app.py

import gradio as gr
from beatgenerator import BeatGenerator
from datetime import datetime
from transformers import GPT2LMHeadModel, GPT2Tokenizer
import json
from json.decoder import JSONDecodeError

STEP_COUNT = 32
INSTRUMENT_COUNT = 9

model = GPT2LMHeadModel.from_pretrained("./model")
tokenizer = GPT2Tokenizer.from_pretrained("./tokenizer")
tokenizer.pad_token = tokenizer.eos_token
beat_generator = BeatGenerator(model=model, tokenizer=tokenizer)

# def on_submit(*grid_rows) -> [str]:
#     step_data_container = []

#     for grid_row_id in range(INSTRUMENT_COUNT):
#         grid_row_as_ints = list(map(lambda x: int(x) - 1, grid_rows[grid_row_id]))
#         step_data_container.append(grid_row_as_ints)

#     temperature: float = grid_rows[9]
#     tempo: int = grid_rows[10]
#     now = datetime.now()
#     date_string = now.strftime("%Y-%m-%d_%H-%M")
    
#     genre, midi_data = beat_generator.generate_beat(user_prompt=step_data_container, temperature=temperature, tempo=tempo)

#     return ["""<div><h3>Genre: {0}</h3></div><br/><div><a href="data:audio/midi;base64,{1}" download="beat-{0}-{2}.mid">Download beat</a></div>""".format(genre, midi_data, date_string)]

# checkbox_rows = [
#     ["{:02d}".format(col + 1) for col in range(STEP_COUNT)] for _ in range(INSTRUMENT_COUNT)
# ]

# inputs = [
#     gr.inputs.CheckboxGroup(checkbox_rows[0], label=f"Kick"),
#     gr.inputs.CheckboxGroup(checkbox_rows[1], label=f"Snare"),
#     gr.inputs.CheckboxGroup(checkbox_rows[2], label=f"Clap"),
#     gr.inputs.CheckboxGroup(checkbox_rows[2], label=f"Hat"),
#     gr.inputs.CheckboxGroup(checkbox_rows[2], label=f"L tom"),
#     gr.inputs.CheckboxGroup(checkbox_rows[2], label=f"Open hat"),
#     gr.inputs.CheckboxGroup(checkbox_rows[2], label=f"M tom"),
#     gr.inputs.CheckboxGroup(checkbox_rows[2], label=f"Crash cymbal"),
#     gr.inputs.CheckboxGroup(checkbox_rows[2], label=f"Ride cymbal"),
#     gr.inputs.Slider(minimum=0.1, maximum=1.0, step=0.1, default=0.7, label="Temperature"),
#     gr.inputs.Slider(minimum=60, maximum=200, step=1, default=120, label="Tempo")
# ]

# iface = gr.Interface(
#     fn=on_submit,
#     inputs=inputs,
#     outputs=["html"],
#     title="Simple (MIDI) Beat Generator",
#     description="A simple beat generator that creates an 8-bar MIDI beats on every run, based on a 32-step (2 bars) prompt in the form of a step sequencer. The generator uses a small fine-tuned GPT-2 model to recognise the genre (currently only Trap and Deep House) and generate the beat."
# )

# iface.launch()

# Create a custom block for JSON input
class JSONInput(gr.inputs.Textbox):
    def preprocess(self, x):
        try:
            # Parse the JSON string into a Python object
            parsed_json = json.loads(x)
            return parsed_json
        except json.JSONDecodeError:
            return None

# Define your processing function
def on_did_receive_input(text: [str]):
    try:
        # Parse the JSON string into a Python object
        # return text
        
        input_json_value = json.loads(text.replace("'", '"'))
        try:
            tempo: int = input_json_value['tempo']
            temperature: float = input_json_value['temperature']
            user_prompt: [[int]] = input_json_value['music_data']
            
            genre, events = beat_generator.generate_beat(
                user_prompt=user_prompt, temperature=temperature, tempo=tempo
            )

            return json.dumps(
                {
                    "genre": genre,
                    "events": events
                }
            )
        except KeyError:
            return "Error! Message was not found in JSON input"
    
    except JSONDecodeError as e:
        return "Error! Invalid JSON input: {0}".format(e)

# Create the Gradio interface using Blocks
iface = gr.Interface(
    fn=on_did_receive_input,
    inputs="text",
    outputs="text"
)

iface.launch()