Update src/webui.py

src/webui.py

@@ -1,394 +1,449 @@
-import json
-import os
-import shutil
-import urllib.request
-import zipfile
-from argparse import ArgumentParser
-import spaces
-import gradio as gr
-import logging
-def configure_logging_libs(debug=False):
-    modules = [
-      "numba",
-      "httpx",
-      "markdown_it",
-      "fairseq",
-      "faiss",
-    ]
-    try:
-        for module in modules:
-            logging.getLogger(module).setLevel(logging.WARNING)
-        os.environ['TF_CPP_MIN_LOG_LEVEL'] = "3" if not debug else "1"
-
-    except Exception as error:
-        pass
-configure_logging_libs()
-
-from main import song_cover_pipeline, yt_download
-
-BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
-IS_ZERO_GPU = os.getenv("SPACES_ZERO_GPU")
-
-mdxnet_models_dir = os.path.join(BASE_DIR, 'mdxnet_models')
-rvc_models_dir = os.path.join(BASE_DIR, 'rvc_models')
-output_dir = os.path.join(BASE_DIR, 'song_output')
-
-
-def get_current_models(models_dir):
-    models_list = os.listdir(models_dir)
-    items_to_remove = ['hubert_base.pt', 'MODELS.txt', 'public_models.json', 'rmvpe.pt']
-    return [item for item in models_list if item not in items_to_remove]
-
-
-def update_models_list():
-    models_l = get_current_models(rvc_models_dir)
-    return gr.update(choices=models_l)
-
-
-def load_public_models():
-    models_table = []
-    for model in public_models['voice_models']:
-        if not model['name'] in voice_models:
-            model = [model['name'], model['description'], model['credit'], model['url'], ', '.join(model['tags'])]
-            models_table.append(model)
-
-    tags = list(public_models['tags'].keys())
-    return gr.update(value=models_table), gr.update(choices=tags)
-
-
-def extract_zip(extraction_folder, zip_name):
-    os.makedirs(extraction_folder)
-    with zipfile.ZipFile(zip_name, 'r') as zip_ref:
-        zip_ref.extractall(extraction_folder)
-    os.remove(zip_name)
-
-    index_filepath, model_filepath = None, None
-    for root, dirs, files in os.walk(extraction_folder):
-        for name in files:
-            if name.endswith('.index') and os.stat(os.path.join(root, name)).st_size > 1024 * 100:
-                index_filepath = os.path.join(root, name)
-
-            if name.endswith('.pth') and os.stat(os.path.join(root, name)).st_size > 1024 * 1024 * 40:
-                model_filepath = os.path.join(root, name)
-
-    if not model_filepath:
-        raise gr.Error(f'No .pth model file was found in the extracted zip. Please check {extraction_folder}.')
-
-    # move model and index file to extraction folder
-    os.rename(model_filepath, os.path.join(extraction_folder, os.path.basename(model_filepath)))
-    if index_filepath:
-        os.rename(index_filepath, os.path.join(extraction_folder, os.path.basename(index_filepath)))
-
-    # remove any unnecessary nested folders
-    for filepath in os.listdir(extraction_folder):
-        if os.path.isdir(os.path.join(extraction_folder, filepath)):
-            shutil.rmtree(os.path.join(extraction_folder, filepath))
-
-
-def download_online_model(url, dir_name, progress=gr.Progress()):
-    try:
-        progress(0, desc=f'[~] Downloading voice model with name {dir_name}...')
-        zip_name = url.split('/')[-1]
-        extraction_folder = os.path.join(rvc_models_dir, dir_name)
-        if os.path.exists(extraction_folder):
-            raise gr.Error(f'Voice model directory {dir_name} already exists! Choose a different name for your voice model.')
-
-        if 'pixeldrain.com' in url:
-            url = f'https://pixeldrain.com/api/file/{zip_name}'
-
-        
-        if "," in url:
-            urls = [u.strip() for u in url.split(",") if u.strip()]
-            os.makedirs(extraction_folder, exist_ok=True)
-            for u in urls:
-                u = u.replace("?download=true", "")
-                file_name = u.split('/')[-1]
-                file_path = os.path.join(extraction_folder, file_name)
-                if not os.path.exists(file_path):  # avoid re-downloading
-                    urllib.request.urlretrieve(u, file_path)
-        else:
-            urllib.request.urlretrieve(url, zip_name)
-
-            progress(0.5, desc='[~] Extracting zip...')
-            extract_zip(extraction_folder, zip_name)
-        return f'[+] {dir_name} Model successfully downloaded!'
-
-    except Exception as e:
-        raise gr.Error(str(e))
-
-
-def upload_local_model(zip_path, dir_name, progress=gr.Progress()):
-    try:
-        extraction_folder = os.path.join(rvc_models_dir, dir_name)
-        if os.path.exists(extraction_folder):
-            raise gr.Error(f'Voice model directory {dir_name} already exists! Choose a different name for your voice model.')
-
-        zip_name = zip_path.name
-        progress(0.5, desc='[~] Extracting zip...')
-        extract_zip(extraction_folder, zip_name)
-        return f'[+] {dir_name} Model successfully uploaded!'
-
-    except Exception as e:
-        raise gr.Error(str(e))
-
-
-def filter_models(tags, query):
-    models_table = []
-
-    # no filter
-    if len(tags) == 0 and len(query) == 0:
-        for model in public_models['voice_models']:
-            models_table.append([model['name'], model['description'], model['credit'], model['url'], model['tags']])
-
-    # filter based on tags and query
-    elif len(tags) > 0 and len(query) > 0:
-        for model in public_models['voice_models']:
-            if all(tag in model['tags'] for tag in tags):
-                model_attributes = f"{model['name']} {model['description']} {model['credit']} {' '.join(model['tags'])}".lower()
-                if query.lower() in model_attributes:
-                    models_table.append([model['name'], model['description'], model['credit'], model['url'], model['tags']])
-
-    # filter based on only tags
-    elif len(tags) > 0:
-        for model in public_models['voice_models']:
-            if all(tag in model['tags'] for tag in tags):
-                models_table.append([model['name'], model['description'], model['credit'], model['url'], model['tags']])
-
-    # filter based on only query
-    else:
-        for model in public_models['voice_models']:
-            model_attributes = f"{model['name']} {model['description']} {model['credit']} {' '.join(model['tags'])}".lower()
-            if query.lower() in model_attributes:
-                models_table.append([model['name'], model['description'], model['credit'], model['url'], model['tags']])
-
-    return gr.update(value=models_table)
-
-
-def pub_dl_autofill(pub_models, event: gr.SelectData):
-    return gr.update(value=pub_models.loc[event.index[0], 'URL']), gr.update(value=pub_models.loc[event.index[0], 'Model Name'])
-
-
-def swap_visibility():
-    return gr.update(visible=True), gr.update(visible=False), gr.update(value=''), gr.update(value=None)
-
-
-def process_file_upload(file):
-    return file.name, gr.update(value=file.name)
-
-
-def show_hop_slider(pitch_detection_algo):
-    if pitch_detection_algo == 'mangio-crepe':
-        return gr.update(visible=True)
-    else:
-        return gr.update(visible=False)
-
-
-
-
-
-
-if __name__ == '__main__':
-    parser = ArgumentParser(description='Generate a AI cover song in the song_output/id directory.', add_help=True)
-    parser.add_argument("--share", action="store_true", dest="share_enabled", default=False, help="Enable sharing")
-    parser.add_argument("--builtin-player",  action="store_true", default=False, help="Use the builtin audio player")
-    parser.add_argument("--listen", action="store_true", default=False, help="Make the WebUI reachable from your local network.")
-    parser.add_argument('--listen-host', type=str, help='The hostname that the server will use.')
-    parser.add_argument('--listen-port', type=int, help='The listening port that the server will use.')
-    parser.add_argument('--theme', type=str, default="NoCrypt/miku", help='Set the theme (default: NoCrypt/miku)')
-    parser.add_argument("--ssr", action="store_true", help="Enable SSR (Server-Side Rendering)")
-    args = parser.parse_args()
-
-    voice_models = get_current_models(rvc_models_dir)
-    with open(os.path.join(rvc_models_dir, 'public_models.json'), encoding='utf8') as infile:
-        public_models = json.load(infile)
-
-    with gr.Blocks(title='AICoverGenWebUI', theme=args.theme, fill_width=True, fill_height=False) as app:
-
-        gr.Label(f'AICoverGen WebUI {"ZeroGPU mode" if IS_ZERO_GPU else ""} created with ❤️', show_label=False)
-        if IS_ZERO_GPU:
-            gr.Markdown(
-                """
-                <details>
-                    <summary style="font-size: 1.5em;">⚠️ Important (click to expand)</summary>
-                    <ul>
-                        <li>🚀 This demo use a Zero GPU, which is available only for a limited time. It's recommended to use audio files that are no longer than 5 minutes. If you want to use it without time restrictions, you can duplicate the 'old CPU space'. ⏳</li>
-                    </ul>
-                </details>
-                """
-            )
-            gr.Markdown("Duplicate the old CPU space for use in private: [![Duplicate this Space](https://huggingface.co/datasets/huggingface/badges/raw/main/duplicate-this-space-sm-dark.svg)](https://huggingface.co/spaces/r3gm/AICoverGen_old_stable_cpu?duplicate=true)\n\n") 
-
-        # main tab
-        with gr.Tab("Generate"):
-
-            with gr.Accordion('Main Options'):
-                with gr.Row():
-                    with gr.Column():
-                        rvc_model = gr.Dropdown(voice_models, label='Voice Models', info='Models folder "AICoverGen --> rvc_models". After new models are added into this folder, click the refresh button')
-                        ref_btn = gr.Button('Refresh Models 🔁', variant='primary')
-
-                    with gr.Column(visible=False) as yt_link_col:
-                        song_input = gr.Text(label='Song input', info='Link to a song on YouTube or full path to a local file. For file upload, click the button below.')
-                        show_file_upload_button = gr.Button('Upload file instead')
-
-                    with gr.Column(visible=True) as file_upload_col:
-                        audio_extensions = ['.mp3', '.m4a', '.flac', '.wav', '.aac', '.ogg', '.wma', '.alac', '.aiff', '.opus', 'amr']
-                        local_file = gr.File(label='Audio file', interactive=True, type="filepath", file_types=audio_extensions, height=150)
-                        if not IS_ZERO_GPU:
-                            with gr.Row():
-                                with gr.Row(scale=2):
-                                    url_media_gui = gr.Textbox(value="", label="Enter URL", placeholder="www.youtube.com/watch?v=g_9rPvbENUw", lines=1)
-                                with gr.Row(scale=1):
-                                    url_button_gui = gr.Button("Process URL", variant="secondary")
-                            url_button_gui.click(yt_download, [url_media_gui], [local_file])
-                        song_input_file = gr.UploadButton('Upload 📂', file_types=['audio'], variant='primary', visible=False)
-                        show_yt_link_button = gr.Button('Paste YouTube link/Path to local file instead', visible=False)
-                        song_input_file.upload(process_file_upload, inputs=[song_input_file], outputs=[local_file, song_input])
-
-                    with gr.Column():
-                        pitch = gr.Slider(-3, 3, value=0, step=1, label='Pitch Change (Vocals ONLY)', info='Generally, use 1 for male to female conversions and -1 for vice-versa. (Octaves)')
-                        pitch_all = gr.Slider(-12, 12, value=0, step=1, label='Overall Pitch Change', info='Changes pitch/key of vocals and instrumentals together. Altering this slightly reduces sound quality. (Semitones)')
-                    show_file_upload_button.click(swap_visibility, outputs=[file_upload_col, yt_link_col, song_input, local_file])
-                    show_yt_link_button.click(swap_visibility, outputs=[yt_link_col, file_upload_col, song_input, local_file])
-
-            with gr.Accordion('Voice conversion options', open=False):
-                with gr.Row():
-                    index_rate = gr.Slider(0, 1, value=0.5, label='Index Rate', info="Controls how much of the AI voice's accent to keep in the vocals")
-                    filter_radius = gr.Slider(0, 7, value=3, step=1, label='Filter radius', info='If >=3: apply median filtering median filtering to the harvested pitch results. Can reduce breathiness')
-                    rms_mix_rate = gr.Slider(0, 1, value=0.25, label='RMS mix rate', info="Control how much to mimic the original vocal's loudness (0) or a fixed loudness (1)")
-                    protect = gr.Slider(0, 0.5, value=0.33, label='Protect rate', info='Protect voiceless consonants and breath sounds. Set to 0.5 to disable.')
-                    with gr.Column():
-                        f0_method = gr.Dropdown(['rmvpe+', 'rmvpe', 'mangio-crepe'], value='rmvpe+', label='Pitch detection algorithm', info='Best option is rmvpe (clarity in vocals), then mangio-crepe (smoother vocals), rmvpe+ use a minimum and maximum allowed pitch values.')
-                        crepe_hop_length = gr.Slider(32, 320, value=128, step=1, visible=False, label='Crepe hop length', info='Lower values leads to longer conversions and higher risk of voice cracks, but better pitch accuracy.')
-                        f0_method.change(show_hop_slider, inputs=f0_method, outputs=crepe_hop_length)
-                with gr.Row():
-                    with gr.Row():
-                        steps = gr.Slider(minimum=1, maximum=3, label="Steps", value=1, step=1, interactive=True)
-                    with gr.Row():
-                        extra_denoise = gr.Checkbox(True, label='Denoise', info='Apply an additional noise reduction step to clean up the audio further.')
-                        keep_files = gr.Checkbox((False if IS_ZERO_GPU else True), label='Keep intermediate files', info='Keep all audio files generated in the song_output/id directory, e.g. Isolated Vocals/Instrumentals. Leave unchecked to save space', interactive=(False if IS_ZERO_GPU else True))
-
-            with gr.Accordion('Audio mixing options', open=False):
-                gr.Markdown('### Volume Change (decibels)')
-                with gr.Row():
-                    main_gain = gr.Slider(-20, 20, value=0, step=1, label='Main Vocals')
-                    backup_gain = gr.Slider(-20, 20, value=0, step=1, label='Backup Vocals')
-                    inst_gain = gr.Slider(-20, 20, value=0, step=1, label='Music')
-
-                gr.Markdown('### Reverb Control on AI Vocals')
-                with gr.Row():
-                    reverb_rm_size = gr.Slider(0, 1, value=0.15, label='Room size', info='The larger the room, the longer the reverb time')
-                    reverb_wet = gr.Slider(0, 1, value=0.2, label='Wetness level', info='Level of AI vocals with reverb')
-                    reverb_dry = gr.Slider(0, 1, value=0.8, label='Dryness level', info='Level of AI vocals without reverb')
-                    reverb_damping = gr.Slider(0, 1, value=0.7, label='Damping level', info='Absorption of high frequencies in the reverb')
-
-                gr.Markdown('### Audio Output Format')
-                output_format = gr.Dropdown(['mp3', 'wav'], value='mp3', label='Output file type', info='mp3: small file size, decent quality. wav: Large file size, best quality')
-
-            with gr.Row():
-                clear_btn = gr.ClearButton(value='Clear', components=[song_input, rvc_model, keep_files, local_file])
-                generate_btn = gr.Button("Generate", variant='primary')
-                ai_cover = (
-                    gr.Audio(label='AI Cover', show_share_button=True)
-                    if args.builtin_player else
-                    gr.File(label="AI Cover", interactive=False)
-                )
-            gr.Markdown("- You can also try `AICoverGen❤️` in Colab’s free tier, which provides free GPU [link](https://github.com/R3gm/AICoverGen?tab=readme-ov-file#aicovergen).")
-
-            ref_btn.click(update_models_list, None, outputs=rvc_model)
-            is_webui = gr.Number(value=1, visible=False)
-            generate_btn.click(song_cover_pipeline,
-                               inputs=[local_file, rvc_model, pitch, keep_files, is_webui, main_gain, backup_gain,
-                                       inst_gain, index_rate, filter_radius, rms_mix_rate, f0_method, crepe_hop_length,
-                                       protect, pitch_all, reverb_rm_size, reverb_wet, reverb_dry, reverb_damping,
-                                       output_format, extra_denoise, steps],
-                               outputs=[ai_cover])
-            clear_btn.click(lambda: [0, 0, 0, 0, 0.5, 3, 0.25, 0.33, 'rmvpe+', 128, 0, 0.15, 0.2, 0.8, 0.7, 'mp3', None, True, 1],
-                            outputs=[pitch, main_gain, backup_gain, inst_gain, index_rate, filter_radius, rms_mix_rate,
-                                     protect, f0_method, crepe_hop_length, pitch_all, reverb_rm_size, reverb_wet,
-                                     reverb_dry, reverb_damping, output_format, ai_cover, extra_denoise, steps])
-
-        # Download tab
-        with gr.Tab('Download model'):
-
-            with gr.Tab('From HuggingFace/Pixeldrain URL'):
-                with gr.Row():
-                    model_zip_link = gr.Text(label='Download link to model', info='Should be a zip file containing a .pth model file and an optional .index file.')
-                    model_name = gr.Text(label='Name your model', info='Give your new model a unique name from your other voice models.')
-
-                with gr.Row():
-                    download_btn = gr.Button('Download 🌐', variant='primary', scale=19)
-                    dl_output_message = gr.Text(label='Output Message', interactive=False, scale=20)
-
-                download_btn.click(download_online_model, inputs=[model_zip_link, model_name], outputs=dl_output_message)
-
-                gr.Markdown('## Input Examples')
-                gr.Examples(
-                    [
-                        ['https://huggingface.co/MrDawg/ToothBrushing/resolve/main/ToothBrushing.zip?download=true', 'ToothBrushing'],
-                        ['https://huggingface.co/sail-rvc/Aldeano_Minecraft__RVC_V2_-_500_Epochs_/resolve/main/model.pth?download=true, https://huggingface.co/sail-rvc/Aldeano_Minecraft__RVC_V2_-_500_Epochs_/resolve/main/model.index?download=true', 'Minecraft_Villager'],
-                        ['https://huggingface.co/phant0m4r/LiSA/resolve/main/LiSA.zip', 'Lisa'],
-                        ['https://pixeldrain.com/u/3tJmABXA', 'Gura'],
-                        ['https://huggingface.co/Kit-Lemonfoot/kitlemonfoot_rvc_models/resolve/main/AZKi%20(Hybrid).zip', 'Azki']
-                    ],
-                    [model_zip_link, model_name],
-                    [],
-                    download_online_model,
-                    cache_examples=False,
-                )
-
-            with gr.Tab('From Public Index'):
-
-                gr.Markdown('## How to use')
-                gr.Markdown('- Click Initialize public models table')
-                gr.Markdown('- Filter models using tags or search bar')
-                gr.Markdown('- Select a row to autofill the download link and model name')
-                gr.Markdown('- Click Download')
-
-                with gr.Row():
-                    pub_zip_link = gr.Text(label='Download link to model')
-                    pub_model_name = gr.Text(label='Model name')
-
-                with gr.Row():
-                    download_pub_btn = gr.Button('Download 🌐', variant='primary', scale=19)
-                    pub_dl_output_message = gr.Text(label='Output Message', interactive=False, scale=20)
-
-                filter_tags = gr.CheckboxGroup(value=[], label='Show voice models with tags', choices=[])
-                search_query = gr.Text(label='Search')
-                load_public_models_button = gr.Button(value='Initialize public models table', variant='primary')
-
-                public_models_table = gr.DataFrame(value=[], headers=['Model Name', 'Description', 'Credit', 'URL', 'Tags'], label='Available Public Models', interactive=False)
-                public_models_table.select(pub_dl_autofill, inputs=[public_models_table], outputs=[pub_zip_link, pub_model_name])
-                load_public_models_button.click(load_public_models, outputs=[public_models_table, filter_tags])
-                search_query.change(filter_models, inputs=[filter_tags, search_query], outputs=public_models_table)
-                filter_tags.change(filter_models, inputs=[filter_tags, search_query], outputs=public_models_table)
-                download_pub_btn.click(download_online_model, inputs=[pub_zip_link, pub_model_name], outputs=pub_dl_output_message)
-
-        # Upload tab
-        with gr.Tab('Upload model'):
-            gr.Markdown('## Upload locally trained RVC v2 model and index file')
-            gr.Markdown('- Find model file (weights folder) and optional index file (logs/[name] folder)')
-            gr.Markdown('- Compress files into zip file')
-            gr.Markdown('- Upload zip file and give unique name for voice')
-            gr.Markdown('- Click Upload model')
-
-            with gr.Row():
-                with gr.Column():
-                    zip_file = gr.File(label='Zip file')
-
-                local_model_name = gr.Text(label='Model name')
-
-            with gr.Row():
-                model_upload_button = gr.Button('Upload model', variant='primary', scale=19)
-                local_upload_output_message = gr.Text(label='Output Message', interactive=False, scale=20)
-                model_upload_button.click(upload_local_model, inputs=[zip_file, local_model_name], outputs=local_upload_output_message)
-
-    app.launch(
-        share=args.share_enabled,
-        debug=args.share_enabled,
-        show_error=True,
-        # enable_queue=True,
-        server_name=None if not args.listen else (args.listen_host or '0.0.0.0'),
-        server_port=args.listen_port,
-        ssr_mode=args.ssr
-    )
+import json
+import os
+import shutil
+import urllib.request
+import zipfile
+from argparse import ArgumentParser
+import spaces
+import gradio as gr
+import logging
+def configure_logging_libs(debug=False):
+    modules = [
+      "numba",
+      "httpx",
+      "markdown_it",
+      "fairseq",
+      "faiss",
+    ]
+    try:
+        for module in modules:
+            logging.getLogger(module).setLevel(logging.WARNING)
+        os.environ['TF_CPP_MIN_LOG_LEVEL'] = "3" if not debug else "1"
+
+    except Exception as error:
+        pass
+configure_logging_libs()
+
+from main import song_cover_pipeline, yt_download
+
+BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
+IS_ZERO_GPU = os.getenv("SPACES_ZERO_GPU")
+
+mdxnet_models_dir = os.path.join(BASE_DIR, 'mdxnet_models')
+rvc_models_dir = os.path.join(BASE_DIR, 'rvc_models')
+output_dir = os.path.join(BASE_DIR, 'song_output')
+
+
+def get_current_models(models_dir):
+    models_list = os.listdir(models_dir)
+    items_to_remove = ['hubert_base.pt', 'MODELS.txt', 'public_models.json', 'rmvpe.pt']
+    return [item for item in models_list if item not in items_to_remove]
+
+
+def update_models_list():
+    models_l = get_current_models(rvc_models_dir)
+    return gr.update(choices=models_l)
+
+
+def load_public_models():
+    models_table = []
+    for model in public_models['voice_models']:
+        if not model['name'] in voice_models:
+            model = [model['name'], model['description'], model['credit'], model['url'], ', '.join(model['tags'])]
+            models_table.append(model)
+
+    tags = list(public_models['tags'].keys())
+    return gr.update(value=models_table), gr.update(choices=tags)
+
+
+def extract_zip(extraction_folder, zip_name):
+    os.makedirs(extraction_folder)
+    with zipfile.ZipFile(zip_name, 'r') as zip_ref:
+        zip_ref.extractall(extraction_folder)
+    os.remove(zip_name)
+
+    index_filepath, model_filepath = None, None
+    for root, dirs, files in os.walk(extraction_folder):
+        for name in files:
+            if name.endswith('.index') and os.stat(os.path.join(root, name)).st_size > 1024 * 100:
+                index_filepath = os.path.join(root, name)
+
+            if name.endswith('.pth') and os.stat(os.path.join(root, name)).st_size > 1024 * 1024 * 40:
+                model_filepath = os.path.join(root, name)
+
+    if not model_filepath:
+        raise gr.Error(f'No .pth model file was found in the extracted zip. Please check {extraction_folder}.')
+
+    # move model and index file to extraction folder
+    os.rename(model_filepath, os.path.join(extraction_folder, os.path.basename(model_filepath)))
+    if index_filepath:
+        os.rename(index_filepath, os.path.join(extraction_folder, os.path.basename(index_filepath)))
+
+    # remove any unnecessary nested folders
+    for filepath in os.listdir(extraction_folder):
+        if os.path.isdir(os.path.join(extraction_folder, filepath)):
+            shutil.rmtree(os.path.join(extraction_folder, filepath))
+
+
+def download_online_model(url, dir_name, progress=gr.Progress()):
+    try:
+        progress(0, desc=f'[~] Downloading voice model with name {dir_name}...')
+        zip_name = url.split('/')[-1]
+        extraction_folder = os.path.join(rvc_models_dir, dir_name)
+        if os.path.exists(extraction_folder):
+            raise gr.Error(f'Voice model directory {dir_name} already exists! Choose a different name for your voice model.')
+
+        if 'pixeldrain.com' in url:
+            url = f'https://pixeldrain.com/api/file/{zip_name}'
+
+        
+        if "," in url:
+            urls = [u.strip() for u in url.split(",") if u.strip()]
+            os.makedirs(extraction_folder, exist_ok=True)
+            for u in urls:
+                u = u.replace("?download=true", "")
+                file_name = u.split('/')[-1]
+                file_path = os.path.join(extraction_folder, file_name)
+                if not os.path.exists(file_path):  # avoid re-downloading
+                    urllib.request.urlretrieve(u, file_path)
+        else:
+            urllib.request.urlretrieve(url, zip_name)
+
+            progress(0.5, desc='[~] Extracting zip...')
+            extract_zip(extraction_folder, zip_name)
+        return f'[+] {dir_name} Model successfully downloaded!'
+
+    except Exception as e:
+        raise gr.Error(str(e))
+
+
+def upload_local_model(zip_path, dir_name, progress=gr.Progress()):
+    try:
+        extraction_folder = os.path.join(rvc_models_dir, dir_name)
+        if os.path.exists(extraction_folder):
+            raise gr.Error(f'Voice model directory {dir_name} already exists! Choose a different name for your voice model.')
+
+        zip_name = zip_path.name
+        progress(0.5, desc='[~] Extracting zip...')
+        extract_zip(extraction_folder, zip_name)
+        return f'[+] {dir_name} Model successfully uploaded!'
+
+    except Exception as e:
+        raise gr.Error(str(e))
+
+
+def filter_models(tags, query):
+    models_table = []
+
+    # no filter
+    if len(tags) == 0 and len(query) == 0:
+        for model in public_models['voice_models']:
+            models_table.append([model['name'], model['description'], model['credit'], model['url'], model['tags']])
+
+    # filter based on tags and query
+    elif len(tags) > 0 and len(query) > 0:
+        for model in public_models['voice_models']:
+            if all(tag in model['tags'] for tag in tags):
+                model_attributes = f"{model['name']} {model['description']} {model['credit']} {' '.join(model['tags'])}".lower()
+                if query.lower() in model_attributes:
+                    models_table.append([model['name'], model['description'], model['credit'], model['url'], model['tags']])
+
+    # filter based on only tags
+    elif len(tags) > 0:
+        for model in public_models['voice_models']:
+            if all(tag in model['tags'] for tag in tags):
+                models_table.append([model['name'], model['description'], model['credit'], model['url'], model['tags']])
+
+    # filter based on only query
+    else:
+        for model in public_models['voice_models']:
+            model_attributes = f"{model['name']} {model['description']} {model['credit']} {' '.join(model['tags'])}".lower()
+            if query.lower() in model_attributes:
+                models_table.append([model['name'], model['description'], model['credit'], model['url'], model['tags']])
+
+    return gr.update(value=models_table)
+
+
+def pub_dl_autofill(pub_models, event: gr.SelectData):
+    return gr.update(value=pub_models.loc[event.index[0], 'URL']), gr.update(value=pub_models.loc[event.index[0], 'Model Name'])
+
+
+def swap_visibility():
+    return gr.update(visible=True), gr.update(visible=False), gr.update(value=''), gr.update(value=None)
+
+
+def process_file_upload(file):
+    return file.name, gr.update(value=file.name)
+
+
+def show_hop_slider(pitch_detection_algo):
+    if pitch_detection_algo == 'mangio-crepe':
+        return gr.update(visible=True)
+    else:
+        return gr.update(visible=False)
+
+
+CSS = """
+:root{color-scheme:dark;--paper:#111412;--panel:#181c19;--panel-2:#141815;--ink:#f3f4ef;--muted:#9ea8a0;--line:#303732;--signal:#2486ff;--signal-hover:#52a0ff;--signal-soft:#15263b}
+html,body,.gradio-container,.dark{background:var(--paper)!important;color:var(--ink)!important;color-scheme:dark!important}
+body,.gradio-container,.gradio-container button,.gradio-container input,.gradio-container textarea{font-family:Inter,ui-sans-serif,-apple-system,BlinkMacSystemFont,"Segoe UI",sans-serif!important}
+.gradio-container{width:min(100%,1640px)!important;max-width:none!important;margin:auto!important;padding:0 clamp(14px,2.2vw,34px) 54px!important;box-sizing:border-box!important}
+.gradio-container>.main{padding:0!important}
+.gradio-container *{box-sizing:border-box}
+.hero-wrap,.hero-wrap.block,.hero-wrap>.wrap{padding:0!important;border:0!important;box-shadow:none!important;background:transparent!important}
+.hero{padding:18px 2px 13px;border-bottom:1px solid var(--line);margin-bottom:2px}
+.hero-top{display:flex;align-items:center;justify-content:space-between;gap:20px}
+.eyebrow{color:var(--signal);font:700 11px/1 ui-monospace,SFMono-Regular,Consolas,monospace;letter-spacing:.13em;text-transform:uppercase}
+.links{display:flex;align-items:center;gap:18px;font-size:12px;font-weight:700}
+.links a{color:var(--muted)!important;text-decoration:none}.links a:hover{color:var(--ink)!important}
+.hero h1{max-width:1040px;margin:15px 0 8px;color:var(--ink);font:650 clamp(40px,4.5vw,56px)/.96 Inter,ui-sans-serif,sans-serif;letter-spacing:-.055em}
+.hero>p{max-width:1000px;margin:0;color:var(--muted)!important;font-size:13px;line-height:1.48}
+.model-facts{display:flex;align-items:stretch;margin-top:13px;border-top:1px solid var(--line)}
+.model-fact{flex:1;padding:8px 24px 0 0;color:var(--muted)!important;font-size:11px;line-height:1.3}
+.model-fact+.model-fact{padding-left:20px;border-left:1px solid var(--line)}
+.model-fact strong{display:block;margin-bottom:2px;color:var(--ink);font-size:14px;line-height:1.2}
+.runtime-tabs{margin:14px 10px 0!important}
+.runtime-tabs>.tab-container,.runtime-tabs .tab-container{display:grid!important;grid-template-columns:repeat(2,minmax(0,1fr))!important;gap:0!important;height:auto!important;overflow:hidden!important;border:1px solid var(--line)!important;border-radius:2px!important;background:var(--panel-2)!important}
+.runtime-tabs>.tab-container button,.runtime-tabs .tab-container button{display:flex!important;min-height:54px!important;padding:9px 14px!important;flex-direction:column!important;align-items:flex-start!important;justify-content:center!important;border:0!important;border-radius:0!important;background:transparent!important;color:var(--ink)!important;font-size:13px!important;font-weight:800!important;line-height:1.2!important;letter-spacing:.005em!important;transition:background .16s ease,color .16s ease!important}
+.runtime-tabs>.tab-container button+button,.runtime-tabs .tab-container button+button{border-left:1px solid var(--line)!important}
+.runtime-tabs>.tab-container button::after,.runtime-tabs .tab-container button::after{margin-top:3px;color:var(--muted);font-size:10px;font-weight:550;letter-spacing:.01em}
+.runtime-tabs>.tab-container button:nth-child(1)::after,.runtime-tabs .tab-container button:nth-child(1)::after{content:"Hugging Face ZeroGPU"}
+.runtime-tabs>.tab-container button:nth-child(2)::after,.runtime-tabs .tab-container button:nth-child(2)::after{content:"WebGPU / WASM · private"}
+.runtime-tabs>.tab-container button:hover,.runtime-tabs .tab-container button:hover{background:#1b242d!important;color:var(--ink)!important}
+.runtime-tabs>.tab-container button.selected,.runtime-tabs .tab-container button.selected{background:var(--signal-soft)!important;color:#fff!important;box-shadow:inset 0 -2px 0 var(--signal)!important}
+.runtime-tabs>.tab-container button.selected::after,.runtime-tabs .tab-container button.selected::after{color:#a9c7e8!important}
+.runtime-tabs>.tabitem,.runtime-tabs .tabitem{padding-top:0!important;border:0!important;background:transparent!important}
+.mode-banner{display:grid;grid-template-columns:minmax(0,1fr) auto;align-items:center;gap:16px;margin:10px 0;padding:9px 11px;border:1px solid var(--line);border-left:2px solid var(--signal);border-radius:2px;background:var(--panel-2)}
+.mode-banner strong{display:block;margin-bottom:2px;color:var(--ink)!important;font-size:12px}
+.mode-banner span{color:var(--muted)!important;font-size:11px;line-height:1.45}
+.mode-badge{padding:5px 7px;border:1px solid #356ea8;border-radius:2px;color:#dceaff!important;font:750 9px/1 ui-monospace,SFMono-Regular,Consolas,monospace!important;letter-spacing:.08em;text-transform:uppercase;white-space:nowrap}
+.browser-frame-shell{margin:0;padding:0;border:1px solid var(--line);border-radius:2px;background:var(--paper);overflow:hidden}
+.browser-frame{display:block;width:100%;height:580px;border:0;background:var(--paper);transition:height .18s ease}
+.browser-help{margin:9px 2px 0!important;color:var(--muted)!important;font-size:11px!important;line-height:1.5!important}
+.workbench{padding:0 0 4px!important;border:0!important;background:transparent!important}
+.workbench.block,.workbench>.wrap{border:0!important;box-shadow:none!important;background:transparent!important}
+.control-row{align-items:stretch!important;gap:18px!important;margin-top:6px!important;padding:12px 14px 11px!important;border:1px solid var(--line)!important;border-radius:3px!important;background:var(--panel-2)!important}
+.control-row>div{min-width:0!important}
+.control-row .form{height:100%!important;border:0!important;background:transparent!important}
+.control-row label>span:first-child{font-size:12px!important;font-weight:750!important;letter-spacing:.015em!important}
+.model-switch .wrap{display:grid!important;grid-template-columns:repeat(2,minmax(0,1fr))!important;gap:0!important;padding:0!important;overflow:hidden!important;border:1px solid var(--line)!important;border-radius:2px!important;background:#101411!important}
+.model-switch .wrap label{min-height:46px!important;margin:0!important;padding:10px 12px!important;border:0!important;border-radius:0!important;background:transparent!important}
+.model-switch .wrap label+label{border-left:1px solid var(--line)!important}
+.model-switch .wrap label:has(input:checked){background:var(--signal-soft)!important;box-shadow:inset 0 -2px 0 var(--signal)!important}
+.model-switch .wrap label span{font-size:12px!important;font-weight:750!important}
+.action-row{justify-content:center!important;gap:12px!important;margin:12px auto 0!important;max-width:840px!important}
+.action-row button{min-height:48px!important}
+.comparison{margin-top:22px!important;padding-top:20px!important;border-top:1px solid var(--line)!important}
+.comparison-title{margin-bottom:9px!important}
+.gradio-container .block,.gradio-container .form{border-radius:3px!important;background:var(--panel-2)!important;border-color:var(--line)!important;color:var(--ink)!important}
+.gradio-container .prose,.gradio-container .markdown-body,.gradio-container label,.gradio-container span,.gradio-container p,.gradio-container h1,.gradio-container h2,.gradio-container h3{color:var(--ink)!important}
+.gradio-container label{background:transparent!important}
+.gradio-container .wrap{background:var(--panel-2)!important}
+.gradio-container select{min-height:48px!important;background:#101411!important;color:var(--ink)!important;border-color:var(--line)!important;text-align:left!important}
+.gradio-container input,.gradio-container textarea{background:#101411!important;color:var(--ink)!important;border-color:var(--line)!important}
+.prompt-input textarea{font-size:16px!important;line-height:1.55!important;min-height:104px!important;padding:15px!important}
+.gradio-container button:not(.primary){background:var(--panel-2)!important;color:var(--ink)!important;border-color:var(--line)!important}
+.gradio-container button:not(.primary):hover{border-color:#527aa6!important;background:#1b242d!important}
+button.primary{min-height:46px!important;border:0!important;border-radius:1px!important;background:var(--signal)!important;color:#fff!important;font-weight:800!important}
+button.primary *{color:#fff!important}button.primary:hover{background:var(--signal-hover)!important}
+.advanced{margin:10px 0 3px!important;background:#131814!important;border-left:2px solid #344138!important}
+.advanced>button{font-size:12px!important;font-weight:750!important;letter-spacing:.01em!important}
+.output-audio{margin-top:8px!important}
+.outputmeta{padding:11px 13px!important;background:var(--signal-soft)!important;border:1px solid #294e78!important}
+.outputmeta *{color:#dceaff!important}
+.helper-copy{margin:8px 2px 4px!important;color:var(--muted)!important;font-size:12px!important}
+.fineprint{color:var(--muted)!important;font-size:12px;line-height:1.55;border-top:1px solid var(--line);padding-top:16px;margin-top:22px}
+footer{display:none!important}
+@media(max-width:760px){
+html,body{overflow-x:hidden!important}.gradio-container{width:100%!important;min-width:0!important;padding:0 14px 38px!important}
+.hero{padding-top:22px}.hero-top{align-items:flex-start;flex-direction:column;gap:12px}.links{gap:14px;font-size:11px}
+.hero h1{margin-top:18px;font-size:42px}.model-facts{display:grid;grid-template-columns:1fr 1fr}.model-fact{padding:11px 10px 9px 0}.model-fact+.model-fact{padding-left:10px}.model-fact:nth-child(3){padding-left:0;border-left:0;border-top:1px solid var(--line)}.model-fact:nth-child(4){border-top:1px solid var(--line)}
+ .runtime-tabs{margin-left:0!important;margin-right:0!important}.runtime-tabs>.tab-container button,.runtime-tabs .tab-container button{min-height:54px!important;padding-inline:10px!important}.runtime-tabs>.tab-container button::after,.runtime-tabs .tab-container button::after{font-size:9px}.mode-banner{grid-template-columns:1fr}.mode-badge{justify-self:start}.browser-frame{height:980px}
+.workbench{min-width:0!important;padding-top:18px!important}.control-row,.action-row,.comparison .row{flex-direction:column!important;min-width:0!important}
+.control-row>*,.action-row>*,.comparison .row>*{width:100%!important;min-width:0!important}.gradio-container .wrap,.gradio-container .form,.gradio-container .block{min-width:0!important}
+}
+"""
+
+
+
+
+
+if __name__ == '__main__':
+    
+    voice_models = get_current_models(rvc_models_dir)
+    with open(os.path.join(rvc_models_dir, 'public_models.json'), encoding='utf8') as infile:
+        public_models = json.load(infile)
+
+    with gr.Blocks(title='AICoverGenWebUI', css=CSS, fill_width=True, fill_height=False) as app:
+
+        
+        # main tab
+        with gr.Tab("Generate"):
+
+            with gr.Accordion('Main Options'):
+                with gr.Row():
+                    with gr.Column():
+                        rvc_model = gr.Dropdown(voice_models, label='Voice Models', info='Models folder "AICoverGen --> rvc_models". After new models are added into this folder, click the refresh button')
+                        ref_btn = gr.Button('Refresh Models 🔁', variant='primary')
+
+                    with gr.Column(visible=False) as yt_link_col:
+                        song_input = gr.Text(label='Song input', info='Link to a song on YouTube or full path to a local file. For file upload, click the button below.')
+                        show_file_upload_button = gr.Button('Upload file instead')
+
+                    with gr.Column(visible=True) as file_upload_col:
+                        audio_extensions = ['.mp3', '.m4a', '.flac', '.wav', '.aac', '.ogg', '.wma', '.alac', '.aiff', '.opus', 'amr']
+                        local_file = gr.Audio(label='Audio file', interactive=True, type="filepath", file_types=audio_extensions, height=150)
+                        if not IS_ZERO_GPU:
+                            with gr.Row():
+                                with gr.Row(scale=2):
+                                    url_media_gui = gr.Textbox(value="", label="Enter URL", placeholder="www.youtube.com/watch?v=g_9rPvbENUw", lines=1)
+                                with gr.Row(scale=1):
+                                    url_button_gui = gr.Button("Process URL", variant="secondary")
+                            url_button_gui.click(yt_download, [url_media_gui], [local_file])
+                        song_input_file = gr.UploadButton('Upload 📂', file_types=['audio'], variant='primary', visible=False)
+                        show_yt_link_button = gr.Button('Paste YouTube link/Path to local file instead', visible=False)
+                        song_input_file.upload(process_file_upload, inputs=[song_input_file], outputs=[local_file, song_input])
+
+                    with gr.Column():
+                        pitch = gr.Slider(-3, 3, value=0, step=1, label='Pitch Change (Vocals ONLY)', info='Generally, use 1 for male to female conversions and -1 for vice-versa. (Octaves)')
+                        pitch_all = gr.Slider(-12, 12, value=0, step=1, label='Overall Pitch Change', info='Changes pitch/key of vocals and instrumentals together. Altering this slightly reduces sound quality. (Semitones)')
+                    show_file_upload_button.click(swap_visibility, outputs=[file_upload_col, yt_link_col, song_input, local_file])
+                    show_yt_link_button.click(swap_visibility, outputs=[yt_link_col, file_upload_col, song_input, local_file])
+
+            with gr.Accordion('Voice conversion options', open=False):
+                with gr.Row():
+                    index_rate = gr.Slider(0, 1, value=0.5, label='Index Rate', info="Controls how much of the AI voice's accent to keep in the vocals")
+                    filter_radius = gr.Slider(0, 7, value=3, step=1, label='Filter radius', info='If >=3: apply median filtering median filtering to the harvested pitch results. Can reduce breathiness')
+                    rms_mix_rate = gr.Slider(0, 1, value=0.25, label='RMS mix rate', info="Control how much to mimic the original vocal's loudness (0) or a fixed loudness (1)")
+                    protect = gr.Slider(0, 0.5, value=0.33, label='Protect rate', info='Protect voiceless consonants and breath sounds. Set to 0.5 to disable.')
+                    with gr.Column():
+                        f0_method = gr.Dropdown(['rmvpe+', 'rmvpe', 'mangio-crepe'], value='rmvpe+', label='Pitch detection algorithm', info='Best option is rmvpe (clarity in vocals), then mangio-crepe (smoother vocals), rmvpe+ use a minimum and maximum allowed pitch values.')
+                        crepe_hop_length = gr.Slider(32, 320, value=128, step=1, visible=False, label='Crepe hop length', info='Lower values leads to longer conversions and higher risk of voice cracks, but better pitch accuracy.')
+                        f0_method.change(show_hop_slider, inputs=f0_method, outputs=crepe_hop_length)
+                with gr.Row():
+                    with gr.Row():
+                        steps = gr.Slider(minimum=1, maximum=3, label="Steps", value=1, step=1, interactive=True)
+                    with gr.Row():
+                        extra_denoise = gr.Checkbox(True, label='Denoise', info='Apply an additional noise reduction step to clean up the audio further.')
+                        keep_files = gr.Checkbox((False if IS_ZERO_GPU else True), label='Keep intermediate files', info='Keep all audio files generated in the song_output/id directory, e.g. Isolated Vocals/Instrumentals. Leave unchecked to save space', interactive=(False if IS_ZERO_GPU else True))
+
+            with gr.Accordion('Audio mixing options', open=False):
+                gr.Markdown('### Volume Change (decibels)')
+                with gr.Row():
+                    main_gain = gr.Slider(-20, 20, value=0, step=1, label='Main Vocals')
+                    backup_gain = gr.Slider(-20, 20, value=0, step=1, label='Backup Vocals')
+                    inst_gain = gr.Slider(-20, 20, value=0, step=1, label='Music')
+
+                gr.Markdown('### Reverb Control on AI Vocals')
+                with gr.Row():
+                    reverb_rm_size = gr.Slider(0, 1, value=0.15, label='Room size', info='The larger the room, the longer the reverb time')
+                    reverb_wet = gr.Slider(0, 1, value=0.2, label='Wetness level', info='Level of AI vocals with reverb')
+                    reverb_dry = gr.Slider(0, 1, value=0.8, label='Dryness level', info='Level of AI vocals without reverb')
+                    reverb_damping = gr.Slider(0, 1, value=0.7, label='Damping level', info='Absorption of high frequencies in the reverb')
+
+                gr.Markdown('### Audio Output Format')
+                output_format = gr.Dropdown(['mp3', 'wav'], value='mp3', label='Output file type', info='mp3: small file size, decent quality. wav: Large file size, best quality')
+
+            with gr.Row():
+                clear_btn = gr.ClearButton(value='Clear', components=[song_input, rvc_model, keep_files, local_file])
+                generate_btn = gr.Button("Generate", variant='primary')
+                ai_cover = gr.File(label="AI Cover", interactive=False)
+                
+            
+            ref_btn.click(update_models_list, None, outputs=rvc_model)
+            is_webui = gr.Number(value=1, visible=False)
+            generate_btn.click(song_cover_pipeline,
+                               inputs=[local_file, rvc_model, pitch, keep_files, is_webui, main_gain, backup_gain,
+                                       inst_gain, index_rate, filter_radius, rms_mix_rate, f0_method, crepe_hop_length,
+                                       protect, pitch_all, reverb_rm_size, reverb_wet, reverb_dry, reverb_damping,
+                                       output_format, extra_denoise, steps],
+                               outputs=[ai_cover])
+            clear_btn.click(lambda: [0, 0, 0, 0, 0.5, 3, 0.25, 0.33, 'rmvpe+', 128, 0, 0.15, 0.2, 0.8, 0.7, 'mp3', None, True, 1],
+                            outputs=[pitch, main_gain, backup_gain, inst_gain, index_rate, filter_radius, rms_mix_rate,
+                                     protect, f0_method, crepe_hop_length, pitch_all, reverb_rm_size, reverb_wet,
+                                     reverb_dry, reverb_damping, output_format, ai_cover, extra_denoise, steps])
+
+        # Download tab
+        with gr.Tab('Download model'):
+
+            with gr.Tab('From HuggingFace/Pixeldrain URL'):
+                with gr.Row():
+                    model_zip_link = gr.Text(label='Download link to model', info='Should be a zip file containing a .pth model file and an optional .index file.')
+                    model_name = gr.Text(label='Name your model', info='Give your new model a unique name from your other voice models.')
+
+                with gr.Row():
+                    download_btn = gr.Button('Download 🌐', variant='primary', scale=19)
+                    dl_output_message = gr.Text(label='Output Message', interactive=False, scale=20)
+
+                download_btn.click(download_online_model, inputs=[model_zip_link, model_name], outputs=dl_output_message)
+
+                gr.Markdown('## Input Examples')
+                gr.Examples(
+                    [
+                        ['https://huggingface.co/MrDawg/ToothBrushing/resolve/main/ToothBrushing.zip?download=true', 'ToothBrushing'],
+                        ['https://huggingface.co/sail-rvc/Aldeano_Minecraft__RVC_V2_-_500_Epochs_/resolve/main/model.pth?download=true, https://huggingface.co/sail-rvc/Aldeano_Minecraft__RVC_V2_-_500_Epochs_/resolve/main/model.index?download=true', 'Minecraft_Villager'],
+                        ['https://huggingface.co/phant0m4r/LiSA/resolve/main/LiSA.zip', 'Lisa'],
+                        ['https://pixeldrain.com/u/3tJmABXA', 'Gura'],
+                        ['https://huggingface.co/Kit-Lemonfoot/kitlemonfoot_rvc_models/resolve/main/AZKi%20(Hybrid).zip', 'Azki']
+                    ],
+                    [model_zip_link, model_name],
+                    [],
+                    download_online_model,
+                    cache_examples=False,
+                )
+
+            with gr.Tab('From Public Index'):
+
+                gr.Markdown('## How to use')
+                gr.Markdown('- Click Initialize public models table')
+                gr.Markdown('- Filter models using tags or search bar')
+                gr.Markdown('- Select a row to autofill the download link and model name')
+                gr.Markdown('- Click Download')
+
+                with gr.Row():
+                    pub_zip_link = gr.Text(label='Download link to model')
+                    pub_model_name = gr.Text(label='Model name')
+
+                with gr.Row():
+                    download_pub_btn = gr.Button('Download 🌐', variant='primary', scale=19)
+                    pub_dl_output_message = gr.Text(label='Output Message', interactive=False, scale=20)
+
+                filter_tags = gr.CheckboxGroup(value=[], label='Show voice models with tags', choices=[])
+                search_query = gr.Text(label='Search')
+                load_public_models_button = gr.Button(value='Initialize public models table', variant='primary')
+
+                public_models_table = gr.DataFrame(value=[], headers=['Model Name', 'Description', 'Credit', 'URL', 'Tags'], label='Available Public Models', interactive=False)
+                public_models_table.select(pub_dl_autofill, inputs=[public_models_table], outputs=[pub_zip_link, pub_model_name])
+                load_public_models_button.click(load_public_models, outputs=[public_models_table, filter_tags])
+                search_query.change(filter_models, inputs=[filter_tags, search_query], outputs=public_models_table)
+                filter_tags.change(filter_models, inputs=[filter_tags, search_query], outputs=public_models_table)
+                download_pub_btn.click(download_online_model, inputs=[pub_zip_link, pub_model_name], outputs=pub_dl_output_message)
+
+        # Upload tab
+        with gr.Tab('Upload model'):
+            gr.Markdown('## Upload locally trained RVC v2 model and index file')
+            gr.Markdown('- Find model file (weights folder) and optional index file (logs/[name] folder)')
+            gr.Markdown('- Compress files into zip file')
+            gr.Markdown('- Upload zip file and give unique name for voice')
+            gr.Markdown('- Click Upload model')
+
+            with gr.Row():
+                with gr.Column():
+                    zip_file = gr.File(label='Zip file')
+
+                local_model_name = gr.Text(label='Model name')
+
+            with gr.Row():
+                model_upload_button = gr.Button('Upload model', variant='primary', scale=19)
+                local_upload_output_message = gr.Text(label='Output Message', interactive=False, scale=20)
+                model_upload_button.click(upload_local_model, inputs=[zip_file, local_model_name], outputs=local_upload_output_message)
+
+    app.launch(
+        share=args.share_enabled,
+        debug=args.share_enabled,
+        show_error=True,
+        # enable_queue=True,
+        server_name=None if not args.listen else (args.listen_host or '0.0.0.0'),
+        server_port=args.listen_port,
+        ssr_mode=args.ssr
+    )