better audits better prints

app.py

@@ -18,19 +18,24 @@ def main ():
 
     labels = entity_labels
 
-    text = "I have a proposal from cgd where they want one outsystems junior developers and one senior for an estimate of three hundred euros a day, for six months."
-    print(f"get entities from sample text: {text}")
-    get_entity_labels(model=ner, text=text, labels=labels)
+    # text = "I have a proposal from cgd where they want one outsystems junior developers and one senior for an estimate of three hundred euros a day, for six months."
+    # print(f"get entities from sample text: {text}")
+    # get_entity_labels(model=ner, text=text, labels=labels)
 
-    print("Render UI")
+    print("Rendering UI...")
+    start_render = set_start()
     wav_audio_data = st_audiorec()
+    audit_elapsedtime(function="Rendering UI", start=start_render)
 
     if wav_audio_data is not None and rec is not None:
         print("Loading data...")
+        start_loading = set_start()
         st.audio(wav_audio_data, format='audio/wav')
         text = transcribe(wav_audio_data, rec)
         if text is not None:    
             get_entity_labels(labels=labels, model=ner, text=text)
+        
+        audit_elapsedtime(function="Loading data", start=start_loading)
 
 
 def init_model_trans ():
@@ -73,6 +78,7 @@ def init_model_ner():
     return model
 
 def transcribe (audio_sample: bytes, pipe) -> str:
+    print("Initiating transcription...")
     start = set_start()
     # dataset = load_dataset("distil-whisper/librispeech_long", "clean", split="validation")
     # sample = dataset[0]["audio"]
@@ -84,6 +90,7 @@ def transcribe (audio_sample: bytes, pipe) -> str:
     return result["text"]
 
 def get_entity_labels(model: GLiNER, text: str, labels: list): #-> Lead_labels:
+    print("Initiating entity recognition...")
     start = set_start()
     entities = model.predict_entities(text, labels)
     audit_elapsedtime(function="Retreiving entity labels from text", start=start)