app.py

import gradio as gr
import base64
import tempfile
import json
import os
from os.path import abspath
import zipfile
import random
import xtts
import re

DO_CHECK = os.getenv('DO_CHECK', '1') 
OUTPUT = "./demo_outputs"
cloned_speakers = {}

print("Preparing file structure...")
if not os.path.exists(OUTPUT):
    os.mkdir(OUTPUT)
    os.mkdir(os.path.join(OUTPUT, "cloned_speakers"))
    os.mkdir(os.path.join(OUTPUT, "generated_audios"))
elif os.path.exists(os.path.join(OUTPUT, "cloned_speakers")):
    print("Loading existing cloned speakers...")
    for file in os.listdir(os.path.join(OUTPUT, "cloned_speakers")):
        if file.endswith(".json"):
            with open(os.path.join(OUTPUT, "cloned_speakers", file), "r") as fp:
                cloned_speakers[file[:-5]] = json.load(fp)
    print("Available cloned speakers:", ", ".join(cloned_speakers.keys()))

AUDIOS_DIR = os.path.join("demo_outputs", "generated_audios");
ZIP_DIR = os.path.join("zip_outputs");

print("Checking zip at", ZIP_DIR)
if not os.path.exists(ZIP_DIR):
    os.mkdir(ZIP_DIR)


try:
    print("Getting metadata from server ...")
    LANUGAGES = xtts.get_languages()
    print("Available languages:", ", ".join(LANUGAGES))
    STUDIO_SPEAKERS = xtts.get_speakers()
    print("Available studio speakers:", ", ".join(STUDIO_SPEAKERS.keys()))
except:
    raise Exception("Please make sure the server is running first.")


def ExtractVars(input_string):
    # Split the string into lines
    lines = input_string.split('\n')
    
    # Initialize an empty dictionary to store key-value pairs
    result_dict = {
         'prefix': None,
         'name': '',
         'speaker': None,
         'num': None,
    }
    
    # List to hold lines that do not start with '!'
    filtered_lines = []
    
    # Iterate through each line
    for line in lines:
        # Check if the line starts with '!'
        if line.strip().startswith('!'):
            
            # Try to split the line into key and value parts
            try:
                # Split on '=' and strip whitespace from key and value
                key, value = line.strip()[1:].split('=')
                key = key.strip()
                value = value.strip()
                # Add to dictionary
                result_dict[key] = value
            except ValueError:
                # Handle the case where there is no '=' or improper format
                continue
        elif len(line.strip()) > 0:
            # Add the line to filtered_lines if it doesn't start with '!'
            filtered_lines.append(line)
    
    # Join the filtered lines back into a single string
    filtered_string = '\n'.join(filtered_lines)
    return result_dict, filtered_string


def ParsePronucs(PronuncStr):
    # Split the string into lines
    lines = PronuncStr.split('\n')
    
    # Initialize an empty dictionary to store key-value pairs
    PronuncWords =  []
    
    # Iterate through each line
    for line in lines:
        if len(line.strip()) > 0:    
            word,*text = line.strip().split('=',1)
            word = word.strip()
            text,*opts = text[0].split("|",1);
            text = text.strip();
            
            if len(opts) > 0:
                opts = opts[0].strip().split(",");
            else:
                opts = [];

                
            PronuncWords.append({'word':word, 'text':text, 'opts':opts})
            
    return PronuncWords


def FindSpeakerByName(name, speakerType):

    srcItems = STUDIO_SPEAKERS if speakerType == "Studio" else cloned_speakers;
    
    for key, value in srcItems.items():
        
        if key == name:
            return key,value 
            
        if key.split(" ")[0] == name:
            return key,value;
            
            
def clone_speaker(upload_file, clone_speaker_name, cloned_speaker_names):
    embeddings =  xtts.predict_speaker(open(upload_file,"rb"))
    with open(os.path.join(OUTPUT, "cloned_speakers", clone_speaker_name + ".json"), "w") as fp:
        json.dump(embeddings, fp)
    cloned_speakers[clone_speaker_name] = embeddings
    cloned_speaker_names.append(clone_speaker_name)
    return upload_file, clone_speaker_name, cloned_speaker_names, gr.Dropdown(choices=cloned_speaker_names)

def tts(text, pronunc, speaker_type, speaker_name_studio, speaker_name_custom, lang, temperature

    ,speed,top_p,top_k, AllFileList,progress=gr.Progress()

):
    embeddings = STUDIO_SPEAKERS[speaker_name_studio] if speaker_type == 'Studio' else cloned_speakers[speaker_name_custom]
    
    
    # break at line!
    lines = text.split("---");
    totalLines = len(lines);
    print("Total parts:", len(lines))
    
    audioNum = 0;
    
    DefaultPrefix = next(tempfile._get_candidate_names());
    
    CurrentPrefix = DefaultPrefix
    
    
    # break pronuc 
    Pronuncs = ParsePronucs(pronunc)
    
    
    
    
    AudioList = [];
    for line in progress.tqdm(lines, desc="Gerando fala..."):
        audioNum += 1;
         
        textVars,cleanLine = ExtractVars(line)

        if textVars['prefix']:
            CurrentPrefix = textVars['prefix']

        audioName = textVars['name'];
        
        if audioName:
            audioName = '_'+audioName

        num = textVars['num'];
        
        if not num:
            num = audioNum;
        
        path = CurrentPrefix +"_n_" + str(num)+audioName+".wav"

        print("Generating audio for line", num, 'sequence', audioNum);
        
        speaker = textVars['speaker'];
        
        if not speaker:
            speaker = speaker_name_studio if speaker_type == 'Studio' else speaker_name_custom
        
        speakerName,embeddings = FindSpeakerByName(speaker, speaker_type)
        
        if not speakerName:
             raise ValueError("InvalidSpeaker: "+speakerName) 
             
        
        
        FixedText = cleanLine;
        
        for pronunc in Pronuncs:
            word = pronunc['word']
            text = pronunc['text']
            opts = pronunc['opts'];
            
            flg = re.IGNORECASE
            
            if 'cs' in opts:
                flg = 0;
            
            FixedText = re.sub(f'\\b{word}\\b', text, FixedText, flags=flg)

        ipts = xtts.TTSInputs(
            speaker_embedding=embeddings["speaker_embedding"],
            gpt_cond_latent=embeddings["gpt_cond_latent"],
            text=FixedText,
            language=lang,
            temperature=temperature,
            speed=speed,
            top_k=top_k,
            top_p=top_p
        )
    
        generated_audio = xtts.predict_speech(ipts)
    
        print("Audio generated.. Saving to", path);
        generated_audio_path = os.path.join(AUDIOS_DIR, path)
        with open(generated_audio_path, "wb") as fp:
            fp.write(base64.b64decode(generated_audio))
            AudioList.append(fp.name);
    
    AllFileList.clear();
    AllFileList.extend(AudioList);
    
    return gr.Dropdown(
            label="Generated Audios",
            choices=list(AudioList),
            value=AudioList[0]
        )
            
def get_file_content(f):
    if len(f) > 0:
        return f[0];
        
    return None;


def UpdateFileList(DirListState):
    DirListState.clear();
    DirListState.extend( os.listdir(AUDIOS_DIR) )
     
def audio_list_update(d):
    fullPath = abspath(d)
    return fullPath
    
def ZipAndDownload(files):
    allFiles = files
    
    DefaultPrefix = next(tempfile._get_candidate_names());
    
    zipFile = abspath( os.path.join(ZIP_DIR, DefaultPrefix + ".zip") );
    
    
    with zipfile.ZipFile(zipFile, 'w') as zipMe:        
        for file in allFiles:
            print("Zipping", file);
            zipMe.write(abspath(file), os.path.basename(file), compress_type=zipfile.ZIP_DEFLATED)
    
    print("Pronto",  zipFile);
    
    return '<a href="/file='+zipFile+'">If donwload dont starts, click here</a>';
   

js = """

function DetectDownloadLink(){

    console.log('Configuring AutoDonwloadObservr...');

    let hiddenLink = document.getElementById("DonwloadLink");

    let onChange= function(mutations){

        

         for (const mutation of mutations) {

            if (mutation.type !== 'childList')

                continue;



              for (const addedNode of mutation.addedNodes) {

                if (addedNode.nodeName === 'A') {

                    location.href = addedNode.href;

                }

              }



          }

    }

    

    let config = {  attributes: true, childList: true, subtree: true, attributeFilter: ["href"] }

    let obs = new MutationObserver(onChange);

    obs.observe(hiddenLink, config);

}

"""

with gr.Blocks(js=js) as demo:
    defaultSpeaker = "Dionisio Schuyler"
    cloned_speaker_names = gr.State(list(cloned_speakers.keys()))
    AllFileList = gr.State(list([]))

    gr.Markdown("By using any functionality of this space, you agree to the terms of this license: https://coqui.ai/cpml")
    
    with gr.Tab("TTS"):
        with gr.Column() as row4:
            with gr.Row() as col4:
                speaker_type = gr.Dropdown(label="Speaker type", choices=["Studio", "Cloned"], value="Studio")
                speaker_name_studio = gr.Dropdown(
                    label="Studio speaker",
                    choices=STUDIO_SPEAKERS.keys(),
                    value=defaultSpeaker if defaultSpeaker in STUDIO_SPEAKERS.keys() else None,
                )
                speaker_name_custom = gr.Dropdown(
                    label="Cloned speaker",
                    choices=cloned_speaker_names.value,
                    value=cloned_speaker_names.value[0] if len(cloned_speaker_names.value) != 0 else None,
                )            
        with gr.Accordion("Advanced options", open=False):
             with gr.Row() as rowAdvanced:
                temperature = gr.Slider(0.00, 1.00, 0.5, step=0.05, label="Temperature", info="Choose between 0 and 1")
                top_p = gr.Slider(0.00, 1.00, 0.8, step=0.05, label="TOP P", info="Choose between 0 and 1")
                top_k = gr.Number(label="TOP K",value=50)
                speed = gr.Slider(0.00, 1000.00, 1.0, step=0.1, label="Speed", info="Speed (0 to 1000)")
        with gr.Column() as col2:
            with gr.Row():
                text = gr.Textbox(label="text",lines=4, value="Customizado por IA Talking, o maior blog de Inteligência Artificial do Brasil!")
                pronunc = gr.Textbox(label="Pronunciation Fix", info="Fix words pronuncation using WORD = SPEAK",lines=4)
            with gr.Row():
                lang = gr.Dropdown(label="Language", choices=LANUGAGES, value="pt")
                tts_button = gr.Button(value="TTS")   
        with gr.Column() as col3:
            # FileList = gr.FileExplorer(
            #     glob="*.wav",
            #     # value=["themes/utils"],
            #     ignore_glob="**/__init__.py",
            #     root_dir=AUDIOS_DIR,
            #     interactive = True,
            #     value=DirectoryList.value
            # )
            
            AudioList = gr.Dropdown(
                    label="Generated Audios",
                    choices=['a','b']
                    ,interactive=True
                )
            
            generated_audio = gr.Audio(label="Audio Play", autoplay=True)
            AudioList.change(fn=audio_list_update, inputs=[AudioList], outputs=[generated_audio])
            
            dummyHtml = gr.HTML(elem_id = "DonwloadLink", render = False); 
            downloadAll = gr.DownloadButton("Download All Files")
            downloadAll.click(ZipAndDownload, inputs=[AllFileList], outputs=[dummyHtml]);
            dummyHtml.render();
            
            
    with gr.Tab("Clone a new speaker"):
        with gr.Column() as col1:
            upload_file = gr.Audio(label="Upload reference audio", type="filepath")
            clone_speaker_name = gr.Textbox(label="Speaker name", value="default_speaker")
            clone_button = gr.Button(value="Clone speaker")


    with gr.Tab("Help"):
         gr.Markdown("""

Welcome to the XTTS WebUI version customized by the IA Talking blog (https://iatalk.ing).



The main goal of this space is to share more scenarios on how XTTS can be used, as well as serve as a study resource to learn more about the TTS process and AI.



In this version, we have some customizations that are quite useful.



# Multiple audios

You can generate multiple audios at once by separating the text with three dashes. For example:



```

Text 1

---

Text 2, line 1

Text 2, line 2

```



In the above example, 2 audio files will be generated! This is very useful when you want to generate a lot of audio but don't want to generate it all at once due to the context lost in XTTS.

You can also specify variables that modify certain aspects.



For example, `!speaker = Dionisio` forces the speaker to be Dionisio only for that specific audio.



List of variables:

- `speaker` = name of the speaker

- `num` = file number (by default, it's the sequential number)

- `prefix` = file name prefix



# Pronunciation adjustment



If you have a text that you cannot or do not want to change the content of, you can use the Pronunciation field to map words with different pronunciations.



Simply separate them by each line. Example:



```

API = A,P,I

SomeFunctionCode = Function Code

```



This is useful for mapping foreign words, abbreviations, acronyms, code, etc.

         """)

    clone_button.click(
        fn=clone_speaker,
        inputs=[upload_file, clone_speaker_name, cloned_speaker_names],
        outputs=[upload_file, clone_speaker_name, cloned_speaker_names, speaker_name_custom],
    )

    tts_button.click(
        fn=tts,
        inputs=[text, pronunc,speaker_type, speaker_name_studio, speaker_name_custom, lang, temperature
                ,speed,top_p,top_k,AllFileList
                ],
        outputs=[AudioList],
    )
    
if __name__ == "__main__" and DO_CHECK == "1":
    print("Warming up server... Checking server healthy...")
    
    speakerName, embs = random.choice(list(STUDIO_SPEAKERS.items()));
   
    print("Testing with", speakerName);

    ipts = xtts.TTSInputs(
        speaker_embedding=embs["speaker_embedding"],
        gpt_cond_latent=embs["gpt_cond_latent"],
        text="This is a warmup request.",
        language="en",
        temperature=0.5,
        speed=1.0,
        top_k=50,
        top_p=0.8
    )
    
    resp = xtts.predict_speech(ipts)
    
    print(" TEST OK")   


if __name__ == "__main__":
    print("STARTING...")
    demo.launch(
        share=False,
        debug=False,
        server_port=7860,
        server_name="0.0.0.0",
        allowed_paths=[ZIP_DIR]
    )