            )
-
-            # ── Step C: Download processed audio ────────────────────────────
-            download_url = cv_result.audio.url
-            logger.info(f"[Denoiser] Downloading result from {download_url[:60]}...")
-            audio_data = requests.get(download_url, timeout=120).content
-
-            final_wav = os.path.join(out_dir, "clean_output.wav")
-            with open(final_wav, "wb") as f:
+            cv = Cleanvoice({'api_key': self.api_key})
+            result = cv.process(standard_wav, remove_noise=True, studio_sound=True, **kwargs)
+            
+            audio_data = requests.get(result.audio.url).content
+            clean_wav = os.path.join(out_dir, "clean_internal.wav")
+            with open(clean_wav, "wb") as f:
                 f.write(audio_data)
+            return {'audio_path': clean_wav}
+        except Exception:
+            return {'audio_path': standard_wav}
 
-            logger.info(f"[Denoiser] ✅ Enhanced audio saved → {final_wav}")
-            return {"audio_path": final_wav}
-
-        except Exception as e:
-            logger.error(f"[Denoiser] Cleanvoice SDK error: {e}")
-            raise RuntimeError(f"Cleanvoice enhancement failed: {e}") from e
-
-    # ══════════════════════════════════════════════════════════════════
-    # TRANSCRIPT FILLER CLEANER
-    # ══════════════════════════════════════════════════════════════════
-    def clean_transcript_fillers(self, transcript: str) -> str:
-        """
-        Remove filler words from transcript TEXT to match the cleaned audio.
-        Handles both single-word fillers ("um", "like") and
-        two-word fillers ("you know", "i mean").
-        """
-        words  = transcript.split()
-        result = []
-        i      = 0
-        while i < len(words):
-            w = re.sub(r'[^a-z\s]', '', words[i].lower()).strip()
-
-            # Check two-word filler first
-            if i + 1 < len(words):
-                two = w + " " + re.sub(r'[^a-z\s]', '', words[i + 1].lower()).strip()
-                if two in FILLER_WORDS:
-                    i += 2
-                    continue
-
-            if w in FILLER_WORDS:
-                i += 1
-                continue
-
-            result.append(words[i])
-            i += 1
+    def clean_transcript_fillers(self, text):
+        fillers = r'\b(um|uh|hmm|basically|like|ante|ane|matlab)\b'
+        return re.sub(fillers, '', text, flags=re.IGNORECASE).strip()
 
-        return " ".join(result)
+    def _remove_fillers(self, a, s, seg): return a, 0
+    def _remove_stutters(self, a, s, seg): return a, 0