Update main.py

main.py

@@ -15,8 +15,8 @@ API_TOKEN = os.environ["API_TOKEN"]
 MODEL_PATH = os.environ["MODEL_PATH"]
 PITCH_PATH = os.environ["PITCH_PATH"]
 
-# QUANTIZED_MODEL_PATH = hf_hub_download(repo_id=MODEL_PATH, filename='quantized_model.pt', token=API_TOKEN)
-# QUANTIZED_PITCH_MODEL_PATH = hf_hub_download(repo_id=PITCH_PATH, filename='quantized_model.pt', token=API_TOKEN)
+QUANTIZED_MODEL_PATH = hf_hub_download(repo_id=MODEL_PATH, filename='quantized_model.pt', token=API_TOKEN)
+QUANTIZED_PITCH_MODEL_PATH = hf_hub_download(repo_id=PITCH_PATH, filename='quantized_model.pt', token=API_TOKEN)
 
 
 ## word preprocessor
@@ -102,10 +102,7 @@ async def predict(
             Levenshtein Distance Score from pitch and word
 
     """
-    upload_audio = ffmpeg_read(file, sampling_rate=16000)
-    # print(upload_audio.shape)
-    # print(np.sum(np.abs(upload_audio)))
-    debug = np.sum(np.abs(upload_audio))               
+    upload_audio = ffmpeg_read(file, sampling_rate=16000)           
     audio_duration = len(upload_audio) / 16000
     current_time = datetime.datetime.now().strftime("%Y-%h-%d-%H:%M:%S")
     start_time = time.time()
@@ -150,5 +147,4 @@ async def predict(
             "wrong word index": wrong_word,
             "wrong pitch index": wrong_pitch,
             "score": score,
-            "debug": debug,
             }