Update app.py

app.py

@@ -27,24 +27,34 @@ from vc_infer_pipeline import VC
 from config import Config
 config = Config()
 logging.getLogger("numba").setLevel(logging.WARNING)
-limitation = os.getenv("SYSTEM") == "spaces"
+spaces = os.getenv("SYSTEM") == "spaces"
+force_support = None
+if config.unsupported is False:
+    if config.device == "mps" or config.device == "cpu":
+        force_support = False
+else:
+    force_support = True
 
 audio_mode = []
 f0method_mode = []
 f0method_info = ""
-if limitation is True:
-    audio_mode = ["Upload audio", "TTS Audio"]
-    f0method_mode = ["pm", "crepe", "harvest"]
-    f0method_info = "PM is fast, rmvpe is middle, Crepe or harvest is good but it was extremely slow (Default: PM)"
+
+if force_support is False or spaces is True:
+    if spaces is True:
+        audio_mode = ["Upload audio", "TTS Audio"]
+    else:
+        audio_mode = ["Input path", "Upload audio", "TTS Audio"]
+    f0method_mode = ["pm", "harvest"]
+    f0method_info = "PM is fast, Harvest is good but extremely slow, Rvmpe is alternative to harvest (might be better). (Default: PM)"
 else:
-    audio_mode = ["Upload audio", "Youtube", "TTS Audio"]
-    f0method_mode = ["pm", "crepe", "harvest"]
-    f0method_info = "PM is fast, rmvpe is middle. Crepe or harvest is good but it was extremely slow (Default: PM))"
+    audio_mode = ["Input path", "Upload audio", "Youtube", "TTS Audio"]
+    f0method_mode = ["pm", "harvest", "crepe"]
+    f0method_info = "PM is fast, Harvest is good but extremely slow, Rvmpe is alternative to harvest (might be better), and Crepe effect is good but requires GPU (Default: PM)"
 
 if os.path.isfile("rmvpe.pt"):
     f0method_mode.insert(2, "rmvpe")
 
-def create_vc_fn(model_title, tgt_sr, net_g, vc, if_f0, version, file_index):
+def create_vc_fn(model_name, tgt_sr, net_g, vc, if_f0, version, file_index):
     def vc_fn(
         vc_audio_mode,
         vc_input, 
@@ -60,6 +70,10 @@ def create_vc_fn(model_title, tgt_sr, net_g, vc, if_f0, version, file_index):
         protect,
     ):
         try:
+            logs = []
+            print(f"Converting using {model_name}...")
+            logs.append(f"Converting using {model_name}...")
+            yield "\n".join(logs), None
             if vc_audio_mode == "Input path" or "Youtube" and vc_input != "":
                 audio, sr = librosa.load(vc_input, sr=16000, mono=True)
             elif vc_audio_mode == "Upload audio":
@@ -67,15 +81,15 @@ def create_vc_fn(model_title, tgt_sr, net_g, vc, if_f0, version, file_index):
                     return "You need to upload an audio", None
                 sampling_rate, audio = vc_upload
                 duration = audio.shape[0] / sampling_rate
-                if duration > 360 and limitation:
-                    return "Please upload an audio file that is less than 1 minute.", None
+                if duration > 20 and spaces:
+                    return "Please upload an audio file that is less than 20 seconds. If you need to generate a longer audio file, please use Colab.", None
                 audio = (audio / np.iinfo(audio.dtype).max).astype(np.float32)
                 if len(audio.shape) > 1:
                     audio = librosa.to_mono(audio.transpose(1, 0))
                 if sampling_rate != 16000:
                     audio = librosa.resample(audio, orig_sr=sampling_rate, target_sr=16000)
             elif vc_audio_mode == "TTS Audio":
-                if len(tts_text) > 600 and limitation:
+                if len(tts_text) > 100 and spaces:
                     return "Text is too long", None
                 if tts_text is None or tts_voice is None:
                     return "You need to enter text and select a voice", None
@@ -106,118 +120,121 @@ def create_vc_fn(model_title, tgt_sr, net_g, vc, if_f0, version, file_index):
                 f0_file=None,
             )
             info = f"[{datetime.now().strftime('%Y-%m-%d %H:%M')}]: npy: {times[0]}, f0: {times[1]}s, infer: {times[2]}s"
-            print(f"{model_title} | {info}")
-            return info, (tgt_sr, audio_opt)
+            print(f"{model_name} | {info}")
+            logs.append(f"Successfully Convert {model_name}\n{info}")
+            yield "\n".join(logs), (tgt_sr, audio_opt)
         except:
             info = traceback.format_exc()
             print(info)
-            return info, (None, None)
+            yield info, None
     return vc_fn
 
 def load_model():
     categories = []
-    with open("weights/folder_info.json", "r", encoding="utf-8") as f:
-        folder_info = json.load(f)
-    for category_name, category_info in folder_info.items():
-        if not category_info['enable']:
-            continue
-        category_title = category_info['title']
-        category_folder = category_info['folder_path']
-        models = []
-        with open(f"weights/{category_folder}/model_info.json", "r", encoding="utf-8") as f:
-            models_info = json.load(f)
-        for character_name, info in models_info.items():
-            if not info['enable']:
+    if os.path.isfile("weights/folder_info.json"):
+        with open("weights/folder_info.json", "r", encoding="utf-8") as f:
+            folder_info = json.load(f)
+        for category_name, category_info in folder_info.items():
+            if not category_info['enable']:
                 continue
-            model_title = info['title']
-            model_name = info['model_path']
-            model_author = info.get("author", None)
-            model_cover = f"weights/{category_folder}/{character_name}/{info['cover']}"
-            model_index = f"weights/{category_folder}/{character_name}/{info['feature_retrieval_library']}"
-            cpt = torch.load(f"weights/{category_folder}/{character_name}/{model_name}", map_location="cpu")
-            tgt_sr = cpt["config"][-1]
-            cpt["config"][-3] = cpt["weight"]["emb_g.weight"].shape[0]  # n_spk
-            if_f0 = cpt.get("f0", 1)
-            version = cpt.get("version", "v1")
-            if version == "v1":
-                if if_f0 == 1:
-                    net_g = SynthesizerTrnMs256NSFsid(*cpt["config"], is_half=config.is_half)
-                else:
-                    net_g = SynthesizerTrnMs256NSFsid_nono(*cpt["config"])
-                model_version = "V1"
-            elif version == "v2":
-                if if_f0 == 1:
-                    net_g = SynthesizerTrnMs768NSFsid(*cpt["config"], is_half=config.is_half)
+            category_title = category_info['title']
+            category_folder = category_info['folder_path']
+            description = category_info['description']
+            models = []
+            with open(f"weights/{category_folder}/model_info.json", "r", encoding="utf-8") as f:
+                models_info = json.load(f)
+            for character_name, info in models_info.items():
+                if not info['enable']:
+                    continue
+                model_title = info['title']
+                model_name = info['model_path']
+                model_author = info.get("author", None)
+                model_cover = f"weights/{category_folder}/{character_name}/{info['cover']}"
+                model_index = f"weights/{category_folder}/{character_name}/{info['feature_retrieval_library']}"
+                cpt = torch.load(f"weights/{category_folder}/{character_name}/{model_name}", map_location="cpu")
+                tgt_sr = cpt["config"][-1]
+                cpt["config"][-3] = cpt["weight"]["emb_g.weight"].shape[0]  # n_spk
+                if_f0 = cpt.get("f0", 1)
+                version = cpt.get("version", "v1")
+                if version == "v1":
+                    if if_f0 == 1:
+                        net_g = SynthesizerTrnMs256NSFsid(*cpt["config"], is_half=config.is_half)
+                    else:
+                        net_g = SynthesizerTrnMs256NSFsid_nono(*cpt["config"])
+                    model_version = "V1"
+                elif version == "v2":
+                    if if_f0 == 1:
+                        net_g = SynthesizerTrnMs768NSFsid(*cpt["config"], is_half=config.is_half)
+                    else:
+                        net_g = SynthesizerTrnMs768NSFsid_nono(*cpt["config"])
+                    model_version = "V2"
+                del net_g.enc_q
+                print(net_g.load_state_dict(cpt["weight"], strict=False))
+                net_g.eval().to(config.device)
+                if config.is_half:
+                    net_g = net_g.half()
                 else:
-                    net_g = SynthesizerTrnMs768NSFsid_nono(*cpt["config"])
-                model_version = "V2"
-            del net_g.enc_q
-            print(net_g.load_state_dict(cpt["weight"], strict=False))
-            net_g.eval().to(config.device)
-            if config.is_half:
-                net_g = net_g.half()
-            else:
-                net_g = net_g.float()
-            vc = VC(tgt_sr, config)
-            print(f"Model loaded: {character_name} / {info['feature_retrieval_library']} | ({model_version})")
-            models.append((character_name, model_title, model_author, model_cover, model_version, create_vc_fn(model_title, tgt_sr, net_g, vc, if_f0, version, model_index)))
-        categories.append([category_title, category_folder, models])
+                    net_g = net_g.float()
+                vc = VC(tgt_sr, config)
+                print(f"Model loaded: {character_name} / {info['feature_retrieval_library']} | ({model_version})")
+                models.append((character_name, model_title, model_author, model_cover, model_version, create_vc_fn(model_name, tgt_sr, net_g, vc, if_f0, version, model_index)))
+            categories.append([category_title, category_folder, description, models])
+    else:
+        categories = []
     return categories
 
-def cut_vocal_and_inst(url, audio_provider, split_model):
-    if url != "":
-        if not os.path.exists("dl_audio"):
-            os.mkdir("dl_audio")
-        if audio_provider == "Youtube":
-            ydl_opts = {
+def download_audio(url, audio_provider):
+    logs = []
+    if url == "":
+        raise gr.Error("URL Required!")
+        return "URL Required"
+    if not os.path.exists("dl_audio"):
+        os.mkdir("dl_audio")
+    if audio_provider == "Youtube":
+        logs.append("Downloading the audio...")
+        yield None, "\n".join(logs)
+        ydl_opts = {
+            'noplaylist': True,
             'format': 'bestaudio/best',
             'postprocessors': [{
                 'key': 'FFmpegExtractAudio',
                 'preferredcodec': 'wav',
             }],
-            "outtmpl": 'dl_audio/youtube_audio',
-            }
-            with yt_dlp.YoutubeDL(ydl_opts) as ydl:
-                ydl.download([url])
-            audio_path = "dl_audio/youtube_audio.wav"
-        else:
-            # Spotify doesnt work.
-            # Need to find other solution soon.
-            ''' 
-            command = f"spotdl download {url} --output dl_audio/.wav"
-            result = subprocess.run(command.split(), stdout=subprocess.PIPE)
-            print(result.stdout.decode())
-            audio_path = "dl_audio/spotify_audio.wav"
-            '''
-        if split_model == "htdemucs":
-            command = f"demucs --two-stems=vocals {audio_path} -o output"
-            result = subprocess.run(command.split(), stdout=subprocess.PIPE)
-            print(result.stdout.decode())
-            return "output/htdemucs/youtube_audio/vocals.wav", "output/htdemucs/youtube_audio/no_vocals.wav", audio_path, "output/htdemucs/youtube_audio/vocals.wav"
-        else:
-            command = f"demucs --two-stems=vocals -n mdx_extra_q {audio_path} -o output"
-            result = subprocess.run(command.split(), stdout=subprocess.PIPE)
-            print(result.stdout.decode())
-            return "output/mdx_extra_q/youtube_audio/vocals.wav", "output/mdx_extra_q/youtube_audio/no_vocals.wav", audio_path, "output/mdx_extra_q/youtube_audio/vocals.wav"
-    else:
-        raise gr.Error("URL Required!")
-        return None, None, None, None
+            "outtmpl": 'dl_audio/audio',
+        }
+        audio_path = "dl_audio/audio.wav"
+        with yt_dlp.YoutubeDL(ydl_opts) as ydl:
+            ydl.download([url])
+        logs.append("Download Complete.")
+        yield audio_path, "\n".join(logs)
+
+def cut_vocal_and_inst(split_model):
+    logs = []
+    logs.append("Starting the audio splitting process...")
+    yield "\n".join(logs), None, None, None, None
+    command = f"demucs --two-stems=vocals -n {split_model} dl_audio/audio.wav -o output"
+    result = subprocess.Popen(command.split(), stdout=subprocess.PIPE, text=True)
+    for line in result.stdout:
+        logs.append(line)
+        yield "\n".join(logs), None, None, None, None
+    print(result.stdout)
+    vocal = f"output/{split_model}/audio/vocals.wav"
+    inst = f"output/{split_model}/audio/no_vocals.wav"
+    logs.append("Audio splitting complete.")
+    yield "\n".join(logs), vocal, inst, vocal
 
-def combine_vocal_and_inst(audio_data, audio_volume, split_model):
+def combine_vocal_and_inst(audio_data, vocal_volume, inst_volume, split_model):
     if not os.path.exists("output/result"):
         os.mkdir("output/result")
     vocal_path = "output/result/output.wav"
     output_path = "output/result/combine.mp3"
-    if split_model == "htdemucs":
-        inst_path = "output/htdemucs/youtube_audio/no_vocals.wav"
-    else:
-        inst_path = "output/mdx_extra_q/youtube_audio/no_vocals.wav"
+    inst_path = f"output/{split_model}/audio/no_vocals.wav"
     with wave.open(vocal_path, "w") as wave_file:
         wave_file.setnchannels(1) 
         wave_file.setsampwidth(2)
         wave_file.setframerate(audio_data[0])
         wave_file.writeframes(audio_data[1].tobytes())
-    command =  f'ffmpeg -y -i {inst_path} -i {vocal_path} -filter_complex [1:a]volume={audio_volume}dB[v];[0:a][v]amix=inputs=2:duration=longest -b:a 320k -c:a libmp3lame {output_path}'
+    command =  f'ffmpeg -y -i {inst_path} -i {vocal_path} -filter_complex [0:a]volume={inst_volume}[i];[1:a]volume={vocal_volume}[v];[i][v]amix=inputs=2:duration=longest[a] -map [a] -b:a 320k -c:a libmp3lame {output_path}'
     result = subprocess.run(command.split(), stdout=subprocess.PIPE)
     print(result.stdout.decode())
     return output_path
@@ -241,16 +258,22 @@ def change_audio_mode(vc_audio_mode):
         return (
             # Input & Upload
             gr.Textbox.update(visible=True),
+            gr.Checkbox.update(visible=False),
             gr.Audio.update(visible=False),
             # Youtube
             gr.Dropdown.update(visible=False),
             gr.Textbox.update(visible=False),
+            gr.Textbox.update(visible=False),
+            gr.Button.update(visible=False),
+            # Splitter
             gr.Dropdown.update(visible=False),
+            gr.Textbox.update(visible=False),
             gr.Button.update(visible=False),
             gr.Audio.update(visible=False),
             gr.Audio.update(visible=False),
             gr.Audio.update(visible=False),
             gr.Slider.update(visible=False),
+            gr.Slider.update(visible=False),
             gr.Audio.update(visible=False),
             gr.Button.update(visible=False),
             # TTS
@@ -261,16 +284,22 @@ def change_audio_mode(vc_audio_mode):
         return (
             # Input & Upload
             gr.Textbox.update(visible=False),
+            gr.Checkbox.update(visible=True),
             gr.Audio.update(visible=True),
             # Youtube
             gr.Dropdown.update(visible=False),
             gr.Textbox.update(visible=False),
+            gr.Textbox.update(visible=False),
+            gr.Button.update(visible=False),
+            # Splitter
             gr.Dropdown.update(visible=False),
+            gr.Textbox.update(visible=False),
             gr.Button.update(visible=False),
             gr.Audio.update(visible=False),
             gr.Audio.update(visible=False),
             gr.Audio.update(visible=False),
             gr.Slider.update(visible=False),
+            gr.Slider.update(visible=False),
             gr.Audio.update(visible=False),
             gr.Button.update(visible=False),
             # TTS
@@ -281,16 +310,22 @@ def change_audio_mode(vc_audio_mode):
         return (
             # Input & Upload
             gr.Textbox.update(visible=False),
+            gr.Checkbox.update(visible=False),
             gr.Audio.update(visible=False),
             # Youtube
             gr.Dropdown.update(visible=True),
             gr.Textbox.update(visible=True),
+            gr.Textbox.update(visible=True),
+            gr.Button.update(visible=True),
+            # Splitter
             gr.Dropdown.update(visible=True),
+            gr.Textbox.update(visible=True),
             gr.Button.update(visible=True),
             gr.Audio.update(visible=True),
             gr.Audio.update(visible=True),
             gr.Audio.update(visible=True),
             gr.Slider.update(visible=True),
+            gr.Slider.update(visible=True),
             gr.Audio.update(visible=True),
             gr.Button.update(visible=True),
             # TTS
@@ -301,61 +336,63 @@ def change_audio_mode(vc_audio_mode):
         return (
             # Input & Upload
             gr.Textbox.update(visible=False),
+            gr.Checkbox.update(visible=False),
             gr.Audio.update(visible=False),
             # Youtube
             gr.Dropdown.update(visible=False),
             gr.Textbox.update(visible=False),
+            gr.Textbox.update(visible=False),
+            gr.Button.update(visible=False),
+            # Splitter
             gr.Dropdown.update(visible=False),
+            gr.Textbox.update(visible=False),
             gr.Button.update(visible=False),
             gr.Audio.update(visible=False),
             gr.Audio.update(visible=False),
             gr.Audio.update(visible=False),
             gr.Slider.update(visible=False),
+            gr.Slider.update(visible=False),
             gr.Audio.update(visible=False),
             gr.Button.update(visible=False),
             # TTS
             gr.Textbox.update(visible=True),
             gr.Dropdown.update(visible=True)
         )
+
+def use_microphone(microphone):
+    if microphone == True:
+        return gr.Audio.update(source="microphone")
     else:
-        return (
-            # Input & Upload
-            gr.Textbox.update(visible=False),
-            gr.Audio.update(visible=True),
-            # Youtube
-            gr.Dropdown.update(visible=False),
-            gr.Textbox.update(visible=False),
-            gr.Dropdown.update(visible=False),
-            gr.Button.update(visible=False),
-            gr.Audio.update(visible=False),
-            gr.Audio.update(visible=False),
-            gr.Audio.update(visible=False),
-            gr.Slider.update(visible=False),
-            gr.Audio.update(visible=False),
-            gr.Button.update(visible=False),
-            # TTS
-            gr.Textbox.update(visible=False),
-            gr.Dropdown.update(visible=False)
-        )
+        return gr.Audio.update(source="upload")
 
 if __name__ == '__main__':
     load_hubert()
     categories = load_model()
-    tts_voice_list = asyncio.get_event_loop().run_until_complete(edge_tts.list_voices())
+    tts_voice_list = asyncio.new_event_loop().run_until_complete(edge_tts.list_voices())
     voices = [f"{v['ShortName']}-{v['Gender']}" for v in tts_voice_list]
-    with gr.Blocks(theme=gr.themes.Base()) as app:
+    with gr.Blocks() as app:
         gr.Markdown(
-            "# <center> RVC Models\n"
-            "### <center> Recommended to use Google Colab to use other character and feature.\n"
-            "[![image](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/aziib/hololive-rvc-models-v2/blob/main/hololive_rvc_models_v2.ipynb)\n\n"
-            "[![ko-fi](https://ko-fi.com/img/githubbutton_sm.svg)](https://ko-fi.com/megaaziib)\n\n"
+            "<div align='center'>\n\n"+
+            "# RVC Models\n\n"+
+            "### Recommended to use Google Colab to use other character and feature.\n\n"+
+            "</div>\n\n"+
+            "[![Repository](https://img.shields.io/badge/Github-Multi%20Model%20RVC%20Inference-blue?style=for-the-badge&logo=github)](https://github.com/ArkanDash/Multi-Model-RVC-Inference)\n\n"+
+            "</div>"
         )
-        for (folder_title, folder, models) in categories:
+        if categories == []:
+            gr.Markdown(
+                "<div align='center'>\n\n"+
+                "## No model found, please add the model into weights folder\n\n"+
+                "</div>"
+            )
+        for (folder_title, folder, description, models) in categories:
             with gr.TabItem(folder_title):
+                if description:
+                    gr.Markdown(f"### <center> {description}")
                 with gr.Tabs():
                     if not models:
                         gr.Markdown("# <center> No Model Loaded.")
-                        gr.Markdown("## <center> Please add model or fix your model path.")
+                        gr.Markdown("## <center> Please add the model or fix your model path.")
                         continue
                     for (name, title, author, cover, model_version, vc_fn) in models:
                         with gr.TabItem(name):
@@ -369,95 +406,217 @@ if __name__ == '__main__':
                                     '</div>'
                                 )
                             with gr.Row():
-                                with gr.Column():
-                                    vc_audio_mode = gr.Dropdown(label="Input voice", choices=audio_mode, allow_custom_value=False, value="Upload audio")
-                                    # Input and Upload
-                                    vc_input = gr.Textbox(label="Input audio path", visible=False)
-                                    vc_upload = gr.Audio(label="Upload audio file", visible=True, interactive=True)
-                                    # Youtube
-                                    vc_download_audio = gr.Dropdown(label="Provider", choices=["Youtube"], allow_custom_value=False, visible=False, value="Youtube", info="Select provider (Default: Youtube)")
-                                    vc_link = gr.Textbox(label="Youtube URL", visible=False, info="Example: https://www.youtube.com/watch?v=Nc0sB1Bmf-A", placeholder="https://www.youtube.com/watch?v=...")
-                                    vc_split_model = gr.Dropdown(label="Splitter Model", choices=["htdemucs", "mdx_extra_q"], allow_custom_value=False, visible=False, value="htdemucs", info="Select the splitter model (Default: htdemucs)")
-                                    vc_split = gr.Button("Split Audio", variant="primary", visible=False)
-                                    vc_vocal_preview = gr.Audio(label="Vocal Preview", visible=False)
-                                    vc_inst_preview = gr.Audio(label="Instrumental Preview", visible=False)
-                                    vc_audio_preview = gr.Audio(label="Audio Preview", visible=False)
-                                    # TTS
-                                    tts_text = gr.Textbox(visible=False, label="TTS text", info="Text to speech input")
-                                    tts_voice = gr.Dropdown(label="Edge-tts speaker", choices=voices, visible=False, allow_custom_value=False, value="en-US-AnaNeural-Female")
-                                with gr.Column():
-                                    vc_transform0 = gr.Number(label="Transpose", value=0, info='Type "12" to change from male to female voice. Type "-12" to change female to male voice')
-                                    f0method0 = gr.Radio(
-                                        label="Pitch extraction algorithm",
-                                        info=f0method_info,
-                                        choices=f0method_mode,
-                                        value="pm",
-                                        interactive=True
-                                    )
-                                    index_rate1 = gr.Slider(
-                                        minimum=0,
-                                        maximum=1,
-                                        label="Retrieval feature ratio",
-                                        info="Accents controling. Too high prob gonna sounds too robotic (Default: 0.4)",
-                                        value=0.4,
-                                        interactive=True,
-                                    )
-                                    filter_radius0 = gr.Slider(
-                                        minimum=0,
-                                        maximum=7,
-                                        label="Apply Median Filtering",
-                                        info="The value represents the filter radius and can reduce breathiness.",
-                                        value=1,
-                                        step=1,
-                                        interactive=True,
-                                    )
-                                    resample_sr0 = gr.Slider(
-                                        minimum=0,
-                                        maximum=48000,
-                                        label="Resample the output audio",
-                                        info="Resample the output audio in post-processing to the final sample rate. Set to 0 for no resampling",
-                                        value=0,
-                                        step=1,
-                                        interactive=True,
-                                    )
-                                    rms_mix_rate0 = gr.Slider(
-                                        minimum=0,
-                                        maximum=1,
-                                        label="Volume Envelope",
-                                        info="Use the volume envelope of the input to replace or mix with the volume envelope of the output. The closer the ratio is to 1, the more the output envelope is used",
-                                        value=1,
-                                        interactive=True,
-                                    )
-                                    protect0 = gr.Slider(
-                                        minimum=0,
-                                        maximum=0.5,
-                                        label="Voice Protection",
-                                        info="Protect voiceless consonants and breath sounds to prevent artifacts such as tearing in electronic music. Set to 0.5 to disable. Decrease the value to increase protection, but it may reduce indexing accuracy",
-                                        value=0.23,
-                                        step=0.01,
-                                        interactive=True,
-                                    )
-                                with gr.Column():
-                                    vc_log = gr.Textbox(label="Output Information", interactive=False)
-                                    vc_output = gr.Audio(label="Output Audio", interactive=False)
-                                    vc_convert = gr.Button("Convert", variant="primary")
-                                    vc_volume = gr.Slider(
-                                        minimum=0,
-                                        maximum=10,
-                                        label="Vocal volume",
-                                        value=4,
-                                        interactive=True,
-                                        step=1,
-                                        info="Adjust vocal volume (Default: 4}",
-                                        visible=False
-                                    )
-                                    vc_combined_output = gr.Audio(label="Output Combined Audio", visible=False)
-                                    vc_combine =  gr.Button("Combine",variant="primary", visible=False)
+                                if spaces is False:
+                                    with gr.TabItem("Input"):
+                                        with gr.Row():
+                                            with gr.Column():
+                                                vc_audio_mode = gr.Dropdown(label="Input voice", choices=audio_mode, allow_custom_value=False, value="Upload audio")
+                                                # Input
+                                                vc_input = gr.Textbox(label="Input audio path", visible=False)
+                                                # Upload
+                                                vc_microphone_mode = gr.Checkbox(label="Use Microphone", value=False, visible=True, interactive=True)
+                                                vc_upload = gr.Audio(label="Upload audio file", source="upload", visible=True, interactive=True)
+                                                # Youtube
+                                                vc_download_audio = gr.Dropdown(label="Provider", choices=["Youtube"], allow_custom_value=False, visible=False, value="Youtube", info="Select provider (Default: Youtube)")
+                                                vc_link = gr.Textbox(label="Youtube URL", visible=False, info="Example: https://www.youtube.com/watch?v=Nc0sB1Bmf-A", placeholder="https://www.youtube.com/watch?v=...")
+                                                vc_log_yt = gr.Textbox(label="Output Information", visible=False, interactive=False)
+                                                vc_download_button = gr.Button("Download Audio", variant="primary", visible=False)
+                                                vc_audio_preview = gr.Audio(label="Audio Preview", visible=False)
+                                                # TTS
+                                                tts_text = gr.Textbox(label="TTS text", info="Text to speech input", visible=False)
+                                                tts_voice = gr.Dropdown(label="Edge-tts speaker", choices=voices, visible=False, allow_custom_value=False, value="en-US-AnaNeural-Female")
+                                            with gr.Column():
+                                                vc_split_model = gr.Dropdown(label="Splitter Model", choices=["hdemucs_mmi", "htdemucs", "htdemucs_ft", "mdx", "mdx_q", "mdx_extra_q"], allow_custom_value=False, visible=False, value="htdemucs", info="Select the splitter model (Default: htdemucs)")
+                                                vc_split_log = gr.Textbox(label="Output Information", visible=False, interactive=False)
+                                                vc_split = gr.Button("Split Audio", variant="primary", visible=False)
+                                                vc_vocal_preview = gr.Audio(label="Vocal Preview", visible=False)
+                                                vc_inst_preview = gr.Audio(label="Instrumental Preview", visible=False)
+                                    with gr.TabItem("Convert"):
+                                        with gr.Row():
+                                            with gr.Column():
+                                                vc_transform0 = gr.Number(label="Transpose", value=0, info='Type "12" to change from male to female voice. Type "-12" to change female to male voice')
+                                                f0method0 = gr.Radio(
+                                                    label="Pitch extraction algorithm",
+                                                    info=f0method_info,
+                                                    choices=f0method_mode,
+                                                    value="pm",
+                                                    interactive=True
+                                                )
+                                                index_rate1 = gr.Slider(
+                                                    minimum=0,
+                                                    maximum=1,
+                                                    label="Retrieval feature ratio",
+                                                    info="(Default: 0.7)",
+                                                    value=0.7,
+                                                    interactive=True,
+                                                )
+                                                filter_radius0 = gr.Slider(
+                                                    minimum=0,
+                                                    maximum=7,
+                                                    label="Apply Median Filtering",
+                                                    info="The value represents the filter radius and can reduce breathiness.",
+                                                    value=3,
+                                                    step=1,
+                                                    interactive=True,
+                                                )
+                                                resample_sr0 = gr.Slider(
+                                                    minimum=0,
+                                                    maximum=48000,
+                                                    label="Resample the output audio",
+                                                    info="Resample the output audio in post-processing to the final sample rate. Set to 0 for no resampling",
+                                                    value=0,
+                                                    step=1,
+                                                    interactive=True,
+                                                )
+                                                rms_mix_rate0 = gr.Slider(
+                                                    minimum=0,
+                                                    maximum=1,
+                                                    label="Volume Envelope",
+                                                    info="Use the volume envelope of the input to replace or mix with the volume envelope of the output. The closer the ratio is to 1, the more the output envelope is used",
+                                                    value=1,
+                                                    interactive=True,
+                                                )
+                                                protect0 = gr.Slider(
+                                                    minimum=0,
+                                                    maximum=0.5,
+                                                    label="Voice Protection",
+                                                    info="Protect voiceless consonants and breath sounds to prevent artifacts such as tearing in electronic music. Set to 0.5 to disable. Decrease the value to increase protection, but it may reduce indexing accuracy",
+                                                    value=0.5,
+                                                    step=0.01,
+                                                    interactive=True,
+                                                )
+                                            with gr.Column():
+                                                vc_log = gr.Textbox(label="Output Information", interactive=False)
+                                                vc_output = gr.Audio(label="Output Audio", interactive=False)
+                                                vc_convert = gr.Button("Convert", variant="primary")
+                                                vc_vocal_volume = gr.Slider(
+                                                    minimum=0,
+                                                    maximum=10,
+                                                    label="Vocal volume",
+                                                    value=1,
+                                                    interactive=True,
+                                                    step=1,
+                                                    info="Adjust vocal volume (Default: 1}",
+                                                    visible=False
+                                                )
+                                                vc_inst_volume = gr.Slider(
+                                                    minimum=0,
+                                                    maximum=10,
+                                                    label="Instrument volume",
+                                                    value=1,
+                                                    interactive=True,
+                                                    step=1,
+                                                    info="Adjust instrument volume (Default: 1}",
+                                                    visible=False
+                                                )
+                                                vc_combined_output = gr.Audio(label="Output Combined Audio", visible=False)
+                                                vc_combine =  gr.Button("Combine",variant="primary", visible=False)
+                                else:
+                                    with gr.Column():
+                                        vc_audio_mode = gr.Dropdown(label="Input voice", choices=audio_mode, allow_custom_value=False, value="Upload audio")
+                                        # Input
+                                        vc_input = gr.Textbox(label="Input audio path", visible=False)
+                                        # Upload
+                                        vc_microphone_mode = gr.Checkbox(label="Use Microphone", value=False, visible=True, interactive=True)
+                                        vc_upload = gr.Audio(label="Upload audio file", source="upload", visible=True, interactive=True)
+                                        # Youtube
+                                        vc_download_audio = gr.Dropdown(label="Provider", choices=["Youtube"], allow_custom_value=False, visible=False, value="Youtube", info="Select provider (Default: Youtube)")
+                                        vc_link = gr.Textbox(label="Youtube URL", visible=False, info="Example: https://www.youtube.com/watch?v=Nc0sB1Bmf-A", placeholder="https://www.youtube.com/watch?v=...")
+                                        vc_log_yt = gr.Textbox(label="Output Information", visible=False, interactive=False)
+                                        vc_download_button = gr.Button("Download Audio", variant="primary", visible=False)
+                                        vc_audio_preview = gr.Audio(label="Audio Preview", visible=False)
+                                        # Splitter
+                                        vc_split_model = gr.Dropdown(label="Splitter Model", choices=["hdemucs_mmi", "htdemucs", "htdemucs_ft", "mdx", "mdx_q", "mdx_extra_q"], allow_custom_value=False, visible=False, value="htdemucs", info="Select the splitter model (Default: htdemucs)")
+                                        vc_split_log = gr.Textbox(label="Output Information", visible=False, interactive=False)
+                                        vc_split = gr.Button("Split Audio", variant="primary", visible=False)
+                                        vc_vocal_preview = gr.Audio(label="Vocal Preview", visible=False)
+                                        vc_inst_preview = gr.Audio(label="Instrumental Preview", visible=False)
+                                        # TTS
+                                        tts_text = gr.Textbox(label="TTS text", info="Text to speech input", visible=False)
+                                        tts_voice = gr.Dropdown(label="Edge-tts speaker", choices=voices, visible=False, allow_custom_value=False, value="en-US-AnaNeural-Female")
+                                    with gr.Column():
+                                        vc_transform0 = gr.Number(label="Transpose", value=0, info='Type "12" to change from male to female voice. Type "-12" to change female to male voice')
+                                        f0method0 = gr.Radio(
+                                            label="Pitch extraction algorithm",
+                                            info=f0method_info,
+                                            choices=f0method_mode,
+                                            value="pm",
+                                            interactive=True
+                                        )
+                                        index_rate1 = gr.Slider(
+                                            minimum=0,
+                                            maximum=1,
+                                            label="Retrieval feature ratio",
+                                            info="(Default: 0.7)",
+                                            value=0.7,
+                                            interactive=True,
+                                        )
+                                        filter_radius0 = gr.Slider(
+                                            minimum=0,
+                                            maximum=7,
+                                            label="Apply Median Filtering",
+                                            info="The value represents the filter radius and can reduce breathiness.",
+                                            value=3,
+                                            step=1,
+                                            interactive=True,
+                                        )
+                                        resample_sr0 = gr.Slider(
+                                            minimum=0,
+                                            maximum=48000,
+                                            label="Resample the output audio",
+                                            info="Resample the output audio in post-processing to the final sample rate. Set to 0 for no resampling",
+                                            value=0,
+                                            step=1,
+                                            interactive=True,
+                                        )
+                                        rms_mix_rate0 = gr.Slider(
+                                            minimum=0,
+                                            maximum=1,
+                                            label="Volume Envelope",
+                                            info="Use the volume envelope of the input to replace or mix with the volume envelope of the output. The closer the ratio is to 1, the more the output envelope is used",
+                                            value=1,
+                                            interactive=True,
+                                        )
+                                        protect0 = gr.Slider(
+                                            minimum=0,
+                                            maximum=0.5,
+                                            label="Voice Protection",
+                                            info="Protect voiceless consonants and breath sounds to prevent artifacts such as tearing in electronic music. Set to 0.5 to disable. Decrease the value to increase protection, but it may reduce indexing accuracy",
+                                            value=0.5,
+                                            step=0.01,
+                                            interactive=True,
+                                        )
+                                    with gr.Column():
+                                        vc_log = gr.Textbox(label="Output Information", interactive=False)
+                                        vc_output = gr.Audio(label="Output Audio", interactive=False)
+                                        vc_convert = gr.Button("Convert", variant="primary")
+                                        vc_vocal_volume = gr.Slider(
+                                            minimum=0,
+                                            maximum=10,
+                                            label="Vocal volume",
+                                            value=1,
+                                            interactive=True,
+                                            step=1,
+                                            info="Adjust vocal volume (Default: 1}",
+                                            visible=False
+                                        )
+                                        vc_inst_volume = gr.Slider(
+                                            minimum=0,
+                                            maximum=10,
+                                            label="Instrument volume",
+                                            value=1,
+                                            interactive=True,
+                                            step=1,
+                                            info="Adjust instrument volume (Default: 1}",
+                                            visible=False
+                                        )
+                                        vc_combined_output = gr.Audio(label="Output Combined Audio", visible=False)
+                                        vc_combine =  gr.Button("Combine",variant="primary", visible=False)
                         vc_convert.click(
                             fn=vc_fn, 
                             inputs=[
                                 vc_audio_mode,
-                                vc_input, 
+                                vc_input,
                                 vc_upload,
                                 tts_text,
                                 tts_voice,
@@ -471,37 +630,49 @@ if __name__ == '__main__':
                             ], 
                             outputs=[vc_log ,vc_output]
                         )
+                        vc_download_button.click(
+                            fn=download_audio, 
+                            inputs=[vc_link, vc_download_audio], 
+                            outputs=[vc_audio_preview, vc_log_yt]
+                        )
                         vc_split.click(
                             fn=cut_vocal_and_inst, 
-                            inputs=[vc_link, vc_download_audio, vc_split_model], 
-                            outputs=[vc_vocal_preview, vc_inst_preview, vc_audio_preview, vc_input]
+                            inputs=[vc_split_model], 
+                            outputs=[vc_split_log, vc_vocal_preview, vc_inst_preview, vc_input]
                         )
                         vc_combine.click(
                             fn=combine_vocal_and_inst,
-                            inputs=[vc_output, vc_volume, vc_split_model],
+                            inputs=[vc_output, vc_vocal_volume, vc_inst_volume, vc_split_model],
                             outputs=[vc_combined_output]
                         )
+                        vc_microphone_mode.change(
+                            fn=use_microphone,
+                            inputs=vc_microphone_mode,
+                            outputs=vc_upload
+                        )
                         vc_audio_mode.change(
                             fn=change_audio_mode,
                             inputs=[vc_audio_mode],
                             outputs=[
-                                vc_input, 
+                                vc_input,
+                                vc_microphone_mode,
                                 vc_upload,
                                 vc_download_audio,
                                 vc_link,
+                                vc_log_yt,
+                                vc_download_button,
                                 vc_split_model,
+                                vc_split_log,
                                 vc_split,
+                                vc_audio_preview,
                                 vc_vocal_preview,
                                 vc_inst_preview,
-                                vc_audio_preview,
-                                vc_volume,
+                                vc_vocal_volume,
+                                vc_inst_volume,
                                 vc_combined_output,
                                 vc_combine,
                                 tts_text,
                                 tts_voice
                             ]
                         )
-if limitation is True:
-    app.queue(concurrency_count=1, max_size=20, api_open=config.api).launch(share=config.colab)
-else:
-    app.queue(concurrency_count=1, max_size=20, api_open=config.api).launch(share=True)
+        app.queue(concurrency_count=1, max_size=20, api_open=config.api).launch(share=config.colab)