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import gradio as gr
import tempfile
import random
import json
import re
import pretty_midi
import subprocess
import os
from openai import OpenAI
# === LLM APIs ===
def query_llm(prompt, model_name=None):
if model_name and model_name != "OpenAI":
import requests
response = requests.post("http://localhost:11434/api/generate", json={"model": model_name, "prompt": prompt, "stream": False})
return response.json().get("response", "")
else:
client = OpenAI(
base_url="https://api.studio.nebius.com/v1/",
api_key=os.environ.get("NEBIUS_API_KEY")
)
response = client.chat.completions.create(
model="Qwen/Qwen3-30B-A3B",
messages=[
{
"role": "system",
"content": "You are a helpful assistant."
},
{
"role": "user",
"content": prompt
}
]
)
return response.choices[0].message.content
# === Step 1: Parse intent ===
def get_intent_from_prompt(prompt, model_name):
system_prompt = f"""
Extract the musical intent from this prompt.
Return JSON with keys: tempo (int), key (A-G#), scale (major/minor), genre (e.g., lo-fi, trap), emotion, instrument.
Prompt: '{prompt}'
"""
response = query_llm(system_prompt, model_name)
match = re.search(r'\{.*\}', response, re.DOTALL)
if match:
try:
return json.loads(match.group(0))
except json.JSONDecodeError:
return {"tempo": 120, "key": "C", "scale": "major", "genre": "default", "emotion": "neutral", "instrument": "piano"}
return {"tempo": 120, "key": "C", "scale": "major", "genre": "default", "emotion": "neutral", "instrument": "piano"}
# === Step 2: Melody planning ===
def get_melody_from_intent(intent, model_name):
melody_prompt = f"""
You are a music composer.
Based on this musical intent:
{json.dumps(intent)}
Generate a melody plan using a list of 16 notes with pitch (A-G#), octave (3-6), and duration (0.25 to 1.0 seconds).
Output ONLY valid JSON like:
[
{{"note": "D", "octave": 4, "duration": 0.5}},
{{"note": "F", "octave": 4, "duration": 1.0}}
]
"""
response = query_llm(melody_prompt, model_name)
print(f"\n[DEBUG] LLM Response for melody:\n{response}\n")
try:
json_strs = re.findall(r'\[\s*\{[^]]+\}\s*\]', response, re.DOTALL)
for js in json_strs:
parsed = json.loads(js)
if isinstance(parsed, list) and all("note" in note and "octave" in note and "duration" in note for note in parsed):
return parsed
except json.JSONDecodeError as e:
print(f"[ERROR] Melody JSON decode error: {e}")
print("[WARNING] Using fallback melody.")
return [
{"note": "C", "octave": 4, "duration": 0.5},
{"note": "E", "octave": 4, "duration": 0.5},
{"note": "G", "octave": 4, "duration": 0.5},
{"note": "B", "octave": 4, "duration": 0.5},
]
# === Step 3: MIDI generation ===
def midi_from_plan(melody, tempo):
midi = pretty_midi.PrettyMIDI()
instrument = pretty_midi.Instrument(program=0)
time = 0.0
seconds_per_beat = 60.0 / tempo
note_map = {"C": 0, "C#": 1, "D": 2, "D#": 3, "E": 4, "F": 5, "F#": 6,
"G": 7, "G#": 8, "A": 9, "A#": 10, "B": 11}
for note_info in melody:
try:
pitch = 12 * (note_info["octave"] + 1) + note_map[note_info["note"].upper()]
duration = float(note_info["duration"])
start = time
end = time + duration
instrument.notes.append(pretty_midi.Note(
velocity=100, pitch=pitch, start=start, end=end
))
time = end
except:
continue
midi.instruments.append(instrument)
return midi
# === Gradio function ===
def generate_midi_from_prompt(prompt, model_name):
intent = get_intent_from_prompt(prompt, model_name)
melody = get_melody_from_intent(intent, model_name)
midi = midi_from_plan(melody, intent.get("tempo", 120))
with tempfile.NamedTemporaryFile(delete=False, suffix=".mid") as tmp:
midi.write(tmp.name)
midi_path = tmp.name
return midi_path
# === Get Ollama models ===
def get_ollama_models():
try:
result = subprocess.run(["ollama", "list"], capture_output=True, text=True)
models = [line.split()[0] for line in result.stdout.strip().splitlines()[1:]]
return ["OpenAI"] + models
except Exception as e:
return ["OpenAI"]
# === Gradio UI ===
models = get_ollama_models()
demo = gr.Interface(
fn=generate_midi_from_prompt,
inputs=[
gr.Textbox(label="Music Prompt"),
gr.Dropdown(choices=models, label="LLM Model", value=models[0])
],
outputs=[
gr.File(label="🎵 Download MIDI File")
],
title="🎼 Music Command Prompt (MCP Agent)",
description="Describe your music idea and download a generated MIDI file. Choose from local or Nebius/OpenAI LLMs."
)
demo.launch(mcp_server=True)
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