import gradio as gr
import librosa
TAG_DEFAULT = "funk, pop, soul, rock, melodic, guitar, drums, bass, keyboard, percussion, 105 BPM, energetic, upbeat, groovy, vibrant, dynamic"
LYRIC_DEFAULT = """[verse]
Neon lights they flicker bright
City hums in dead of night
Rhythms pulse through concrete veins
Lost in echoes of refrains
[verse]
Bassline groovin' in my chest
Heartbeats match the city's zest
Electric whispers fill the air
Synthesized dreams everywhere
[chorus]
Turn it up and let it flow
Feel the fire let it grow
In this rhythm we belong
Hear the night sing out our song
[verse]
Guitar strings they start to weep
Wake the soul from silent sleep
Every note a story told
In this night we’re bold and gold
[bridge]
Voices blend in harmony
Lost in pure cacophony
Timeless echoes timeless cries
Soulful shouts beneath the skies
[verse]
Keyboard dances on the keys
Melodies on evening breeze
Catch the tune and hold it tight
In this moment we take flight
"""
def create_output_ui(task_name="Text2Music"):
# For many consumer-grade GPU devices, only one batch can be run
output_audio1 = gr.Audio(type="filepath", label=f"{task_name} Generated Audio 1")
# output_audio2 = gr.Audio(type="filepath", label="Generated Audio 2")
with gr.Accordion(f"{task_name} Parameters", open=False):
input_params_json = gr.JSON(label=f"{task_name} Parameters")
# outputs = [output_audio1, output_audio2]
outputs = [output_audio1]
return outputs, input_params_json
def dump_func(*args):
print(args)
return []
def create_text2music_ui(
gr,
text2music_process_func,
sample_data_func=None,
):
with gr.Row():
with gr.Column():
with gr.Row(equal_height=True):
# add markdown, tags and lyrics examples are from ai music generation community
audio_duration = gr.Slider(-1, 240.0, step=0.00001, value=-1, label="Audio Duration", interactive=True, info="-1 means random duration (30 ~ 240).", scale=9)
sample_bnt = gr.Button("Sample", variant="primary", scale=1)
prompt = gr.Textbox(lines=2, label="Tags", max_lines=4, value=TAG_DEFAULT, info="Support tags, descriptions, and scene. Use commas to separate different tags.\ntags and lyrics examples are from ai music generation community")
lyrics = gr.Textbox(lines=9, label="Lyrics", max_lines=13, value=LYRIC_DEFAULT, info="Support lyric structure tags like [verse], [chorus], and [bridge] to separate different parts of the lyrics.\nUse [instrumental] or [inst] to generate instrumental music. Not support genre structure tag in lyrics")
with gr.Accordion("Basic Settings", open=False):
infer_step = gr.Slider(minimum=1, maximum=60, step=1, value=27, label="Infer Steps", interactive=True)
guidance_scale = gr.Slider(minimum=0.0, maximum=200.0, step=0.1, value=15.0, label="Guidance Scale", interactive=True, info="When guidance_scale_lyric > 1 and guidance_scale_text > 1, the guidance scale will not be applied.")
guidance_scale_text = gr.Slider(minimum=0.0, maximum=10.0, step=0.1, value=0.0, label="Guidance Scale Text", interactive=True, info="Guidance scale for text condition. It can only apply to cfg. set guidance_scale_text=5.0, guidance_scale_lyric=1.5 for start")
guidance_scale_lyric = gr.Slider(minimum=0.0, maximum=10.0, step=0.1, value=0.0, label="Guidance Scale Lyric", interactive=True)
manual_seeds = gr.Textbox(label="manual seeds (default None)", placeholder="1,2,3,4", value=None, info="Seed for the generation")
with gr.Accordion("Advanced Settings", open=False):
scheduler_type = gr.Radio(["euler", "heun"], value="euler", label="Scheduler Type", elem_id="scheduler_type", info="Scheduler type for the generation. euler is recommended. heun will take more time.")
cfg_type = gr.Radio(["cfg", "apg", "cfg_star"], value="apg", label="CFG Type", elem_id="cfg_type", info="CFG type for the generation. apg is recommended. cfg and cfg_star are almost the same.")
use_erg_tag = gr.Checkbox(label="use ERG for tag", value=True, info="Use Entropy Rectifying Guidance for tag. It will multiple a temperature to the attention to make a weaker tag condition and make better diversity.")
use_erg_lyric = gr.Checkbox(label="use ERG for lyric", value=True, info="The same but apply to lyric encoder's attention.")
use_erg_diffusion = gr.Checkbox(label="use ERG for diffusion", value=True, info="The same but apply to diffusion model's attention.")
omega_scale = gr.Slider(minimum=-100.0, maximum=100.0, step=0.1, value=10.0, label="Granularity Scale", interactive=True, info="Granularity scale for the generation. Higher values can reduce artifacts")
guidance_interval = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, value=0.5, label="Guidance Interval", interactive=True, info="Guidance interval for the generation. 0.5 means only apply guidance in the middle steps (0.25 * infer_steps to 0.75 * infer_steps)")
guidance_interval_decay = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, value=0.0, label="Guidance Interval Decay", interactive=True, info="Guidance interval decay for the generation. Guidance scale will decay from guidance_scale to min_guidance_scale in the interval. 0.0 means no decay.")
min_guidance_scale = gr.Slider(minimum=0.0, maximum=200.0, step=0.1, value=3.0, label="Min Guidance Scale", interactive=True, info="Min guidance scale for guidance interval decay's end scale")
oss_steps = gr.Textbox(label="OSS Steps", placeholder="16, 29, 52, 96, 129, 158, 172, 183, 189, 200", value=None, info="Optimal Steps for the generation. But not test well")
text2music_bnt = gr.Button("Generate", variant="primary")
with gr.Column():
outputs, input_params_json = create_output_ui()
with gr.Tab("retake"):
retake_variance = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, value=0.2, label="variance")
retake_seeds = gr.Textbox(label="retake seeds (default None)", placeholder="", value=None)
retake_bnt = gr.Button("Retake", variant="primary")
retake_outputs, retake_input_params_json = create_output_ui("Retake")
def retake_process_func(json_data, retake_variance, retake_seeds):
return text2music_process_func(
json_data["audio_duration"],
json_data["prompt"],
json_data["lyrics"],
json_data["infer_step"],
json_data["guidance_scale"],
json_data["scheduler_type"],
json_data["cfg_type"],
json_data["omega_scale"],
", ".join(map(str, json_data["actual_seeds"])),
json_data["guidance_interval"],
json_data["guidance_interval_decay"],
json_data["min_guidance_scale"],
json_data["use_erg_tag"],
json_data["use_erg_lyric"],
json_data["use_erg_diffusion"],
", ".join(map(str, json_data["oss_steps"])),
json_data["guidance_scale_text"] if "guidance_scale_text" in json_data else 0.0,
json_data["guidance_scale_lyric"] if "guidance_scale_lyric" in json_data else 0.0,
retake_seeds=retake_seeds,
retake_variance=retake_variance,
task="retake",
)
retake_bnt.click(
fn=retake_process_func,
inputs=[
input_params_json,
retake_variance,
retake_seeds,
],
outputs=retake_outputs + [retake_input_params_json],
)
with gr.Tab("repainting"):
retake_variance = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, value=0.2, label="variance")
retake_seeds = gr.Textbox(label="repaint seeds (default None)", placeholder="", value=None)
repaint_start = gr.Slider(minimum=0.0, maximum=240.0, step=0.01, value=0.0, label="Repaint Start Time", interactive=True)
repaint_end = gr.Slider(minimum=0.0, maximum=240.0, step=0.01, value=30.0, label="Repaint End Time", interactive=True)
repaint_source = gr.Radio(["text2music", "last_repaint", "upload"], value="text2music", label="Repaint Source", elem_id="repaint_source")
repaint_source_audio_upload = gr.Audio(label="Upload Audio", type="filepath", visible=False, elem_id="repaint_source_audio_upload")
repaint_source.change(
fn=lambda x: gr.update(visible=x == "upload", elem_id="repaint_source_audio_upload"),
inputs=[repaint_source],
outputs=[repaint_source_audio_upload],
)
repaint_bnt = gr.Button("Repaint", variant="primary")
repaint_outputs, repaint_input_params_json = create_output_ui("Repaint")
def repaint_process_func(
text2music_json_data,
repaint_json_data,
retake_variance,
retake_seeds,
repaint_start,
repaint_end,
repaint_source,
repaint_source_audio_upload,
prompt,
lyrics,
infer_step,
guidance_scale,
scheduler_type,
cfg_type,
omega_scale,
manual_seeds,
guidance_interval,
guidance_interval_decay,
min_guidance_scale,
use_erg_tag,
use_erg_lyric,
use_erg_diffusion,
oss_steps,
guidance_scale_text,
guidance_scale_lyric,
):
if repaint_source == "upload":
src_audio_path = repaint_source_audio_upload
audio_duration = librosa.get_duration(filename=src_audio_path)
json_data = {
"audio_duration": audio_duration
}
elif repaint_source == "text2music":
json_data = text2music_json_data
src_audio_path = json_data["audio_path"]
elif repaint_source == "last_repaint":
json_data = repaint_json_data
src_audio_path = json_data["audio_path"]
return text2music_process_func(
json_data["audio_duration"],
prompt,
lyrics,
infer_step,
guidance_scale,
scheduler_type,
cfg_type,
omega_scale,
manual_seeds,
guidance_interval,
guidance_interval_decay,
min_guidance_scale,
use_erg_tag,
use_erg_lyric,
use_erg_diffusion,
oss_steps,
guidance_scale_text,
guidance_scale_lyric,
retake_seeds=retake_seeds,
retake_variance=retake_variance,
task="repaint",
repaint_start=repaint_start,
repaint_end=repaint_end,
src_audio_path=src_audio_path,
)
repaint_bnt.click(
fn=repaint_process_func,
inputs=[
input_params_json,
repaint_input_params_json,
retake_variance,
retake_seeds,
repaint_start,
repaint_end,
repaint_source,
repaint_source_audio_upload,
prompt,
lyrics,
infer_step,
guidance_scale,
scheduler_type,
cfg_type,
omega_scale,
manual_seeds,
guidance_interval,
guidance_interval_decay,
min_guidance_scale,
use_erg_tag,
use_erg_lyric,
use_erg_diffusion,
oss_steps,
guidance_scale_text,
guidance_scale_lyric,
],
outputs=repaint_outputs + [repaint_input_params_json],
)
with gr.Tab("edit"):
edit_prompt = gr.Textbox(lines=2, label="Edit Tags", max_lines=4)
edit_lyrics = gr.Textbox(lines=9, label="Edit Lyrics", max_lines=13)
retake_seeds = gr.Textbox(label="edit seeds (default None)", placeholder="", value=None)
edit_type = gr.Radio(["only_lyrics", "remix"], value="only_lyrics", label="Edit Type", elem_id="edit_type", info="`only_lyrics` will keep the whole song the same except lyrics difference. Make your diffrence smaller, e.g. one lyrc line change.\nremix can change the song melody and genre")
edit_n_min = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, value=0.6, label="edit_n_min", interactive=True)
edit_n_max = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, value=1.0, label="edit_n_max", interactive=True)
def edit_type_change_func(edit_type):
if edit_type == "only_lyrics":
n_min = 0.6
n_max = 1.0
elif edit_type == "remix":
n_min = 0.2
n_max = 0.4
return n_min, n_max
edit_type.change(
edit_type_change_func,
inputs=[edit_type],
outputs=[edit_n_min, edit_n_max]
)
edit_source = gr.Radio(["text2music", "last_edit", "upload"], value="text2music", label="Edit Source", elem_id="edit_source")
edit_source_audio_upload = gr.Audio(label="Upload Audio", type="filepath", visible=False, elem_id="edit_source_audio_upload")
edit_source.change(
fn=lambda x: gr.update(visible=x == "upload", elem_id="edit_source_audio_upload"),
inputs=[edit_source],
outputs=[edit_source_audio_upload],
)
edit_bnt = gr.Button("Edit", variant="primary")
edit_outputs, edit_input_params_json = create_output_ui("Edit")
def edit_process_func(
text2music_json_data,
edit_input_params_json,
edit_source,
edit_source_audio_upload,
prompt,
lyrics,
edit_prompt,
edit_lyrics,
edit_n_min,
edit_n_max,
infer_step,
guidance_scale,
scheduler_type,
cfg_type,
omega_scale,
manual_seeds,
guidance_interval,
guidance_interval_decay,
min_guidance_scale,
use_erg_tag,
use_erg_lyric,
use_erg_diffusion,
oss_steps,
guidance_scale_text,
guidance_scale_lyric,
retake_seeds,
):
if edit_source == "upload":
src_audio_path = edit_source_audio_upload
audio_duration = librosa.get_duration(filename=src_audio_path)
json_data = {
"audio_duration": audio_duration
}
elif edit_source == "text2music":
json_data = text2music_json_data
src_audio_path = json_data["audio_path"]
elif edit_source == "last_edit":
json_data = edit_input_params_json
src_audio_path = json_data["audio_path"]
if not edit_prompt:
edit_prompt = prompt
if not edit_lyrics:
edit_lyrics = lyrics
return text2music_process_func(
json_data["audio_duration"],
prompt,
lyrics,
infer_step,
guidance_scale,
scheduler_type,
cfg_type,
omega_scale,
manual_seeds,
guidance_interval,
guidance_interval_decay,
min_guidance_scale,
use_erg_tag,
use_erg_lyric,
use_erg_diffusion,
oss_steps,
guidance_scale_text,
guidance_scale_lyric,
task="edit",
src_audio_path=src_audio_path,
edit_target_prompt=edit_prompt,
edit_target_lyrics=edit_lyrics,
edit_n_min=edit_n_min,
edit_n_max=edit_n_max,
retake_seeds=retake_seeds,
)
edit_bnt.click(
fn=edit_process_func,
inputs=[
input_params_json,
edit_input_params_json,
edit_source,
edit_source_audio_upload,
prompt,
lyrics,
edit_prompt,
edit_lyrics,
edit_n_min,
edit_n_max,
infer_step,
guidance_scale,
scheduler_type,
cfg_type,
omega_scale,
manual_seeds,
guidance_interval,
guidance_interval_decay,
min_guidance_scale,
use_erg_tag,
use_erg_lyric,
use_erg_diffusion,
oss_steps,
guidance_scale_text,
guidance_scale_lyric,
retake_seeds,
],
outputs=edit_outputs + [edit_input_params_json],
)
with gr.Tab("extend"):
extend_seeds = gr.Textbox(label="extend seeds (default None)", placeholder="", value=None)
left_extend_length = gr.Slider(minimum=0.0, maximum=240.0, step=0.01, value=0.0, label="Left Extend Length", interactive=True)
right_extend_length = gr.Slider(minimum=0.0, maximum=240.0, step=0.01, value=30.0, label="Right Extend Length", interactive=True)
extend_source = gr.Radio(["text2music", "last_extend", "upload"], value="text2music", label="Extend Source", elem_id="extend_source")
extend_source_audio_upload = gr.Audio(label="Upload Audio", type="filepath", visible=False, elem_id="extend_source_audio_upload")
extend_source.change(
fn=lambda x: gr.update(visible=x == "upload", elem_id="extend_source_audio_upload"),
inputs=[extend_source],
outputs=[extend_source_audio_upload],
)
extend_bnt = gr.Button("Extend", variant="primary")
extend_outputs, extend_input_params_json = create_output_ui("Extend")
def extend_process_func(
text2music_json_data,
extend_input_params_json,
extend_seeds,
left_extend_length,
right_extend_length,
extend_source,
extend_source_audio_upload,
prompt,
lyrics,
infer_step,
guidance_scale,
scheduler_type,
cfg_type,
omega_scale,
manual_seeds,
guidance_interval,
guidance_interval_decay,
min_guidance_scale,
use_erg_tag,
use_erg_lyric,
use_erg_diffusion,
oss_steps,
guidance_scale_text,
guidance_scale_lyric,
):
if extend_source == "upload":
src_audio_path = extend_source_audio_upload
# get audio duration
audio_duration = librosa.get_duration(filename=src_audio_path)
json_data = {
"audio_duration": audio_duration
}
elif extend_source == "text2music":
json_data = text2music_json_data
src_audio_path = json_data["audio_path"]
elif extend_source == "last_extend":
json_data = extend_input_params_json
src_audio_path = json_data["audio_path"]
repaint_start = -left_extend_length
repaint_end = json_data["audio_duration"] + right_extend_length
return text2music_process_func(
json_data["audio_duration"],
prompt,
lyrics,
infer_step,
guidance_scale,
scheduler_type,
cfg_type,
omega_scale,
manual_seeds,
guidance_interval,
guidance_interval_decay,
min_guidance_scale,
use_erg_tag,
use_erg_lyric,
use_erg_diffusion,
oss_steps,
guidance_scale_text,
guidance_scale_lyric,
retake_seeds=extend_seeds,
retake_variance=1.0,
task="extend",
repaint_start=repaint_start,
repaint_end=repaint_end,
src_audio_path=src_audio_path,
)
extend_bnt.click(
fn=extend_process_func,
inputs=[
input_params_json,
extend_input_params_json,
extend_seeds,
left_extend_length,
right_extend_length,
extend_source,
extend_source_audio_upload,
prompt,
lyrics,
infer_step,
guidance_scale,
scheduler_type,
cfg_type,
omega_scale,
manual_seeds,
guidance_interval,
guidance_interval_decay,
min_guidance_scale,
use_erg_tag,
use_erg_lyric,
use_erg_diffusion,
oss_steps,
guidance_scale_text,
guidance_scale_lyric,
],
outputs=extend_outputs + [extend_input_params_json],
)
def sample_data():
json_data = sample_data_func()
return (
json_data["audio_duration"],
json_data["prompt"],
json_data["lyrics"],
json_data["infer_step"],
json_data["guidance_scale"],
json_data["scheduler_type"],
json_data["cfg_type"],
json_data["omega_scale"],
", ".join(map(str, json_data["actual_seeds"])),
json_data["guidance_interval"],
json_data["guidance_interval_decay"],
json_data["min_guidance_scale"],
json_data["use_erg_tag"],
json_data["use_erg_lyric"],
json_data["use_erg_diffusion"],
", ".join(map(str, json_data["oss_steps"])),
json_data["guidance_scale_text"] if "guidance_scale_text" in json_data else 0.0,
json_data["guidance_scale_lyric"] if "guidance_scale_lyric" in json_data else 0.0,
)
sample_bnt.click(
sample_data,
outputs=[
audio_duration,
prompt,
lyrics,
infer_step,
guidance_scale,
scheduler_type,
cfg_type,
omega_scale,
manual_seeds,
guidance_interval,
guidance_interval_decay,
min_guidance_scale,
use_erg_tag,
use_erg_lyric,
use_erg_diffusion,
oss_steps,
guidance_scale_text,
guidance_scale_lyric,
],
)
text2music_bnt.click(
fn=text2music_process_func,
inputs=[
audio_duration,
prompt,
lyrics,
infer_step,
guidance_scale,
scheduler_type,
cfg_type,
omega_scale,
manual_seeds,
guidance_interval,
guidance_interval_decay,
min_guidance_scale,
use_erg_tag,
use_erg_lyric,
use_erg_diffusion,
oss_steps,
guidance_scale_text,
guidance_scale_lyric,
], outputs=outputs + [input_params_json]
)
def create_main_demo_ui(
text2music_process_func=dump_func,
sample_data_func=dump_func,
):
with gr.Blocks(
title="ACE-Step Model 1.0 DEMO",
) as demo:
gr.Markdown(
"""
ACE-Step: A Step Towards Music Generation Foundation Model
Project |
Checkpoints |
Discord
""")
with gr.Tab("text2music"):
create_text2music_ui(
gr=gr,
text2music_process_func=text2music_process_func,
sample_data_func=sample_data_func,
)
return demo
if __name__ == "__main__":
demo = create_main_demo_ui()
demo.launch(
server_name="0.0.0.0",
server_port=7860,
)