app.py

import gradio as gr
import torch
import os
from miditoolkit import MidiFile
from src.model.generate import batch_performance_render, map_midi
from src.model.pianoformer import PianoT5Gemma

# ------------------------------
# Load model
# ------------------------------
def load_model():
    print("Loading model...")
    model = PianoT5Gemma.from_pretrained(
        "yhj137/pianist-transformer-rendering",
        token=os.environ.get("hf_token"),
        torch_dtype=torch.bfloat16
    )
    model.eval()
    return model

model = load_model()

# ------------------------------
# Define inference function
# ------------------------------
def render_midi(midi_file, temperature, top_p):
    try:
        input_path = midi_file.name
        midi = MidiFile(input_path)

        # Run inference
        res = batch_performance_render(
            model,
            [midi],
            temperature=temperature,
            top_p=top_p,
            device="cpu"  # change to "cuda" if GPU available
        )

        # Save raw (unmapped) result
        raw_out_path = "raw_render.mid"
        res[0].dump(raw_out_path)

        # Try to create editable (mapped) version
        editable_out_path = "editable_render.mid"
        try:
            mapped = map_midi(midi, res[0])
            mapped.dump(editable_out_path)
            return [raw_out_path, editable_out_path]
        except Exception as e:
            print(f"[Warning] map_midi failed: {e}")
            return [raw_out_path, f"[Error] map_midi failed: {e}"]

    except Exception as e:
        raise gr.Error(f"Inference failed: {e}")

# ------------------------------
# Build Gradio interface
# ------------------------------
demo = gr.Interface(
    fn=render_midi,
    inputs=[
        gr.File(label="Upload a Score MIDI File (.mid or .midi)", file_types=[".mid", ".midi", ".MID", ".MIDI"]),
        gr.Slider(0.1, 2.0, value=1.0, step=0.01, label="Temperature"),
        gr.Slider(0.1, 1.0, value=0.95, step=0.01, label="Top-p"),
    ],
    outputs=[
        gr.File(label="Raw Performance"),
        gr.File(label="Editable Version")
    ],
    title="🎹 Pianist Transformer Rendering",
    description=(
        "Upload a piano score MIDI file and let the Pianist Transformer render it into "
        "a more expressive performance MIDI.\n\n"
        "Two versions will be saved:\n\n"
        "• **Raw Performance** – directly generated by the model\n\n"
        "• **Editable Version** – aligned with the score using our Expressive Tempo Mapping algorithm\n\n"
        "If mapping fails, only the raw version will be returned with an error message.\n\n"
        "⚠️ **This is only a demo running on limited compute resources. Please do not upload long pieces — "
        "we recommend clips shorter than 1 minute.**"
    ),
)

if __name__ == "__main__":
    demo.launch()