""" ACE-Step: A Step Towards Music Generation Foundation Model https://github.com/ace-step/ACE-Step Apache 2.0 License """ import gradio as gr import librosa import os 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 """ # First, let's define the presets at the top of the file, after the imports GENRE_PRESETS = { "Modern Pop": "pop, synth, drums, guitar, 120 bpm, upbeat, catchy, vibrant, female vocals, polished vocals", "Rock": "rock, electric guitar, drums, bass, 130 bpm, energetic, rebellious, gritty, male vocals, raw vocals", "Hip Hop": "hip hop, 808 bass, hi-hats, synth, 90 bpm, bold, urban, intense, male vocals, rhythmic vocals", "Country": "country, acoustic guitar, steel guitar, fiddle, 100 bpm, heartfelt, rustic, warm, male vocals, twangy vocals", "EDM": "edm, synth, bass, kick drum, 128 bpm, euphoric, pulsating, energetic, instrumental", "Reggae": "reggae, guitar, bass, drums, 80 bpm, chill, soulful, positive, male vocals, smooth vocals", "Classical": "classical, orchestral, strings, piano, 60 bpm, elegant, emotive, timeless, instrumental", "Jazz": "jazz, saxophone, piano, double bass, 110 bpm, smooth, improvisational, soulful, male vocals, crooning vocals", "Metal": "metal, electric guitar, double kick drum, bass, 160 bpm, aggressive, intense, heavy, male vocals, screamed vocals", "R&B": "r&b, synth, bass, drums, 85 bpm, sultry, groovy, romantic, female vocals, silky vocals" } # Add this function to handle preset selection def update_tags_from_preset(preset_name): if preset_name == "Custom": return "" return GENRE_PRESETS.get(preset_name, "") 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, load_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="secondary", scale=1) # audio2audio with gr.Row(equal_height=True): audio2audio_enable = gr.Checkbox(label="Enable Audio2Audio", value=False, info="Check to enable Audio-to-Audio generation using a reference audio.", elem_id="audio2audio_checkbox") lora_name_or_path = gr.Dropdown( label="Lora Name or Path", choices=["ACE-Step/ACE-Step-v1-chinese-rap-LoRA", "none"], value="none", allow_custom_value=True, ) ref_audio_input = gr.Audio(type="filepath", label="Reference Audio (for Audio2Audio)", visible=False, elem_id="ref_audio_input", show_download_button=True) ref_audio_strength = gr.Slider( label="Refer audio strength", minimum=0.0, maximum=1.0, step=0.01, value=0.5, elem_id="ref_audio_strength", visible=False, interactive=True, ) def toggle_ref_audio_visibility(is_checked): return ( gr.update(visible=is_checked, elem_id="ref_audio_input"), gr.update(visible=is_checked, elem_id="ref_audio_strength"), ) audio2audio_enable.change( fn=toggle_ref_audio_visibility, inputs=[audio2audio_enable], outputs=[ref_audio_input, ref_audio_strength], ) with gr.Column(scale=2): with gr.Group(): gr.Markdown("""
Support tags, descriptions, and scene. Use commas to separate different tags.
Tags and lyrics examples are from AI music generation community.
""") with gr.Row(): genre_preset = gr.Dropdown( choices=["Custom"] + list(GENRE_PRESETS.keys()), value="Custom", label="Preset", scale=1, ) prompt = gr.Textbox( lines=1, label="Tags", max_lines=4, value=TAG_DEFAULT, scale=9, ) # Add the change event for the preset dropdown genre_preset.change( fn=update_tags_from_preset, inputs=[genre_preset], outputs=[prompt] ) with gr.Group(): gr.Markdown("""
Support lyric structure tags like [verse], [chorus], and [bridge] to separate different parts of the lyrics.
Use [instrumental] or [inst] to generate instrumental music. Not support genre structure tag in lyrics
""") lyrics = gr.Textbox( lines=9, label="Lyrics", max_lines=13, value=LYRIC_DEFAULT, ) with gr.Accordion("Basic Settings", open=False): infer_step = gr.Slider( minimum=1, maximum=200, step=1, value=60, label="Infer Steps", interactive=True, ) guidance_scale = gr.Slider( minimum=0.0, maximum=30.0, 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=False, 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", lora_name_or_path="none" if "lora_name_or_path" not in json_data else json_data["lora_name_or_path"] ) 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", show_download_button=True, ) 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, lora_name_or_path="none" if "lora_name_or_path" not in json_data else json_data["lora_name_or_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", show_download_button=True, ) 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, lora_name_or_path="none" if "lora_name_or_path" not in json_data else json_data["lora_name_or_path"] ) 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", show_download_button=True, ) 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, lora_name_or_path="none" if "lora_name_or_path" not in json_data else json_data["lora_name_or_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 json2output(json_data): 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 ), ( json_data["audio2audio_enable"] if "audio2audio_enable" in json_data else False ), ( json_data["ref_audio_strength"] if "ref_audio_strength" in json_data else 0.5 ), ( json_data["ref_audio_input"] if "ref_audio_input" in json_data else None ), ) def sample_data(lora_name_or_path_): json_data = sample_data_func(lora_name_or_path_) return json2output(json_data) sample_bnt.click( sample_data, inputs=[lora_name_or_path], 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, audio2audio_enable, ref_audio_strength, ref_audio_input, ], ) 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, audio2audio_enable, ref_audio_strength, ref_audio_input, lora_name_or_path, ], outputs=outputs + [input_params_json], ) def create_main_demo_ui( text2music_process_func=dump_func, sample_data_func=dump_func, load_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, load_data_func=load_data_func, ) return demo if __name__ == "__main__": demo = create_main_demo_ui() demo.launch( server_name="0.0.0.0", server_port=7860, )