Create app.py

app.py

@@ -0,0 +1,303 @@
+# Initalize a pipeline
+from kokoro import KPipeline
+# from IPython.display import display, Audio
+# import soundfile as sf
+import os
+from huggingface_hub import list_repo_files
+import uuid
+import re 
+import gradio as gr
+
+
+# Language mapping dictionary
+language_map = {
+    "American English": "a",
+    "British English": "b",
+    "Hindi": "h",
+    "Spanish": "e",
+    "French": "f",
+    "Italian": "i",
+    "Brazilian Portuguese": "p",
+    "Japanese": "j",
+    "Mandarin Chinese": "z"
+}
+
+# Print installation instructions if necessary
+install_messages = {
+    "Japanese": "pip install misaki[ja]",
+    "Mandarin Chinese": "pip install misaki[zh]"
+}
+
+
+
+def update_pipeline(Language):
+    """ Updates the pipeline only if the language has changed. """
+    global pipeline, last_used_language
+
+    # Print installation instructions if necessary
+    if Language in install_messages:
+        # raise gr.Error(f"To Use {Language} Install: {install_messages[Language]}",duration=10)
+        gr.Warning(f"To Use {Language} Install: {install_messages[Language]}",duration=10)
+        # gr.Warning("Reverting to default English pipeline...", duration=5)
+        # print(f"To use {Language}, install: {install_messages[Language]}")
+        # print("Reverting to default English pipeline...")
+        
+
+        # Revert to default English and return immediately
+        pipeline = KPipeline(lang_code="a")
+        last_used_language = "a"
+        return  
+
+    # Get language code, default to 'a' if not found
+    new_lang = language_map.get(Language, "a")
+
+    # Only update if the language is different
+    if new_lang != last_used_language:
+        try:
+            pipeline = KPipeline(lang_code=new_lang)
+            last_used_language = new_lang  # Update last used language
+            print(f"Pipeline updated to {Language} ({new_lang})")
+        except Exception as e:
+            print(f"Error initializing KPipeline: {e}\nRetrying with default language...")
+            pipeline = KPipeline(lang_code="a")  # Fallback to English
+            last_used_language = "a"
+
+
+
+def get_voice_names(repo_id):
+    """Fetches and returns a list of voice names (without extensions) from the given Hugging Face repository."""
+    return [os.path.splitext(file.replace("voices/", ""))[0] for file in list_repo_files(repo_id) if file.startswith("voices/")]
+
+def create_audio_dir():
+    """Creates the 'kokoro_audio' directory in the root folder if it doesn't exist."""
+    root_dir = os.getcwd()  # Use current working directory instead of __file__
+    audio_dir = os.path.join(root_dir, "kokoro_audio")
+
+    if not os.path.exists(audio_dir):
+        os.makedirs(audio_dir)
+        print(f"Created directory: {audio_dir}")
+    else:
+        print(f"Directory already exists: {audio_dir}")
+    return audio_dir
+
+import re
+
+def clean_text(text):
+    # Define replacement rules
+    replacements = {
+        "–": " ",  # Replace en-dash with space
+        "-": " ",  # Replace hyphen with space
+        "**": " ", # Replace double asterisks with space
+        "*": " ",  # Replace single asterisk with space
+        "#": " ",  # Replace hash with space
+    }
+
+    # Apply replacements
+    for old, new in replacements.items():
+        text = text.replace(old, new)
+
+    # Remove emojis using regex (covering wide range of Unicode characters)
+    emoji_pattern = re.compile(
+        r'[\U0001F600-\U0001F64F]|'  # Emoticons
+        r'[\U0001F300-\U0001F5FF]|'  # Miscellaneous symbols and pictographs
+        r'[\U0001F680-\U0001F6FF]|'  # Transport and map symbols
+        r'[\U0001F700-\U0001F77F]|'  # Alchemical symbols
+        r'[\U0001F780-\U0001F7FF]|'  # Geometric shapes extended
+        r'[\U0001F800-\U0001F8FF]|'  # Supplemental arrows-C
+        r'[\U0001F900-\U0001F9FF]|'  # Supplemental symbols and pictographs
+        r'[\U0001FA00-\U0001FA6F]|'  # Chess symbols
+        r'[\U0001FA70-\U0001FAFF]|'  # Symbols and pictographs extended-A
+        r'[\U00002702-\U000027B0]|'  # Dingbats
+        r'[\U0001F1E0-\U0001F1FF]'   # Flags (iOS)
+        r'', flags=re.UNICODE)
+  
+    text = emoji_pattern.sub(r'', text)
+
+    # Remove multiple spaces and extra line breaks
+    text = re.sub(r'\s+', ' ', text).strip()
+
+    return text
+
+def tts_file_name(text):
+    global temp_folder
+    # Remove all non-alphabetic characters and convert to lowercase
+    text = re.sub(r'[^a-zA-Z\s]', '', text)  # Retain only alphabets and spaces
+    text = text.lower().strip()             # Convert to lowercase and strip leading/trailing spaces
+    text = text.replace(" ", "_")           # Replace spaces with underscores
+    
+    # Truncate or handle empty text
+    truncated_text = text[:20] if len(text) > 20 else text if len(text) > 0 else "empty"
+    
+    # Generate a random string for uniqueness
+    random_string = uuid.uuid4().hex[:8].upper()
+    
+    # Construct the file name
+    file_name = f"{temp_folder}/{truncated_text}_{random_string}.wav"
+    return file_name
+
+
+# import soundfile as sf
+import numpy as np
+import wave
+from pydub import AudioSegment
+from pydub.silence import split_on_silence
+
+def remove_silence_function(file_path,minimum_silence=50):
+    # Extract file name and format from the provided path
+    output_path = file_path.replace(".wav", "_no_silence.wav")
+    audio_format = "wav"
+    # Reading and splitting the audio file into chunks
+    sound = AudioSegment.from_file(file_path, format=audio_format)
+    audio_chunks = split_on_silence(sound,
+                                    min_silence_len=100,
+                                    silence_thresh=-45,
+                                    keep_silence=minimum_silence) 
+    # Putting the file back together
+    combined = AudioSegment.empty()
+    for chunk in audio_chunks:
+        combined += chunk
+    combined.export(output_path, format=audio_format)
+    return output_path
+
+def generate_and_save_audio(text, Language="American English",voice="af_bella", speed=1,remove_silence=False,keep_silence_up_to=0.05):
+    text=clean_text(text)
+    update_pipeline(Language)
+    generator = pipeline(text, voice=voice, speed=speed, split_pattern=r'\n+')
+    save_path=tts_file_name(text)
+    # Open the WAV file for writing
+    with wave.open(save_path, 'wb') as wav_file:
+        # Set the WAV file parameters
+        wav_file.setnchannels(1)  # Mono audio
+        wav_file.setsampwidth(2)  # 2 bytes per sample (16-bit audio)
+        wav_file.setframerate(24000)  # Sample rate
+
+        # Process each audio chunk
+        for i, (gs, ps, audio) in enumerate(generator):
+            # print(f"{i}. {gs}")
+            # print(f"Phonetic Transcription: {ps}")
+            # display(Audio(data=audio, rate=24000, autoplay=i==0))
+            print("\n")
+            # Convert the Tensor to a NumPy array
+            audio_np = audio.numpy()  # Convert Tensor to NumPy array
+            audio_int16 = (audio_np * 32767).astype(np.int16)  # Scale to 16-bit range
+            audio_bytes = audio_int16.tobytes()  # Convert to bytes
+
+            # Write the audio chunk to the WAV file
+            wav_file.writeframes(audio_bytes)
+    if remove_silence:            
+      keep_silence = int(keep_silence_up_to * 1000)
+      new_wave_file=remove_silence_function(save_path,minimum_silence=keep_silence)
+      return new_wave_file,new_wave_file
+    return save_path,save_path
+
+
+
+
+
+def ui():
+    def toggle_autoplay(autoplay):
+        return gr.Audio(interactive=False, label='Output Audio', autoplay=autoplay)
+
+    # Define examples in the format you mentioned
+    dummy_examples = [
+        ["Hey, y'all, let’s grab some coffee and catch up!", "American English", "af_bella"],
+        ["I'd like a large coffee, please.", "British English", "bf_isabella"],
+        ["नमस्ते, कैसे हो?", "Hindi", "hf_alpha"],
+        ["Hola, ¿cómo estás?", "Spanish", "ef_dora"],
+        ["Bonjour, comment ça va?", "French", "ff_siwis"],
+        ["Ciao, come stai?", "Italian", "if_sara"],
+        ["Olá, como você está?", "Brazilian Portuguese", "pf_dora"],
+        ["こんにちは、お元気ですか？", "Japanese", "jf_nezumi"],
+        ["你好，你怎么样?", "Mandarin Chinese", "zf_xiaoni"]
+    ]
+    
+    with gr.Blocks() as demo:
+        # gr.Markdown("<center><h1 style='font-size: 40px;'>KOKORO TTS</h1></center>")  # Larger title with CSS
+        lang_list = ['American English', 'British English', 'Hindi', 'Spanish', 'French', 'Italian', 'Brazilian Portuguese', 'Japanese', 'Mandarin Chinese']
+        voice_names = get_voice_names("hexgrad/Kokoro-82M")
+
+        with gr.Row():
+            with gr.Column():
+                text = gr.Textbox(label='Enter Text', lines=3)
+                
+                with gr.Row():
+                    language_name = gr.Dropdown(lang_list, label="Select Language", value=lang_list[0])
+
+                with gr.Row():
+                    voice_name = gr.Dropdown(voice_names, label="Choose VoicePack", value=voice_names[0])
+
+                with gr.Row():
+                    generate_btn = gr.Button('Generate', variant='primary')
+
+                with gr.Accordion('Audio Settings', open=False):
+                    speed = gr.Slider(minimum=0.25, maximum=2, value=1, step=0.1, label='⚡️Speed', info='Adjust the speaking speed')
+                    remove_silence = gr.Checkbox(value=False, label='✂️ Remove Silence From TTS')
+
+            with gr.Column():
+                audio = gr.Audio(interactive=False, label='Output Audio', autoplay=True)
+                audio_file = gr.File(label='Download Audio')
+
+                with gr.Accordion('Enable Autoplay', open=False):
+                    autoplay = gr.Checkbox(value=True, label='Autoplay')
+                    autoplay.change(toggle_autoplay, inputs=[autoplay], outputs=[audio])
+
+        text.submit(generate_and_save_audio, inputs=[text, language_name, voice_name, speed, remove_silence], outputs=[audio, audio_file])
+        generate_btn.click(generate_and_save_audio, inputs=[text, language_name, voice_name, speed, remove_silence], outputs=[audio, audio_file])
+
+        # Add examples to the interface
+        gr.Examples(examples=dummy_examples, inputs=[text, language_name, voice_name])
+
+    return demo
+
+def tutorial():
+    # Markdown explanation for language code
+    explanation = """
+    ## Language Code Explanation:
+    Example: `'af_bella'` 
+    - **'a'** stands for **American English**.
+    - **'f_'** stands for **Female** (If it were 'm_', it would mean Male).
+    - **'bella'** refers to the specific voice.
+
+    The first character in the voice code stands for the language:
+    - **"a"**: American English
+    - **"b"**: British English
+    - **"h"**: Hindi
+    - **"e"**: Spanish
+    - **"f"**: French
+    - **"i"**: Italian
+    - **"p"**: Brazilian Portuguese
+    - **"j"**: Japanese
+    - **"z"**: Mandarin Chinese
+
+    The second character stands for gender:
+    - **"f_"**: Female
+    - **"m_"**: Male
+    """
+    with gr.Blocks() as demo2:
+        gr.Markdown(explanation)  # Display the explanation
+    return demo2
+
+
+
+import click
+@click.command()
+@click.option("--debug", is_flag=True, default=False, help="Enable debug mode.")
+@click.option("--share", is_flag=True, default=False, help="Enable sharing of the interface.")
+def main(debug, share):
+    demo1 = ui()
+    demo2 = tutorial()
+    demo = gr.TabbedInterface([demo1, demo2],["Multilingual TTS","VoicePack Explanation"],title="Kokoro TTS",theme='JohnSmith9982/small_and_pretty')
+    demo.queue().launch(debug=debug, share=share)
+    #Run on local network
+    # laptop_ip="192.168.0.30"
+    # port=8080
+    # demo.queue().launch(debug=debug, share=share,server_name=laptop_ip,server_port=port)
+
+
+
+# Initialize default pipeline
+last_used_language = "a"
+pipeline = KPipeline(lang_code=last_used_language)
+temp_folder = create_audio_dir()
+if __name__ == "__main__":
+    main()