Add sentiment scoring to complete sonification.

app.py

@@ -33,7 +33,9 @@ from huggingface_hub import hf_hub_download
 print('Downloading model.')
 model_cache_path = hf_hub_download(repo_id="psistolar/musicautobot-fine1", filename="model.pth")
 
+from transformers import pipeline
 
+classifier = pipeline("sentiment-analysis")
 
 # Default config options
 config = default_config()
@@ -62,6 +64,8 @@ def sonify_text(text, sentiment):
 
     note_names = [f"{letter.upper()}4" for letter in text.lower() if letter in musical_letters]
 
+
+
     p = music21.stream.Part()
     if sentiment == 'NEGATIVE':
         # If negative, use TODO 
@@ -99,13 +103,18 @@ def process_midi(MIDI_File, Text_to_Sonify, Randomness, Amount_of_Music_to_Add):
     
     # create the model input object
     if sonification:
-        sentiment = 'NEGATIVE'
+        sentiment_analysis = classifier(Text_to_Sonify)[0]
+        sentiment = sentiment_analysis['label']
+        score = sentiment_analysis['score']
         item = sonify_text(Text_to_Sonify, sentiment)
+        # the lower our confidence in the sentiment, the more randomness we inject
+        score = max(0.25, score)
+        temp = Randomness / (100 * score)
     else:
         item = MusicItem.from_file(name, data.vocab)
+        temp = Randomness / 100
 
     # full is the prediction appended to the input
-    temp = Randomness / 100
     pred, full = learner.predict(
         item, 
         n_words=Amount_of_Music_to_Add,