Create model.py

model.py

@@ -0,0 +1,71 @@
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+from music21 import converter, instrument, note, chord, stream
+import gradio as gr
+
+# Load Models
+melody_model = AutoModelForCausalLM.from_pretrained("your_melody_model")  # Replace with actual model name
+harmony_model = AutoModelForCausalLM.from_pretrained("your_harmony_model")  # Replace with actual model name
+rhythm_model = AutoModelForCausalLM.from_pretrained("your_rhythm_model")  # Replace with actual model name
+tokenizer = AutoTokenizer.from_pretrained("gpt2")
+
+# Define functions for each step
+
+def generate_melody(prompt, length=50):
+    """Generates a melody sequence based on the given prompt."""
+    inputs = tokenizer(prompt, return_tensors="pt")
+    melody_output = melody_model.generate(inputs['input_ids'], max_length=length)
+    melody_notes = tokenizer.decode(melody_output[0], skip_special_tokens=True)
+    return melody_notes
+
+def generate_harmony(melody_sequence, length=100):
+    """Generates harmonic support based on the melody."""
+    harmony_input = torch.cat([tokenizer.encode(melody_sequence, return_tensors="pt"), tokenizer("add harmony", return_tensors="pt")['input_ids']], dim=1)
+    harmony_output = harmony_model.generate(harmony_input, max_length=length)
+    harmony_notes = tokenizer.decode(harmony_output[0], skip_special_tokens=True)
+    return harmony_notes
+
+def generate_rhythm(harmony_sequence, length=50):
+    """Adds rhythm to the harmony for structure."""
+    rhythm_input = torch.cat([tokenizer.encode(harmony_sequence, return_tensors="pt"), tokenizer("add rhythm", return_tensors="pt")['input_ids']], dim=1)
+    rhythm_output = rhythm_model.generate(rhythm_input, max_length=length)
+    rhythm_sequence = tokenizer.decode(rhythm_output[0], skip_special_tokens=True)
+    return rhythm_sequence
+
+def create_midi(melody, harmony, rhythm):
+    """Converts melody, harmony, and rhythm sequences to MIDI format."""
+    composition = stream.Stream()
+    
+    for part in [melody, harmony, rhythm]:
+        for token in part.split():
+            if token.isdigit():
+                midi_note = note.Note(int(token))
+                midi_note.quarterLength = 0.5
+                composition.append(midi_note)
+            elif token == "rest":
+                rest_note = note.Rest()
+                rest_note.quarterLength = 0.5
+                composition.append(rest_note)
+    
+    midi_fp = "generated_music.mid"
+    composition.write('midi', fp=midi_fp)
+    return midi_fp
+
+# Full generation function
+def generate_music(prompt, length=50):
+    melody = generate_melody(prompt, length)
+    harmony = generate_harmony(melody, length)
+    rhythm = generate_rhythm(harmony, length)
+    midi_file = create_midi(melody, harmony, rhythm)
+    return midi_file
+
+# Set up Gradio interface
+iface = gr.Interface(
+    fn=generate_music,
+    inputs=["text", "slider"],
+    outputs="file",
+    title="Multi-Model AI Music Generator",
+    description="Generate music using a multi-model AI system that combines melody, harmony, and rhythm layers.",
+)
+
+iface.launch()