Update app.py

app.py

@@ -4,10 +4,11 @@ from t2a import text_to_audio
 import joblib
 from sentence_transformers import SentenceTransformer
 import numpy as np
+import os
 
 reg = joblib.load('text_reg.joblib')
 model = SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2')
-finetune = "davinci:ft-personal:autodrummer-v4-2022-11-01-22-44-58"
+finetune = os.environ['finetune']
 
 def get_note_text(prompt):
     prompt = prompt + " ->"
@@ -24,24 +25,22 @@ def get_note_text(prompt):
     )
     return response.choices[0].text.strip()
 
-def get_drummer_output(prompt, openai_api_key):
-    openai.api_key = openai_api_key
+def get_drummer_output(prompt):
+    openai.api_key = os.environ['key']
     note_text = get_note_text(prompt)
     # note_text = note_text + " " + note_text
-    # note_text = "k n k n k n k n s n h n k n s n k n k n k n k n k n k n h n k n n"
     prompt_enc = model.encode([prompt])
     bpm = int(reg.predict(prompt_enc)[0]) + 20
     print(bpm, "bpm", "notes are", note_text)
     audio = text_to_audio(note_text, bpm)
-    # audio to numpy
     audio = np.array(audio.get_array_of_samples(), dtype=np.float32)
     return (96000, audio)
 
 iface = gr.Interface(
     fn=get_drummer_output,
-    inputs=["text", "text"],
+    inputs="text",
     outputs="audio",
-    title='Auto-drummer',
-    description='Stable Diffusion for drum beats. Type in a genre and some descriptors to the prompt box, enter your OpenAI API key, and get a drum beat in that genre'
+    title='Autodrummer',
+    description="Stable Diffusion for drum beats. Type in a genre and some descriptors (e.g., 'hiphop groove 808') to the prompt box and get a drum beat in that genre"
 )
 iface.launch()