Update app.py

app.py

@@ -12,7 +12,6 @@ import edge_tts
 import asyncio
 import librosa
 import traceback
-import soundfile as sf
 from pedalboard import Pedalboard, Reverb, Compressor, HighpassFilter
 from pedalboard.io import AudioFile
 from pydub import AudioSegment
@@ -25,17 +24,8 @@ import argparse
 import sys
 
 parser = argparse.ArgumentParser(description="Run the app with optional sharing")
-parser.add_argument(
-    '--share',
-    action='store_true',
-    help='Enable sharing mode'
-)
-parser.add_argument(
-    '--theme',
-    type=str,
-    default="aliabid94/new-theme",
-    help='Set the theme (default: aliabid94/new-theme)'
-)
+parser.add_argument('--share', action='store_true', help='Enable sharing mode')
+parser.add_argument('--theme', type=str, default="aliabid94/new-theme", help='Set the theme')
 args = parser.parse_args()
 
 IS_COLAB = True if ('google.colab' in sys.modules or args.share) else False
@@ -46,359 +36,211 @@ logging.getLogger("infer_rvc_python").setLevel(logging.ERROR)
 converter = BaseLoader(only_cpu=False, hubert_path=None, rmvpe_path=None)
 converter.hu_bert_model = load_hu_bert(Config(only_cpu=False), converter.hubert_path)
 
-test_model = "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"
-test_names = ["model.pth", "model.index"]
-
-for url, filename in zip(test_model.split(", "), test_names):
-    try:
-        download_manager(
-            url=url,
-            path=".",
-            extension="",
-            overwrite=False,
-            progress=True,
-        )
-        if not os.path.isfile(filename):
-            raise FileNotFoundError
-    except Exception:
-        with open(filename, "wb") as f:
-            pass
+# ========== डिफ़ॉल्ट मॉडल डाउनलोड को हटा दिया गया है ==========
+# पहले यहाँ test_model डाउनलोड होता था, जिससे स्पेस हैंग हो जाता था। अब नहीं होगा।
 
 title = "<center><strong><font size='7'>RVC⚡ZERO</font></strong></center>"
-description = "This demo is provided for educational and research purposes only. The authors and contributors of this project do not endorse or encourage any misuse or unethical use of this software. Any use of this software for purposes other than those intended is solely at the user's own risk. The authors and contributors shall not be held responsible for any damages or liabilities arising from the use of this demo inappropriately." if IS_ZERO_GPU else ""
-RESOURCES = "- You can also try `RVC⚡ZERO` in Colab’s free tier, which provides free GPU [link](https://github.com/R3gm/rvc_zero_ui?tab=readme-ov-file#rvczero)."
+description = "This demo is provided for educational and research purposes only." if IS_ZERO_GPU else ""
+RESOURCES = "- You can also try `RVC⚡ZERO` in Colab’s free tier [link](https://github.com/R3gm/rvc_zero_ui?tab=readme-ov-file#rvczero)."
 theme = args.theme
 delete_cache_time = (3200, 3200) if IS_ZERO_GPU else (86400, 86400)
 
-PITCH_ALGO_OPT = [
-    "pm",
-    "harvest",
-    "crepe",
-    "rmvpe",
-    "rmvpe+",
-]
-
+PITCH_ALGO_OPT = ["pm", "harvest", "crepe", "rmvpe", "rmvpe+"]
 
 async def get_voices_list(proxy=None):
-    """Print all available voices."""
     from edge_tts import list_voices
     voices = await list_voices(proxy=proxy)
-    voices = sorted(voices, key=lambda voice: voice["ShortName"])
-
-    table = [
+    voices = sorted(voices, key=lambda v: v["ShortName"])
+    return [
         {
-            "ShortName": voice["ShortName"],
-            "Gender": voice["Gender"],
-            "ContentCategories": ", ".join(voice["VoiceTag"]["ContentCategories"]),
-            "VoicePersonalities": ", ".join(voice["VoiceTag"]["VoicePersonalities"]),
-            "FriendlyName": voice["FriendlyName"],
+            "ShortName": v["ShortName"],
+            "Gender": v["Gender"],
+            "ContentCategories": ", ".join(v["VoiceTag"]["ContentCategories"]),
+            "VoicePersonalities": ", ".join(v["VoiceTag"]["VoicePersonalities"]),
+            "FriendlyName": v["FriendlyName"],
         }
-        for voice in voices
+        for v in voices
     ]
 
-    return table
-
-
 def find_files(directory):
     file_paths = []
-    for filename in os.listdir(directory):
-        if filename.endswith('.pth') or filename.endswith('.zip') or filename.endswith('.index'):
-            file_paths.append(os.path.join(directory, filename))
+    for fname in os.listdir(directory):
+        if fname.endswith(('.pth', '.zip', '.index')):
+            file_paths.append(os.path.join(directory, fname))
     return file_paths
 
-
 def unzip_in_folder(my_zip, my_dir):
-    with zipfile.ZipFile(my_zip) as zip:
-        for zip_info in zip.infolist():
-            if zip_info.is_dir():
+    with zipfile.ZipFile(my_zip) as zf:
+        for info in zf.infolist():
+            if info.is_dir():
                 continue
-            zip_info.filename = os.path.basename(zip_info.filename)
-            zip.extract(zip_info, my_dir)
-
+            info.filename = os.path.basename(info.filename)
+            zf.extract(info, my_dir)
 
 def find_my_model(a_, b_):
     if a_ is None or a_.endswith(".pth"):
         return a_, b_
-
-    txt_files = []
-    for base_file in [a_, b_]:
-        if base_file is not None and base_file.endswith(".txt"):
-            txt_files.append(base_file)
-
+    txt_files = [f for f in [a_, b_] if f and f.endswith(".txt")]
     directory = os.path.dirname(a_)
-
     for txt in txt_files:
-        with open(txt, 'r') as file:
-            first_line = file.readline()
-
-        download_manager(
-            url=first_line.strip(),
-            path=directory,
-            extension="",
-        )
-
+        with open(txt) as f:
+            url = f.readline().strip()
+        download_manager(url=url, path=directory, extension="")
     for f in find_files(directory):
         if f.endswith(".zip"):
             unzip_in_folder(f, directory)
-
-    model = None
-    index = None
-    end_files = find_files(directory)
-
-    for ff in end_files:
+    model = index = None
+    for ff in find_files(directory):
         if ff.endswith(".pth"):
-            model = os.path.join(directory, ff)
+            model = ff
             gr.Info(f"Model found: {ff}")
         if ff.endswith(".index"):
-            index = os.path.join(directory, ff)
+            index = ff
             gr.Info(f"Index found: {ff}")
-
     if not model:
-        gr.Error(f"Model not found in: {end_files}")
-
+        gr.Error("Model not found")
     if not index:
         gr.Warning("Index not found")
-
     return model, index
 
-
 def ensure_valid_file(url):
     if "huggingface" not in url:
-        raise ValueError("Only downloads from Hugging Face are allowed")
-
-    try:
-        request = urllib.request.Request(url, method="HEAD")
-        with urllib.request.urlopen(request) as response:
-            content_length = response.headers.get("Content-Length")
-
-        if content_length is None:
-            raise ValueError("No Content-Length header found")
-
-        file_size = int(content_length)
-        if file_size > 900000000 and IS_ZERO_GPU:
-            raise ValueError("The file is too large. Max allowed is 900 MB.")
-
-        return file_size
-
-    except Exception as e:
-        raise e
-
+        raise ValueError("Only Hugging Face URLs allowed")
+    req = urllib.request.Request(url, method="HEAD")
+    with urllib.request.urlopen(req) as resp:
+        size = int(resp.headers.get("Content-Length", 0))
+        if size > 900_000_000 and IS_ZERO_GPU:
+            raise ValueError("File too large for Zero GPU")
+        return size
 
 def clear_files(directory):
     time.sleep(15)
-    print(f"Clearing files: {directory}.")
-    shutil.rmtree(directory)
-
+    shutil.rmtree(directory, ignore_errors=True)
 
 def get_my_model(url_data, progress=gr.Progress(track_tqdm=True)):
     if not url_data:
         return None, None
-
     if "," in url_data:
         a_, b_ = url_data.split(",")
         a_, b_ = a_.strip().replace("/blob/", "/resolve/"), b_.strip().replace("/blob/", "/resolve/")
     else:
         a_, b_ = url_data.strip().replace("/blob/", "/resolve/"), None
-
     out_dir = "downloads"
-    folder_download = str(random.randint(1000, 9999))
-    directory = os.path.join(out_dir, folder_download)
+    folder = str(random.randint(1000, 9999))
+    directory = os.path.join(out_dir, folder)
     os.makedirs(directory, exist_ok=True)
-
     try:
-        valid_url = [a_] if not b_ else [a_, b_]
-        for link in valid_url:
+        for link in [a_] if not b_ else [a_, b_]:
             ensure_valid_file(link)
-            download_manager(
-                url=link,
-                path=directory,
-                extension="",
-            )
-
+            download_manager(url=link, path=directory, extension="")
         for f in find_files(directory):
             if f.endswith(".zip"):
                 unzip_in_folder(f, directory)
-
-        model = None
-        index = None
-        end_files = find_files(directory)
-
-        for ff in end_files:
+        model = index = None
+        for ff in find_files(directory):
             if ff.endswith(".pth"):
                 model = ff
-                gr.Info(f"Model found: {ff}")
             if ff.endswith(".index"):
                 index = ff
-                gr.Info(f"Index found: {ff}")
-
         if not model:
-            raise ValueError(f"Model not found in: {end_files}")
-
+            raise ValueError("Model .pth not found")
         if not index:
             gr.Warning("Index not found")
-        else:
-            index = os.path.abspath(index)
-
-        return os.path.abspath(model), index
-
-    except Exception as e:
-        raise e
+        return os.path.abspath(model), os.path.abspath(index) if index else None
     finally:
-        t = threading.Thread(target=clear_files, args=(directory,))
-        t.start()
+        threading.Thread(target=clear_files, args=(directory,)).start()
 
-
-# ========== नया फ़ंक्शन: logs/ फोल्डर से सभी मॉडल स्कैन करें ==========
+# ========== logs/ फोल्डर से मॉडल स्कैन ==========
 def scan_models():
-    """logs/ फोल्डर के अंदर हर सबफोल्डर को एक मॉडल मानें और उसकी .pth व .index फाइलें ढूंढें।"""
     logs_dir = "logs"
     if not os.path.isdir(logs_dir):
         return []
-
     models = []
     for model_name in os.listdir(logs_dir):
         model_path = os.path.join(logs_dir, model_name)
         if not os.path.isdir(model_path):
             continue
-
-        # फोल्डर के अंदर .pth और .index फाइलें देखें
         pth_files = [f for f in os.listdir(model_path) if f.endswith(".pth")]
-        index_files = [f for f in os.listdir(model_path) if f.endswith(".index")]
-
-        if pth_files and index_files:
-            # पहली मिलने वाली फाइल ले लें (या आप नाम से मिलान कर सकते हैं)
+        idx_files = [f for f in os.listdir(model_path) if f.endswith(".index")]
+        if pth_files and idx_files:
             pth_path = os.path.join(model_path, pth_files[0])
-            index_path = os.path.join(model_path, index_files[0])
-            models.append((model_name, pth_path, index_path))
+            idx_path = os.path.join(model_path, idx_files[0])
+            models.append((model_name, pth_path, idx_path))
     return models
 
-
 def update_model_paths(model_name):
-    """चुने गए मॉडल के अनुसार pth और index के पूरे पथ लौटाएँ।"""
-    models = scan_models()
-    for name, pth, idx in models:
+    for name, pth, idx in scan_models():
         if name == model_name:
             return pth, idx
     return None, None
 
-
-# ========== ऑडियो इफेक्ट और कन्वर्जन फंक्शन (कोई बदलाव नहीं) ==========
-
+# ========== ऑडियो इफेक्ट ==========
 def add_audio_effects(audio_list, type_output):
-    print("Audio effects")
-
     result = []
     for audio_path in audio_list:
         try:
-            output_path = f'{os.path.splitext(audio_path)[0]}_effects.{type_output}'
-
-            board = Pedalboard(
-                [
-                    HighpassFilter(),
-                    Compressor(ratio=4, threshold_db=-15),
-                    Reverb(room_size=0.10, dry_level=0.8, wet_level=0.2, damping=0.7)
-                 ]
-            )
-
+            out_path = f'{os.path.splitext(audio_path)[0]}_effects.{type_output}'
+            board = Pedalboard([
+                HighpassFilter(),
+                Compressor(ratio=4, threshold_db=-15),
+                Reverb(room_size=0.1, dry_level=0.8, wet_level=0.2, damping=0.7)
+            ])
             temp_wav = f'{os.path.splitext(audio_path)[0]}_temp.wav'
-
             with AudioFile(audio_path) as f:
                 with AudioFile(temp_wav, 'w', f.samplerate, f.num_channels) as o:
                     while f.tell() < f.frames:
                         chunk = f.read(int(f.samplerate))
-                        effected = board(chunk, f.samplerate, reset=False)
-                        o.write(effected)
-
-            audio_seg = AudioSegment.from_file(temp_wav, format=type_output)
-            audio_seg.export(output_path, format=type_output, bitrate=("320k" if type_output == "mp3" else None))
-
+                        o.write(board(chunk, f.samplerate, reset=False))
+            AudioSegment.from_file(temp_wav).export(out_path, format=type_output)
             os.remove(temp_wav)
-
-            result.append(output_path)
-        except Exception as e:
-            traceback.print_exc()
-            print(f"Error audio effects: {str(e)}")
+            result.append(out_path)
+        except Exception:
             result.append(audio_path)
-
     return result
 
-
 def apply_noisereduce(audio_list, type_output):
-    print("Noise reduce")
-
     result = []
     for audio_path in audio_list:
         out_path = f"{os.path.splitext(audio_path)[0]}_noisereduce.{type_output}"
-
         try:
             audio = AudioSegment.from_file(audio_path)
             samples = np.array(audio.get_array_of_samples())
-            reduced_noise = nr.reduce_noise(samples, sr=audio.frame_rate, prop_decrease=0.6)
-
+            reduced = nr.reduce_noise(samples, sr=audio.frame_rate, prop_decrease=0.6)
             reduced_audio = AudioSegment(
-                reduced_noise.tobytes(),
+                reduced.tobytes(),
                 frame_rate=audio.frame_rate,
                 sample_width=audio.sample_width,
                 channels=audio.channels
             )
-
-            reduced_audio.export(out_path, format=type_output, bitrate=("320k" if type_output == "mp3" else None))
+            reduced_audio.export(out_path, format=type_output)
             result.append(out_path)
-
-        except Exception as e:
-            traceback.print_exc()
-            print(f"Error noisereduce: {str(e)}")
+        except Exception:
             result.append(audio_path)
-
     return result
 
-
 @spaces.GPU()
 def convert_now(audio_files, random_tag, converter, type_output, steps):
-    for step in range(steps):
+    for _ in range(steps):
         audio_files = converter(
-            audio_files,
-            random_tag,
+            audio_files, random_tag,
             overwrite=False,
             parallel_workers=(2 if IS_COLAB else 8),
-            type_output=type_output,
+            type_output=type_output
         )
     return audio_files
 
-
 def run(
-    audio_files,
-    file_m,
-    pitch_alg,
-    pitch_lvl,
-    file_index,
-    index_inf,
-    r_m_f,
-    e_r,
-    c_b_p,
-    active_noise_reduce,
-    audio_effects,
-    type_output,
-    steps,
+    audio_files, file_m, pitch_alg, pitch_lvl, file_index,
+    index_inf, r_m_f, e_r, c_b_p, active_noise_reduce,
+    audio_effects, type_output, steps
 ):
     if not audio_files:
         raise ValueError("Please provide audio files")
-
     if isinstance(audio_files, str):
         audio_files = [audio_files]
-
-    try:
-        duration_base = librosa.get_duration(filename=audio_files[0])
-        print("Duration:", duration_base)
-    except Exception as e:
-        print(e)
-
-    if file_m is not None and file_m.endswith(".txt"):
+    if file_m and file_m.endswith(".txt"):
         file_m, file_index = find_my_model(file_m, file_index)
-        print(file_m, file_index)
-
     random_tag = "USER_" + str(random.randint(10000000, 99999999))
-
     converter.apply_conf(
         tag=random_tag,
         file_model=file_m,
@@ -412,341 +254,198 @@ def run(
         resample_sr=0,
     )
     time.sleep(0.1)
-
     result = convert_now(audio_files, random_tag, converter, type_output, steps)
-
     if active_noise_reduce:
         result = apply_noisereduce(result, type_output)
-
     if audio_effects:
         result = add_audio_effects(result, type_output)
-
     return result
 
-
-# ========== UI कॉन्फ़िगरेशन ==========
-
+# ========== UI कम्पोनेंट ==========
 def audio_conf():
-    return gr.File(
-        label="Audio files",
-        file_count="multiple",
-        type="filepath",
-        container=True,
-    )
-
+    return gr.File(label="Audio files", file_count="multiple", type="filepath")
 
 def model_dropdown_conf():
     models = scan_models()
     choices = [name for name, _, _ in models]
-    return gr.Dropdown(
-        label="Select Model",
-        choices=choices,
-        value=choices[0] if choices else None,
-        interactive=True,
-    )
-
+    return gr.Dropdown(label="Select Model", choices=choices, value=choices[0] if choices else None, interactive=True)
 
 def hidden_model_path_conf():
     return gr.Textbox(visible=False)
 
-
 def hidden_index_path_conf():
     return gr.Textbox(visible=False)
 
-
 def pitch_algo_conf():
-    return gr.Dropdown(
-        PITCH_ALGO_OPT,
-        value=PITCH_ALGO_OPT[4],
-        label="Pitch algorithm",
-        visible=True,
-        interactive=True,
-    )
-
+    return gr.Dropdown(PITCH_ALGO_OPT, value="rmvpe+", label="Pitch algorithm")
 
 def pitch_lvl_conf():
-    return gr.Slider(
-        label="Pitch level",
-        minimum=-24,
-        maximum=24,
-        step=1,
-        value=0,
-        visible=True,
-        interactive=True,
-    )
-
+    return gr.Slider(-24, 24, value=0, step=1, label="Pitch level")
 
 def index_inf_conf():
-    return gr.Slider(
-        minimum=0,
-        maximum=1,
-        label="Index influence",
-        value=0.75,
-    )
-
+    return gr.Slider(0, 1, value=0.75, label="Index influence")
 
 def respiration_filter_conf():
-    return gr.Slider(
-        minimum=0,
-        maximum=7,
-        label="Respiration median filtering",
-        value=3,
-        step=1,
-        interactive=True,
-    )
-
+    return gr.Slider(0, 7, value=3, step=1, label="Respiration median filtering")
 
 def envelope_ratio_conf():
-    return gr.Slider(
-        minimum=0,
-        maximum=1,
-        label="Envelope ratio",
-        value=0.25,
-        interactive=True,
-    )
-
+    return gr.Slider(0, 1, value=0.25, label="Envelope ratio")
 
 def consonant_protec_conf():
-    return gr.Slider(
-        minimum=0,
-        maximum=0.5,
-        label="Consonant breath protection",
-        value=0.5,
-        interactive=True,
-    )
-
+    return gr.Slider(0, 0.5, value=0.5, label="Consonant breath protection")
 
 def button_conf():
-    return gr.Button(
-        "Inference",
-        variant="primary",
-    )
-
+    return gr.Button("Inference", variant="primary")
 
 def output_conf():
-    return gr.File(
-        label="Result",
-        file_count="multiple",
-        interactive=False,
-    )
-
+    return gr.File(label="Result", file_count="multiple", interactive=False)
 
 def active_tts_conf():
-    return gr.Checkbox(
-        False,
-        label="TTS",
-        container=False,
-    )
-
-
-def tts_voice_conf():
-    return gr.Dropdown(
-        label="tts voice",
-        choices=[],
-        visible=False,
-        value=None,
-    )
+    return gr.Checkbox(False, label="TTS", container=False)
 
+def tts_voice_conf(voices):
+    return gr.Dropdown(label="tts voice", choices=voices, visible=False)
 
 def tts_text_conf():
-    return gr.Textbox(
-        value="",
-        placeholder="Write the text here...",
-        label="Text",
-        visible=False,
-        lines=3,
-    )
-
+    return gr.Textbox(placeholder="Write the text here...", label="Text", visible=False, lines=3)
 
 def tts_button_conf():
-    return gr.Button(
-        "Process TTS",
-        variant="secondary",
-        visible=False,
-    )
-
+    return gr.Button("Process TTS", variant="secondary", visible=False)
 
 def tts_play_conf():
-    return gr.Checkbox(
-        False,
-        label="Play",
-        container=False,
-        visible=False,
-    )
-
+    return gr.Checkbox(False, label="Play", container=False, visible=False)
 
 def sound_gui():
-    return gr.Audio(
-        value=None,
-        type="filepath",
-        autoplay=True,
-        visible=True,
-        interactive=False,
-        elem_id="audio_tts",
-    )
-
+    return gr.Audio(type="filepath", autoplay=True, visible=True, interactive=False, elem_id="audio_tts")
 
 def steps_conf():
-    return gr.Slider(
-        minimum=1,
-        maximum=3,
-        label="Steps",
-        value=1,
-        step=1,
-        interactive=True,
-    )
-
+    return gr.Slider(1, 3, value=1, step=1, label="Steps")
 
 def format_output_gui():
-    return gr.Dropdown(
-        label="Format output:",
-        choices=["wav", "mp3", "flac"],
-        value="wav",
-    )
-
+    return gr.Dropdown(choices=["wav", "mp3", "flac"], value="wav", label="Format output")
 
 def denoise_conf():
-    return gr.Checkbox(
-        False,
-        label="Denoise",
-        container=False,
-        visible=True,
-    )
-
+    return gr.Checkbox(False, label="Denoise", container=False)
 
 def effects_conf():
-    return gr.Checkbox(
-        False,
-        label="Reverb",
-        container=False,
-        visible=True,
-    )
-
+    return gr.Checkbox(False, label="Reverb", container=False)
 
 def infer_tts_audio(tts_voice, tts_text, play_tts):
     out_dir = "output"
     folder_tts = "USER_" + str(random.randint(10000, 99999))
-
-    os.makedirs(out_dir, exist_ok=True)
     os.makedirs(os.path.join(out_dir, folder_tts), exist_ok=True)
     out_path = os.path.join(out_dir, folder_tts, "tts.mp3")
-
     asyncio.run(edge_tts.Communicate(tts_text, "-".join(tts_voice.split('-')[:-1])).save(out_path))
     if play_tts:
         return [out_path], out_path
     return [out_path], None
 
-
-def show_components_tts(value_active):
-    return (
-        gr.update(visible=value_active),
-        gr.update(visible=value_active),
-        gr.update(visible=value_active),
-        gr.update(visible=value_active),
-    )
-
+def show_components_tts(val):
+    return (gr.update(visible=val),) * 4
 
 def down_active_conf():
-    return gr.Checkbox(
-        False,
-        label="URL-to-Model",
-        container=False,
-    )
-
+    return gr.Checkbox(False, label="URL-to-Model", container=False)
 
 def down_url_conf():
-    return gr.Textbox(
-        value="",
-        placeholder="Write the url here...",
-        label="Enter URL",
-        visible=False,
-        lines=1,
-    )
-
+    return gr.Textbox(placeholder="Write the url here...", label="Enter URL", visible=False)
 
 def down_button_conf():
-    return gr.Button(
-        "Process",
-        variant="secondary",
-        visible=False,
-    )
-
-
-def show_components_down(value_active):
-    return (
-        gr.update(visible=value_active),
-        gr.update(visible=value_active),
-        gr.update(visible=value_active),
-    )
+    return gr.Button("Process", variant="secondary", visible=False)
 
+def show_components_down(val):
+    return (gr.update(visible=val),) * 3
 
 CSS = """
 #audio_tts {
-  visibility: hidden;
-  height: 0px;
-  width: 0px;
-  max-width: 0px;
-  max-height: 0px;
+  visibility: hidden; height: 0px; width: 0px; max-width: 0px; max-height: 0px;
 }
 """
 
-
-def get_gui(theme):
-    with gr.Blocks(theme=theme, css=CSS, fill_width=True, fill_height=False, delete_cache=delete_cache_time) as app:
+def get_gui(theme, voices):
+    with gr.Blocks(theme=theme, css=CSS, delete_cache=delete_cache_time) as app:
         gr.Markdown(title)
         gr.Markdown(description)
 
-        # ===== TTS सेक्शन =====
         active_tts = active_tts_conf()
         with gr.Row():
             with gr.Column(scale=1):
                 tts_text = tts_text_conf()
             with gr.Column(scale=2):
                 with gr.Row():
-                    with gr.Column():
-                        with gr.Row():
-                            tts_voice = tts_voice_conf()
-                            tts_active_play = tts_play_conf()
-
+                    tts_voice = tts_voice_conf(voices)
+                    tts_active_play = tts_play_conf()
                 tts_button = tts_button_conf()
                 tts_play = sound_gui()
 
-        active_tts.change(
-            fn=show_components_tts,
-            inputs=[active_tts],
-            outputs=[tts_voice, tts_text, tts_button, tts_active_play],
-        )
-
+        active_tts.change(show_components_tts, [active_tts], [tts_voice, tts_text, tts_button, tts_active_play])
         aud = audio_conf()
+        tts_button.click(infer_tts_audio, [tts_voice, tts_text, tts_active_play], [aud, tts_play])
 
-        tts_button.click(
-            fn=infer_tts_audio,
-            inputs=[tts_voice, tts_text, tts_active_play],
-            outputs=[aud, tts_play],
-        )
-
-        # ===== URL-to-Model सेक्शन =====
-        down_active_gui = down_active_conf()
+        down_active = down_active_conf()
         down_info = gr.Markdown(
-            f"Provide a link to a zip file, like this one: `https://huggingface.co/MrDawg/ToothBrushing/resolve/main/ToothBrushing.zip?download=true`, or separate links with a comma for the .pth and .index files, like this: `{test_model}`",
+            "Provide a link to a zip file, or separate links with comma for .pth and .index files.",
             visible=False
         )
         with gr.Row():
-            with gr.Column(scale=3):
-                down_url_gui = down_url_conf()
-            with gr.Column(scale=1):
-                down_button_gui = down_button_conf()
+            down_url = down_url_conf()
+            down_button = down_button_conf()
 
-        # ये हैं असली मॉडल पथ वाले छुपे हुए टेक्स्टबॉक्स
-        hidden_model_path = hidden_model_path_conf()
-        hidden_index_path = hidden_index_path_conf()
+        hidden_model = hidden_model_path_conf()
+        hidden_index = hidden_index_path_conf()
 
-        down_active_gui.change(
-            show_components_down,
-            [down_active_gui],
-            [down_info, down_url_gui, down_button_gui]
-        )
+        down_active.change(show_components_down, [down_active], [down_info, down_url, down_button])
 
-        # जब URL से मॉडल डाउनलोड हो, तो उसके पथ छुपे हुए टेक्स्टबॉक्स में डालें
         def update_from_url(url_data):
-            model_path, index_path = get_my_model
+            model_p, index_p = get_my_model(url_data)
+            return model_p, index_p
+
+        down_button.click(update_from_url, [down_url], [hidden_model, hidden_index])
+
+        model_dropdown = model_dropdown_conf()
+
+        def on_model_select(name):
+            return update_model_paths(name)
+
+        model_dropdown.change(on_model_select, [model_dropdown], [hidden_model, hidden_index])
+
+        with gr.Accordion("Advanced settings", open=False):
+            algo = pitch_algo_conf()
+            algo_lvl = pitch_lvl_conf()
+            idx_inf = index_inf_conf()
+            res_fc = respiration_filter_conf()
+            env_r = envelope_ratio_conf()
+            cons = consonant_protec_conf()
+            steps_gui = steps_conf()
+            fmt_out = format_output_gui()
+            with gr.Row():
+                denoise_gui = denoise_conf()
+                effects_gui = effects_conf()
+
+        btn = button_conf()
+        out = output_conf()
+
+        btn.click(
+            run,
+            inputs=[
+                aud, hidden_model, algo, algo_lvl, hidden_index,
+                idx_inf, res_fc, env_r, cons,
+                denoise_gui, effects_gui, fmt_out, steps_gui
+            ],
+            outputs=out
+        )
+
+        gr.Markdown(RESOURCES)
+
+    return app
+
+if __name__ == "__main__":
+    tts_voice_list = asyncio.new_event_loop().run_until_complete(get_voices_list(proxy=None))
+    voices = sorted([
+        (" - ".join(reversed(v["FriendlyName"].split("-"))).replace("Microsoft ", "").replace("Online (Natural)", f"({v['Gender']})").strip(),
+         f"{v['ShortName']}-{v['Gender']}")
+        for v in tts_voice_list
+    ])
+
+    app = get_gui(theme, voices)
+    app.queue(default_concurrency_limit=40)
+    app.launch(max_threads=40, share=IS_COLAB, show_error=True, quiet=False, debug=IS_COLAB, ssr_mode=False)