gradio-thing

error

Traceback (most recent call last):
  File "/home/blackroot/mambaforge/lib/python3.10/site-packages/gradio/routes.py", line 437, in run_predict
    output = await app.get_blocks().process_api(
  File "/home/blackroot/mambaforge/lib/python3.10/site-packages/gradio/blocks.py", line 1344, in process_api
    inputs = self.preprocess_data(fn_index, inputs, state)
  File "/home/blackroot/mambaforge/lib/python3.10/site-packages/gradio/blocks.py", line 1194, in preprocess_data
    processed_input.append(block.preprocess(inputs[i]))
  File "/home/blackroot/mambaforge/lib/python3.10/site-packages/gradio/components.py", line 2463, in preprocess
    sample_rate, data = processing_utils.audio_from_file(
  File "/home/blackroot/mambaforge/lib/python3.10/site-packages/gradio/processing_utils.py", line 133, in audio_from_file
    audio = AudioSegment.from_file(filename)
  File "/home/blackroot/mambaforge/lib/python3.10/site-packages/pydub/audio_segment.py", line 728, in from_file
    info = mediainfo_json(orig_file, read_ahead_limit=read_ahead_limit)
  File "/home/blackroot/mambaforge/lib/python3.10/site-packages/pydub/utils.py", line 279, in mediainfo_json
    info = json.loads(output)
  File "/home/blackroot/mambaforge/lib/python3.10/json/__init__.py", line 346, in loads
    return _default_decoder.decode(s)
  File "/home/blackroot/mambaforge/lib/python3.10/json/decoder.py", line 337, in decode
    obj, end = self.raw_decode(s, idx=_w(s, 0).end())
  File "/home/blackroot/mambaforge/lib/python3.10/json/decoder.py", line 355, in raw_decode
    raise JSONDecodeError("Expecting value", s, err.value) from None
json.decoder.JSONDecodeError: Expecting value: line 1 column 1 (char 0)

webui.py

import gradio as gr
import os, json
from generator import HijackedMusicGen
from audiocraft.data.audio import audio_write
from audio import predict
from itertools import zip_longest

def split_prompt(bigly_prompt, num_segments):
    prompts = bigly_prompt.split(',,')
    num_segments = int(num_segments)  # Assuming 'segment' comes as a string from Gradio slider
    # repeat last prompt to fill in the rest
    if len(prompts) < num_segments:
        prompts += [prompts[-1]] * (num_segments - len(prompts))
    elif len(prompts) > num_segments:
        prompts = prompts[:num_segments]
    return prompts

loaded_model = None
audio_files = []
def model_interface(model_name, top_k, top_p, temperature, cfg_coef, segments, overlap, duration, optional_audio, prompt):
    global loaded_model

    if loaded_model is None or loaded_model.name != model_name:
        loaded_model = HijackedMusicGen.get_pretrained(None, name=model_name)
        
    print(optional_audio)
        
    loaded_model.set_generation_params(
        use_sampling=True,
        duration=duration,
        top_p=top_p,
        top_k=top_k,
        temperature=temperature,
        cfg_coef=cfg_coef,
    )
    
    extension_parameters = {"segments":segments, "overlap":overlap}
    
    prompts = split_prompt(prompt, segments)
    first_prompt = prompts[0]
    sample_rate, audio = predict(loaded_model, prompts, None, extension_parameters)
    counter = 1
    audio_path = "static/"
    audio_name = first_prompt
    while os.path.exists(audio_path + audio_name + ".wav"):
        audio_name = f"{first_prompt}({counter})"
        counter += 1
        
    file = audio_write(audio_path + audio_name, audio.squeeze(), sample_rate, strategy="loudness")
    audio_files.append(file)

    audio_list_html = "<br>".join([
        f'''
        <div style="border:1px solid #000; padding:10px; margin-bottom:10px;">
            <div>{os.path.splitext(os.path.basename(file))[0]}</div>
            <audio controls><source src="/file={file}" type="audio/wav"></audio>
        </div>
        ''' 
        for file in reversed(audio_files)
    ])

    return audio_list_html

slider_param = {
    "top_k": {"minimum": 0, "maximum": 1000, "value": 0, "label": "Top K"},
    "top_p": {"minimum": 0.0, "maximum": 1.0, "value": 0.0, "label": "Top P"},
    "temperature": {"minimum": 0.1, "maximum": 10.0, "value": 1.0, "label": "Temperature"},
    "cfg_coef": {"minimum": 0.0, "maximum": 10.0, "value": 4.0, "label": "CFG Coefficient"},
    "segments": {"minimum": 1, "maximum": 10, "value": 1, "step": 1, "label": "Number of Segments"},
    "overlap": {"minimum": 0.0, "maximum": 10.0, "value": 1.0, "label": "Segment Overlap"},
    "duration": {"minimum": 1, "maximum": 300, "value": 10, "label": "Duration"},
}

slider_params = {
    key: gr.components.Slider(**params) 
    for key, params in slider_param.items()
}

with gr.Blocks() as interface:
    with gr.Row():

        with gr.Column():
            with gr.Row():
                model_dropdown = gr.components.Dropdown(choices=["small", "medium", "large", "melody"], label="Model Size", value="large")
                optional_audio = gr.Audio(source="upload", type="numpy", label="Optional Audio", interactive=True)

            slider_keys = list(slider_param.keys())
            slider_pairs = list(zip_longest(slider_keys[::2], slider_keys[1::2]))

            for key1, key2 in slider_pairs:
                with gr.Row():
                    with gr.Column():
                        slider_params[key1] = gr.components.Slider(**slider_param[key1])
                    if key2 is not None:
                        with gr.Column():
                            slider_params[key2] = gr.components.Slider(**slider_param[key2])

            prompt_box = gr.components.Textbox(lines=5, placeholder="""Insert a double comma ,, to indicate this should prompt a new segment. For example: 
    Rock Opera,,Dueling Banjos
    This allows you to prompt each segment individually. If you only provide one prompt, every segment will use that one prompt. If you provide multiple prompts but less than the number of segments, then the last prompt will be used to fill in the rest.
    """)
            submit = gr.Button("Submit")

        with gr.Column():
            output = gr.outputs.HTML()

    inputs_list = [model_dropdown] + list(slider_params.values()) + [optional_audio] + [prompt_box]
    submit.click(model_interface, inputs=inputs_list, outputs=[output])
    
interface.queue()
interface.launch()