Merge pull request #68 from erew123/dev

Update to Main
Update README.md
2024-01-13 21:28:59 +00:00 · 2024-01-13 21:23:47 +00:00 · 2024-01-13 21:16:01 +00:00 · 2024-01-13 21:07:18 +00:00 · 2024-01-13 20:22:10 +00:00 · 2024-01-13 20:13:38 +00:00
55 changed files with 10931 additions and 1122 deletions
@@ -0,0 +1,32 @@
 ---
 name: Bug report/Support request
 about: Create a report to help us improve
 title: ''
 labels: ''
 assignees: ''
 ---
 Please generate a diagnostics report and upload the "diagnostics.log".
 https://github.com/erew123/alltalk_tts/tree/main?#-how-to-make-a-diagnostics-report-file
 **Describe the bug**
 A clear and concise description of what the bug is.
 **To Reproduce**
 Steps to reproduce the behaviour:
 **Screenshots**
 If applicable, add screenshots to help explain your problem.
 **Text/logs**
 If applicable, copy/paste in your logs here from the console.
 **Desktop (please complete the following information):**
 AllTalk was updated: [approx. date]
 Custom Python environment: [yes/no give details if yes]
 Text-generation-webUI was updated: [approx. date]
 **Additional context**
 Add any other context about the problem here.
@@ -0,0 +1,20 @@
 ---
 name: Feature request
 about: Suggest an idea for this project
 title: ''
 labels: ''
 assignees: ''
 ---
 **Is your feature request related to a problem? Please describe.**
 A clear and concise description of what the problem is. Ex. I'm always frustrated when [...]
 **Describe the solution you'd like**
 A clear and concise description of what you want to happen.
 **Describe alternatives you've considered**
 A clear and concise description of any alternative solutions or features you've considered.
 **Additional context**
 Add any other context or screenshots about the feature request here.
@@ -1,160 +1,8 @@
-# Byte-compiled / optimized / DLL files
+voices/*.*
-__pycache__/
+models/*.*
-*.py[cod]
+outputs/*.*
-*$py.class
+finetune/*.*
-
+config.json
-# C extensions
+confignew.json
-*.so
+models.json
-
+diagnostics.log
 # Distribution / packaging
 .Python
 build/
 develop-eggs/
 dist/
 downloads/
 eggs/
 .eggs/
 lib/
 lib64/
 parts/
 sdist/
 var/
 wheels/
 share/python-wheels/
 *.egg-info/
 .installed.cfg
 *.egg
 MANIFEST
 # PyInstaller
 #  Usually these files are written by a python script from a template
 #  before PyInstaller builds the exe, so as to inject date/other infos into it.
 *.manifest
 *.spec
 # Installer logs
 pip-log.txt
 pip-delete-this-directory.txt
 # Unit test / coverage reports
 htmlcov/
 .tox/
 .nox/
 .coverage
 .coverage.*
 .cache
 nosetests.xml
 coverage.xml
 *.cover
 *.py,cover
 .hypothesis/
 .pytest_cache/
 cover/
 # Translations
 *.mo
 *.pot
 # Django stuff:
 *.log
 local_settings.py
 db.sqlite3
 db.sqlite3-journal
 # Flask stuff:
 instance/
 .webassets-cache
 # Scrapy stuff:
 .scrapy
 # Sphinx documentation
 docs/_build/
 # PyBuilder
 .pybuilder/
 target/
 # Jupyter Notebook
 .ipynb_checkpoints
 # IPython
 profile_default/
 ipython_config.py
 # pyenv
 #   For a library or package, you might want to ignore these files since the code is
 #   intended to run in multiple environments; otherwise, check them in:
 # .python-version
 # pipenv
 #   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
 #   However, in case of collaboration, if having platform-specific dependencies or dependencies
 #   having no cross-platform support, pipenv may install dependencies that don't work, or not
 #   install all needed dependencies.
 #Pipfile.lock
 # poetry
 #   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
 #   This is especially recommended for binary packages to ensure reproducibility, and is more
 #   commonly ignored for libraries.
 #   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
 #poetry.lock
 # pdm
 #   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
 #pdm.lock
 #   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
 #   in version control.
 #   https://pdm.fming.dev/#use-with-ide
 .pdm.toml
 # PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
 __pypackages__/
 # Celery stuff
 celerybeat-schedule
 celerybeat.pid
 # SageMath parsed files
 *.sage.py
 # Environments
 .env
 .venv
 env/
 venv/
 ENV/
 env.bak/
 venv.bak/
 # Spyder project settings
 .spyderproject
 .spyproject
 # Rope project settings
 .ropeproject
 # mkdocs documentation
 /site
 # mypy
 .mypy_cache/
 .dmypy.json
 dmypy.json
 # Pyre type checker
 .pyre/
 # pytype static type analyzer
 .pytype/
 # Cython debug symbols
 cython_debug/
 # PyCharm
 #  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
 #  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
 #  and can be added to the global gitignore or merged into this file.  For a more nuclear
 #  option (not recommended) you can uncomment the following to ignore the entire idea folder.
 #.idea/
@@ -0,0 +1,9 @@
 {
    "files.associations": {
        "*.html": "jinja-html"
    },
    "emmet.includeLanguages": {
        "jinja-html": "html",
        "jinja2": "html"
    },
 }
@@ -0,0 +1,661 @@
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@@ -1,147 +1,586 @@
 # AllTalk TTS
 AllTalk is an updated version of the Coqui_tts extension for Text Generation web UI. Features include:
- **Custom Start-up Settings:** Adjust your default start-up settings. [Screenshot](https://github.com/erew123/alltalk_tts#screenshots)
+- **Can be run as a** [standalone](https://github.com/erew123/alltalk_tts/#-quick-setup-text-generation-webui--standalone-installation) **or part of** [Text-generation-webui](https://github.com/erew123/alltalk_tts/#-quick-setup-text-generation-webui--standalone-installation) **using the a quick setup utility**
- **Narrarator:** Use different voices for main character and narration. [Example Narration](https://vocaroo.com/18fYWVxiQpk1)
+- **Model Finetuning:** Train the model specifically on a voice of your choosing for better reproduction.
 - **Low VRAM mode:** Improve generation performance if your VRAM is filled by your LLM. [Screenshot](https://github.com/erew123/alltalk_tts#screenshots)
 - **DeepSpeed:** A 3-4x performance boost generating TTS. [DeepSpeed Windows/Linux Instructions](https://github.com/erew123/alltalk_tts?tab=readme-ov-file#deepspeed-installation-options) [Screenshot](https://github.com/erew123/alltalk_tts/assets/35898566/548619c8-5f1b-47d0-a73d-54d2fee3f3db)
 - **Local/Custom models:** Use any of the XTTSv2 models (API Local and XTTSv2 Local).
- **Optional wav file maintenance:** Configurable deletion of old output wav files. [Screenshot](https://github.com/erew123/alltalk_tts#screenshots)
+- **Bulk TTS Generator/Editor:** Generate hours of TTS into one big file or have something read back to you [demo](https://www.youtube.com/watch?v=hunvXn0mLzc).
- **Documentation:** Fully documented with a built in webpage. [Screenshot](https://github.com/erew123/alltalk_tts#screenshots)
+- **DeepSpeed:** A 2-3x performance boost generating TTS. [Screenshot](https://github.com/erew123/screenshots/raw/main/deepspeed.jpg)
- **Console output** Clear command line output for any warnings or issues.
+- **Low VRAM mode:** Great for people with small GPU memory or if your VRAM is filled by your LLM.
- **Standalone/3rd Party support via JSON calls** Can be used with 3rd party applications via JSON calls.
+- **Custom Start-up Settings:** Adjust your default start-up settings. [Screenshot](https://github.com/erew123/screenshots/raw/main/settingsanddocs.jpg)
 - **Narrarator:** Use different voices for main character and narration. [Example Narration](https://vocaroo.com/18nrv7FR6wuA)
 - **Optional wav file maintenance:** Configurable deletion of old output wav files. [Screenshot](https://github.com/erew123/screenshots/raw/main/settingsanddocs.jpg)
 - **Documentation:** Fully documented with a built in webpage. [Screenshot](https://github.com/erew123/screenshots/raw/main/settingsanddocs.jpg)
 - **Clear Console output:** Clear command line output for any warnings or issues.
 - **API Suite and 3rd Party support via JSON calls:** Can be used with 3rd party applications via JSON calls.
 - **SillyTavern integration:** Full integration with SillyTavern. [Screenshot](https://github.com/erew123/screenshots/raw/main/sillytavern.jpg)
-#### Updates
+## Index
 The latest build (13 Dec 2023) has had the entire text filtering engine and narration engine rebuilt from scratch. It's highly complicated how its actually working, but the end result it a much clearer TTS output and much better control over the narrator option and how to handle text that isnt within quotes or asterisks. Its a highly recommened update, for the improved quality it gives to the TTS output, if nothing else.
-Should you want the older version of the narrator engine+text filtering, I will leave this older copy [here](https://github.com/erew123/alltalk_tts/releases/tag/v1-old-narrator)
+- 🟩 [Installation](https://github.com/erew123/alltalk_tts/#-quick-setup-text-generation-webui--standalone-installation)
 - 🟪 [Updating & problems with updating](https://github.com/erew123/alltalk_tts?#-updating)
 - 🟫 [Screenshots](https://github.com/erew123/alltalk_tts#-screenshots)
 - 🟨 [Help with problems](https://github.com/erew123/alltalk_tts?#-help-with-problems)
 - ⚫ [Finetuning a model](https://github.com/erew123/alltalk_tts?#-finetuning-a-model)
 - 🔵🟢🟡 [DeepSpeed Installation (Windows & Linux)](https://github.com/erew123/alltalk_tts?#-deepspeed-installation-options)
 - ⬜ [AllTalk TTS Generator](https://github.com/erew123/alltalk_tts?#-alltalk-tts-generator)
 - 🟠 [API Suite and JSON-CURL](https://github.com/erew123/alltalk_tts?#-api-suite-and-json-curl)
 - 🔴 [Future to-do list & Upcoming updates](https://github.com/erew123/alltalk_tts?#-future-to-do-list)
-DeepSpeed **v11.2** can be installed within the **default text-generation-webui Python 3.11 environment**. Instructions [here](https://github.com/erew123/alltalk_tts#deepspeed-112-for-windows--python-311) (or scroll down). Please note, this is **not** an official Microsoft method (currently) so they will not support you with this style installation. Officially, only DeepSpeed v8.3 is installing on Python 3.9.x.
+## 🔄 Updates & Bug fixes
 Please check the below link to find a list of all recent updates and changes.
 #### &nbsp;&nbsp;&nbsp;&nbsp;🔄 **Updates list & bug fixes list** can be found [here](https://github.com/erew123/alltalk_tts/issues/25)
-#### The one thing I cant easily work around
+## 🟩 Quick Setup (Text-generation-webui & Standalone Installation)
-With a RP chat with your AI, **on your character card** `parameters menu` > `character tab` > `greeting` make sure that anything in there that is the **narrator is in asterisks** and anything **spoken is in double quotes**, then hit the `save` (disk) button. Greeting paragraphs/sentences are handled differently from how the AI sends text and so its difficut to account for them both.
+For Windows 10/11 and Linux machines there is a quick setup script. Click to expand the correct section below:
 <details>
 	<summary>QUICK SETUP - Text-Generation-webui</summary><br>
-I could force a delimeter in at this stage, but I know it would/may affect things further down the line in the chat and I need a good think about that before just making a change. This issue **only** affects the greeting card/start of conversation and the "example" card that comes with text-generation-webui suffers this issue (if you want to try it for yourself). So you would put double quotes around like this (from the example card):
+ If you wish to see this as a video, please go [here](https://www.youtube.com/watch?v=icn2XS5rUH8)
 1) To download the AllTalk setup you can either:
   - A) On this page select **CODE** > **Download ZIP** then extract it to the text-generation-webui extensions folder<br>e.g. `\text-generation-webui\extensions\alltalk_tts\`<br><br>
   - B) Go to a terminal/console, move into the `\text-generation-webui\extensions\` folder<br>and `git clone https://github.com/erew123/alltalk_tts`<br><br>
 3) In a terminal/command prompt, in the text-generation-webui folder you will start its Python environment with either `cmd_windows.bat` or `./cmd_linux.sh`
 4) Move into the AllTalk folder e.g. `cd extensions` then `cd alltalk_tts`
 5) Start the AllTalk setup script `atsetup.bat` or `./atsetup.sh`
 6) Follow the on-screen prompts and install the correct requirements files that you need. It's recommended to test AllTalk works before installing DeepSpeed.
-`"`Hey! I'm so excited to finally meet you. I've heard so many great things about you and I'm eager to pick your brain about computers. I'm sure you have a wealth of knowledge that I can learn from.`"`
+   Any time you need to make changes to AllTalk, or use Finetuning etc, always start the Text-generation-webui Python environment first.
-## 🟩 Installation on Text generation web UI
+   Please read the `🟩 Other installation notes` (also additional voices are available there).
 This has been tested on the current Dec 2023 release of Text generation webUI. If you have not updated it for a while, you may wish to update Text generation webUI, instructions [here](https://github.com/oobabooga/text-generation-webui#getting-updates)
-1) In a command prompt/terminal window you need to move into your Text generation webUI folder:
+   Finetuning & DeepSpeed have other installation requirements (depending on your OS) so please read any instructions in the setup utility and refer back here to this page for detailed instructions (as needed).<br><br>
 </details>
 <details>
 	<summary>QUICK SETUP - Standalone Installation</summary><br>
 If you wish to see this as a video, please go [here](https://www.youtube.com/watch?v=AQYCccDRbaY)
 1) To download the AllTalk setup you can either:
   - A) On this page select **CODE** > **Download ZIP** then extract it to the folder of your choice<br>e.g. `C:\myfiles\alltalk_tts\`<br><br>
   - B) Go to a terminal/console, move into the folder of your choice e.g `C:\myfiles\` folder<br>and `git clone https://github.com/erew123/alltalk_tts`<br><br>
 4) In a terminal/command prompt, move into the AllTalk folder e.g. `cd alltalk_tts`
 5) Start the AllTalk setup script `atsetup.bat` or `./atsetup.sh`
 6) Follow the on-screen prompts and install the correct requirements files that you need. It's recommended to test AllTalk works before installing DeepSpeed.
   DeepSpeed on Windows machines will be installed as standard. Linux machines have other requirements which are detailed within the setup utility and on this page.
   Please read the `🟩 Other installation notes` (also additional voices are available there).
   Finetuning has other installation requirements so please read any instructions in the setup utility and refer back here to this page for detailed instructions.<br><br>
 </details>
 ## 🟩 Manual Installation - As part of Text generation web UI
 On Mac's or if you wish to perform a manual installation. Click to expand the correct section below:
 <details>
 	<summary>MANUAL INSTALLATION - Text-Generation-webui</summary><br>
 This has been tested on the current Dec 2023 release of Text generation webUI. If you have not updated it for a while, you may wish to update Text generation webUI, [instructions here](https://github.com/oobabooga/text-generation-webui?tab=readme-ov-file#how-to-install)
 - If you want to watch a video of how to do the below [link here](https://youtu.be/9BPKuwaav5w)<br>
 1) In a command prompt/terminal window you need to move into your Text generation webUI folder:<br><br>
 `cd text-generation-webui`
-2) Start the Text generation webUI Python environment for your OS:
+2) Start the Text generation webUI Python environment for your OS with whichever **one** of the below is correct for your OS:<br><br>
-
+`cmd_windows.bat`, `./cmd_linux.sh`, `cmd_macos.sh` or `cmd_wsl.bat`<br><br> Loading Text-generation-webui's Python Environment is $\textcolor{red}{\textsf{VERY IMPORTANT}}$. If you are uncertain what a loaded Python environment looks like, image [here](https://github.com/erew123/alltalk_tts/issues/25#issuecomment-1869344442) and video [here](https://www.youtube.com/watch?v=9BPKuwaav5w)
 `cmd_windows.bat`, `./cmd_linux.sh`, `cmd_macos.sh` or `cmd_wsl.bat`
 3) Move into your extensions folder:
 3) Move into your extensions folder:<br><br>
 `cd extensions`
-4) Once there git clone this repository:
+4) Once there git clone this repository:<br><br>
 `git clone https://github.com/erew123/alltalk_tts`
-5) Move into the **alltalk_tts** folder:
+5) Move into the **alltalk_tts** folder:<br><br>
 `cd alltalk_tts`
-6) Install the requirements:
+6) Install one of the two requirements files. Whichever one of the two is correct for your machine type:<br><br>
 **Nvidia graphics card machines** - `pip install -r requirements_nvidia.txt`<br><br>
 **Other machines (mac, amd etc)** - `pip install -r requirements_other.txt`
-*Nvidia graphics card machines* - `pip install -r requirements_nvidia.txt`
+7) **(Optional DeepSpeed)** If you have an Nvidia Graphics card on a system running Linux or Windows and wish to use **DeepSpeed** please follow these instructions [here](https://github.com/erew123/alltalk_tts?#-deepspeed-installation-options). **However**, I would highly reccommend before you install DeepSpeed, you start text-generation-webui up, confirm AllTalk starts correctly and everything is working, as DeepSpeed can add another layer of complications troubleshooting any potential start-up issues. If necessary you can `pip uninstall deepspeed`.
-*Other machines (mac, amd etc)* - `pip install -r requirements_other.txt`
+8) You can now start move back to the main Text generation webUI folder `cd ..` (a few times), start Text generation webUI with whichever **one** of the startup scripts is correct for your OS (`start_windows.bat`,`./start_linux.sh`, `start_macos.sh` or `start_wsl.bat`)  and load the AllTalk extension in the Text generation webUI **session** tab.<br><br> Starting Text-generation-webui with its correct start-up script is $\textcolor{red}{\textsf{VERY IMPORTANT}}$.
-7) You can now start move back to the main Text generation webUI folder `cd ..` (a few times), start Text generation webUI (`start_windows.bat`,`./start_linux.sh`, `start_macos.sh` or `start_wsl.bat`)  and load the AllTalk extension in the Text generation webUI **session** tab.
+   Any time you need to make changes to AllTalk, or use Finetuning etc, always start the Text-generation-webui Python environment first.
-8) Please read the note below about start-up times and also the note above about ensuring your character cards are set up [correctly](https://github.com/erew123/alltalk_tts#the-one-thing-i-cant-easily-work-around)
+   Please read the `🟩 Other installation notes` (also additional voices are available there).
-9) Some extra voices downloadable [here](https://drive.google.com/file/d/1bYdZdr3L69kmzUN3vSiqZmLRD7-A3M47/view?usp=drive_link)
+   Finetuning & DeepSpeed have other installation requirements (depending on your OS) so please read any instructions in the setup utility and refer back here to this page for detailed instructions (as needed).<br><br>
-**Note: It can take a while to start up.** Check the command prompt/terminal window if you want to know what its doing. After it says "Model Loaded" the Text generation webUI is usually available on its IP address a few seconds later, for you to connect to in your browser.
+</details>
-**Documentation:** Click on the link when inside Text generation webUI as shown in the screenshot [here](https://github.com/erew123/alltalk_tts#screenshots)
+## 🟩 Manual Installation - As a Standalone Application
 On Mac's or if you wish to perform a manual installation. Click to expand the correct section below:
 <details>
 	<summary>MANUAL INSTALLATION - I want to run AllTalk as a standalone when installed with Text-generation-webui</summary><br>
-**Where to find voices** https://aiartes.com/voiceai or https://commons.wikimedia.org/ or interviews on youtube etc. Instructions on how to cut down and prepare a voice sample are within the built in documentation.
+If you already have AllTalk as a extension of Text-generation-webui, and wish to run it as standalone, load Text-generation-webui's Python environment `cmd_windows.bat`, `./cmd_linux.sh`, `cmd_macos.sh` or `cmd_wsl.bat`, move into the AllTalk folder `cd extensions` > `cd alltalk_tts` and start AllTalk with `python script.py`. There is nothing beyond this you would need to do.
 </details>
 <details>
 	<summary>MANUAL INSTALLATION - I wish to do a custom install of AllTalk</summary><br>
-### 🟩 Other installation notes
+AllTalk will run as a standalone app, as long as you install its requirements files into whatever Python environment you are using. You can follow the steps to install the AllTalk's requirements into whatever Python environment you wish. Because I dont know what Python environment you are wanting to use, I can only give you a loose set of installation instructions. 
-On first startup, AllTalk will download the Coqui XTTSv2 2.0.2 model to its **models** folder (1.8GB space required). You can customse your model or use the TTS latest model within the interface (details in documentation).
+
 Please note, at time of writing, the TTS engine requires Python **3.9.x** to **3.11.x** [TTS Engine details here](https://pypi.org/project/TTS/). AllTalk and its requirements are tested on Python **3.11.x**.
 #### 🟩 A very quick understanding of Python Environments.
 Different Python applications have different requirements, some of those requirement’s conflict with other Python applications requirements. To work around this problem, you can create different Python environments that remain separated from one another. A simple way of looking at Python environments, is just like how your house has different rooms for specific purposes (Kitchen, Bathroom, Bedroom etc). You can create a Python environment that is built/customised specifically for your current applications needs/purposes and will **not** interfere with any other Python applications environments/installations. <br><br>If you are adept at managing Python environments, have an existing Python environment and know that you won’t cause any conflicts by installing AllTalk's requirements within that Python environment, then load up your Python environment and install the requirements. For everyone else, here is a basic guide on installing AllTalk in its own custom Python environment (there will be small variations between OS's, but the principle is the same).
 **Note:** A standard VENV can cause module path issues, hence Conda is the correct method to create a Python environment for AllTalk. 
 #### 🟩 Building a custom Python Environment with Miniconda
 1) Open a terminal/command prompt, and confirm that both `python --version` and `pip` both work. Neither of them should give an error message. If they do you may need to install Python (and maybe Pip).<br><br>[Python Website](https://www.python.org/downloads/)<br>[Pip Website](https://pip.pypa.io/en/stable/installation/)<br><br>Once you have those working you can now continue on.<br><br>
 2) Assuming you don't already have Miniconda installed, we will need to download and install Minoconda as this is what we will use to build our custom Python environment.<br><br>[Miniconda Website](https://docs.conda.io/projects/miniconda/en/latest/)<br><br>Download the Miniconda version that is correct for your OS and then install it. Miniconda will create some items in your Start Menu or Application Launcher called something like `Anaconda Prompt`<br><br> You will start the `Anaconda Prompt` and your prompt in your terminal/command prompt will say something like: <br><br>`(base) C:\users\myaccount\>`<br><br> The important bit is that it has the `(base)`, the location after that doesn't matter. `(base)` signifies we are in the base conda Python environment and can now create custom Python environments with Conda.<br><br>
 3) In your Anaconda Prompt command prompt/terminal, move into the folder where you want to download AllTalk to and then git clone this repository. For simplicity I am going to assume that location is `c:\myfiles\`. So you will:<br><br>`cd myfiles`<br><br>`git clone https://github.com/erew123/alltalk_tts`<br><br>
 4) Now we will create our custom Conda Python 3.11.5 environment and give it the name alltalkenv by typing the following at the prompt:<br><br>`conda create --name alltalkenv python=3.11.5`<br><br>You will be prompted if you want to continue and you say yes.<br><br>Once that process has completed, we now need to change from the `(base)` Conda Python environment, to our newly created `(alltalkenv)` environment. So type the following:<br><br>`conda activate alltalkenv`<br><br>Your prompt should now change from `(base) C:\myfiles\>` to `(alltalkenv) C:\myfiles\>`<br><br>
 5) **If you are NOT using an Nvidia card and CUDA, skip to step 6**. To force PyTorch to install with CUDA, perform the following:<br><br>`pip cache purge` (Clear the current Pip cache)<br><br>`pip uninstall torch torchaudio` (Uninstall Torch and Torchaudio from the `alltalkenv` environment)<br><br>
 You can now either install the CUDA 11.8 or 12.1 version of Torch and Torchaudio with **one** of the following<br><br>**CUDA 11.8** > `pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118`<br><br>**CUDA 12.1** > `pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121`<br><br>
 6) Move into the alltalk_tts folder and install one of the two requirements files. Whichever one of the two is correct for your machine type:<br><br>`cd alltalk_tts`<br><br>
 **Nvidia graphics card machines** - `pip install -r requirements_nvidia.txt`<br><br>
 **Other machines (mac, amd etc)** - `pip install -r requirements_other.txt`<br><br>
 7) Start AllTalk with `python script.py`<br><br>
 🟩 Anytime you wish to use AllTalk, update its requirements, install some other requirements such as DeepSpeed, you will need to start its Conda Python Environment in the terminal/prompt, which you will do with `conda activate alltalkenv` as long as the Conda executable is accessible at the command prompt/terminal you are in.<br><br>It is fully possible to create a batch file or script file that you can use as a launcher from your Start Menu/Application Launcher that will start the environment and AllTalk for you. 
 Deepspeed and other such things can be installed. Please read the relevant instructions for those items, however, make the relevant changes to load your correct Python environment when installing any requirements files and starting AllTalk.<br><br>
   Any time you need to make changes to AllTalk, or use Finetuning etc, always start your Python environment first.
   Please read the `🟩 Other installation notes` (also additional voices are available there).
   Finetuning & DeepSpeed have other installation requirements (depending on your OS) so please read any instructions in the setup utility and refer back here to this page for detailed instructions (as needed).<br><br>
 </details>
 #### 🟩 Other installation notes
 On first startup, AllTalk will download the Coqui XTTSv2 2.0.2 model to its **models** folder (1.8GB space required). Check the command prompt/terminal window if you want to know what its doing. After it says "Model Loaded" the Text generation webUI is usually available on its IP address a few seconds later, for you to connect to in your browser.
 Once the extension is loaded, please find all documentation and settings on the link provided in the interface (as shown in the screenshot below).
-To start AllTalk every Text generation webUI loads, edit the Text generation webUI `CMD_FLAGS.txt` file in the main `text-generation-webui` folder and add `--extensions alltalk_tts`.
+**Where to find voices** https://aiartes.com/voiceai or https://commons.wikimedia.org/ or interviews on youtube etc. Instructions on how to cut down and prepare a voice sample are within the built in documentation.
-## Screenshots
+Please read the note below about start-up times and also the note about ensuring your character cards are set up [correctly](https://github.com/erew123/alltalk_tts#-a-note-on-character-cards--greeting-messages)
 |![image](https://github.com/erew123/alltalk_tts/assets/35898566/4ca9b4c7-60ce-4ac6-82e5-fd1989b84644) | ![image](https://github.com/erew123/alltalk_tts/assets/35898566/b0e13dba-c6b1-4ab7-845d-244ac1158330) |
 |:---:|:---:|
 |![image](https://github.com/erew123/alltalk_tts/assets/35898566/548619c8-5f1b-47d0-a73d-54d2fee3f3db) | ![image](https://github.com/erew123/alltalk_tts/assets/35898566/e35e987c-543a-486b-b4fb-ee6ebe6f59c6) |
-## DeepSpeed Installation Options
+Some extra voices for AllTalk are downloadable [here](https://drive.google.com/file/d/1bYdZdr3L69kmzUN3vSiqZmLRD7-A3M47/view?usp=drive_link)
-### 🔵 For Linux
+#### 🟩 A note on Character Cards & Greeting Messages
-Covered in the online/buit-in documentation, but a nice easy install.
+Messages intended for the Narrator should be enclosed in asterisks `*` and those for the character inside quotation marks `"`. However, AI systems often deviate from these rules, resulting in text that is neither in quotes nor asterisks. Sometimes, text may appear with only a single asterisk, and AI models may vary their formatting mid-conversation. For example, they might use asterisks initially and then switch to unmarked text. A properly formatted line should look like this:
-### 🟢🟡 For Windows & Python 3.11
+`"`Hey! I'm so excited to finally meet you. I've heard so many great things about you and I'm eager to pick your brain about computers.`"` `*`She walked across the room and picked up her cup of coffee`*`
-DeepSpeed v11.1 and v11.2 will work on the current text-generation-webui Python 3.11 environment! You have 2x options for how to setup DeepSpeed on Windows. A quick way (🟢Option 1) and a long way (🟡Option 2).
+
 Most narrator/character systems switch voices upon encountering an asterisk or quotation marks, which is somewhat effective. AllTalk has undergone several revisions in its sentence splitting and identification methods. While some irregularities and AI deviations in message formatting are inevitable, any line beginning or ending with an asterisk should now be recognized as Narrator dialogue. Lines enclosed in double quotes are identified as Character dialogue. For any other text, you can choose how AllTalk handles it: whether it should be interpreted as Character or Narrator dialogue (most AI systems tend to lean more towards one format when generating text not enclosed in quotes or asterisks).
 With improvements to the splitter/processor, I'm confident it's functioning well. You can monitor what AllTalk identifies as Narrator lines on the command line and adjust its behavior if needed (Text Not Inside - Function).
 ## 🟪 Updating
 <details>
 	<summary>UPDATING - I am using Text-Generation-webui</summary><br>
 This is pretty much a repeat of the installation process. 
 1) In a command prompt/terminal window you need to move into your Text generation webUI folder:<br><br>
 `cd text-generation-webui` and start the Python environment for your OS with whichever **one** of the below is correct for your OS:<br><br>
 `cmd_windows.bat`, `./cmd_linux.sh`, `cmd_macos.sh` or `cmd_wsl.bat`<br>
 2) Move into your extensions and alltalk_tts folder e.g. `cd extensions` then `cd alltalk_tts`
 3) At the command prompt/terminal, type `git pull`
 4) Install the correct requirements for your machine:<br><br>
 **Nvidia graphics card machines** - `pip install -r requirements_nvidia.txt`<br><br>
 **Other machines (mac, amd etc)** - `pip install -r requirements_other.txt`<br><br>
 </details>
 <details>
 	<summary>UPDATING - I am running as a Standalone Application</summary><br>
 1) In a command prompt/terminal window you need to move into your `alltalk_tts` folder and run `start_environment.bat` or `/start_environment.sh` to load the Python environment.
 2) At the command prompt/terminal, type `git pull` and wait for it to complete the download.
 3) Install the correct requirements for your machine:<br><br>
 **Nvidia graphics card machines** - `pip install -r requirements_nvidia.txt`<br><br>
 **Other machines (mac, amd etc)** - `pip install -r requirements_other.txt`<br><br>
 </details>
 #### 🟪 Updating "git pull" error
 <details>
 	<summary>Click to expand</summary><br>
 I did leave a mistake in the `/extensions/alltalk_tts/.gitignore` file at one point. If your `git pull` doesnt work, you can either follow the Problems Updating section below, or edit the `.gitignore` file and **replace its entire contents** with the below, save the file, then re-try the `git pull`<br><br>
 ```
 voices/*.*
 models/*.*
 outputs/*.*
 finetune/*.*
 config.json
 confignew.json
 models.json
 diagnostics.log
 ```
 </details>
 #### 🟪 Updating other problems
 <details>
 	<summary>Click to expand</summary><br>
 If you do experience any problems, the simplest method to resolve this will be:
 1) re-name the existing `alltalk_tts` folder to something like `alltalk_tts.old`
 2) Start a console/terminal then:<br><br>
 `cd text-generation-webui` and start your python environment `cmd_windows.bat`, `./cmd_linux.sh`, `cmd_macos.sh` or `cmd_wsl.bat`
 3) Move into the extensions folder, same as if you were doing a fresh installation:<br><br>
 `cd extensions` then<br><br>
 `git clone https://github.com/erew123/alltalk_tts`
 This will download a fresh installation. 
 3) Move into the **alltalk_tts** folder:<br><br>
 `cd alltalk_tts`
 4) Install the correct requirements for your machine:<br><br>
 **Nvidia graphics card machines** - `pip install -r requirements_nvidia.txt`<br><br>
 **Other machines (mac, amd etc)** - `pip install -r requirements_other.txt`
 5) Before starting it up, copy/merge the `models`, `voices` and `outputs` folders over from the `alltalk_tts.old` folder to the newly created `alltalk_tts` folder. This will keep your voices history and also stop it re-downloading the model again.
 You can now start text-generation-webui or AllTalk (standalone) and it should start up fine. You will need to re-set any saved configuration changes on the configuration page. 
 Assuming its all working fine and you are happy, you can delete the old alltalk_tts.old folder.
 </details>
 ## 🟫 Screenshots
 |![image](https://github.com/erew123/screenshots/raw/main/textgensettings.jpg) | ![image](https://github.com/erew123/screenshots/raw/main/setuputilitys.jpg) | ![image](https://github.com/erew123/screenshots/raw/main/deepspeed.jpg) |![image](https://github.com/erew123/screenshots/raw/main/textgen.jpg) |
 |:---:|:---:|:---:|:---:|
 |![image](https://github.com/erew123/screenshots/raw/main/settingsanddocs.jpg) | ![image](https://github.com/erew123/screenshots/raw/main/finetune1.jpg) | ![image](https://github.com/erew123/screenshots/raw/main/finetune2.jpg) |![image](https://github.com/erew123/screenshots/raw/main/sillytavern.jpg)|
 ## 🟨 Help with problems
 #### &nbsp;&nbsp;&nbsp;&nbsp; 🔄 **Minor updates/bug fixes list** can be found [here](https://github.com/erew123/alltalk_tts/issues/25)
 #### 🟨 How to make a diagnostics report file
 If you are on a Windows machine or a Linux machine, you should be able to use the `atsetup.bat` or `./atsetup.sh` utility to create a diagnositcs file. If you are unable to use the `atsetup` utility, please follow the instructions below.
 <details>
 	<summary>Click to expand</summary>
 1) Open a command prompt window, move into your **text-generation-webui** folder, you can now start the Python environment for text-generation-webui:<br><br>
 `cmd_windows.bat`, `./cmd_linux.sh`, `cmd_macos.sh` or `cmd_wsl.bat`
 2) Move into the **alltalk_tts** folder:<br><br>
 `cd extensions` and then `cd alltalk_tts`
 3) Run the diagnostics and select the requirements file name you installed AllTalk with:<br><br>
 `python diagnostics.py`
 4) You will have an on screen output showing your environment setttings, file versions request vs whats installed and details of your graphics card (if Nvidia). This will also create a file called `diagnostics.log` in the `alltalk_tts` folder, that you can upload if you need to create a support ticket on here.<br><br>
 ![image](https://github.com/erew123/alltalk_tts/assets/35898566/81b9a6e1-c54b-4da0-b85d-3c6fde566d6a)
 <br><br></details>
 #### 🟨 [AllTalk Startup] Warning TTS Subprocess has NOT started up yet, Will keep trying for 120 seconds maximum. Please wait. It times out after 120 seconds.
 <details>
 	<summary>Click to expand</summary><br>
 	When the subprocess is starting 2x things are occurring:<br><br>
 **A)** Its trying to load the voice model into your graphics card VRAM (assuming you have a Nvidia Graphics card, otherwise its your system RAM)<br>
 **B)** Its trying to start up the mini-webserver and send the "ready" signal back to the main process.
 Before giving other possibilities a go, some people with **old machines** are finding their startup times are **very** slow 2-3 minutes. Ive extended the allowed time within the script from 1 minute to 2 minutes. **If you have an older machine** and wish to try extending this further, you can do so by editing `script.py` and changing line 251 `timeout = 120` changing the timeout to a larger value e.g `timeout = 240` (4 minutes).
 **Note:** If you need to create a support ticket, please create a `diagnostics.log` report file to submit with a support request. Details on doing this are above.
 Other possibilities for this issue are:
 1) You are starting AllTalk in both your `CMD FLAG.txt` and `settings.yaml` file. The `CMD FLAG.txt` you would have manually edited and the `settings.yaml` is the one you change and save in the `session` tab of text-generation-webui and you can `Save UI defaults to settings.yaml`. Please only have one of those two starting up AllTalk.
 2) You are not starting text-generation-webui with its normal Python environment. Please start it with start_{your OS version} as detailed [here](https://github.com/oobabooga/text-generation-webui#how-to-install) (`start_windows.bat`,`./start_linux.sh`, `start_macos.sh` or `start_wsl.bat`) OR (`cmd_windows.bat`, `./cmd_linux.sh`, `cmd_macos.sh` or `cmd_wsl.bat` and then `python server.py`).
 3) You have installed the wrong version of DeepSpeed on your system, for the wrong version of Python/Text-generation-webui. You can go to your text-generation-webui folder in a terminal/command prompt and run the correct cmd version for your OS e.g. (`cmd_windows.bat`, `./cmd_linux.sh`, `cmd_macos.sh` or `cmd_wsl.bat`) and then you can type `pip uninstall deepspeed` then try loading it again. If that works, please see here for the correct instructions for installing DeepSpeed [here](https://github.com/erew123/alltalk_tts#-deepspeed-installation-options). 
 4) You have an old version of text-generation-webui (pre Dec 2023) I have not tested on older versions of text-generation-webui, so cannot confirm viability on older versions. For instructions on updating the text-generation-webui, please look [here](https://github.com/oobabooga/text-generation-webui#how-to-install) (`update_linux.sh`, `update_windows.bat`, `update_macos.sh`, or `update_wsl.bat`).
 5) You already have something running on port 7851 on your computer, so the mini-webserver cant start on that port. You can change this port number by editing the `confignew.json` file and changing `"port_number": "7851"` to `"port_number": "7602"` or any port number you wish that isn’t reserved. Only change the number and save the file, do not change the formatting of the document. This will at least discount that you have something else clashing on the same port number.
 6) You have antivirus/firewalling that is blocking that port from being accessed. If you had to do something to allow text-generation-webui through your antivirus/firewall, you will have to do that for this too.
 7) You have quite old graphics drivers and may need to update them.
 8) Something within text-generation-webui is not playing nicely for some reason. You can go to your text-generation-webui folder in a terminal/command prompt and run the correct cmd version for your OS e.g. (`cmd_windows.bat`, `./cmd_linux.sh`, `cmd_macos.sh` or `cmd_wsl.bat`) and then you can type `python extensions\alltalk_tts\script.py` and see if AllTalk starts up correctly. If it does then something else is interfering. 
 9) Something else is already loaded into your VRAM or there is a crashed python process. Either check your task manager for erroneous Python processes or restart your machine and try again.
 10) You are running DeepSpeed on a Linux machine and although you are starting with `./start_linux.sh` AllTalk is failing there on starting. This is because text-generation-webui will overwrite some environment variables when it loads its python environment. To see if this is the problem, from a terminal go into your text-generation-webui folder and `./cmd_linux.sh` then set your environment variable again e.g. `export CUDA_HOME=/usr/local/cuda` (this may vary depending on your OS, but this is the standard one for Linux, and assuming you have installed the CUDA toolkit), then `python server.py` and see if it starts up. If you want to edit the environment permanently you can do so, I have not managed to write full instructions yet, but here is the conda guide [here](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html#set-env-vars).
 11) You have built yourself a custom Python environment and something is funky with it. This is very hard to diagnose as its not a standard environment. You may want to updating text-generation-webui and re installing its requirements file (whichever one you use that comes down with text-generation-webui).
 </details>
 #### 🟨 I think AllTalks requirements file has installed something another extension doesn't like
 <details>
 	<summary>Click to expand</summary><br>
 Ive paid very close attention to **not** impact what Text-generation-webui is requesting on a factory install. This is one of the requirements of submitting an extension to Text-generation-webui. If you want to look at a comparison of a factory fresh text-generation-webui installed packages (with cuda 12.1, though AllTalk's requirements were set on cuda 11.8) you can find that comparison [here](https://github.com/erew123/alltalk_tts/issues/23). This comparison shows that AllTalk is requesting the same package version numbers as Text-generation-webui or even lower version numbers (meaning AllTalk will not update them to a later version). What other extensions do, I cant really account for that.
 I will note that the TTS engine downgrades Pandas data validator to 1.5.3 though its unlikely to cause any issues. You can upgrade it back to text-generation-webui default (december 2023) with `pip install pandas==2.1.4` when inside of the python environment. I have noticed no ill effects from it being a lower or higher version, as far as AllTalk goes. This is also the same behaviour as the Coqui_tts extension that comes with Text-generation-webui.
 Other people are reporting issues with extensions not starting with errors about Pydantic e.g. ```pydantic.errors.PydanticImportError: BaseSettings` has been moved to the pydantic-settings package. See https://docs.pydantic.dev/2.5/migration/#basesettings-has-moved-to-pydantic-settings for more details.```
 Im not sure if the Pydantic version has been recently updated by the Text-generation-webui installer, but this is nothing to do with AllTalk. The other extension you are having an issue with, need to be updated to work with Pydantic 2.5.x. AllTalk was updated in mid december to work with 2.5.x. I am not specifically condoning doing this, as it may have other knock on effects, but within the text-gen Python environment, you can use `pip install pydantic==2.5.0` or `pip install pydantic==1.10.13` to change the version of Pydantic installed.
 </details>
 #### 🟨 I activated DeepSpeed in the settings page, but I didnt install DeepSpeed yet and now I have issues starting up
 <details>
 	<summary>Click to expand</summary><br>
 You can either follow the [Problems Updating](https://github.com/erew123/alltalk_tts#-problems-updating) and fresh install your config. Or you can edit the `confignew.json` file within the `alltalk_tts` folder. You would look for '"deepspeed_activate": true,' and change the word true to false `"deepspeed_activate": false,' ,then save the file and try starting again.<br><br>
 If you want to use DeepSpeed, you need an Nvidia Graphics card and to install DeepSpeed on your system. Instructions are [here](https://github.com/erew123/alltalk_tts#-deepspeed-installation-options)
 </details>
 #### 🟨 I am having problems updating/some other issue where it wont start up/Im sure this is a bug
 <details>
 	<summary>Click to expand</summary><br>
 Please see [Problems Updating](https://github.com/erew123/alltalk_tts#-problems-updating). If that doesnt help you can raise an ticket [here](https://github.com/erew123/alltalk_tts/issues). It would be handy to have any log files from the console where your error is being shown. I can only losely support custom built Python environments and give general pointers. Please create a `diagnostics.log` report file to submit with a support request.<br><br>
 Also, is your text-generation-webui up to date? [instructions here](https://github.com/oobabooga/text-generation-webui?tab=readme-ov-file#how-to-install)
 </details>
 #### 🟨 I am having problems getting AllTalk to start after changing settings or making a custom setup/model setup.
 <details>
 	<summary>Click to expand</summary><br>
 I would suggest following [Problems Updating](https://github.com/erew123/alltalk_tts#-problems-updating) and if you still have issues after that, you can raise an issue [here](https://github.com/erew123/alltalk_tts/issues)
 </details>
 #### 🟨 I see some red "asyncio" messages
 <details>
 	<summary>Click to expand</summary><br>
 As far as I am aware, these are to do with the chrome browser the gradio text-generation-webui in some way. I raised an issue about this on the text-generation-webui [here](https://github.com/oobabooga/text-generation-webui/issues/4788) where you can see that AllTalk is not loaded and the messages persist. Either way, this is more a warning than an actual issue, so shouldnt affect any functionality of either AllTalk or text-generation-webui, they are more just an annoyance.
 </details>
 #### 🟨 I have multiple GPU's and I have problems running Finetuning
 <details>
 	<summary>Click to expand</summary><br>
 Finetuning pulls in various other scripts and some of those scripts can have issues with multiple Nvidia GPU's being present. Until the people that created those other scripts fix up their code, there is a workaround to temporarily tell your system to only use the 1x of your Nvidia GPU's. To do this:
 - **Windows** - You will start the script with `set CUDA_VISIBLE_DEVICES=0 && python finetune.py`<br>
 After you have completed training, you can reset back with `set CUDA_VISIBLE_DEVICES=`<br>
 - **Linux** - You will start the script with `CUDA_VISIBLE_DEVICES=0 python finetune.py`<br>
 After you have completed training, you can reset back with `unset CUDA_VISIBLE_DEVICES`<br>
 Rebooting your system will also unset this. The setting is only applied temporarily.
 Depending on which of your Nvidia GPU's is the more powerful one, you can change the `0` to `1` or whichever of your GPU's is the most powerful.
 </details>
 ## ⚫ Finetuning a model
 If you have a voice that the model doesnt quite reproduce correctly, or indeed you just want to improve the reproduced voice, then finetuning is a way to train your "XTTSv2 local" model **(stored in `/alltalk_tts/models/xxxxx/`)** on a specific voice. For this you will need:
 - An Nvidia graphics card. (Please see this [note](https://github.com/erew123/alltalk_tts#-i-have-multiple-gpus-and-i-have-problems-running-finetuning) if you have multiple Nvidia GPU's).
 - To install a few portions of the Nvidia CUDA 11.8 Toolkit (this will not impact text-generation-webui's cuda setup.
 - 18GB of disk space free (most of this is used temporarily)
 - At least 2 minutes of good quality speech from your chosen speaker in mp3, wav or flacc format, in one or more files (have tested as far as 20 minutes worth of audio).
 - As a side note, many people seem to think that the Whisper v2 model (used on Step 1) is giving better results at generating training datasets, so you may prefer to try that, as opposed to the Whisper 3 model.
 #### ⚫ How will this work/How complicated is it?
 Everything has been done to make this as simple as possible. At its simplest, you can literally just download a large chunk of audio from an interview, and tell the finetuning to strip through it, find spoken parts and build your dataset. You can literally click 4 buttons, then copy a few files and you are done. At it's more complicated end you will clean up the audio a little beforehand, but its still only 4x buttons and copying a few files.
 #### ⚫ The audio you will use
 I would suggest that if its in an interview format, you cut out the interviewer speaking in audacity or your chosen audio editing package. You dont have to worry about being perfect with your cuts, the finetuning Step 1 will go and find spoken audio and cut it out for you. Is there is music over the spoken parts, for best quality you would cut out those parts, though its not 100% necessary. As always, try to avoid bad quality audio with noises in it (humming sounds, hiss etc). You can try something like [Audioenhancer](https://audioenhancer.ai/) to try clean up noisier audio. There is no need to down-sample any of the audio, all of that is handled for you. Just give the finetuning some good quality audio to work with. 
 #### ⚫ Important requirements CUDA 11.8
 As mentioned you must have a small portion of the Nvidia CUDA Toolkit **11.8** installed. Not higher or lower versions. Specifically **11.8**. You do not have to uninstall any other versions, change any graphics drivers, reinstall torch or anything like that. This requirement is for Step1 of Finetuning. To keep the download+install as small as possible, you will need to:
 - Download the **xxx (network)** install of the Nvidia CUDA Toolkit 11.8 from [here](https://developer.nvidia.com/cuda-11-8-0-download-archive)
 - Run the installer. At minimum, you need to [minimally] install the `nvcc` compiler and the `CUBLAS` development and runtime libraries:
  - Select **Custom Advanced** as your installation type.
  - Uncheck all the checkboxes in the list.
  - Now check the following elements:
    - `CUDA` > `Development` > `Compiler` > `nvcc`
    - `CUDA` > `Development` > `Compiler` > `Libraries` > `CUBLAS`
    - `CUDA` > `Runtime` > `Libraries` > `CUBLAS`
  - You can now proceed through the install.
 - When that has installed, open a terminal/command prompt and type `nvcc --version`. If it reports back `Cuda compilation tools, release 11.8.` you are good to go. **Specifically, 11.8**. If not continue to the next step.
 - For both Windows and Linux, you need to ensure that `nvcc` and the 11.8 cuda library files are in your environments search path. You can undo the changes below after finetuning if you prefer:
  - **Windows**: Edit the Windows `Path` environment variable and add `C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\bin`
  - **Linux**: The path may be different depending on what flavour of Linux you are running, so you may need to seek out specific instructions on the internet. Generic paths **may** be:
    - `export LD_LIBRARY_PATH=/usr/local/cuda-11.8/lib64:${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}` and
    - `export LD_LIBRARY_PATH=/usr/local/cuda-11.8/bin`
    - Add these to your '~/.bashrc' if you want this to be permanent and not something you have to set each time you open a new terminal.
 - When you have made the changes, open a **new** terminal/command prompt (in order to load the new search paths) and `nvcc --version`. It should report back `Cuda compilation tools, release 11.8.` at which point, you are good to go.
 - If it doesn't report that, check you have correctly set the search environment paths, dont have overlapping other versions of cuda paths etc.
 **Note:** Its also important that your Torch and Torchaudio have cuda installed (of any version). If you run the AllTalk diagnostics you can see your Torch and Torchaudio versions listed there. Cuda 11.8 will be listed as `cu118` and Cuda 12.1 as `cu121`. This Torch and Torchaudio is seperate to the above requirement to have the Nvidia CUDA Toolkit installed, so dont confuse the two different requirements. If you dont have Cuda installed on Torch and Torchaudio, Step 2 of Finetuning will fail.
 #### ⚫ Starting Finetuning
 **NOTE:** Please make sure you have started AllTalk at least once after updating, so that it downloads the additional files needed for finetuning. 
 1) Close all other applications that are using your GPU/VRAM and copy your audio samples into:<br><br>
   `/alltalk_tts/finetune/put-voice-samples-in-here/`
 3) In a command prompt/terminal window you need to move into your Text generation webUI folder:<br><br>
 `cd text-generation-webui`
 4) Start the Text generation webUI Python environment for your OS:<br><br>
 `cmd_windows.bat`, `./cmd_linux.sh`, `cmd_macos.sh` or `cmd_wsl.bat`
 5) You can double check your search path environment still works correctly with `nvcc --version`. It should report back 11.8:<br><br>
   `Cuda compilation tools, release 11.8.`
 7) Move into your extensions folder:<br><br>
 `cd extensions`
 8) Move into the **alltalk_tts** folder:<br><br>
 `cd alltalk_tts`
 9) Install the finetune requirements file: `pip install -r requirements_finetune.txt`
 10) Type `python finetune.py` and it should start up.
 11) Follow the on-screen instructions when the web interface starts up.
 12) When you have finished finetuning, the final tab will tell you what to do with your files and how to move your newly trained model to the correct location on disk.
 #### ⚫ Using a Finetuned model in Text-generation-webui
 At the end of the finetune process, you will have an option to `Compact and move model to /trainedmodel/` this will compact the raw training file and move it to `/model/trainedmodel/`. When AllTalk starts up within Text-generation-webui, if it finds a model in this location a new loader will appear in the interface for `XTTSv2 FT` and you can use this to load your finetuned model. <br><br>**Be careful** not to train a new model from the base model, then overwrite your current `/model/trainedmodel/` **if** you want a seperately trained model. This is why there is an `OPTION B` to move your just trained model to `/models/lastfinetuned/`.
 #### ⚫ Training one model with multiple voices
 At the end of the finetune process, you will have an option to `Compact and move model to /trainedmodel/` this will compact the raw training file and move it to `/model/trainedmodel/`. This model will become available when you start up finetuning. You will have a choice to train the Base Model or the `Existing finetuned model` (which is the one in `/model/trainedmodel/`). So you can use this to keep further training this model with additional voices, then copying it back to `/model/trainedmodel/` at the end of training.
 #### ⚫ Do I need to keep the raw training data/model?
 If you've compacted and moved your model, its highly unlikely you would want to keep that data, however the choice is there to keep it if you wish. It will be between 5-10GB in size, so most people will want to delete it.
 ## 🔵🟢🟡 DeepSpeed Installation Options
 **NOTE**: You **DO NOT** need to set Text-generation-webUI's **--deepspeed** setting for AllTalk to be able to use DeepSpeed. These are two completely separate things and incorrectly setting that on Text-generation-webUI may cause other complications.
 #### 🔵 Linux Installation
 <details>
 	<summary>Click to expand: Linux DeepSpeed installation</summary>
 ➡️DeepSpeed requires an Nvidia Graphics card!⬅️
 - #### DeepSpeed Installation for Text generation webUI
 1) Preferably use your built in package manager to install CUDA tools. Alternatively download and install the Nvidia Cuda Toolkit for Linux [Nvidia Cuda Toolkit 11.8 or 12.1](https://developer.nvidia.com/cuda-toolkit-archive)<br><br>
 2) Open a terminal console.<br><br>
 3) Install libaio-dev (however your Linux version installs things) e.g. `sudo apt install libaio-dev`<br><br>
 4) Move into your Text generation webUI folder e.g. `cd text-generation-webui`<br><br>
 5) Start the Text generation webUI Python environment `./cmd_linux.sh`<br><br>
 6) Text generation webUI **overwrites** the **CUDA_HOME** environment variable each time you `./cmd_linux.sh` or `./start_linux.sh`, so you will need to either permanently change within the python environment OR set CUDA_HOME it each time you `./cmd_linux.sh`. Details to change it each time are on the next step. Below is a link to Conda's manual and changing environment variables permanently though its possible changing it permanently could affect other extensions, you would have to test.<br> <br>
 [Conda manual - Environment variables](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html#set-env-vars)<br><br>
 7) You can temporarily set the **CUDA_HOME** environment with (Standard paths on Ubuntu, but could vary on other Linux flavours):<br><br>
 `export CUDA_HOME=/etc/alternatives/cuda`<br><br>
 **every** time you run `./cmd_linux.sh`.<br> <br>
 If you try to start DeepSpeed with the CUDA_HOME path set incorrectly, expect an error similar to `[Errno 2] No such file or directory: /home/yourname/text-generation-webui/installer_files/env/bin/nvcc`<br> <br>
 8) Now install deepspeed with pip install deepspeed<br><br>
 9) You can now start Text generation webUI `python server.py` ensuring to activate your extensions.<br><br>
 Just to reiterate, starting Text-generation-webUI with `./start_linux.sh` will overwrite the CUDA_HOME variable unless you have permanently changed it, hence always starting it with `./cmd_linux.sh` **then** setting the environment variable manually (step 7) and **then** `python server.py`, which is how you would need to run it each time, unless you permanently set the environment variable for CUDA_HOME within Text-generation-webUI's standard Python environment.
 <br><br>
 **Removal** - If it became necessary to uninstall DeepSpeed, you can do so with `./cmd_linux.sh` and then `pip uninstall deepspeed`<br><br>
 - #### DeepSpeed Installation for standalone alltalk_tts app
 1) Preferably use your built in package manager to install CUDA tools. Alternatively download and install the Nvidia Cuda Toolkit for Linux [Nvidia Cuda Toolkit 11.8 or 12.1](https://developer.nvidia.com/cuda-toolkit-archive)<br><br>
 2) Open a terminal console.<br><br>
 3) Install libaio-dev (however your Linux version installs things) e.g. `sudo apt install libaio-dev` If you are using an RPM based distribution the package will probably be named `libaio-devel`.<br><br> 
 4) Navigate to your alltalk_tts folder e.g. `cd alltext_tts`<br><br>
 5) Start the alltalk_tts Python environment `conda activate alltalkenv`<br><br>
 6) You will need to set the **CUDA_HOME** environment variable. Details to change it each time are on the next step. Below is a link to Conda's manual and changing environment variables permanently though its possible changing it permanently could affect other extensions, you would have to test.<br> <br>
 [Conda manual - Environment variables](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html#set-env-vars)<br><br>
 7) Set the environment path for CUDA_HOME e.g. `export CUDA_HOME=/usr/local/cuda-12.1/bin` or `export CUDA_HOME=/etc/alternative/cuda`.  Verify the path on your Linux distro before setting this variable.<br>
 If you try to start DeepSpeed with the CUDA_HOME path set incorrectly, expect an error similar to `[Errno 2] No such file or directory` or `CUDA_HOME does not exist`<br> <br>
 If you set the `env` variable and you receive an error of `[Errno 2] No such file or directory: '/usr/local/cuda-12.1/bin/bin/nvcc'` with a double `bin/bin` path, you can remove the env variable with `unset CUDA_HOME` and add the path to your linux PATH env variable with: `export PATH=$PATH:/usr/local/cuda-12.1/bin`. (Verify the path on your Linux distro before setting this variable.)  However if you are using other applications that use CUDA, you will want to verify that configuring the path did not break those applications. <br><br> 
 8) Now install deepspeed with `pip install deepspeed`<br><br>
 9) You can now start the alltalk_tts webUI with `python script.py`<br><br>
 <br><br>
 **Removal** - If it became necessary to uninstall DeepSpeed, you can do so by entering your `alltalkenv` enviroment `conda activate alltalkenv` and then running `pip uninstall deepspeed`<br><br>
 </details>
 #### 🟢🟡 Windows Installation
 <details>
 	<summary>Click to Expand: Windows DeepSpeed options</summary><br>
 DeepSpeed v11.2 will work on the current default text-generation-webui Python 3.11 environment! You have 2x options for how to setup DeepSpeed on Windows. A quick way (🟢Option 1) and a long way (🟡Option 2).
 Thanks to [@S95Sedan](https://github.com/S95Sedan) - They managed to get DeepSpeed 11.2 working on Windows via making some edits to the original Microsoft DeepSpeed v11.2 installation. The original post is [here](https://github.com/oobabooga/text-generation-webui/issues/4734#issuecomment-1843984142).
 #### 🟢 OPTION 1 - Quick and easy!
-#### Pre-Compiled Wheel Deepspeed v11.1 (for Windows and Python 3.11)
+<details>
-[@S95Sedan](https://github.com/S95Sedan) has kindly provided a pre-compiled DeepSpeed v11.1 wheel file, which you can download and use. To use this, you will need to:
+	<summary>Click to expand: Pre-Compiled Wheel Deepspeed v11.2 (Python 3.11 and 3.10)</summary>
 ➡️DeepSpeed requires an Nvidia Graphics card!⬅️<br>
-**Note:** In my tests, with this method you will **not** need to install the Nvidia CUDA toolkit to make this work, but AllTalk may warn you when starting DeepSpeed that it doesnt see the CUDA Toolkit, however, it works fine for TTS purposes.
+1) Download the correct wheel version for your Python/Cuda from [here](https://github.com/erew123/alltalk_tts/releases/tag/deepspeed) and save the file it inside your **text-generation-webui** folder.
 1) Download the file [deepspeed-0.11.1+e9503fe-cp311-cp311-win_amd64.whl](https://drive.google.com/file/d/1PFsf6uSPY5Cb4o9VxiZ7DLv-j35L7Y41/view?usp=sharing) by going to the link and clicking the **download** icon at the top right of the screen and save the file it inside your **text-generation-webui** folder.
 2) Open a command prompt window, move into your **text-generation-webui folder**, you can now start the Python environment for text-generation-webui:
 2) Open a command prompt window, move into your **text-generation-webui folder**, you can now start the Python environment for text-generation-webui:<br><br>
 `cmd_windows.bat`
-3) With the file that you saved in the **text-generation-webui folder** you now type the following:
+3) With the file that you saved in the **text-generation-webui folder** you now type the following, replacing YOUR-VERSION with the name of the file you have:<br><br>
 `pip install "deepspeed-0.11.2+YOUR-VERSION-win_amd64.whl"`
-`pip install "deepspeed-0.11.1+e9503fe-cp311-cp311-win_amd64.whl"`
+5) This should install through cleanly and you should now have DeepSpeed v11.2 installed within the Python 3.11/3.10 environment of text-generation-webui.
-4) This should install through cleanly and you should now have DeepSpeed v11.1 installed within the Python 3.11 environment of text-generation-webui.
+6) When you start up text-generation-webui, and AllTalk starts, you should see **[AllTalk Startup] DeepSpeed Detected**
-5) When you start up text-generation-webui, and AllTalk starts, you should see **[AllTalk Startup] DeepSpeed Detected**
+7) Within AllTalk, you will now have a checkbox for **Activate DeepSpeed** though remember you can only change **1x setting every 15 or so seconds**, so dont try to activate DeepSpeed **and** LowVRAM/Change your model simultantiously. Do one of those, wait 15-20 seconds until the change is confirmed in the terminal/command prompt, then you can change the other. When you are happy it works, you can set the default start-up settings in the settings page.
-    
+<br><br>
-6) Within AllTalk, you will now have a checkbox for **Activate DeepSpeed** though remember you can only change **1x setting every 15 or so seconds**, so dont try to activate DeepSpeed **and** LowVRAM/Change your model simultantiously. Do one of those, wait 15-20 seconds until the change is confirmed in the terminal/command prompt, then you can change the other. When you are happy it works, you can set the default start-up settings in the settings page.
+**Removal** - If it became necessary to uninstall DeepSpeed, you can do so with `cmd_windows.bat` and then `pip uninstall deepspeed`<br><br>
 </details>
 #### 🟡 OPTION 2 - A bit more complicated!
 <details>
 	<summary>Click to expand: Manual Build DeepSpeed v11.2 (Python 3.11 and 3.10)</summary>
 ➡️DeepSpeed requires an Nvidia Graphics card!⬅️<br><br>
-#### Manual Build DeepSpeed v11.2 (for Windows and Python 3.11)
+This will take about 1 hour to complete and about 6GB of disk space.<br>
 DeepSpeed Version 11.2 with CUDA 12.1 - Installation Instructions:
 1. Download the 11.2 release of [DeepSpeed](https://github.com/microsoft/DeepSpeed/releases/tag/v0.11.2) extract it to a folder. 
 2. Install Visual C++ build tools, such as [VS2019 C++ x64/x86](https://learn.microsoft.com/en-us/visualstudio/releases/2019/redistribution#vs2019-download) build tools.
-3. Download and install the [Nvidia Cuda Toolkit 12.1](https://developer.nvidia.com/cuda-12-1-0-download-archive)
+3. Download and install the [Nvidia Cuda Toolkit 11.8 or 12.1](https://developer.nvidia.com/cuda-toolkit-archive)
-4. Edit your Windows environment variables to ensure that CUDA_HOME and CUDA_PATH are set to your Nvidia Cuda Toolkit path. (The folder above the bin folder that nvcc.exe is installed in). Examples are:<br>
+4. **OPTIONAL** If you do not have an python environment already created and you are **not** going to use Text-generation-webui's environment, you can install [Miniconda](https://docs.conda.io/projects/miniconda/en/latest/miniconda-install.html), then at a command prompt, create and activate your environment with:<br><br>
 ```set CUDA_HOME=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.1```<br>
 ```set CUDA_PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.1```<br>
 5. OPTIONAL If you do not have an python environment already created, you can install [Miniconda](https://docs.conda.io/projects/miniconda/en/latest/miniconda-install.html), then at a command prompt, create and activate your environment with:<br>
 ```conda create -n pythonenv python=3.11```<br>
 ```activate pythonenv```<br>
-6. Launch the Command Prompt cmd with Administrator privilege as it requires admin to allow creating symlink folders.
+5. Launch the Command Prompt cmd with Administrator privilege as it requires admin to allow creating symlink folders.
-7. Install PyTorch, 2.1.0 with CUDA 12.1 into your Python 3.11 environment e.g:<br>
+6. If you are using the **Text-generation-webui** python environment, then in the `text-generation-webui` folder you will run `cmd_windows.bat` to start the python evnironment.<br><br>
 Otherwise Install PyTorch, 2.1.0 with CUDA 11.8 or 12.1 into your Python 3.1x.x environment e.g:<br><br>
 ```activate pythonenv``` (activate your python environment)<br>
-```conda install pytorch==2.1.0 torchvision==0.16.0 torchaudio==2.1.0 pytorch-cuda=12.1 -c pytorch -c nvidia```
+```conda install pytorch==2.1.0 torchvision==0.16.0 torchaudio==2.1.0 pytorch-cuda=12.1 -c pytorch -c nvidia```<br>
 or<br>
 ```conda install pytorch==2.1.0 torchvision==0.16.0 torchaudio==2.1.0 pytorch-cuda=11.8 -c pytorch -c nvidia```<br>
-8. In your python environment check that your CUDA_HOME and CUDA_PATH are still pointing to the correct location.<br>
+9. Set your CUDA Windows environment variables in the command prompt to ensure that CUDA_HOME and CUDA_PATH are set to your Nvidia Cuda Toolkit path. (The folder above the bin folder that nvcc.exe is installed in). Examples are:<br><br>
-```set``` (to list and check the windows environment variables. Refer to step 4 if not)
+```set CUDA_HOME=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.1```<br>
 ```set CUDA_PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.1```<br>
 or<br>
 ```set CUDA_HOME=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8```<br>
 ```set CUDA_PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8```<br>
-9. Navigate to your deepspeed folder in the Command Prompt:<br>
+10. Navigate to wherever you extracted the deepspeed folder in the Command Prompt:<br><br>
-```cd c:\deepspeed``` (wherever you extracted it to)
+```cd c:\DeepSpeed-0.11.2``` (wherever you extracted it to)
-10. Modify the following files:<br>
+11. Modify the following files:<br>
 **(These modified files are included in the git-pull of AllTalk, in the DeepSpeed Windows folder and so can just be copied over the top of the exsting folders/files, but if you want to modify them yourself, please follow the below)**<br>
-**(These modified files are included in the git-pull of AllTalk, but if you want to modify them yourself, please follow the below)**
+deepspeed-0.11.2/build_win.bat - at the top of the file, add:<br><br>
 deepspeed-0.11.2/build_win.bat** - at the top of the file, add:<br>
 ```set DS_BUILD_EVOFORMER_ATTN=0```
 deepspeed-0.11.2/csrc/quantization/pt_binding.cpp - lines 244-250 - change to:
@@ -197,7 +636,268 @@ def get_shm_size():
        return "UNKNOWN", [f"Error getting shared memory size: {e}"]
 ```
-11. While still in your command line with python environment enabled run:<br>
+10. While still in your command line with python environment enabled run:<br>
-```build_win.bat```
+```build_win.bat``` and wait 10-20 minutes.
-12. Now cd dist to go into your dist folder and you can now pip install deepspeed-YOURFILENAME.whl (or whatever your WHL file is called).
+11. Now `cd dist` to go into your dist folder and you can now `pip install deepspeed-YOURFILENAME.whl` (or whatever your WHL file is called).
 <br><br>
 **Removal** - If it became necessary to uninstall DeepSpeed, you can do so with `cmd_windows.bat` and then `pip uninstall deepspeed`<br><br>
 </details>
 </details>
 ## ⬜ AllTalk TTS Generator
 AllTalk TTS Generator is the solution for converting large volumes of text into speech using the voice of your choice. Whether you're creating audio content or just want to hear text read aloud, the TTS Generator is equipped to handle it all efficiently. Please see here for a quick [demo](https://www.youtube.com/watch?v=hunvXn0mLzc)<br><br>The link to open the TTS generator can be found on the built-in Settings and Documentation page.<br><br>**DeepSpeed** is **highly** recommended to speed up generation. **Low VRAM** would be best turned off and your LLM model unloaded from your GPU VRAM (unload your model). **No Playback** will reduce memory overhead on very large generations (15,000 words or more). Splitting **Export to Wav** into smaller groups will also reduce memory overhead at the point of exporting your wav files (so good for low memory systems). 
 #### ⬜ Estimated Throughput
 This will vary by system for a multitude of reasons, however, while generating a 58,000 word document to TTS, with DeepSpeed enabled, LowVram disabled, splitting size 2 and on an Nvidia RTX 4070, throughput was around 1,000 words per minute. Meaning, this took 1 hour to generate the TTS. Exporting to combined wavs took about 2-3 minutes total.
 #### ⬜ Quick Start
 - **Text Input:** Enter the text you wish to convert into speech in the 'Text Input' box.
 - **Generate TTS:** Hit this to start the text-to-speech conversion.
 - **Pause/Resume:** Used to pause and resume the playback of the initial generation of wavs or the stream.
 - **Stop Playback:** This will stop the current audio playing back. It does not stop the text from being generated however. 
 Once you have sent text off to be generated, either as a stream or wav file generation, the TTS server will remain busy until this process has competed. As such, think carefully as to how much you want to send to the server. 
 If you are generating wav files and populating the queue, you can generate one lot of text to speech, then input your next lot of text and it will continue adding to the list.
 #### ⬜ TTS Generation Modes
 - **Wav Chunks:** Perfect for creating audio books, or anything you want to keep long term. Breaks down your text into manageable wav files and queues them up. Generation begins automatically, and playback will start after a few chunks have been prepared ahead. You can set the volume to 0 if you don’t want to hear playback. With Wav chunks, you can edit and/or regenerate portions of the TTS as needed.
 - **Streaming:** For immediate playback without the ability to save. Ideal for on-the-fly speech generation and listening. This will not generate wav files and it will play back through your browser. You cannot stop the server generating the TTS once it has been sent.<br><br>
 With wav chunks you can either playback “In Browser” which is the web page you are on, or “On Server” which is through the console/terminal where AllTalk is running from, or "No Playback". Only generation “In Browser” can play back smoothly and populate the Generated TTS List. Setting the Volume will affect the volume level played back both “In Browser” and “On Server”.<br><br>
 For generating **large amounts of TTS**, it's recommended to select the **No Playback** option. This setting minimizes the memory usage in your web browser by avoiding the loading and playing of audio files directly within the browser, which is particularly beneficial for handling extensive audio generations. The definition of large will vary depending on your system RAM availability (will update when I have more information as to guidelines). Once the audio is generated, you can export your list to JSON (for safety) and use the **Play List** option to play back your audio.
 #### ⬜ Playback and List Management
 - **Playback Controls:** Utilize 'Play List' to start from the beginning or 'Stop Playback' to halt at any time.
 - **Custom Start:** Jump into your list at a specific ID to hear a particular section.
 - **Regeneration and Editing:** If a chunk isn't quite right, you can opt to regenerate it or edit the text directly. Click off the text to save changes and hit regenerate for the specific line.
 - **Export/Import List:** Save your TTS list as a JSON file or import one. Note: Existing wav files are needed for playback. Exporting is handy if you want to take your files away into another program and have a list of which wav is which, or if you keep your audio files, but want to come back at a later date, edit one or two lines, regenerate the speech and re-combine the wav’s into one new long wav.
 #### ⬜ Exporting Your Audio
 - **Export to WAV:** Combine all generated TTS from the list, into one single WAV file for easy download and distribution. Its always recommended to export your list to a JSON before exporting, so that you have a backup, should something go wrong. You can simply re-import the list and try exporting again.<br><br>When exporting, there is a file size limit of 1GB and as such you have the option to choose how many files to include in each block of audio exported. 600 is just on the limit of 1GB, depending on the average file size, so 500 or less is a good amount to work with. You can combine the generated files after if you wish, in Audacity or similar.<br><br>Additionally, lower export batches will lower the memory requirements, so if your system is low on memory (maybe 8 or 16GB system), you can use smaller export batches to keep the memory requirement down.
 #### ⬜ Customization and Preferences
 - **Character Voice:** Choose the voice that will read your text.
 - **Language:** Select the language of your text.
 - **Chunk Sizes:** Decide the size of text chunks for generation. Smaller sizes are recommended for better TTS quality.
 #### ⬜ Interface and Accessibility
 - **Dark/Light Mode:** Switch between themes for your visual comfort.
 - **Word Count and Generation Queue:** Keep track of the word count and the generation progress.
 #### ⬜ Notes on Usage
 - For seamless TTS generation, it's advised to keep text chunks under 250 characters, which you can control with the Chunk sizes.
 - Generated audio can be played back from the list, which also highlights the currently playing chunk.
 - The TTS Generator remembers your settings, so you can pick up where you left off even after refreshing the page.
 ## 🟠 API Suite and JSON-CURL
 ### 🟠Overview
 The Text-to-Speech (TTS) Generation API allows you to generate speech from text input using various configuration options. This API supports both character and narrator voices, providing flexibility for creating dynamic and engaging audio content.
 #### 🟠 Ready Endpoint<br>
 Check if the Text-to-Speech (TTS) service is ready to accept requests.
 - URL: `http://127.0.0.1:7851/api/ready`<br> - Method: `GET`<br> 
   `curl -X GET "http://127.0.0.1:7851/api/ready"`
  Response: `Ready`
 #### 🟠 Voices List Endpoint<br>
 Retrieve a list of available voices for generating speech.
 - URL: `http://127.0.0.1:7851/api/voices`<br> - Method: `GET`<br>
   `curl -X GET "http://127.0.0.1:7851/api/voices"`
   JSON return: `{"voices": ["voice1.wav", "voice2.wav", "voice3.wav"]}`
 #### 🟠 Current Settings Endpoint<br>
 Retrieve a list of available voices for generating speech.
 - URL: `http://127.0.0.1:7851/api/currentsettings`<br> - Method: `GET`<br>
   `curl -X GET "http://127.0.0.1:7851/api/currentsettings"`
   JSON return: ```{"models_available":[{"name":"Coqui","model_name":"API TTS"},{"name":"Coqui","model_name":"API Local"},{"name":"Coqui","model_name":"XTTSv2 Local"}],"current_model_loaded":"XTTSv2 Local","deepspeed_available":true,"deepspeed_status":true,"low_vram_status":true,"finetuned_model":false}```
  `name & model_name` = listing the currently available models.<br>
  `current_model_loaded` = what model is currently loaded into VRAM.<br>
  `deepspeed_available` = was DeepSpeed detected on startup and available to be activated.<br>
  `deepspeed_status` = If DeepSpeed was detected, is it currently activated.<br>
  `low_vram_status` = Is Low VRAM currently enabled.<br>
  `finetuned_model` = Was a finetuned model detected. (XTTSv2 FT).<br>
 #### 🟠 Preview Voice Endpoint
 Generate a preview of a specified voice with hardcoded settings.
 - URL: `http://127.0.0.1:7851/api/previewvoice/`<br> - Method: `POST`<br> - Content-Type: `application/x-www-form-urlencoded`<br>
   `curl -X POST "http://127.0.0.1:7851/api/previewvoice/" -F "voice=female_01.wav"`
   Replace `female_01.wav` with the name of the voice sample you want to hear.
   JSON return: `{"status": "generate-success", "output_file_path": "/path/to/outputs/api_preview_voice.wav", "output_file_url": "http://127.0.0.1:7851/audio/api_preview_voice.wav"}`
 #### 🟠 Switching Model Endpoint<br>
 - URL: `http://127.0.0.1:7851/api/reload`<br> - Method: `POST`<br><br>
   `curl -X POST "http://127.0.0.1:7851/api/reload?tts_method=API%20Local"`<br>
   `curl -X POST "http://127.0.0.1:7851/api/reload?tts_method=API%20TTS"`<br>
   `curl -X POST "http://127.0.0.1:7851/api/reload?tts_method=XTTSv2%20Local"`<br>
   Switch between the 3 models respectively.
   `curl -X POST "http://127.0.0.1:7851/api/reload?tts_method=XTTSv2%20FT"`<br>
   If you have a finetuned model in `/models/trainedmodel/` (will error otherwise)
   JSON return `{"status": "model-success"}`
 #### 🟠 Switch DeepSpeed Endpoint<br>
 - URL: `http://127.0.0.1:7851/api/deepspeed`<br> - Method: `POST`<br><br>
   `curl -X POST "http://127.0.0.1:7851/api/deepspeed?new_deepspeed_value=True"`
   Replace True with False to disable DeepSpeed mode.
   JSON return `{"status": "deepspeed-success"}`
 #### 🟠 Switching Low VRAM Endpoint<br>
 - URL: `http://127.0.0.1:7851/api/lowvramsetting`<br> - Method: `POST`<br><br>
   `curl -X POST "http://127.0.0.1:7851/api/lowvramsetting?new_low_vram_value=True"`
   Replace True with False to disable Low VRAM mode.
   JSON return `{"status": "lowvram-success"}`
 ### 🟠 TTS Generation Endpoint (Standard Generation)
 - URL: `http://127.0.0.1:7851/api/tts-generate`<br> - Method: `POST`<br> - Content-Type: `application/x-www-form-urlencoded`<br>
 ### 🟠 Example command lines (Standard Generation)
 Standard TTS generation supports Narration and will generate a wav file/blob. Standard TTS speech Example (standard text) generating a time-stamped file<br>
 `curl -X POST "http://127.0.0.1:7851/api/tts-generate" -d "text_input=All of this is text spoken by the character. This is text not inside quotes, though that doesnt matter in the slightest" -d "text_filtering=standard" -d "character_voice_gen=female_01.wav" -d "narrator_enabled=false" -d "narrator_voice_gen=male_01.wav" -d "text_not_inside=character" -d "language=en" -d "output_file_name=myoutputfile" -d "output_file_timestamp=true" -d "autoplay=true" -d "autoplay_volume=0.8"`<br>
 Narrator Example (standard text) generating a time-stamped file
 `curl -X POST "http://127.0.0.1:7851/api/tts-generate" -d "text_input=*This is text spoken by the narrator* \"This is text spoken by the character\". This is text not inside quotes." -d "text_filtering=standard" -d "character_voice_gen=female_01.wav" -d "narrator_enabled=true" -d "narrator_voice_gen=male_01.wav" -d "text_not_inside=character" -d "language=en" -d "output_file_name=myoutputfile" -d "output_file_timestamp=true" -d "autoplay=true" -d "autoplay_volume=0.8"`<br>
 Note that if your text that needs to be generated contains double quotes you will need to escape them with `\"` (Please see the narrator example).
 ### 🟠 Request Parameters
 🟠 **text_input**: The text you want the TTS engine to produce. Use escaped double quotes for character speech and asterisks for narrator speech if using the narrator function. Example:
 `-d "text_input=*This is text spoken by the narrator* \"This is text spoken by the character\". This is text not inside quotes."`
 🟠 **text_filtering**: Filter for text. Options:
 - **none** No filtering. Whatever is sent will go over to the TTS engine as raw text, which may result in some odd sounds with some special characters.<br>
 - **standard** Human-readable text and a basic level of filtering, just to clean up some special characters.<br>
 - **html** HTML content. Where you are using HTML entity's like &quot;<br>
 `-d "text_filtering=none"`<br>
 `-d "text_filtering=standard"`<br>
 `-d "text_filtering=html"`<br>
 Example:
 - **Standard Example**: `*This is text spoken by the narrator* "This is text spoken by the character" This is text not inside quotes.`<br>
 - **HTML Example**: `&ast;This is text spoken by the narrator&ast; &quot;This is text spoken by the character&quot; This is text not inside quotes.`<br>
 - **None**: `Will just pass whatever characters/text you send at it.`<br>
 🟠 **character_voice_gen**: The WAV file name for the character's voice.<br>
 `-d "character_voice_gen=female_01.wav"`
 🟠 **narrator_enabled**: Enable or disable the narrator function. If true, minimum text filtering is set to standard. Anything between double quotes is considered the character's speech, and anything between asterisks is considered the narrator's speech.
 `-d "narrator_enabled=true"`<br>
 `-d "narrator_enabled=false"` 
 🟠 **narrator_voice_gen**: The WAV file name for the narrator's voice.
 `-d "narrator_voice_gen=male_01.wav"`
 🟠 **text_not_inside**: Specify the handling of lines not inside double quotes or asterisks, for the narrator feature. Options:
 - **character**: Treat as character speech.<br>
 - **narrator**: Treat as narrator speech.<br>
 `-d "text_not_inside=character"`<br>
 `-d "text_not_inside=narrator"`
 🟠 **language**: Choose the language for TTS. Options:
 `ar` Arabic<br>
 `zh-cn` Chinese (Simplified)<br>
 `cs` Czech<br>
 `nl` Dutch<br>
 `en` English<br>
 `fr` French<br>
 `de` German<br>
 `hu` Hungarian<br>
 `it` Italian<br>
 `ja` Japanese<br>
 `ko` Korean<br>
 `pl` Polish<br>
 `pt` Portuguese<br>
 `ru` Russian<br>
 `es` Spanish<br>
 `tr` Turkish<br>
 `-d "language=en"`<br>
 🟠 **output_file_name**: The name of the output file (excluding the .wav extension).
 `-d "output_file_name=myoutputfile"`<br>
 🟠 **output_file_timestamp**: Add a timestamp to the output file name. If true, each file will have a unique timestamp; otherwise, the same file name will be overwritten each time you generate TTS.
 `-d "output_file_timestamp=true"`<br>
 `-d "output_file_timestamp=false"`
 🟠 **autoplay**: Enable or disable playing the generated TTS to your standard sound output device at time of TTS generation.
 `-d "autoplay=true"`<br>
 `-d "autoplay=false"`
 🟠 **autoplay_volume**: Set the autoplay volume. Should be between 0.1 and 1.0. Needs to be specified in the JSON request even if autoplay is false.
 `-d "autoplay_volume=0.8"`
 ### 🟠 TTS Generation Response
 The API returns a JSON object with the following properties:
 - **status** Indicates whether the generation was successful (generate-success) or failed (generate-failure).<br>
 - **output_file_path** The on-disk location of the generated WAV file.<br>
 - **output_file_url** The HTTP location for accessing the generated WAV file for browser playback.<br>
 - **output_cache_url** The HTTP location for accessing the generated WAV file as a pushed download.<br>
 Example JSON TTS Generation Response:
 `{"status":"generate-success","output_file_path":"C:\\text-generation-webui\\extensions\\alltalk_tts\\outputs\\myoutputfile_1704141936.wav","output_file_url":"http://127.0.0.1:7851/audio/myoutputfile_1704141936.wav","output_cache_url":"http://127.0.0.1:7851/audiocache/myoutputfile_1704141936.wav"}`
 ### 🟠 Example command lines (Streaming Generation)
 Streaming TTS generation does NOT support Narration and will generate an audio stream. Streaming TTS speech JavaScript Example:<br>
 - URL: `http://localhost:7851/api/tts-generate-streaming`<br> - Method: `POST`<br> - Content-Type: `application/x-www-form-urlencoded`<br><br>
 ```
 // Example parameters
 const text = "Here is some text";
 const voice = "female_01.wav";
 const language = "en";
 const outputFile = "stream_output.wav";
 // Encode the text for URL
 const encodedText = encodeURIComponent(text);
 // Create the streaming URL
 const streamingUrl = `http://localhost:7851/api/tts-generate-streaming?text=${encodedText}&voice=${voice}&language=${language}&output_file=${outputFile}`;
 // Create and play the audio element
 const audioElement = new Audio(streamingUrl);
 audioElement.play(); // Play the audio stream directly
 ```
 - **Text (text):** This is the actual text you want to convert to speech. It should be a string and must be URL-encoded to ensure that special characters (like spaces and punctuation) are correctly transmitted in the URL. Example: `Hello World` becomes `Hello%20World` when URL-encoded.<br>
 - **Voice (voice):** This parameter specifies the voice type to be used for the TTS. The value should match one of the available voice options in AllTalks voices folder. This is a string representing the file, like `female_01.wav`.<br>
 - **Language (language):** This setting determines the language in which the text should be spoken. A two-letter language code (like `en` for English, `fr` for French, etc.).<br>
 - **Output File (output_file):** This parameter names the output file where the audio will be streamed. It should be a string representing the file name, such as `stream_output.wav`. AllTalk will not save this as a file in its outputs folder.<br>
 <br>
 ### 🔴 Future to-do list
 - Possibly add some additional TTS engines (TBD).
 - Tagging support within text.
 - Have a break!
@@ -0,0 +1,503 @@
@echo off
 cd /D "%~dp0"
 set PATH=%PATH%;%SystemRoot%\system32
 :: Generate the ESC character
 for /F %%a in ('echo prompt $E ^| cmd') do set "ESC=%%a"
 :: Standard Colors
 set "BLACK=%ESC%[30m"
 set "RED=%ESC%[31m"
 set "GREEN=%ESC%[32m"
 set "YELLOW=%ESC%[33m"
 set "BLUE=%ESC%[34m"
 set "MAGENTA=%ESC%[35m"
 set "CYAN=%ESC%[36m"
 set "WHITE=%ESC%[37m"
 set "L_BLACK=%ESC%[90m"
 set "L_RED=%ESC%[91m"
 set "L_GREEN=%ESC%[92m"
 set "L_YELLOW=%ESC%[93m"
 set "L_BLUE=%ESC%[94m"
 set "L_MAGENTA=%ESC%[95m"
 set "L_CYAN=%ESC%[96m"
 set "L_WHITE=%ESC%[97m"
 set "RESET=%ESC%[0m"
@rem Check if curl is available
 curl --version >nul 2>&1
 if "%ERRORLEVEL%" NEQ "0" (
    echo curl is not available on this system. Please install curl then re-run the script https://curl.se/ 
 	echo or perform a manual installation of a Conda Python environment.
    goto end
 )
 :MainMenu
 cls
 echo.
 echo    %L_BLUE%ALLTALK WINDOWS SETUP UTILITY%RESET%
 echo.
 echo    INSTALLATION TYPE
 echo    1) I am using AllTalk as part of %L_GREEN%Text-generation-webui%RESET%
 echo    2) I am using AllTalk as a %L_GREEN%Standalone Application%RESET%
 echo.
 echo    9) %L_RED%Exit/Quit%RESET%
 echo.
 set /p UserOption="    Enter your choice: "
 if "%UserOption%"=="1" goto WebUIMenu
 if "%UserOption%"=="2" goto StandaloneMenu
 if "%UserOption%"=="9" goto End
 goto MainMenu
 :WebUIMenu
 cls
 echo.
 echo    %L_BLUE%TEXT-GENERATION-WEBUI SETUP%RESET%
 echo.
 echo    Please ensure you have started your Text-generation-webui Python 
 echo    environment. If you have NOT done this, please run %L_GREEN%cmd_windows.bat%RESET% 
 echo    in the %L_GREEN%text-generation-webui%RESET% folder and then re-run this script.
 echo.
 echo    BASE REQUIREMENTS
 echo    1) Install the requirements for a %L_GREEN%Nvidia machine%RESET%.
 echo    2) Install the requirements for a %L_GREEN%AMD or MAC machine%RESET%.
 echo.
 echo    OPTIONAL
 echo    3) Install the Finetuning requirements.
 echo    4) Install DeepSpeed v11.2 for CUDA %L_GREEN%11.8%RESET% and Python-3.11.x.
 echo    5) Install DeepSpeed v11.2 for CUDA %L_GREEN%12.1%RESET% and Python-3.11.x.
 echo    6) Uninstall DeepSpeed.
 echo.
 echo.   OTHER
 echo    7) Generate a diagnostics file.
 echo.
 echo    9) %L_RED%Exit/Quit%RESET%
 echo.
 set /p WebUIOption="Enter your choice: "
 if "%WebUIOption%"=="1" goto InstallNvidiaTextGen
 if "%WebUIOption%"=="2" goto InstallOtherTextGen
 if "%WebUIOption%"=="3" goto InstallFinetuneTextGen
 if "%WebUIOption%"=="4" goto InstallDeepSpeed118TextGen
 if "%WebUIOption%"=="5" goto InstallDeepSpeed121TextGen
 if "%WebUIOption%"=="6" goto UnInstallDeepSpeed
 if "%WebUIOption%"=="7" goto GenerateDiagsTextGen
 if "%WebUIOption%"=="9" goto End
 goto WebUIMenu
 :StandaloneMenu
 cls
 echo.
 echo    %L_BLUE%ALLTALK STANDALONE APPLICATION SETUP%RESET%
 echo.
 echo    BASE REQUIREMENTS
 echo    1) Install AllTalk as a Standalone Application
 echo.
 echo    OPTIONAL
 echo    2) Delete AllTalk's custom Python environment
 echo    3) Install the Finetuning requirements
 echo.
 echo.   OTHER
 echo    4) Generate a diagnostics file
 echo.
 echo    9) %L_RED%Exit/Quit%RESET%
 echo.
 set /p StandaloneOption="Enter your choice: "
 if "%StandaloneOption%"=="1" goto InstallCustomStandalone
 if "%StandaloneOption%"=="2" goto DeleteCustomStandalone
 if "%StandaloneOption%"=="3" goto InstallFinetuneStandalone
 if "%StandaloneOption%"=="4" goto GenerateDiagsStandalone
 if "%StandaloneOption%"=="9" goto End
 goto StandaloneMenu
 :InstallNvidiaTextGen
 pip install -r requirements_nvidia.txt
 if %ERRORLEVEL% neq 0 (
    echo.
    echo    There was an error installing the Nvidia requirements.
    echo    Press any key to return to the menu.
    echo.
    pause
    goto WebUIMenu
 )
 Echo.
 echo.
 Echo    Nvidia machine requirements installed successfully.
 Echo. 
 pause
 goto WebUIMenu
 :InstallOtherTextGen
 pip install -r requirements_other.txt
 if %ERRORLEVEL% neq 0 (
    echo. 
    echo    There was an error installing the Other requirements.
    echo    Press any key to return to the menu.
    echo.
    pause
    goto WebUIMenu
 )
 Echo.
 echo.
 Echo    Other machine requirements installed successfully.
 Echo. 
 pause
 goto WebUIMenu
 :InstallFinetuneTextGen
 pip install -r requirements_finetune.txt
 if %ERRORLEVEL% neq 0 (
    echo.
    echo    There was an error installing the Finetune requirements.
    echo    Press any key to return to the menu.
    echo.
    pause
    goto WebUIMenu
 )
 Echo.
 Echo    Finetune requirements installed successfully. Please ensure you have installed CUDA 11.8.
 Echo    Finetune needs access to %L_GREEN%cublas64_11.dll%RESET% and will error if this is not setup correctly.
 Echo    Please see here for details %L_GREEN%https://github.com/erew123/alltalk_tts#-finetuning-a-model%RESET%
 Echo.
 pause
 goto WebUIMenu
 :InstallDeepSpeed118TextGen
 echo Downloading DeepSpeed...
 curl -LO https://github.com/erew123/alltalk_tts/releases/download/deepspeed/deepspeed-0.11.2+cuda118-cp311-cp311-win_amd64.whl
 if %ERRORLEVEL% neq 0 (
    echo.
    echo    Failed to download DeepSpeed wheel file.
    echo    Please check your internet connection or try again later.
    echo    Press any key to return to the menu.
    echo.
    pause
    goto WebUIMenu
 )
 echo DeepSpeed wheel file downloaded successfully.
 echo Installing DeepSpeed...
 pip install deepspeed-0.11.2+cuda118-cp311-cp311-win_amd64.whl
 if %ERRORLEVEL% neq 0 (
    echo. 
    echo    Failed to install DeepSpeed.
    echo    Please check if the wheel file is compatible with your system.
    echo    Press any key to return to the menu.
    echo.
    pause
    goto WebUIMenu
 )
 Echo.
 echo.
 Echo    DeepSpeed installed successfully.
 Echo. 
 del deepspeed-0.11.2+cuda118-cp311-cp311-win_amd64.whl
 pause
 goto WebUIMenu
 :InstallDeepSpeed121TextGen
 echo Downloading DeepSpeed...
 curl -LO https://github.com/erew123/alltalk_tts/releases/download/deepspeed/deepspeed-0.11.2+cuda121-cp311-cp311-win_amd64.whl
 if %ERRORLEVEL% neq 0 (
    echo.
    echo    Failed to download DeepSpeed wheel file.
    echo    Please check your internet connection or try again later.
    echo    Press any key to return to the menu.
    echo.
    pause
    goto WebUIMenu
 )
 echo    DeepSpeed wheel file downloaded successfully.
 echo    Installing DeepSpeed...
 pip install deepspeed-0.11.2+cuda121-cp311-cp311-win_amd64.whl
 if %ERRORLEVEL% neq 0 (
    echo. 
    echo    Failed to install DeepSpeed.
    echo    Please check if the wheel file is compatible with your system.
    echo    Press any key to return to the menu.
    echo.
    pause
    goto WebUIMenu
 )
 Echo.
 echo.
 Echo    DeepSpeed installed successfully.
 Echo. 
 del deepspeed-0.11.2+cuda121-cp311-cp311-win_amd64.whl
 pause
 goto WebUIMenu
 :UnInstallDeepSpeed
 pip uninstall deepspeed
 if %ERRORLEVEL% neq 0 (
    echo. 
    echo    There was an error uninstalling DeepSpeed.
    echo    Press any key to return to the menu.
    echo.
    pause
    goto WebUIMenu
 )
 echo.
 Echo    DeepSpeed uninstalled successfully.
 Echo. 
 pause
 goto WebUIMenu
 :GenerateDiagsTextGen
 Python diagnostics.py
 if %ERRORLEVEL% neq 0 (
    echo.
    echo    There was an error running diagnostics. Have you correctly started your 
    echo    Text-generation-webui Python environment with %L_GREEN%cmd_windows.bat%RESET%?
    echo.
    pause
    goto WebUIMenu
 )
 Echo.
 echo.
 Echo    Diagnostics.log generated. Please scroll up to look over the log.
 Echo. 
 pause
 goto WebUIMenu
 :InstallCustomStandalone
 set PATH=%PATH%;%SystemRoot%\system32
@rem Check if curl is available
 curl --version >nul 2>&1
 if "%ERRORLEVEL%" NEQ "0" (
    echo curl is not available on this system. Please install curl then re-run the script https://curl.se/ 
 	echo or perform a manual installation of a Conda Python environment.
    goto end
 )
 echo "%CD%"| findstr /C:" " >nul && echo This script relies on Miniconda which can not be silently installed under a path with spaces. Please correct your folder names and re-try installation. && goto exit
@rem Check for special characters in installation path
 set "SPCHARMESSAGE=WARNING: Special characters were detected in the installation path! This can cause the installation to fail!"
 echo "%CD%"| findstr /R /C:"[!#\$%&()\*+,;<=>?@\[\]\^`{|}~]" >nul && (
    call :PrintBigMessage %SPCHARMESSAGE%
 )
 set SPCHARMESSAGE=
@rem fix failed install when installing to a separate drive
 set TMP=%cd%\alltalk_environment
 set TEMP=%cd%\alltalk_environment
@rem deactivate existing conda envs as needed to avoid conflicts
 (call conda deactivate && call conda deactivate && call conda deactivate) 2>nul
@rem config
 set INSTALL_DIR=%cd%\alltalk_environment
 set CONDA_ROOT_PREFIX=%cd%\alltalk_environment\conda
 set INSTALL_ENV_DIR=%cd%\alltalk_environment\env
 set MINICONDA_DOWNLOAD_URL=https://repo.anaconda.com/miniconda/Miniconda3-py310_23.3.1-0-Windows-x86_64.exe
 set conda_exists=F
@rem figure out whether git and conda need to be installed
 call "%CONDA_ROOT_PREFIX%\_conda.exe" --version >nul 2>&1
 if "%ERRORLEVEL%" EQU "0" (
    set conda_exists=T
    call "%CONDA_ROOT_PREFIX%\condabin\conda.bat" activate "%INSTALL_ENV_DIR%"
    goto RunScript
 )
@rem download and install conda if not installed
 echo Downloading Miniconda from %MINICONDA_DOWNLOAD_URL% to %INSTALL_DIR%\miniconda_installer.exe
 mkdir "%INSTALL_DIR%"
 call curl -Lk "%MINICONDA_DOWNLOAD_URL%" > "%INSTALL_DIR%\miniconda_installer.exe" || ( echo. && echo Miniconda failed to download. && goto end )
 echo Installing Miniconda to %CONDA_ROOT_PREFIX%
 start /wait "" "%INSTALL_DIR%\miniconda_installer.exe" /InstallationType=JustMe /NoShortcuts=1 /AddToPath=0 /RegisterPython=0 /NoRegistry=1 /S /D=%CONDA_ROOT_PREFIX%
 echo Miniconda version:
 call "%CONDA_ROOT_PREFIX%\_conda.exe" --version || ( echo. && echo Miniconda not found. && goto end )
@rem create the installer env
 echo Packages to install: %PACKAGES_TO_INSTALL%
 call "%CONDA_ROOT_PREFIX%\_conda.exe" create --no-shortcuts -y -k --prefix "%INSTALL_ENV_DIR%" python=3.11 || ( echo. && echo Conda environment creation failed. && goto end )
@rem check if conda environment was actually created
 if not exist "%INSTALL_ENV_DIR%\python.exe" ( echo. && echo Conda environment is empty. && goto end )
@rem activate installer env
 call "%CONDA_ROOT_PREFIX%\condabin\conda.bat" activate "%INSTALL_ENV_DIR%" || ( echo. && echo Miniconda hook not found. && goto end )
@rem Ask user for the type of requirements to install
 echo.
 echo    %L_BLUE%Choose the type of requirements to install%RESET%
 echo.
 echo    1. Nvidia graphics card machines
 echo    2. Other machines (mac, amd, etc)
 echo.
 set /p UserChoice="Enter your choice (1 or 2): "
@rem Install requirements based on user choice
 if "%UserChoice%" == "1" (
    echo.
    echo Installing Nvidia requirements...
    echo Downloading Pytorch with CUDA..
    pip install torch==2.1.0 torchvision==0.16.0 torchaudio==2.1.0 --upgrade --force-reinstall --index-url https://download.pytorch.org/whl/cu121
    pip install numpy==1.24.4
    pip install typing-extensions>=4.8.0
    pip install networkx<3.0.0,>=2.5.0
    pip install fsspec>=2023.6.0
    pip install soundfile==0.12.1
    pip install uvicorn==0.24.0.post1
    pip install TTS==0.21.3
    pip install fastapi==0.104.1
    pip install Jinja2==3.1.2
    pip install requests==2.31.0
    pip install tqdm==4.66.1
    pip install importlib-metadata==4.8.1
    pip install packaging==23.2
    pip install pydantic==1.10.13
    pip install sounddevice==0.4.6
    pip install python-multipart==0.0.6
    echo Downloading DeepSpeed...
    curl -LO https://github.com/erew123/alltalk_tts/releases/download/DeepSpeed-12.7/deepspeed-0.12.7+d058d4b-cp311-cp311-win_amd64.whl
    echo Installing DeepSpeed...
    pip install deepspeed-0.12.7+d058d4b-cp311-cp311-win_amd64.whl
    del deepspeed-0.12.7+d058d4b-cp311-cp311-win_amd64.whl
 ) else (
    echo Installing requirements for other machines...
    pip install -r requirements_other.txt
 )
@rem Create start_environment.bat to run AllTalk environment
 echo @echo off > start_environment.bat
 echo cd /D "%~dp0" >> start_environment.bat
 echo set CONDA_ROOT_PREFIX=%cd%\alltalk_environment\conda >> start_environment.bat
 echo set INSTALL_ENV_DIR=%cd%\alltalk_environment\env >> start_environment.bat
 echo call "%CONDA_ROOT_PREFIX%\condabin\conda.bat" activate "%INSTALL_ENV_DIR%" >> start_environment.bat
 echo exit >> start_environment.bat
@rem Create start_alltalk.bat to run AllTalk
 echo @echo off > start_alltalk.bat
 echo cd /D "%~dp0" >> start_alltalk.bat
 echo set CONDA_ROOT_PREFIX=%cd%\alltalk_environment\conda >> start_alltalk.bat
 echo set INSTALL_ENV_DIR=%cd%\alltalk_environment\env >> start_alltalk.bat
 echo call "%CONDA_ROOT_PREFIX%\condabin\conda.bat" activate "%INSTALL_ENV_DIR%" >> start_alltalk.bat
 echo call python script.py >> start_alltalk.bat
 echo exit >> start_alltalk.bat
 Echo.
 Echo    start_alltalk.bat has been created.
 Echo    You can now start AllTalk with %L_YELLOW%start_alltalk.bat%RESET%
 Echo.
 pause
 goto StandaloneMenu
 :DeleteCustomStandalone
@rem Check if the alltalk_environment directory exists
 if not exist "%cd%\alltalk_environment\" (
    echo.
    echo    %L_GREEN%alltalk_environment%RESET% directory does not exist. No need to delete.
    echo.
    pause
    goto StandaloneMenu
 )
@rem Check if a Conda environment is active
 if not defined CONDA_PREFIX goto NoCondaEnvDeleteCustomStandalone
@rem Deactivate Conda environment if it's active
 Echo    Exiting the Conda Environment. Please run %L_GREEN%atsetup.bat%RESET% again and delete the environment.
 conda deactivate
 :NoCondaEnvDeleteCustomStandalone
 echo Deleting "alltalk_environment". Please wait.
 rd /s /q "alltalk_environment"
 del start_alltalk.bat
 del start_environment.bat
 if %ERRORLEVEL% neq 0 (
    echo.
    echo    Failed to delete alltalk_environment folder.
    echo    Please make sure it is not in use and try again.
    echo.
    pause
    goto StandaloneMenu
 )
 echo.
 Echo.
 echo    Environment %L_GREEN%alltalk_environment%RESET% deleted. Please set up the environment again.
 Echo.
 pause
 goto StandaloneMenu
 :InstallFinetuneStandalone
 cd /D "%~dp0"
 set CONDA_ROOT_PREFIX=%cd%\alltalk_environment\conda
 set INSTALL_ENV_DIR=%cd%\alltalk_environment\env
@rem Check if the Conda environment exists
 if not exist "%INSTALL_ENV_DIR%\python.exe" (
    echo.
    echo    The Conda environment at "%INSTALL_ENV_DIR%" does not exist.
    echo    Please install the environment before proceeding.
    echo.
    pause
    goto StandaloneMenu
 )
@rem Attempt to activate the Conda environment
 call "%CONDA_ROOT_PREFIX%\condabin\conda.bat" activate "%INSTALL_ENV_DIR%"
 if errorlevel 1 (
    echo. 
    echo    Failed to activate the Conda environment.
    echo    Please check your installation and try again.
    echo.
    pause
    goto StandaloneMenu
 )
@rem Proceed with installing requirements
 pip install -r requirements_finetune.txt
 if %ERRORLEVEL% neq 0 (
    echo. 
    echo    There was an error installing the Finetune requirements.
    echo    Press any key to return to the menu.
    echo.
    pause
    goto StandaloneMenu
 )
 Echo.
 Echo    Finetune requirements installed successfully. Please ensure you have installed CUDA 11.8.
 Echo    Finetune needs access to %L_GREEN%cublas64_11.dll%RESET% and will error if this is not setup correctly.
 Echo    Please see here for details %L_GREEN%https://github.com/erew123/alltalk_tts#-finetuning-a-model%RESET%
 Echo.
 pause
 goto StandaloneMenu
 :GenerateDiagsStandalone
 cd /D "%~dp0"
 set CONDA_ROOT_PREFIX=%cd%\alltalk_environment\conda
 set INSTALL_ENV_DIR=%cd%\alltalk_environment\env
@rem Check if the Conda environment exists
 if not exist "%INSTALL_ENV_DIR%\python.exe" (
    echo.
    echo    The Conda environment at "%INSTALL_ENV_DIR%" does not exist.
    echo    Please install the environment before proceeding.
    echo. 
    pause
    goto StandaloneMenu
 )
@rem Attempt to activate the Conda environment
 call "%CONDA_ROOT_PREFIX%\condabin\conda.bat" activate "%INSTALL_ENV_DIR%"
 if errorlevel 1 (
    echo. 
    echo    Failed to activate the Conda environment.
    echo    Please check your installation and try again.
    echo.
    pause
    goto StandaloneMenu
 )
@rem Run diagnostics
 Python diagnostics.py
 if %ERRORLEVEL% neq 0 (
    echo.
    echo    There was an error running diagnostics.
    echo    Press any key to return to the menu.
    echo.
    pause
    goto StandaloneMenu
 )
 Echo.
 Echo.
 Echo    Diagnostics.log generated. Please scroll up to look over the log.
 Echo.
 pause
 goto StandaloneMenu
 :End
 echo Exiting AllTalk Setup Utility...
 exit /b
@@ -0,0 +1,440 @@
 #!/bin/bash
 # ANSI color codes
 RED='\033[1;31m'
 GREEN='\033[1;32m'
 YELLOW='\033[1;33m'
 BLUE='\033[1;34m'
 CYAN='\033[1;36m'
 MAGENTA='\033[1;35m'
 WHITE='\033[1;37m'
 L_RED='\033[1;91m'
 L_GREEN='\033[1;92m'
 L_YELLOW='\033[1;93m'
 L_BLUE='\033[1;94m'
 L_CYAN='\033[1;96m'
 L_MAGENTA='\033[1;95m'
 NC='\033[0m' # No Color
 # Navigate to the script's directory
 cd "$(dirname "$0")"
 # Function to check if curl is installed
 check_curl() {
    if ! command -v curl &> /dev/null; then
        echo "curl is not available on this system. Please install curl then re-run the script https://curl.se/"
        echo "or perform a manual installation of a Conda Python environment."
        exit 1
    fi
 }
 # Main Menu
 main_menu() {
    while true; do
        clear
        echo
        echo -e "    ${L_BLUE}ALLTALK LINUX SETUP UTILITY${NC}"
        echo
        echo "    INSTALLATION TYPE"
        echo -e "    1) I am using AllTalk as part of ${L_GREEN}Text-generation-webui${NC}"
        echo -e "    2) I am using AllTalk as a ${L_GREEN}Standalone Application${NC}"
        echo
        echo -e "    9)${L_RED} Exit/Quit${NC}"
        echo
        read -p "    Enter your choice: " user_option
        case $user_option in
            1) webui_menu ;;
            2) standalone_menu ;;
            9) exit 0 ;;
            *) echo "Invalid option"; sleep 2 ;;
        esac
    done
 }
 # Text-generation-webui Menu
 webui_menu() {
    while true; do
        clear
        echo
        echo -e "    ${L_BLUE}TEXT-GENERATION-WEBUI SETUP${NC}"
        echo
        echo -e "    Please ensure you have started your Text-generation-webui Python"
        echo -e "    environment. If you have NOT done this, please run ${L_GREEN}/cmd_linux.sh${NC}"
        echo -e "    in the ${L_GREEN}text-generation-webui${NC} folder and then re-run this script."
        echo
        echo "    BASE REQUIREMENTS"
        echo -e "    1) Install the AllTalk requirements for an ${L_GREEN}Nvidia GPU machine.${NC}"
        echo -e "    2) Install the AllTalk requirements for an ${L_GREEN}AMD or MAC machine.${NC}"
        echo
        echo "    OPTIONAL"
        echo "    3) Install the Finetuning requirements."
        echo "    4) Install DeepSpeed."
        echo "    5) Uninstall DeepSpeed."
        echo
        echo "    OTHER"
        echo "    6) Generate a diagnostics file."
        echo
        echo -e "    9)${L_RED} Exit/Quit${NC}"
        echo
        read -p "    Enter your choice: " webui_option
        case $webui_option in
            1) install_nvidia_textgen ;;
            2) install_other_textgen ;;
            3) install_finetune_textgen ;;
            4) install_deepspeed ;;
            5) uninstall_deepspeed ;;
            6) generate_diagnostics_textgen ;;
            9) exit 0 ;;
            *) echo "Invalid option"; sleep 2 ;;
        esac
    done
 }
 install_nvidia_textgen() {
    local requirements_file="requirements_nvidia.txt"
    echo "    Installing Finetune requirements from $requirements_file..."
    if ! pip install -r "$requirements_file"; then
        echo "    There was an error installing the Nvidia requirements."
        echo "    Please check the output for details."
        read -p "    Press any key to return to the menu. " -n 1
        echo
        return
    fi
    echo "    Nvidia requirements installed successfully."
    read -p "    Press any key to continue. " -n 1
    echo
 }
 install_other_textgen() {
    local requirements_file="requirements_other.txt"
    echo "    Installing Other machine requirements from $requirements_file..."
    if ! pip install -r "$requirements_file"; then
        echo "    There was an error installing the Other requirements."
        echo "    Please check the output for details."
        read -p "    Press any key to return to the menu. " -n 1
        echo
        return
    fi
    echo "    Other machine requirements installed successfully."
    read -p "    Press any key to continue. " -n 1
    echo
 }
 install_finetune_textgen() {
    local requirements_file="requirements_finetune.txt"
    echo "    Installing Finetune requirements from $requirements_file..."
    if ! pip install -r "$requirements_file"; then
        echo "    There was an error installing the Finetune requirements."
        echo "    Please check the output for details."
        read -p "    Press any key to return to the menu. " -n 1
        echo
        return
    fi
    echo
    echo "    Finetune base requirements installed successfully."
    echo
    echo -e "    Finetuning requires access to ${GREEN}Cublas${NC} from the ${GREEN}Nvidia CUDA Toolkit${NC}, so will need installing."
    echo
    echo -e "    Instructions can be found here:"
    echo -e "    ${GREEN}https://github.com/erew123/alltalk_tts?#-finetuning-a-model${NC}"
    echo
    read -p "    Press any key to continue. " -n 1
    echo
 }
 # Function to install DeepSpeed
 install_deepspeed() {
    clear
    echo
    echo -e "    ${L_BLUE}DEEPSPEED INSTALLATION REQUIREMENTS${NC}"
    echo
    echo -e "    - NVIDIA CUDA Toolkit must be installed from your ${L_GREEN}Linux package manager${NC}"
    echo -e "      or ${L_GREEN}https://developer.nvidia.com/cuda-toolkit-archive${NC}"
    echo -e "    - The environment variable ${L_GREEN}CUDA_HOME${NC} must be set in your Python env"
    echo -e "      e.g. export CUDA_HOME=/usr/local/cuda."
    echo -e "    - ${L_GREEN}libaio-dev${NC} must be installed."
    echo
    echo -e "    See the following link for full instructions:"
    echo -e "    ${L_GREEN}https://github.com/erew123/alltalk_tts?#-deepspeed-installation-options${NC}"
    echo
    echo -e "    ${L_BLUE}Please ${L_RED}confirm${L_BLUE} that you have completed these steps before continuing" 
    echo -e "    with the DeepSpeed installation, or the install ${L_RED}will fail.${NC}"
    echo
    read -p "    Have you completed all the above steps? (y/n): " confirm
    if [ "$confirm" != "y" ]; then
        echo -e "    ${RED}DeepSpeed installation cannot proceed without completing the prerequisites.${NC}"
        return
    fi
    echo -e "\n    ${GREEN}Proceeding with DeepSpeed installation...${NC}"
    pip install deepspeed
    if [ $? -ne 0 ]; then
        echo -e "    ${RED}There was an error installing DeepSpeed.${NC}"
        return
    fi
    echo -e "    ${GREEN}DeepSpeed installed successfully.${NC}"
    read -p "    Press any key to continue. " -n 1
    echo
 }
 uninstall_deepspeed() {
    echo "Uninstalling DeepSpeed..."
    pip uninstall -y deepspeed
    if [ $? -ne 0 ]; then
        echo "    There was an error uninstalling DeepSpeed."
        echo "    Press any key to return to the menu."
        read -n 1
        return
    fi
    echo "    DeepSpeed uninstalled successfully."
    echo "    Press any key to continue."
    read -n 1
 }
 generate_diagnostics_textgen() {
    # Run diagnostics
    if ! python diagnostics.py; then
        echo "    There was an error running diagnostics."
        read -p "    Press any key to return to the menu. " -n 1
        echo
        return
    fi
    echo "    Diagnostics completed successfully."
    read -p "    Press any key to continue. " -n 1
    echo
 }
 # Standalone Menu
 standalone_menu() {
    while true; do
        clear
        echo
        echo -e "    ${L_BLUE}ALLTALK STANDALONE APPLICATION SETUP${NC}"
        echo
        echo "    BASE REQUIREMENTS"
        echo "    1) Install AllTalk as a Standalone Application"
        echo
        echo "    OPTIONAL"
        echo "    2) Delete AllTalk's custom Python environment"
        echo "    3) Install the Finetuning requirements"
        echo "    4) Install DeepSpeed."
        echo
        echo "    OTHER"        
        echo "    5) Generate a diagnostics file"
        echo
        echo -e "    9)${L_RED} Exit/Quit${NC}"
        echo
        read -p "    Enter your choice: " standalone_option
        case $standalone_option in
            1) install_custom_standalone ;;
            2) delete_custom_standalone ;;
            3) install_finetune_standalone ;;
            4) install_deepspeed ;;
            5) generate_diagnostics_standalone ;;
            9) exit 0 ;;
            *) echo "Invalid option"; sleep 2 ;;
        esac
    done
 }
 install_custom_standalone() {
    cd "$(dirname "${BASH_SOURCE[0]}")"
    if [[ "$(pwd)" =~ " " ]]; then
        echo "This script relies on Miniconda which can not be silently installed under a path with spaces."
        exit
    fi
    # Deactivate existing conda envs as needed to avoid conflicts
    { conda deactivate && conda deactivate && conda deactivate; } 2> /dev/null
    OS_ARCH=$(uname -m)
    case "${OS_ARCH}" in
        x86_64*)    OS_ARCH="x86_64" ;;
        arm64* | aarch64*) OS_ARCH="aarch64" ;;
        *)          echo "Unknown system architecture: $OS_ARCH! This script runs only on x86_64 or arm64" && exit ;;
    esac
    # Config
    INSTALL_DIR="$(pwd)/alltalk_environment"
    CONDA_ROOT_PREFIX="${INSTALL_DIR}/conda"
    INSTALL_ENV_DIR="${INSTALL_DIR}/env"
    MINICONDA_DOWNLOAD_URL="https://repo.anaconda.com/miniconda/Miniconda3-py310_23.3.1-0-Linux-${OS_ARCH}.sh"
    if [ ! -x "${CONDA_ROOT_PREFIX}/bin/conda" ]; then
        echo "Downloading Miniconda from $MINICONDA_DOWNLOAD_URL to ${INSTALL_DIR}/miniconda_installer.sh"
        mkdir -p "${INSTALL_DIR}"
        curl -L "${MINICONDA_DOWNLOAD_URL}" -o "${INSTALL_DIR}/miniconda_installer.sh"
        chmod +x "${INSTALL_DIR}/miniconda_installer.sh"
        bash "${INSTALL_DIR}/miniconda_installer.sh" -b -p "${CONDA_ROOT_PREFIX}"
        echo "Miniconda installed."
    fi
    if [ ! -d "${INSTALL_ENV_DIR}" ]; then
        "${CONDA_ROOT_PREFIX}/bin/conda" create -y --prefix "${INSTALL_ENV_DIR}" python=3.11
        echo "Conda environment created at ${INSTALL_ENV_DIR}."
    fi
    # Activate the environment and install requirements
    source "${CONDA_ROOT_PREFIX}/etc/profile.d/conda.sh"
    conda activate "${INSTALL_ENV_DIR}"
    echo
    echo -e "    ${L_BLUE}Choose the type of requirements to install${NC}"
    echo
    echo "    1. Nvidia graphics card machines"
    echo "    2. Other machines (mac, amd, etc)"
    echo
    read -p "    Enter your choice (1 or 2): " user_choice
    if [ "$user_choice" == "1" ]; then
    	pip install torch==2.1.0 torchvision==0.16.0 torchaudio==2.1.0 --upgrade --force-reinstall --index-url https://download.pytorch.org/whl/cu121
    	pip install numpy==1.24.4
 	pip install typing-extensions>=4.8.0
 	pip install networkx<3.0.0,>=2.5.0
    	pip install fsspec>=2023.6.0
 	pip install soundfile==0.12.1
    	pip install uvicorn==0.24.0.post1
    	pip install TTS==0.21.3
    	pip install fastapi==0.104.1
    	pip install Jinja2==3.1.2
    	pip install requests==2.31.0
    	pip install tqdm==4.66.1
    	pip install importlib-metadata==4.8.1
    	pip install packaging==23.2
    	pip install pydantic==1.10.13
    	pip install sounddevice==0.4.6
    	pip install python-multipart==0.0.6
    else
        pip install -r requirements_other.txt
    fi
    # Create start_environment.sh to run AllTalk
    cat << EOF > start_environment.sh
 #!/bin/bash
 cd "$(dirname "${BASH_SOURCE[0]}")"
 if [[ "$(pwd)" =~ " " ]]; then echo This script relies on Miniconda which can not be silently installed under a path with spaces. && exit; fi
 # deactivate existing conda envs as needed to avoid conflicts
 { conda deactivate && conda deactivate && conda deactivate; } 2> /dev/null
 # config
 CONDA_ROOT_PREFIX="$(pwd)/alltalk_environment/conda"
 INSTALL_ENV_DIR="$(pwd)/alltalk_environment/env"
 # environment isolation
 export PYTHONNOUSERSITE=1
 unset PYTHONPATH
 unset PYTHONHOME
 export CUDA_PATH="$INSTALL_ENV_DIR"
 export CUDA_HOME="$CUDA_PATH"
 # activate env
 bash --init-file <(echo "source \"$CONDA_ROOT_PREFIX/etc/profile.d/conda.sh\" && conda activate \"$INSTALL_ENV_DIR\"")
 EOF
    # Create start_alltalk.sh to run AllTalk
    cat << EOF > start_alltalk.sh
 #!/bin/bash
 source "${CONDA_ROOT_PREFIX}/etc/profile.d/conda.sh"
 conda activate "${INSTALL_ENV_DIR}"
 python script.py
 EOF
    chmod +x start_alltalk.sh
    chmod +x start_environment.sh
    echo
    echo
    echo -e "    start_alltalk.sh has been created."
    echo -e "    You can now start AllTalk with ${L_YELLOW}./start_alltalk.sh${NC}"
    echo
    read -p "    Press any key to continue. " -n 1
 }
 delete_custom_standalone() {
    local env_dir="$PWD/alltalk_environment"
    # Check if the alltalk_environment directory exists
    if [ ! -d "$env_dir" ]; then
        echo "    \"$env_dir\" directory does not exist. No need to delete."
        read -p "    Press any key to continue. " -n 1
        echo
        return
    fi
    # Check if a Conda environment is active and deactivate it
    if [ -n "$CONDA_PREFIX" ]; then
        echo "    Exiting the Conda environment. You may need to start ./atstart.sh again"
        conda deactivate
    fi
    echo "Deleting \"$env_dir\". Please wait."
    rm -rf "$env_dir"
    if [ -d "$env_dir" ]; then
        echo "    Failed to delete \"$env_dir\" folder."
        echo "    Please make sure it is not in use and try again."
    else
        echo "    Environment \"$env_dir\" deleted successfully."
    fi
    read -p "    Press any key to continue. " -n 1
    echo
 }
 install_finetune_standalone() {
    local env_dir="$PWD/alltalk_environment"
    local conda_root_prefix="${env_dir}/conda"
    local install_env_dir="${env_dir}/env"
    if [ ! -d "${install_env_dir}" ]; then
        echo "    The Conda environment at '${install_env_dir}' does not exist."
        echo "    Please install the environment before proceeding."
        read -p "    Press any key to return to the menu. " -n 1
        echo
        return
    fi
    source "${conda_root_prefix}/etc/profile.d/conda.sh"
    conda activate "${install_env_dir}"
    local requirements_file="requirements_finetune.txt"
    echo "Installing Finetune requirements from $requirements_file..."
    if ! pip install -r "$requirements_file"; then
        echo "    There was an error installing the Finetune requirements."
        echo "    Please check the output for details."
        read -p "    Press any key to return to the menu. " -n 1
        echo
        return
    fi
    echo
    echo "    Finetune base requirements installed successfully."
    echo
    echo -e "    Finetuning requires access to ${GREEN}Cublas${NC} from the ${GREEN}Nvidia CUDA Toolkit${NC}, so will need installing."
    echo
    echo -e "    Instructions can be found here:"
    echo -e "    ${GREEN}https://github.com/erew123/alltalk_tts?#-finetuning-a-model${NC}"
    echo
    read -p "    Press any key to continue. " -n 1
    echo
 }
 generate_diagnostics_standalone() {
    local env_dir="$PWD/alltalk_environment"
    local conda_root_prefix="${env_dir}/conda"
    local install_env_dir="${env_dir}/env"
    if [ ! -d "${install_env_dir}" ]; then
        echo "    The Conda environment at '${install_env_dir}' does not exist."
        echo "    Please install the environment before proceeding."
        read -p "    Press any key to return to the menu. " -n 1
        echo
        return
    fi
    source "${conda_root_prefix}/etc/profile.d/conda.sh"
    conda activate "${install_env_dir}"
    if ! python diagnostics.py; then
        echo "    There was an error running diagnostics."
        read -p "    Press any key to return to the menu. " -n 1
        echo
        return
    fi
    echo "    Diagnostics completed successfully."
    read -p "    Press any key to continue. " -n 1
    echo
 }
 # Start the main menu
 main_menu
@@ -1 +0,0 @@
 {"activate": true, "autoplay": true, "branding": "AllTalk ", "narrator_enabled": false, "deepspeed_activate": false, "delete_output_wavs": "Disabled", "ip_address": "127.0.0.1", "language": "English", "low_vram": false, "local_temperature": "0.7", "local_repetition_penalty": "12.0", "model_loaded": true, "model_name": "tts_models/multilingual/multi-dataset/xtts_v2", "narrator_voice": "female_01.wav", "output_folder_wav": "extensions/alltalk_tts/outputs/", "port_number": "7851", "remove_trailing_dots": false, "show_text": true, "tts_method_api_local": false, "tts_method_api_tts": false, "tts_method_xtts_local": true, "voice": "female_01.wav"}
@@ -0,0 +1 @@
 {"activate": true, "autoplay": true, "branding": "AllTalk ", "narrator_enabled": false, "deepspeed_activate": false, "delete_output_wavs": "Disabled", "ip_address": "127.0.0.1", "language": "English", "low_vram": false, "local_temperature": "0.7", "local_repetition_penalty": "10.0", "tts_model_loaded": true, "tts_model_name": "tts_models/multilingual/multi-dataset/xtts_v2", "narrator_voice": "female_01.wav", "output_folder_wav": "extensions/alltalk_tts/outputs/", "output_folder_wav_standalone": "outputs/", "port_number": "7851", "remove_trailing_dots": false, "show_text": true, "tts_method_api_local": false, "tts_method_api_tts": false, "tts_method_xtts_local": true, "voice": "female_01.wav"}
@@ -0,0 +1,239 @@
 try:
    import platform
    import subprocess
    import logging
    from importlib_metadata import distributions
    import torch
    import os  # Import the os module
    import re
    import sys
    import glob
    import textwrap
    import packaging.version
    import packaging.specifiers
    from packaging.specifiers import SpecifierSet
    from packaging.specifiers import SpecifierSet
    from packaging.version import parse as parse_version
 except ImportError as e:
    print(f"\033[91mError importing module: {e}\033[0m\n")
    print("\033[94mPlease ensure you started the Text-generation-webUI Python environment with either\033[0m")
    print("\033[92mcmd_linux.sh\033[0m, \033[92mcmd_windows.bat\033[0m, \033[92mcmd_macos.sh\033[0m, or \033[92mcmd_wsl.bat\033[0m")
    print("\033[94mfrom the text-generation-webui directory, and then try running the diagnostics again.\033[0m")
    exit(1)
 try:
    import psutil
 except ImportError:
    print("psutil not found. Installing...")
    subprocess.run(['pip', 'install', 'psutil'])
    import psutil
 def get_requirements_file():
    requirements_files = glob.glob("requirements*.txt")
    if not requirements_files:
        print("\033[91mNo requirements files found.\033[0m")
        return None
    print("\033[94m\nSelect a requirements file to check against (or press Enter for default 'requirements.txt'):\033[0m\n")
    for i, file in enumerate(requirements_files, start=1):
        print(f"{i}. {file}")
    choice = input("\nEnter the number of your choice: ")
    try:
        choice = int(choice) - 1
        return requirements_files[choice]
    except (ValueError, IndexError):
        return "requirements.txt"
 # Set up logging with filemode='w'
 logging.basicConfig(filename='diagnostics.log', filemode='w', level=logging.INFO)
 # Function to get GPU information using subprocess
 def get_gpu_info():
    try:
        result = subprocess.run(['nvidia-smi'], stdout=subprocess.PIPE, text=True)
        return result.stdout
    except FileNotFoundError:
        return "NVIDIA GPU information not available"
 # Function to check if a port is in use
 def is_port_in_use(port):
    for conn in psutil.net_connections():
        if conn.laddr.port == port:
            return True
    return False
 def satisfies_wildcard(installed_version, required_version):
    if '*' in required_version:
        required_parts = required_version.split('.')
        installed_parts = installed_version.split('.')
        for req, inst in zip(required_parts, installed_parts):
            if req != '*' and req != inst:
                return False
        return True
    return False
 # Function to log and print system information
 def log_system_info():
    # System information
    os_version = platform.system() + " " + platform.version()
    # Get CUDA_HOME environment variable
    cuda_home = os.environ.get('CUDA_HOME', 'N/A')
    gpu_info = get_gpu_info()
    # Python environment information
    python_version = platform.python_version()
    # Torch version
    torch_version = torch.__version__
    # System RAM using psutil
    try:
        virtual_memory = psutil.virtual_memory()
        total_ram = f"{virtual_memory.total / (1024 ** 3):.2f} GB"
        available_ram = f"{virtual_memory.available / (1024 ** 3):.2f} GB"
        system_ram = f"{available_ram} available out of {total_ram} total"
    except NameError:
        print("psutil is not installed. Unable to check system RAM.")
        system_ram = "N/A"
    # Port check (if psutil is available)
    port_status = "N/A"
    if 'psutil' in globals():
        port_to_check = 7851
        if is_port_in_use(port_to_check):
            port_status = f"Port {port_to_check} is in use."
        else:
            port_status = f"Port {port_to_check} is available."
    # Package versions using importlib_metadata
    package_versions = {d.metadata['Name']: d.version for d in distributions()}
    # Python environment information
    python_executable = sys.executable
    python_version_info = sys.version_info
    python_virtual_env = os.environ.get('VIRTUAL_ENV', 'N/A')
    # Conda environment information
    conda_env = os.environ.get('CONDA_DEFAULT_ENV', 'N/A')
    # Get Path environment information
    search_path = sys.path
    path_env = os.environ.get('PATH', 'N/A')
    # Compare with requirements file
    requirements_file = get_requirements_file()
    if requirements_file:
        required_packages = {}
        installed_packages = {}
        try:
            with open(requirements_file, 'r') as req_file:
                requirements = [line.strip() for line in req_file]
                for req in requirements:
                    # Use regular expression to parse package name and version
                    match = re.match(r'([^\s>=]+)\s*([>=<]+)\s*([^,]+)', req)
                    if match:
                        package_name, operator, version_spec = match.groups()
                        installed_version = package_versions.get(package_name, 'Not installed')
                        if installed_version != 'Not installed':
                            required_packages[package_name] = (operator, version_spec)
                            installed_packages[package_name] = installed_version
        except FileNotFoundError:
            print(f"\n{requirements_file} not found. Skipping version checks.")
            logging.info(f"NOTE {requirements_file} not found. Skipping version checks.")
    # Log and print information
    logging.info(f"OS Version: {os_version}")
    logging.info(f"Note: Windows 11 will list as build is 10.x.22xxx")
    logging.info(f"Torch Version: {torch_version}")
    logging.info(f"System RAM: {system_ram}")
    logging.info(f"CUDA_HOME: {cuda_home}")
    logging.info(f"Port Status: {port_status}")
    logging.info(f"Python Version: {platform.python_version()}")
    logging.info(f"Python Version Info: {python_version_info}")
    logging.info(f"Python Executable: {python_executable}")
    logging.info(f"Python Virtual Environment: {python_virtual_env} (Should be N/A when in Text-generation-webui Conda Python environment)")
    logging.info(f"Conda Environment: {conda_env}")
    logging.info("\nPython Search Path:")
    for path in search_path:
        logging.info(f"  {path}")
    logging.info("\nOS PATH Environment Variable:")
    for path in path_env.split(';'):
        logging.info(f"  {path}")
    if required_packages:  # Check if the dictionary is not empty
        logging.info("\nPackage Versions:")
        max_package_length = max(len(package) for package in required_packages.keys())
        for package_name, (operator, required_version) in required_packages.items():
            installed_version = installed_packages.get(package_name, 'Not installed')
            logging.info(f"{package_name.ljust(max_package_length)}  Required: {operator} {required_version.ljust(12)}  Installed: {installed_version}")
    logging.info(f"GPU Information:\n{gpu_info}")
    logging.info("Package Versions:")
    for package, version in package_versions.items():
        logging.info(f"{package}>= {version}")
    # Print to screen
    print(f"\n\033[94mOS Version:\033[0m \033[92m{os_version}\033[0m")
    print(f"\033[94mOS Ver note:\033[0m \033[92m(Windows 11 will say build is 10.x.22xxx)\033[0m")
    print(f"\033[94mCUDA_HOME:\033[0m \033[92m{cuda_home}\033[0m")
    print(f"\033[94mSystem RAM:\033[0m \033[92m{system_ram}\033[0m")
    print(f"\033[94mPort Status:\033[0m \033[92m{port_status}\033[0m")
    print(f"\033[94mTorch Version:\033[0m \033[92m{torch_version}\033[0m")
    print(f"\033[94mPython Version:\033[0m \033[92m{platform.python_version()}\033[0m")
    print(f"\033[94mPython Version Info:\033[0m \033[92m{python_version_info}\033[0m")
    print(f"\033[94mPython Executable:\033[0m \033[92m{python_executable}\033[0m")
    print(f"\033[94mPython Virtual Environment:\033[0m \033[92m{python_virtual_env}\033[0m (Should be N/A when in Text-generation-webui Conda Python environment)")
    print(f"\033[94mConda Environment:\033[0m \033[92m{conda_env}\033[0m")
    print(f"\n\033[94mPython Search Path:\033[0m")
    for path in search_path:
        print(f"  {path}")
    print(f"\n\033[94mOS Search PATH Environment Variable:\033[0m")
    for path in path_env.split(';'):
        print(f"  {path}")
    if required_packages:  # Check if the dictionary is not empty
        print("\033[94m\nRequirements file package comparison:\033[0m")
        max_package_length = max(len(package) for package in required_packages.keys())
        for package_name, (operator, required_version) in required_packages.items():
            installed_version = installed_packages.get(package_name, 'Not installed')
            # Exclude build information (e.g., +cu118) before creating the SpecifierSet
            required_version_no_build = required_version.split("+")[0]
            if '*' in required_version:
                condition_met = satisfies_wildcard(installed_version, required_version)
            else:
                # Compare versions using packaging.version
                required_specifier = SpecifierSet(f"{operator}{required_version_no_build}")
                installed_version = parse_version(installed_version)
                condition_met = installed_version in required_specifier
            color_required = "\033[92m" if condition_met else "\033[91m"
            color_installed = "\033[92m" if condition_met else "\033[91m"
            # Print colored output
            print(f"{package_name.ljust(max_package_length)}  Required: {color_required}{operator} {required_version.ljust(12)}\033[0m  Installed: {color_installed}{installed_version}\033[0m")
        print("\nOn Nvidia Graphics cards machines, if your \033[92mInstalled\033[0m version of \033[92mTorch\033[0m and \033[92mTorchaudio\033[0m does")    
        print("not have \033[92m+cu118\033[0m (Cuda 11.8) or \033[92m+cu121\033[0m (Cuda 12.1) listed after them, you do not have CUDA")
        print("installed for Torch or Torchaudio in this Python environment. This will cause you problems")
        print("with \033[94mAllTalk\033[0m and \033[94mFinetuning.\033[0m You may have to 'pip install' a new version of torch and")
        print("torchaudio, using '\033[94m--upgrade --force-reinstall\033[0m' with the correct version of PyTorch for\033[0m")
        print("your Python environment.\033[0m")
        print("\033[94m\nRequirements file specifier meanings:\033[0m")
        explanation = textwrap.dedent("""
        == Exact version              != Any version except          < Less than               
        <= Less than or equal to      >  Greater than                >= Greater than or equal to
        ~ Compatible release          ;  Environment marker          AND Logical AND           
        OR Logical OR
        """)
        print(explanation.strip())
    print("")
    print(f"GPU Information:{gpu_info}")
    print(f"\033[94mDiagnostic log created:\033[0m \033[92mdiagnostics.log\033[0m")
    print(f"\033[94mPlease upload the log file with any support ticket.\033[0m")
 if __name__ == "__main__":
    log_system_info()
@@ -0,0 +1,26 @@
 import torch
 import os
 MODEL_PATH = "best_model.pth"
 # Check if best_model.pth exists
 if not os.path.exists(MODEL_PATH):
    print(f"\nCannot find \033[94m{MODEL_PATH}\033[0m in the current folder.")
    # Check if model.pth exists as an alternative
    ALTERNATIVE_PATH = "model.pth"
    if os.path.exists(ALTERNATIVE_PATH):
        print(f"\nIf your model is currently called \033[93m{ALTERNATIVE_PATH}\033[0m please rename it to \033[94mbest_model.pth\033[0m.")
    else:
        print(f"Please put \033[91mbest_model.pth\033[0m in the current folder or rename your model file to \033[94mbest_model.pth\033[0m.")
    exit(1)
 # Attempt to load the model
 try:
    checkpoint = torch.load(MODEL_PATH, map_location=torch.device("cpu"))
 except Exception as e:
    print("Error loading checkpoint:", e)
    raise
 del checkpoint["optimizer"]
 for key in list(checkpoint["model"].keys()):
    if "dvae" in key:
        del checkpoint["model"][key]
 torch.save(checkpoint, "model.pth")
 print(f"\nYour compacted model is created \033[93mmodel.pth\033[0m.")
@@ -6,6 +6,9 @@
        "README.md": "https://huggingface.co/coqui/XTTS-v2/resolve/v2.0.2/README.md?download=true",
        "config.json": "https://huggingface.co/coqui/XTTS-v2/resolve/v2.0.2/config.json?download=true",
        "model.pth": "https://huggingface.co/coqui/XTTS-v2/resolve/v2.0.2/model.pth?download=true",
        "dvae.pth": "https://huggingface.co/coqui/XTTS-v2/resolve/v2.0.2/dvae.pth?download=true",
        "mel_stats.pth": "https://huggingface.co/coqui/XTTS-v2/resolve/v2.0.2/mel_stats.pth?download=true",
        "speakers_xtts.pth": "https://huggingface.co/coqui/XTTS-v2/resolve/v2.0.2/speakers_xtts.pth?download=true",
        "vocab.json": "https://huggingface.co/coqui/XTTS-v2/resolve/v2.0.2/vocab.json?download=true"
    }
 }
@@ -6,9 +6,9 @@ import importlib.metadata as metadata
 import json
 from packaging import version
-##############################################################
+#################################################################
-#### LOAD PARAMS FROM CONFIG.JSON - REQUIRED FOR BRANDING ####
+#### LOAD PARAMS FROM confignew.json - REQUIRED FOR BRANDING ####
-##############################################################
+#################################################################
 # STARTUP VARIABLE - Create "this_dir" variable as the current script directory
 this_dir = Path(__file__).parent.resolve()
@@ -20,7 +20,7 @@ def load_config(file_path):
    return config
-config_file_path = this_dir / "config.json"
+config_file_path = this_dir / "confignew.json"
 params = load_config(config_file_path)
 # Define the path to the modeldownload config file file
@@ -0,0 +1,7 @@
 gradio>=3.50.2
 torch>=2.1.0+cu118
 torchaudio>=2.1.0+cu118
 TTS==0.21.3
 faster-whisper>=0.10.0
 tqdm>=4.66.0
 pandas>=1.5.0
@@ -10,3 +10,6 @@ requests>=2.31.0
 tqdm>=4.66.1
 importlib-metadata>=4.8.1
 packaging>=23.2
 pydantic>=1.10.13
 sounddevice>=0.4.6
 python-multipart>=0.0.6
@@ -10,3 +10,6 @@ requests>=2.31.0
 tqdm>=4.66.1
 importlib-metadata>=4.8.1
 packaging>=23.2
 pydantic>=1.10.13
 sounddevice>=0.4.6
 python-multipart>=0.0.6
@@ -16,9 +16,9 @@ import numpy as np
 import soundfile as sf
 import uuid
-##############################################################
+#################################################################
-#### LOAD PARAMS FROM CONFIG.JSON - REQUIRED FOR BRANDING ####
+#### LOAD PARAMS FROM confignew.json - REQUIRED FOR BRANDING ####
-##############################################################
+#################################################################
 # STARTUP VARIABLE - Create "this_dir" variable as the current script directory
 this_dir = Path(__file__).parent.resolve()
@@ -28,8 +28,8 @@ def load_config(file_path):
        config = json.load(config_file)
    return config
-config_file_path = this_dir / "config.json"
+config_file_path = this_dir / "confignew.json"
-# Load the params dictionary from the config.json file
+# Load the params dictionary from the confignew.json file
 params = load_config(config_file_path)
 # Required for sentence splitting
@@ -39,8 +39,8 @@ try:
 except ModuleNotFoundError:
    logger.error(
        f"[{params['branding']}]\033[91mWarning\033[0m Could not find the TTS module. Make sure to install the requirements for the {params['branding']} extension."
-        f"[{params['branding']}]\033[91mWarning\033[0m Linux / Mac:\npip install -r extensions/alltalk_tts/requirements.txt\n"
+        f"[{params['branding']}]\033[91mWarning\033[0m Linux / Mac:\npip install -r /alltalk_tts/requirements.txt\n"
-        f"[{params['branding']}]\033[91mWarning\033[0m Windows:\npip install -r extensions\\alltalk_tts\\requirements.txt\n"
+        f"[{params['branding']}]\033[91mWarning\033[0m Windows:\npip install -r \\alltalk_tts\\requirements.txt\n"
        f"[{params['branding']}]\033[91mWarning\033[0m If you used the one-click installer, paste the command above in the terminal window launched after running the cmd_ script. On Windows, that's cmd_windows.bat."
    )
    raise
@@ -62,7 +62,9 @@ try:
    from modules.utils import gradio
    # This is set to check if the script is being run within text generation webui or as a standalone script. False is running as part of text gen web ui or a gradio interface
    running_in_standalone = False
    output_folder_wav = params["output_folder_wav"]
 except ModuleNotFoundError:
    output_folder_wav = params["output_folder_wav_standalone"]
    print(f"[{params['branding']}Startup] Running script.py in standalone mode")
    # This is set to check if the script is being run within text generation webui or as a standalone script. true means standalone
    running_in_standalone = True
@@ -75,6 +77,8 @@ with open(this_dir / "languages.json", encoding="utf8") as f:
    languages = json.load(f)
 # Create a global lock
 process_lock = threading.Lock()
 # Base setting for a possible FineTuned model existing and the loader being available
 tts_method_xtts_ft = False
 # Gather the voice files
 def get_available_voices():
@@ -108,7 +112,6 @@ def delete_old_files(folder_path, days_to_keep):
 # Extract settings using params dictionary
 delete_output_wavs_setting = params["delete_output_wavs"]
 output_folder_wav = params["output_folder_wav"]
 output_folder_wav = os.path.normpath(output_folder_wav)
 # Check and perform file deletion
@@ -138,14 +141,27 @@ def check_required_files():
    subprocess.run(["python", str(download_script_path)])
    print(f"[{params['branding']}Startup] All required files are present.")
 # STARTUP Call Check routine
 check_required_files()
 ##################################################
 #### Check to see if a finetuned model exists ####
 ##################################################
 # Set the path to the directory
 trained_model_directory = this_dir / "models" / "trainedmodel"
 # Check if the directory "trainedmodel" exists
 finetuned_model = trained_model_directory.exists()
 # If the directory exists, check for the existence of the required files
 # If true, this will add a extra option in the Gradio interface for loading Xttsv2 FT
 if finetuned_model:
    required_files = ["model.pth", "config.json", "vocab.json"]
    finetuned_model = all((trained_model_directory / file).exists() for file in required_files)
 if finetuned_model:
    print(f"[{params['branding']}Startup] Finetuned model \033[93mDetected\033[0m")
-#################################################
+####################################################
-#### SET GRADIO BUTTONS BASED ON CONFIG.JSON ####
+#### SET GRADIO BUTTONS BASED ON confignew.json ####
-#################################################
+####################################################
 if params["tts_method_api_tts"] == True:
    gr_modelchoice = "API TTS"
@@ -221,10 +237,12 @@ process = subprocess.Popen(["python", script_path])
 # Check if the subprocess has started successfully
 if process.poll() is None:
    print(f"[{params['branding']}Startup] TTS Subprocess starting")
    print(f"[{params['branding']}Startup]")
    print(
-        f"[{params['branding']}Startup] Readme available here:",
+        f"[{params['branding']}Startup] \033[94mSettings & Documentation:\033[00m",
-        f"http://{params['ip_address']}:{params['port_number']}",
+        f"\033[92mhttp://{params['ip_address']}:{params['port_number']}\033[00m",
    )
    print(f"[{params['branding']}Startup]")
 else:
    print(
        f"[{params['branding']}Startup] \033[91mWarning\033[0m TTS Subprocess Webserver failing to start process"
@@ -248,10 +266,10 @@ else:
    # Cleanly kill off this script, but allow text-generation-webui to keep running, albeit without this alltalk_tts
    sys.exit(1)
-timeout = 60  # Adjust the timeout as needed
+timeout = 120  # Adjust the timeout as needed
 # Introduce a delay before starting the check loop
-time.sleep(25)  # Wait 25 secs before checking if the tts_server.py has started up.
+time.sleep(26)  # Wait 26 secs before checking if the tts_server.py has started up.
 start_time = time.time()
 while time.time() - start_time < timeout:
    try:
@@ -261,9 +279,9 @@ while time.time() - start_time < timeout:
    except requests.RequestException as e:
        # Print the exception for debugging purposes
        print(
-            f"[{params['branding']}Startup] \033[91mWarning\033[0m TTS Subprocess has NOT started up yet, Will keep trying for 60 seconds maximum. Please wait."
+            f"[{params['branding']}Startup] \033[91mWarning\033[0m TTS Subprocess has NOT started up yet, Will keep trying for 120 seconds maximum. Please wait."
        )
-    time.sleep(1)
+    time.sleep(4)
 else:
    print(
        f"[{params['branding']}Startup] Startup timed out. Check the server logs for more information."
@@ -271,13 +289,15 @@ else:
    # Cleanly kill off this script, but allow text-generation-webui to keep running, albeit without this alltalk_tts
    sys.exit(1)
 #####################################
 #### MODEL LOADING AND UNLOADING ####
 #####################################
 # MODEL - Swap model based on Gradio selection API TTS, API Local, XTTSv2 Local
 def send_reload_request(tts_method):
    global tts_method_xtts_ft
    try:
-        params["model_loaded"] = False
+        params["tts_model_loaded"] = False
        url = f"{base_url}/api/reload"
        payload = {"tts_method": tts_method}
        response = requests.post(url, params=payload)
@@ -285,8 +305,8 @@ def send_reload_request(tts_method):
        json_response = response.json()
        # Check if the reload operation was successful
        if json_response.get("status") == "model-success":
-            # Update model_loaded to True if the reload was successful
+            # Update tts_tts_model_loaded to True if the reload was successful
-            params["model_loaded"] = True
+            params["tts_model_loaded"] = True
            # Update local script parameters based on the tts_method
            if tts_method == "API TTS":
                params["tts_method_api_local"] = False
@@ -294,17 +314,26 @@ def send_reload_request(tts_method):
                params["tts_method_api_tts"] = True
                params["deepspeed_activate"] = False
                audio_path = this_dir / "templates" / "apitts.wav"
                tts_method_xtts_ft = False
            elif tts_method == "API Local":
                params["tts_method_api_tts"] = False
                params["tts_method_xtts_local"] = False
                params["tts_method_api_local"] = True
                params["deepspeed_activate"] = False
                audio_path = this_dir / "templates" / "apilocal.wav"
                tts_method_xtts_ft = False
            elif tts_method == "XTTSv2 Local":
                params["tts_method_api_tts"] = False
                params["tts_method_api_local"] = False
                params["tts_method_xtts_local"] = True
                audio_path = this_dir / "templates" / "xttslocal.wav"
                tts_method_xtts_ft = False
            elif tts_method == "XTTSv2 FT":
                params["tts_method_api_tts"] = False
                params["tts_method_api_local"] = False
                params["tts_method_xtts_local"] = False
                audio_path = this_dir / "templates" / "xttsfinetuned.wav"
                tts_method_xtts_ft = True
        return f'<audio src="file/{audio_path}" controls autoplay></audio>'
    except requests.exceptions.RequestException as e:
        # Handle the HTTP request error
@@ -319,7 +348,7 @@ def send_reload_request(tts_method):
 # LOW VRAM - Gradio Checkbox handling
 def send_lowvram_request(low_vram):
    try:
-        params["model_loaded"] = False
+        params["tts_model_loaded"] = False
        if low_vram:
            audio_path = this_dir / "templates" / "lowvramenabled.wav"
        else:
@@ -332,7 +361,7 @@ def send_lowvram_request(low_vram):
        # Check if the low VRAM request was successful
        if json_response.get("status") == "lowvram-success":
            # Update any relevant variables or perform other actions on success
-            params["model_loaded"] = True
+            params["tts_model_loaded"] = True
        return f'<audio src="file/{audio_path}" controls autoplay></audio>'
    except requests.exceptions.RequestException as e:
        # Handle the HTTP request error
@@ -348,7 +377,7 @@ def send_lowvram_request(low_vram):
 # DEEPSPEED - Reload the model when DeepSpeed checkbox is enabled/disabled
 def send_deepspeed_request(deepspeed_param):
    try:
-        params["model_loaded"] = False
+        params["tts_model_loaded"] = False
        if deepspeed_param:
            audio_path = this_dir / "templates" / "deepspeedenabled.wav"
        else:
@@ -362,7 +391,7 @@ def send_deepspeed_request(deepspeed_param):
        # Check if the deepspeed request was successful
        if json_response.get("status") == "deepspeed-success":
            # Update any relevant variables or perform other actions on success
-            params["model_loaded"] = True
+            params["tts_model_loaded"] = True
        return f'<audio src="file/{audio_path}" controls autoplay></audio>'
    except requests.exceptions.RequestException as e:
        # Handle the HTTP request error
@@ -400,7 +429,7 @@ Synthesizer.split_into_sentences = new_split_into_sentences
 # Check model is loaded and string isnt empty, before sending a TTS request.
 def before_audio_generation(string, params):
    # Check Model is loaded into cuda or cpu and error if not
-    if not params["model_loaded"]:
+    if not params["tts_model_loaded"]:
        print(
            f"[{params['branding']}Model] \033[91mWarning\033[0m Model is still loading, please wait before trying to generate TTS"
        )
@@ -482,6 +511,54 @@ def voice_preview(string):
        return f"[{params['branding']}Server] Audio generation failed. Status: {generate_response.get('status')}"
 def process_text(text):
    # Normalize HTML encoded quotes
    text = html.unescape(text)
    # Replace ellipsis with a single dot
    text = re.sub(r'\.{3,}', '.', text)
    # Pattern to identify combined narrator and character speech
    combined_pattern = r'(\*[^*"]+\*|"[^"*]+")'
    # List to hold parts of speech along with their type
    ordered_parts = []
    # Track the start of the next segment
    start = 0
    # Find all matches
    for match in re.finditer(combined_pattern, text):
        # Add the text before the match, if any, as ambiguous
        if start < match.start():
            ambiguous_text = text[start:match.start()].strip()
            if ambiguous_text:
                ordered_parts.append(('ambiguous', ambiguous_text))
        # Add the matched part as either narrator or character
        matched_text = match.group(0)
        if matched_text.startswith('*') and matched_text.endswith('*'):
            ordered_parts.append(('narrator', matched_text.strip('*').strip()))
        elif matched_text.startswith('"') and matched_text.endswith('"'):
            ordered_parts.append(('character', matched_text.strip('"').strip()))
        else:
            # In case of mixed or improperly formatted parts
            if '*' in matched_text:
                ordered_parts.append(('narrator', matched_text.strip('*').strip('"')))
            else:
                ordered_parts.append(('character', matched_text.strip('"').strip('*')))
        # Update the start of the next segment
        start = match.end()
    # Add any remaining text after the last match as ambiguous
    if start < len(text):
        ambiguous_text = text[start:].strip()
        if ambiguous_text:
            ordered_parts.append(('ambiguous', ambiguous_text))
    return ordered_parts
 #################################
 #### TTS STANDARD GENERATION ####
 #################################
@@ -490,6 +567,7 @@ def output_modifier(string, state):
    if not params["activate"]:
        return string
    original_string = string
    #print("ORIGINAL STRING IS:", original_string)
    cleaned_string = before_audio_generation(string, params)
    if cleaned_string is None:
        return
@@ -500,85 +578,55 @@ def output_modifier(string, state):
    if process_lock.acquire(blocking=False):
        try:
            if params["narrator_enabled"]:
-                # print(original_string)
+                processed_parts = process_text(original_string)
-                # Do Some basic stripping and remove any double CR's
+
                processed_string = (
                    original_string
                    .replace("***", "*")
                    .replace("**", "*")
                    .replace("\n\n", "\n")
                )
                # Clean up two asterisks (narrators) being made between a newline, making it one sentence.
                processed_string = re.sub(r'\.\*\n\*', '. ', processed_string)
                # Clean up a few other bits.
                processed_string = (
                    processed_string
                    .replace("&#x27;", "'")
                    .replace("\n", " ")
                    # Add special characters to the quote so that we can use it to identify things later after its been split
                    .replace('&quot;', '&quot;<')
                    # Capture new conversations which wont have things like &quote in them
                    .replace('"', '&quot;<')
                )
                #capturing another outlier in inital character paragraph
                # print("processed string 1 is:", processed_string)
                processed_string = processed_string.replace('&quot;<. *', '&quot;< *"')
                processed_string = processed_string.replace('< *"', '< *')
                processed_string = processed_string.replace('. *', '< *')
                # print("processed string 2 is:", processed_string)
                # Set up a tracking of the individual wav files.
                audio_files_all_paragraphs = []
-                # Split the line using &quot; and ".* " (so end of sentences, leaving special characters added to the start of all OTHER sentences, bar possibly the first one if its starting with a *
+                for part_type, part in processed_parts:
                parts = re.split(r'&quot;|\.\*', processed_string)
                audio_files_paragraph = []
                for i, part in enumerate(parts):
                    # Skip parts that are too short
-                    if len(part.strip()) <= 1:
+                    if len(part.strip()) <= 3:
                        continue
-                    # Figure out which type of line it is, then replace characters as necessary to avoid TTS trying to pronunce them, htmlunescape after. 
+
-                    # Character will always be a < with a letter immediately after it
+                    # Determine the voice to use based on the part type
-                    if '<' in part and '< *' not in part and '<*' not in part and '<  *' not in part and '< ' not in part and '<  ' not in part:
+                    if part_type == 'narrator':
                        cleaned_part = html.unescape(part.replace('<', ''))
                        voice_to_use = params["voice"]
                    #Narrator will always be an * or < with an * a position or two after it.
                    elif '<*' in part or '< *' in part or '<  *' in part or '*' in part:
                        cleaned_part = html.unescape(part.replace('<*', '').replace('< *', '').replace('<  *', '').replace('*', ''))
                        voice_to_use = params["narrator_voice"]
-                    #If the other two dont capture it, aka, the AI gave no * or &quot; on the line, use non_quoted_text_is aka user interface, user can choose Char or Narrator
+                        print(f"[{params['branding']}TTSGen] \033[92mNarrator\033[0m")  # Green
-                    elif non_quoted_text_is:
+                    elif part_type == 'character':
                        cleaned_part = html.unescape(part.replace('< ', '').replace('<  ', '').replace('<  ', ''))
                        voice_to_use = params["voice"]
                        print(f"[{params['branding']}TTSGen] \033[36mCharacter\033[0m")  # Yellow
                    else:
-                        cleaned_part = html.unescape(part.replace('< ', '').replace('<  ', '').replace('<  ', ''))
+                        # Handle ambiguous parts based on user preference
-                        voice_to_use = params["narrator_voice"]
+                        voice_to_use = params["voice"] if non_quoted_text_is else params["narrator_voice"]
-                    # Check if character name exists and if not, just call it TTSOUT_
+                        voice_description = "\033[36mCharacter (Text-not-inside)\033[0m" if non_quoted_text_is else "\033[92mNarrator (Text-not-inside)\033[0m"
-                    if "character_menu" in state:
+                        print(f"[{params['branding']}TTSGen] {voice_description}")
-                        output_file = Path(f'{params["output_folder_wav"]}/{state["character_menu"]}_{int(time.time())}_{i}.wav')
+
-                    else:
+                    # Replace multiple exclamation marks, question marks, or other punctuation with a single instance
-                        output_file = Path(f'{params["output_folder_wav"]}/TTSOUT_{int(time.time())}_{i}.wav')
+                    cleaned_part = re.sub(r'([!?.])\1+', r'\1', part)
-                    # Generate that TTS and output to a file
+                    # Further clean to remove any other unwanted characters
-                    output_file_str = output_file.as_posix()
+                    cleaned_part = re.sub(r'[^a-zA-Z0-9\s\.,;:!?\-\'"\u0400-\u04FFÀ-ÿ\u0150\u0151\u0170\u0171\$]', '', cleaned_part)
                    # Remove all newline characters (single or multiple)
                    cleaned_part = re.sub(r'\n+', ' ', cleaned_part)
                    # Generate TTS and output to a file
                    output_filename = get_output_filename(state)
                    generate_response = send_generate_request(
-                        cleaned_part, voice_to_use, language_code, output_file_str
+                        cleaned_part, voice_to_use, language_code, output_filename
                    )
                    audio_path = generate_response.get("data", {}).get("audio_path")
-                    audio_files_paragraph.append(audio_path)
+                    audio_files_all_paragraphs.append(audio_path)
-                # Accumulate audio files within the paragraph
+
                audio_files_all_paragraphs.extend(audio_files_paragraph)
                # Combine audio files across paragraphs
                final_output_file = combine(
                    audio_files_all_paragraphs, params["output_folder_wav"], state
                )
            else:
-                processed_string = (
+                # Decode HTML entities first
-                    original_string
+                cleaned_part = html.unescape(original_string)
-                    .replace("***", "")
+                # Replace multiple instances of certain punctuation marks with a single instance
-                    .replace("**", "")
+                cleaned_part = re.sub(r'([!?.])\1+', r'\1', cleaned_part)
-                    .replace("*", "")
+                # Further clean to remove any other unwanted characters
-                    .replace("\n\n", "\n")
+                cleaned_part = re.sub(r'[^a-zA-Z0-9\s\.,;:!?\-\'"\u0400-\u04FFÀ-ÿ\u0150\u0151\u0170\u0171\$]', '', cleaned_part)
-                    .replace("&#x27;", "'")
+                # Remove all newline characters (single or multiple)
-                )
+                cleaned_part = re.sub(r'\n+', ' ', cleaned_part)
                cleaned_part = html.unescape(processed_string)                
                # Process the part and give it a non-character name if being used vai API or standalone.
                if "character_menu" in state:
                    output_file = Path(f'{params["output_folder_wav"]}/{state["character_menu"]}_{int(time.time())}.wav')
@@ -627,9 +675,10 @@ def output_modifier(string, state):
 def get_output_filename(state):
-    return Path(
+    if "character_menu" in state:
-        f'{params["output_folder_wav"]}/{state["character_menu"]}_{str(uuid.uuid4())[:8]}.wav'
+        return Path(f'{params["output_folder_wav"]}/{state["character_menu"]}_{str(uuid.uuid4())[:8]}.wav').as_posix()
-    ).as_posix()
+    else:
        return Path(f'{params["output_folder_wav"]}/TTSOUT_{str(uuid.uuid4())[:8]}.wav').as_posix()
 ###############################################
@@ -685,112 +734,58 @@ def input_modifier(string, state):
    shared.processing_message = "*Is recording a voice message...*"
    return string
 def custom_css():
    path_to_css = Path(f"{this_dir}/style.css")
    return open(path_to_css, "r").read()
 def ui():
    with gr.Accordion(params["branding"] + " TTS (XTTSv2)"):
        with gr.Row():
-            activate = gr.Checkbox(value=params["activate"], label="Activate TTS")
+            activate = gr.Checkbox(value=params['activate'], label='Enable TTS')
-            autoplay = gr.Checkbox(
+            autoplay = gr.Checkbox(value=params['autoplay'], label='Autoplay TTS')
-                value=params["autoplay"], label="Play TTS automatically"
+            show_text = gr.Checkbox(value=params['show_text'], label='Show Text')
            )
        with gr.Row():
-            show_text = gr.Checkbox(
+            low_vram = gr.Checkbox(value=params['low_vram'], label='Enable Low VRAM Mode')
                value=params["show_text"], label="Show message text under audio player"
            )
            remove_trailing_dots = gr.Checkbox(
                value=params["remove_trailing_dots"],
                label='Remove trailing "." from text segments before generation',
            )
        with gr.Row():
            with gr.Row():
                available_voices = get_available_voices()
                default_voice = params["voice"]
                # Check if the default voice is in the list of available voices
                if default_voice not in available_voices:
                    # Handle the case where the default voice is not in the list (choose a default value or update it)
                    default_voice = available_voices[
                        0
                    ]  # Choose the first available voice as the default
                # Add allow_custom_value=True to the Dropdown
                voice = gr.Dropdown(
                    available_voices,
                    label="Default Voice",
                    value=default_voice,
                    allow_custom_value=True,
                )
                create_refresh_button(
                    voice,
                    lambda: None,
                    lambda: {
                        "choices": get_available_voices(),
                        "value": params["voice"],
                    },
                    "refresh-button",
                )
            language = gr.Dropdown(
                languages.keys(),
                label="Language",
                allow_custom_value=True,
                value=params["language"],
            )
        with gr.Row():
            with gr.Row():
                narrator_voice_gr = gr.Dropdown(
                    get_available_voices(),
                    label="Narrator Voice",
                    allow_custom_value=True,
                    value=params["narrator_voice"],
                )
                create_refresh_button(
                    narrator_voice_gr,
                    lambda: None,
                    lambda: {
                        "choices": get_available_voices(),
                        "value": params["narrator_voice"],
                    },
                    "refresh-button",
                )
                narrator_enabled_gr = gr.Radio(
                    choices={"Enabled": "true", "Disabled": "false"},
                    label="Narrator Activation",
                    value="Enabled" if params.get("narrator_enabled") else "Disabled",
                )
                non_quoted_text_is_gr = gr.Radio(
                    choices={"Char": "true", "Narrator": "false"},
                    label='Text NOT inside of * or " is',
                    value="Char" if non_quoted_text_is else "Narrator",
                )
        with gr.Row():
            low_vram = gr.Checkbox(
                value=params["low_vram"], label="Low VRAM mode (Read NOTE)"
            )
            low_vram_play = gr.HTML(visible=False)
-            deepspeed_checkbox = gr.Checkbox(
+            deepspeed_checkbox = gr.Checkbox(value=params['deepspeed_activate'], label='Enable DeepSpeed', visible=deepspeed_installed)
                value=params["deepspeed_activate"],
                label="Activate DeepSpeed (Read NOTE)",
                visible=deepspeed_installed,
            )
            deepspeed_checkbox_play = gr.HTML(visible=False)
            remove_trailing_dots = gr.Checkbox(value=params['remove_trailing_dots'], label='Remove trailing "."')
        with gr.Row():
            model_loader_choices=["API TTS", "API Local", "XTTSv2 Local"]
            if finetuned_model:
                model_loader_choices.append("XTTSv2 FT")
            tts_radio_buttons = gr.Radio(
-                choices=["API TTS", "API Local", "XTTSv2 Local"],
+                choices=model_loader_choices,
-                label="Select TTS Generation Method (Read NOTE)",
+                label="TTS Method (Each method sounds slightly different)",
                value=gr_modelchoice,  # Set the default value
            )
            tts_radio_buttons_play = gr.HTML(visible=False)
            with gr.Row():
                available_voices = get_available_voices()
                default_voice = params["voice"] # Check if the default voice is in the list of available voices
                if default_voice not in available_voices:
                    default_voice = available_voices[ 0 ] # Choose the first available voice as the default
                # Add allow_custom_value=True to the Dropdown
                voice = gr.Dropdown(available_voices, label="Character Voice", value=default_voice, allow_custom_value=True, )
                create_refresh_button(voice, lambda: None, lambda: {"choices": get_available_voices(), "value": params["voice"],}, "refresh-button",)
        with gr.Row():
            language = gr.Dropdown(languages.keys(), label="Language", value=params["language"])
            with gr.Row():
                narrator_voice_gr = gr.Dropdown(get_available_voices(), label="Narrator Voice", allow_custom_value=True, value=params["narrator_voice"])
                create_refresh_button(narrator_voice_gr, lambda: None, lambda: {"choices": get_available_voices(), "value": params["narrator_voice"],}, "refresh-button")
        # Temperature and Repetition Penalty (Not yet parsed to api/implemented)
        # with gr.Row():
        #     local_temperature_gr = gr.Slider(minimum=0, maximum=1, step=0.05, label="Temperature", value=params["local_temperature"])
        #     local_repetition_penalty_gr = gr.Slider(minimum=0, maximum=20, step=0.5, label="Repetition Penalty", value=params["local_repetition_penalty"])
        with gr.Row():
            with gr.Row():
                narrator_enabled_gr = gr.Radio(choices={"Enabled": "true", "Disabled": "false"}, label="Narrator", value="Enabled" if params.get("narrator_enabled") else "Disabled")
                non_quoted_text_is_gr = gr.Radio(choices={"Character": "true", "Narrator": "false"}, label='Unmarked text NOT inside of * or " is', value="Character" if non_quoted_text_is else "Narrator")
                explanation_text = gr.HTML(
-                f"<p>NOTE: Switching Model Type, Low VRAM & DeepSpeed takes 15 seconds. Each TTS generation method has a slightly different sound. DeepSpeed checkbox is only visible if DeepSpeed is present. Readme & Settings: <a href='http://{params['ip_address']}:{params['port_number']}'>http://{params['ip_address']}:{params['port_number']}</a>"
+                f"<p>⚙️ <a href='http://{params['ip_address']}:{params['port_number']}'>Settings and Documentation Page</a><a href='http://{params['ip_address']}:{params['port_number']}'></a>⚙️<br>- Low VRAM Mode and Deepspeed take 15 seconds to be enabled or disabled.<br>- The DeepSpeed checkbox is only visible if DeepSpeed is present.</p>")
            )
        with gr.Row():
            preview_text = gr.Text(
@@ -869,6 +864,11 @@ def ui():
    voice.change(lambda x: params.update({"voice": x}), voice, None)
    language.change(lambda x: params.update({"language": x}), language, None)
    # TS Settings (Not yet parsed to api/implemented)
    # local_temperature_gr.change(lambda x: params.update({"local_temperature": x}), local_temperature_gr, None)
    # local_repetition_penalty_gr.change(lambda x: params.update({"local_repetition_penalty": x}), local_repetition_penalty_gr, None)
    # Narrator selection actions
    narrator_enabled_gr.change(update_narrator_enabled, narrator_enabled_gr, None)
    non_quoted_text_is_gr.change(update_non_quoted_text_is, non_quoted_text_is_gr, None)
@@ -1,8 +0,0 @@
 .SDAP .hires_opts input[type="number"] {
    width: 6em !important;
 }
 /* silero_tts preview */
 .form:has(> #silero_preview_text) {
    min-width: 75%
 }
@@ -0,0 +1,938 @@
 import { doExtrasFetch, getApiUrl, modules } from '../../extensions.js';
 import { saveTtsProviderSettings } from './index.js';
 export { AllTalkTtsProvider };
 const css = `
 .settings-row {
    display: flex;
    justify-content: space-between; /* Distribute space evenly between the children */
    align-items: center;
    width: 100%; /* Full width to spread out the children */
 }
 .settings-option {
    flex: 1; /* Each child will take equal space */
    margin: 0 10px; /* Adjust spacing as needed */
 }
 .endpoint-option {
    flex: 1; /* Each child will take equal space */
    margin: 0 10px; /* Adjust spacing as needed */
    margin-right: 25px;
    width: 38%; /* Full width to spread out the children */
 }
 .website-row {
    display: flex;
    justify-content: start; /* Aligns items to the start of the row */
    align-items: center;
    margin-top: 10px; /* Top margin */
    margin-bottom: 10px; /* Bottom margin */
 }
 .website-option {
    flex: 1; /* Allows each option to take equal space */
    margin-right: 10px; /* Spacing between the two options, adjust as needed */
    margin-left: 10px; /* Adjust this value to align as desired */
    /* Remove the individual margin top and bottom declarations if they are set globally on the .settings-row */
 }
 .settings-separator {
    margin-top: 10px;
    margin-bottom: 10px;
    padding: 18x;
    font-weight: bold;
    border-top: 1px solid #e1e1e1; /* Grey line */
    border-bottom: 1px solid #e1e1e1; /* Grey line */
    text-align: center;
 }
 .status-message {
    flex: 1; /* Adjust as needed */
    margin: 0 10px;
    /* Additional styling */
 }
 .model-endpoint-row {
    display: flex;
    justify-content: space-between;
    align-items: center;
    width: 100%;
 }
 .model-option, .endpoint-option {
    flex: 1;
    margin: 0 10px;
    margin-left: 10px; /* Adjust this value to align as desired */
    /* Adjust width as needed to fit in one line */
 }
 .endpoint-option {
    /* Adjust width to align with model dropdown */
    width: 38%;
 }
 #status_info {
    color: lightgreen; /* Or any specific shade of green you prefer */
 }
 `;
 const style = document.createElement('style');
 style.type = 'text/css';
 style.appendChild(document.createTextNode(css));
 document.head.appendChild(style);
 class AllTalkTtsProvider {
    //########//
    // Config //
    //########//
    settings;
    ready = false;
    voices = [];
    separator = '. ';
    audioElement = document.createElement('audio');
    languageLabels = {
        'Arabic': 'ar',
        'Brazilian Portuguese': 'pt',
        'Chinese': 'zh-cn',
        'Czech': 'cs',
        'Dutch': 'nl',
        'English': 'en',
        'French': 'fr',
        'German': 'de',
        'Italian': 'it',
        'Polish': 'pl',
        'Russian': 'ru',
        'Spanish': 'es',
        'Turkish': 'tr',
        'Japanese': 'ja',
        'Korean': 'ko',
        'Hungarian': 'hu',
        'Hindi': 'hi',
    };
    Settings = {
        provider_endpoint: 'http://localhost:7851',
        language: 'en',
        voiceMap: {},
        at_generation_method: 'standard_generation',
        narrator_enabled: 'false',
        at_narrator_text_not_inside: 'narrator',
        narrator_voice_gen: 'female_01.wav',
        finetuned_model: 'false'
    };
    get settingsHtml() {
        let html = `<div class="settings-separator">AllTalk Settings</div>`;
        html += `<div class="settings-row">
        <div class="settings-option">
            <label for="at_generation_method">AllTalk TTS Generation Method</label>
                <select id="at_generation_method">
                <option value="standard_generation">Standard Audio Generation (AT Narrator - Optional)</option>
                <option value="streaming_enabled">Streaming Audio Generation (AT Narrator - Disabled)</option>
        </select>
        </div>
        </div>`;
        html += `<div class="settings-row">
        <div class="settings-option">
            <label for="at_narrator_enabled">AT Narrator</label>
                <select id="at_narrator_enabled">
                <option value="true">Enabled</option>
                <option value="false">Disabled</option>
        </select>
        </div>
        <div class="settings-option">
            <label for="at_narrator_text_not_inside">Text Not Inside * or " is</label>
                <select id="at_narrator_text_not_inside">
                <option value="narrator">Narrator</option>
                <option value="character">Character</option>
        </select>
        </div>
    </div>`;
        html += `<div class="settings-row">
        <div class="settings-option">
            <label for="narrator_voice">Narrator Voice</label>
            <select id="narrator_voice">`;
        if (this.voices) {
            for (let voice of this.voices) {
                html += `<option value="${voice.voice_id}">${voice.name}</option>`;
            }
        }
        html += `</select>
        </div>
        <div class="settings-option">
            <label for="language_options">Language</label>
            <select id="language_options">`;
        for (let language in this.languageLabels) {
            html += `<option value="${this.languageLabels[language]}" ${this.languageLabels[language] === this.settings?.language ? 'selected="selected"' : ''}>${language}</option>`;
        }
        html += `</select>
        </div>
    </div>`;
        html += `<div class="model-endpoint-row">
    <div class="model-option">
            <label for="switch_model">Switch Model</label>
            <select id="switch_model">
            <option value="api_tts">API TTS</option>
            <option value="api_local">API Local</option>
            <option value="xttsv2_local">XTTSv2 Local</option>
        </select>
        </div>
        <div class="endpoint-option">
            <label for="at_server">AllTalk Endpoint:</label>
            <input id="at_server" type="text" class="text_pole" maxlength="80" value="${this.Settings.provider_endpoint}"/>
        </div>
   </div>`;
        html += `<div class="model-endpoint-row">
    <div class="settings-option">
        <label for="low_vram">Low VRAM</label>
        <input id="low_vram" type="checkbox"/>
    </div>
    <div class="settings-option">
        <label for="deepspeed">DeepSpeed</label>
        <input id="deepspeed" type="checkbox"/>
    </div>
    <div class="settings-option status-option">
        <span>Status: <span id="status_info">Ready</span></span>
    </div>
    <div class="settings-option empty-option">
        <!-- This div remains empty for spacing -->
    </div>
 </div>`;
        html += `<div class="website-row">
        <div class="website-option">
        <span>AllTalk <a target="_blank" href="${this.Settings.provider_endpoint}">Config & Docs</a>.</span>
    </div>
    <div class="website-option">
        <span>AllTalk <a target="_blank" href="https://github.com/erew123/alltalk_tts/">Website</a>.</span>
    </div>
 </div>`;
 html += `<div class="website-row">
 <div class="website-option">
 <span><strong>Text-generation-webui</strong> users - Uncheck <strong>Enable TTS</strong> in Text-generation-webui.</span>
 </div>
 </div>`;
        return html;
    }
    //#################//
    // Startup ST & AT //
    //#################//
    async loadSettings(settings) {
        updateStatus('Offline');
        // Use default settings if no settings are provided
        this.settings = Object.keys(settings).length === 0 ? this.Settings : settings;
        try {
            // Check if TTS provider is ready
            await this.checkReady();
            await this.fetchTtsVoiceObjects(); // Fetch voices only if service is ready
            await this.updateSettingsFromServer();
            this.updateNarratorVoicesDropdown();
            this.updateLanguageDropdown();
            this.setupEventListeners();
            this.applySettingsToHTML();
            updateStatus('Ready');
        } catch (error) {
            console.error("Error loading settings:", error);
            // Set status to Error if there is an issue in loading settings
            updateStatus('Offline');
        }
    }
    applySettingsToHTML() {
        // Load AllTalk specific settings first
        const loadedSettings = loadAllTalkSettings();
        // Apply loaded settings or use defaults
        this.settings = loadedSettings ? { ...this.Settings, ...loadedSettings } : this.Settings;
        const narratorVoiceSelect = document.getElementById('narrator_voice');
        const atNarratorSelect = document.getElementById('at_narrator_enabled');
        const textNotInsideSelect = document.getElementById('at_narrator_text_not_inside');
        const generationMethodSelect = document.getElementById('at_generation_method');
        // Apply settings to Narrator Voice dropdown
        if (narratorVoiceSelect && this.settings.narrator_voice) {
            narratorVoiceSelect.value = this.settings.narrator_voice.replace('.wav', '');
            this.settings.narrator_voice_gen = this.settings.narrator_voice;
            //console.log(this.settings.narrator_voice_gen)
        }
        // Apply settings to AT Narrator Enabled dropdown
        if (atNarratorSelect) {
            //console.log(this.settings.narrator_enabled)
            // Sync the state with the checkbox in index.js
            const ttsPassAsterisksCheckbox = document.getElementById('tts_pass_asterisks'); // Access the checkbox from index.js
            const ttsNarrateQuotedCheckbox = document.getElementById('tts_narrate_quoted'); // Access the checkbox from index.js
            const ttsNarrateDialoguesCheckbox = document.getElementById('tts_narrate_dialogues'); // Access the checkbox from index.js
            // Sync the state with the checkbox in index.js
            if (this.settings.narrator_enabled) {
                ttsPassAsterisksCheckbox.checked = false;
                $('#tts_pass_asterisks').click(); // Simulate a click event
                $('#tts_pass_asterisks').trigger('change');
            }
            if (!this.settings.narrator_enabled) {
                ttsPassAsterisksCheckbox.checked = true;
                $('#tts_pass_asterisks').click(); // Simulate a click event
                $('#tts_pass_asterisks').trigger('change');
            }
            // Uncheck and set tts_narrate_quoted to false if narrator is enabled
            if (this.settings.narrator_enabledd) {
                ttsNarrateQuotedCheckbox.checked = true;
                ttsNarrateDialoguesCheckbox.checked = true;
                // Trigger click events instead of change events
                $('#tts_narrate_quoted').click();
                $('#tts_narrate_quoted').trigger('change');
                $('#tts_narrate_dialogues').click();
                $('#tts_narrate_dialogues').trigger('change');
            }
            atNarratorSelect.value = this.settings.narrator_enabled.toString();
            this.settings.narrator_enabled = this.settings.narrator_enabled.toString();
        }
        // Apply settings to the Language dropdown
        const languageSelect = document.getElementById('language_options');
        if (languageSelect && this.settings.language) {
            languageSelect.value = this.settings.language;
            //console.log(this.settings.language)
        }
        // Apply settings to Text Not Inside dropdown
        if (textNotInsideSelect && this.settings.text_not_inside) {
            textNotInsideSelect.value = this.settings.text_not_inside;
            this.settings.at_narrator_text_not_inside = this.settings.text_not_inside;
            //console.log(this.settings.at_narrator_text_not_inside)
        }
        // Apply settings to Generation Method dropdown
        if (generationMethodSelect && this.settings.at_generation_method) {
            generationMethodSelect.value = this.settings.at_generation_method;
            //console.log(this.settings.at_generation_method)
        }
        // Additional logic to disable/enable dropdowns based on the selected generation method
        const isStreamingEnabled = this.settings.at_generation_method === 'streaming_enabled';
        if (isStreamingEnabled) {
            // Disable certain dropdowns when streaming is enabled
            if (atNarratorSelect) atNarratorSelect.disabled = true;
            if (textNotInsideSelect) textNotInsideSelect.disabled = true;
            if (narratorVoiceSelect) narratorVoiceSelect.disabled = true;
        } else {
            // Enable dropdowns for standard generation
            if (atNarratorSelect) atNarratorSelect.disabled = false;
            if (textNotInsideSelect) textNotInsideSelect.disabled = !this.settings.narrator_enabled;
            if (narratorVoiceSelect) narratorVoiceSelect.disabled = !this.settings.narrator_enabled;
        }
        const modelSelect = document.getElementById('switch_model');
        if (this.settings.finetuned_model === 'true') {
            const ftOption = document.createElement('option');
            ftOption.value = 'XTTSv2 FT';
            ftOption.textContent = 'XTTSv2 FT';
            modelSelect.appendChild(ftOption);
        }
        //console.log("Settings applied to HTML.");
    }
    //##############################//
    // Check AT Server is Available //
    //##############################//
    async checkReady() {
        try {
            const response = await fetch(`${this.settings.provider_endpoint}/api/ready`);
            // Check if the HTTP request was successful
            if (!response.ok) {
                throw new Error(`HTTP Error Response: ${response.status} ${response.statusText}`);
            }
            const statusText = await response.text();
            // Check if the response is 'Ready'
            if (statusText === 'Ready') {
                this.ready = true; // Set the ready flag to true
                console.log('TTS service is ready.');
            } else {
                this.ready = false;
                console.log('TTS service is not ready.');
            }
        } catch (error) {
            console.error('Error checking TTS service readiness:', error);
            this.ready = false; // Ensure ready flag is set to false in case of error
        }
    }
    //######################//
    // Get Available Voices //
    //######################//
    async fetchTtsVoiceObjects() {
        const response = await fetch(`${this.settings.provider_endpoint}/api/voices`);
        if (!response.ok) {
            const errorText = await response.text();
            throw new Error(`HTTP ${response.status}: ${errorText}`);
        }
        const data = await response.json();
        const voices = data.voices.map(filename => {
            const voiceName = filename.replace('.wav', '');
            return {
                name: voiceName,
                voice_id: voiceName,
                preview_url: null, // Preview URL will be dynamically generated
                lang: 'en' // Default language
            };
        });
        this.voices = voices; // Assign to the class property
        return voices; // Also return this list
    }
    //##########################################//
    // Get Current AT Server Config & Update ST //
    //##########################################//
    async updateSettingsFromServer() {
        try {
            // Fetch current settings
            const response = await fetch(`${this.settings.provider_endpoint}/api/currentsettings`);
            if (!response.ok) {
                throw new Error(`Failed to fetch current settings: ${response.statusText}`);
            }
            const currentSettings = await response.json();
            // Update internal settings
            this.settings.modelsAvailable = currentSettings.models_available;
            this.settings.currentModel = currentSettings.current_model_loaded;
            this.settings.deepspeed_available = currentSettings.deepspeed_available;
            this.settings.deepSpeedEnabled = currentSettings.deepspeed_status;
            this.settings.lowVramEnabled = currentSettings.low_vram_status;
            this.settings.finetuned_model = currentSettings.finetuned_model
            // Update HTML elements
            this.updateModelDropdown();
            this.updateCheckboxes();
        } catch (error) {
            console.error(`Error updating settings from server: ${error}`);
        }
    }
    //###################################################//
    // Get Current AT Server Config & Update ST (Models) //
    //###################################################//
    updateModelDropdown() {
        const modelSelect = document.getElementById('switch_model');
        if (modelSelect) {
            modelSelect.innerHTML = ''; // Clear existing options
            this.settings.modelsAvailable.forEach(model => {
                const option = document.createElement('option');
                option.value = model.model_name;
                option.textContent = model.model_name; // Use model_name instead of name
                option.selected = model.model_name === this.settings.currentModel;
                modelSelect.appendChild(option);
            });
        }
    }
    //#######################################################//
    // Get Current AT Server Config & Update ST (DS and LVR) //
    //#######################################################//
    updateCheckboxes() {
        const deepspeedCheckbox = document.getElementById('deepspeed');
        const lowVramCheckbox = document.getElementById('low_vram');
        if (lowVramCheckbox) lowVramCheckbox.checked = this.settings.lowVramEnabled;
        if (deepspeedCheckbox) {
            deepspeedCheckbox.checked = this.settings.deepSpeedEnabled;
            deepspeedCheckbox.disabled = !this.settings.deepspeed_available; // Disable checkbox if deepspeed is not available
        }
    }
    //###############################################################//
    // Get Current AT Server Config & Update ST (AT Narrator Voices) //
    //###############################################################//
    updateNarratorVoicesDropdown() {
        const narratorVoiceSelect = document.getElementById('narrator_voice');
        if (narratorVoiceSelect && this.voices) {
            // Clear existing options
            narratorVoiceSelect.innerHTML = '';
            // Add new options
            for (let voice of this.voices) {
                const option = document.createElement('option');
                option.value = voice.voice_id;
                option.textContent = voice.name;
                narratorVoiceSelect.appendChild(option);
            }
        }
    }
    //######################################################//
    // Get Current AT Server Config & Update ST (Languages) //
    //######################################################//
    updateLanguageDropdown() {
        const languageSelect = document.getElementById('language_options');
        if (languageSelect) {
            // Ensure default language is set
            this.settings.language = this.Settings.language;
            languageSelect.innerHTML = '';
            for (let language in this.languageLabels) {
                const option = document.createElement('option');
                option.value = this.languageLabels[language];
                option.textContent = language;
                if (this.languageLabels[language] === this.settings.language) {
                    option.selected = true;
                }
                languageSelect.appendChild(option);
            }
        }
    }
    //########################################//
    // Start AT TTS extenstion page listeners //
    //########################################//
    setupEventListeners() {
        let debounceTimeout;
        const debounceDelay = 500; // Milliseconds
        // Define the event handler function
        const onModelSelectChange = async (event) => {
            console.log("Model select change event triggered"); // Debugging statement
            const selectedModel = event.target.value;
            console.log(`Selected model: ${selectedModel}`); // Debugging statement 
            // Set status to Processing
            updateStatus('Processing');
            try {
                const response = await fetch(`${this.settings.provider_endpoint}/api/reload?tts_method=${encodeURIComponent(selectedModel)}`, {
                    method: 'POST'
                });
                if (!response.ok) {
                    throw new Error(`HTTP Error: ${response.status}`);
                }
                const data = await response.json();
                console.log("POST response data:", data); // Debugging statement 
                // Set status to Ready if successful
                updateStatus('Ready');
            } catch (error) {
                console.error("POST request error:", error); // Debugging statement
                // Set status to Error in case of failure
                updateStatus('Error');
            }
            // Handle response or error
        };
        const debouncedModelSelectChange = (event) => {
            clearTimeout(debounceTimeout);
            debounceTimeout = setTimeout(() => {
                onModelSelectChange(event);
            }, debounceDelay);
        };
        // Switch Model Listener
        const modelSelect = document.getElementById('switch_model');
        if (modelSelect) {
            // Remove the event listener if it was previously added
            modelSelect.removeEventListener('change', debouncedModelSelectChange);
            // Add the debounced event listener
            modelSelect.addEventListener('change', debouncedModelSelectChange);
        }
        // DeepSpeed Listener
        const deepspeedCheckbox = document.getElementById('deepspeed');
        if (deepspeedCheckbox) {
            deepspeedCheckbox.addEventListener('change', async (event) => {
                const deepSpeedValue = event.target.checked ? 'True' : 'False';
                // Set status to Processing
                updateStatus('Processing');
                try {
                    const response = await fetch(`${this.settings.provider_endpoint}/api/deepspeed?new_deepspeed_value=${deepSpeedValue}`, {
                        method: 'POST'
                    });
                    if (!response.ok) {
                        throw new Error(`HTTP Error: ${response.status}`);
                    }
                    const data = await response.json();
                    console.log("POST response data:", data); // Debugging statement
                    // Set status to Ready if successful
                    updateStatus('Ready');
                } catch (error) {
                    console.error("POST request error:", error); // Debugging statement
                    // Set status to Error in case of failure
                    updateStatus('Error');
                }
            });
        }
        // Low VRAM Listener
        const lowVramCheckbox = document.getElementById('low_vram');
        if (lowVramCheckbox) {
            lowVramCheckbox.addEventListener('change', async (event) => {
                const lowVramValue = event.target.checked ? 'True' : 'False';
                // Set status to Processing
                updateStatus('Processing');
                try {
                    const response = await fetch(`${this.settings.provider_endpoint}/api/lowvramsetting?new_low_vram_value=${lowVramValue}`, {
                        method: 'POST'
                    });
                    if (!response.ok) {
                        throw new Error(`HTTP Error: ${response.status}`);
                    }
                    const data = await response.json();
                    console.log("POST response data:", data); // Debugging statement
                    // Set status to Ready if successful
                    updateStatus('Ready');
                } catch (error) {
                    console.error("POST request error:", error); // Debugging statement
                    // Set status to Error in case of failure
                    updateStatus('Error');
                }
            });
        }
        // Narrator Voice Dropdown Listener
        const narratorVoiceSelect = document.getElementById('narrator_voice');
        if (narratorVoiceSelect) {
            narratorVoiceSelect.addEventListener('change', (event) => {
                this.settings.narrator_voice_gen = `${event.target.value}.wav`;
                this.onSettingsChangeAllTalk(); // Save the settings after change
            });
        }
        const textNotInsideSelect = document.getElementById('at_narrator_text_not_inside');
        if (textNotInsideSelect) {
            textNotInsideSelect.addEventListener('change', (event) => {
                this.settings.text_not_inside = event.target.value;
                this.onSettingsChangeAllTalk(); // Save the settings after change
            });
        }
        // AT Narrator Dropdown Listener
        const atNarratorSelect = document.getElementById('at_narrator_enabled');
        const ttsPassAsterisksCheckbox = document.getElementById('tts_pass_asterisks'); // Access the checkbox from index.js
        const ttsNarrateQuotedCheckbox = document.getElementById('tts_narrate_quoted'); // Access the checkbox from index.js
        const ttsNarrateDialoguesCheckbox = document.getElementById('tts_narrate_dialogues'); // Access the checkbox from index.js
        if (atNarratorSelect && textNotInsideSelect && narratorVoiceSelect) {
            atNarratorSelect.addEventListener('change', (event) => {
                const isNarratorEnabled = event.target.value === 'true';
                this.settings.narrator_enabled = isNarratorEnabled; // Update the setting here
                textNotInsideSelect.disabled = !isNarratorEnabled;
                narratorVoiceSelect.disabled = !isNarratorEnabled;
                // Sync the state with the checkbox in index.js
                if (isNarratorEnabled) {
                    ttsPassAsterisksCheckbox.checked = false;
                    $('#tts_pass_asterisks').click(); // Simulate a click event
                    $('#tts_pass_asterisks').trigger('change');
                }
                if (!isNarratorEnabled) {
                    ttsPassAsterisksCheckbox.checked = true;
                    $('#tts_pass_asterisks').click(); // Simulate a click event
                    $('#tts_pass_asterisks').trigger('change');
                }
                // Uncheck and set tts_narrate_quoted to false if narrator is enabled
                if (isNarratorEnabled) {
                    ttsNarrateQuotedCheckbox.checked = true;
                    ttsNarrateDialoguesCheckbox.checked = true;
                    // Trigger click events instead of change events
                    $('#tts_narrate_quoted').click();
                    $('#tts_narrate_quoted').trigger('change');
                    $('#tts_narrate_dialogues').click();
                    $('#tts_narrate_dialogues').trigger('change');
                }
                this.onSettingsChangeAllTalk(); // Save the settings after change
            });
        }
        // Event Listener for AT Generation Method Dropdown
        const atGenerationMethodSelect = document.getElementById('at_generation_method');
        const atNarratorEnabledSelect = document.getElementById('at_narrator_enabled');
        if (atGenerationMethodSelect) {
            atGenerationMethodSelect.addEventListener('change', (event) => {
                const selectedMethod = event.target.value;
                if (selectedMethod === 'streaming_enabled') {
                    // Disable and unselect AT Narrator
                    atNarratorEnabledSelect.disabled = true;
                    atNarratorEnabledSelect.value = 'false';
                    textNotInsideSelect.disabled = true;
                    narratorVoiceSelect.disabled = true;
                } else if (selectedMethod === 'standard_generation') {
                    // Enable AT Narrator
                    atNarratorEnabledSelect.disabled = false;
                }
                this.settings.at_generation_method = selectedMethod; // Update the setting here
                this.onSettingsChangeAllTalk(); // Save the settings after change
            });
        }
        // Listener for Language Dropdown
        const languageSelect = document.getElementById('language_options');
        if (languageSelect) {
            languageSelect.addEventListener('change', (event) => {
                this.settings.language = event.target.value;
                this.onSettingsChangeAllTalk(); // Save the settings after change
            });
        }
    }
    //#############################//
    // Store ST interface settings //
    //#############################//
    onSettingsChange() {
        // Update settings that SillyTavern will save
        this.settings.provider_endpoint = $('#at_server').val();
        this.settings.language = $('#language_options').val();
        saveTtsProviderSettings(); // This function should save settings handled by SillyTavern
        // Call the function to handle AllTalk specific settings
        this.onSettingsChangeAllTalk(); // Save the settings after change
    }
    onSettingsChangeAllTalk() {
        // Update AllTalk specific settings and save to localStorage
        this.settings.narrator_enabled = $('#at_narrator_enabled').val() === 'true';
        this.settings.narrator_voice = $('#narrator_voice').val() + '.wav'; // assuming you need to append .wav
        this.settings.text_not_inside = $('#at_narrator_text_not_inside').val(); // "character" or "narrator"
        this.settings.at_generation_method = $('#at_generation_method').val(); // Streaming or standard
        this.settings.language = $('#language_options').val(); // Streaming or standard
        // Call the save function with the current settings
        saveAllTalkSettings({
            narrator_voice: this.settings.narrator_voice,
            narrator_enabled: this.settings.narrator_enabled,
            text_not_inside: this.settings.text_not_inside,
            at_generation_method: this.settings.at_generation_method,
            language: this.settings.language
        });
    }
    //#########################//
    // ST Handle Reload button //
    //#########################//
    async onRefreshClick() {
        await this.checkReady(); // Check if the TTS provider is ready
        await this.loadSettings(this.settings); // Reload the settings
        // Additional actions as needed
    }
    //##################//
    // Preview AT Voice //
    //##################//
    async previewTtsVoice(voiceName) {
        try {
            // Prepare data for POST request
            const postData = new URLSearchParams();
            postData.append("voice", `${voiceName}.wav`);
            // Making the POST request
            const response = await fetch(`${this.settings.provider_endpoint}/api/previewvoice/`, {
                method: "POST",
                headers: {
                    'Content-Type': 'application/x-www-form-urlencoded'
                },
                body: postData,
            });
            if (!response.ok) {
                const errorText = await response.text();
                console.error(`[previewTtsVoice] Error Response Text:`, errorText);
                throw new Error(`HTTP ${response.status}: ${errorText}`);
            }
            // Assuming the server returns a URL to the .wav file
            const data = await response.json();
            if (data.output_file_url) {
                // Use an audio element to play the .wav file
                const audioElement = new Audio(data.output_file_url);
                audioElement.play().catch(e => console.error("Error playing audio:", e));
            } else {
                console.warn("[previewTtsVoice] No output file URL received in the response");
                throw new Error("No output file URL received in the response");
            }
        } catch (error) {
            console.error("[previewTtsVoice] Exception caught during preview generation:", error);
            throw error;
        }
    }
    //#####################//
    //  Populate ST voices //
    //#####################//
    async getVoice(voiceName, generatePreview = false) {
        // Ensure this.voices is populated
        if (this.voices.length === 0) {
            // Fetch voice objects logic
        }
        // Find the object where the name matches voiceName
        const match = this.voices.find(voice => voice.name === voiceName);
        if (!match) {
            // Error handling
        }
        // Generate preview URL only if requested
        if (!match.preview_url && generatePreview) {
            // Generate preview logic
        }
        return match; // Return the found voice object
    }
    //##########################################//
    //  Generate TTS Streaming or call Standard //
    //##########################################//
    async generateTts(inputText, voiceId) {
        try {
            if (this.settings.at_generation_method === 'streaming_enabled') {
                // For streaming method
                const streamingUrl = `${this.settings.provider_endpoint}/api/tts-generate-streaming?text=${encodeURIComponent(inputText)}&voice=${encodeURIComponent(voiceId)}.wav&language=${encodeURIComponent(this.settings.language)}&output_file=stream_output.wav`;
                const audioElement = new Audio(streamingUrl);
                audioElement.play(); // Play the audio stream directly
                console.log("Streaming URL:", streamingUrl);
                return new Response(null, {
                    status: 200,
                    statusText: "OK",
                    headers: {
                        "Content-Type": "audio/wav",
                        "Content-Location": streamingUrl
                    }
                });
            } else {
                // For standard method
                const outputUrl = await this.fetchTtsGeneration(inputText, voiceId);
                // Fetch the audio data as a blob from the URL
                const audioResponse = await fetch(outputUrl);
                if (!audioResponse.ok) {
                    throw new Error(`HTTP ${audioResponse.status}: Failed to fetch audio data`);
                }
                const audioBlob = await audioResponse.blob();
                if (!audioBlob.type.startsWith('audio/')) {
                    throw new Error(`Invalid audio data format. Expecting audio/*, got ${audioBlob.type}`);
                }
                return new Response(audioBlob, {
                    status: 200,
                    statusText: "OK",
                    headers: {
                        "Content-Type": audioBlob.type
                    }
                });
            }
        } catch (error) {
            console.error("Error in generateTts:", error);
            throw error;
        }
    }
    //####################//
    //  Generate Standard //
    //####################//
    async fetchTtsGeneration(inputText, voiceId) {
        // Prepare the request payload
        const requestBody = new URLSearchParams({
            'text_input': inputText,
            'text_filtering': "standard",
            'character_voice_gen': voiceId + ".wav",
            'narrator_enabled': this.settings.narrator_enabled,
            'narrator_voice_gen': this.settings.narrator_voice_gen,
            'text_not_inside': this.settings.text_not_inside,
            'language': this.settings.language,
            'output_file_name': "st_output",
            'output_file_timestamp': "true",
            'autoplay': "false",
            'autoplay_volume': "0.8"
        }).toString();
        try {
            const response = await doExtrasFetch(
                `${this.settings.provider_endpoint}/api/tts-generate`,
                {
                    method: 'POST',
                    headers: {
                        'Content-Type': 'application/x-www-form-urlencoded',
                        'Cache-Control': 'no-cache',
                    },
                    body: requestBody
                }
            );
            if (!response.ok) {
                const errorText = await response.text();
                console.error(`[fetchTtsGeneration] Error Response Text:`, errorText);
                // Uncomment the following line if you have a UI element for displaying errors
                // toastr.error(response.statusText, 'TTS Generation Failed');
                throw new Error(`HTTP ${response.status}: ${errorText}`);
            }
            const data = await response.json();
            const outputUrl = data.output_file_url;
            return outputUrl; // Return only the output_file_url
        } catch (error) {
            console.error("[fetchTtsGeneration] Exception caught:", error);
            throw error; // Rethrow the error for further handling
        }
    }
 }
 //#########################//
 //  Update Status Messages //
 //#########################//
 function updateStatus(message) {
    const statusElement = document.getElementById('status_info');
    if (statusElement) {
        statusElement.textContent = message;
        switch (message) {
            case 'Offline':
                statusElement.style.color = 'red';
                break;
            case 'Ready':
                statusElement.style.color = 'lightgreen';
                break;
            case 'Processing':
                statusElement.style.color = 'blue';
                break;
            case 'Error':
                statusElement.style.color = 'red';
                break;
            // Add more cases as needed
        }
    }
 }
 //########################//
 //  Save/load AT Settings //
 //########################//
 function saveAllTalkSettings(settingsToSave) {
    // Save the specific settings to localStorage
    console.log("settings", settingsToSave)
    localStorage.setItem('AllTalkSettings', JSON.stringify(settingsToSave));
 }
 function loadAllTalkSettings() {
    // Retrieve the settings from localStorage
    const settings = localStorage.getItem('AllTalkSettings');
    // If settings exist, parse them back into an object
    if (settings) {
        return JSON.parse(settings);
    }
    return null;
 }
@@ -201,12 +201,12 @@
            value="{{ data.output_folder_wav }}" />
-        <input type="hidden" id="model_loaded" name="model_loaded" value="{{ data.model_loaded }}" />
+        <input type="hidden" id="tts_model_loaded" name="tts_model_loaded" value="{{ data.tts_model_loaded }}" />
        <!-- Continue updating other dropdowns and inputs in a similar manner -->
-        <label for="model_name" style="color: red;"> API TTS Model Name:</label>
+        <label for="tts_model_name" style="color: red;"> API TTS Model Name:</label>
-        <input id="model_name" name="model_name" required="" type="text" value="{{ data.model_name }}" />
+        <input id="tts_model_name" name="tts_model_name" required="" type="text" value="{{ data.tts_model_name }}" />
        <label for="model_version"
            style="color: red; font-size: 16px; line-height: 1; vertical-align: bottom; margin-bottom: 0;">&nbsp;
@@ -0,0 +1,179 @@
 export interface CrunkerConstructorOptions {
    /**
     * Sample rate for Crunker's internal audio context.
     *
     * @default 44100
     */
    sampleRate: number;
 }
 export type CrunkerInputTypes = string | File | Blob;
 /**
 * An exported Crunker audio object.
 */
 export interface ExportedCrunkerAudio {
    blob: Blob;
    url: string;
    element: HTMLAudioElement;
 }
 /**
 * Crunker is the simple way to merge, concatenate, play, export and download audio files using the Web Audio API.
 */
 export default class Crunker {
    private readonly _sampleRate;
    private readonly _context;
    /**
     * Creates a new instance of Crunker with the provided options.
     *
     * If `sampleRate` is not defined, it will auto-select an appropriate sample rate
     * for the device being used.
     */
    constructor({ sampleRate }?: Partial<CrunkerConstructorOptions>);
    /**
     * Creates Crunker's internal AudioContext.
     *
     * @internal
     */
    private _createContext;
    /**
     *
     * The internal AudioContext used by Crunker.
     */
    get context(): AudioContext;
    /**
     * Asynchronously fetches multiple audio files and returns an array of AudioBuffers.
     */
    fetchAudio(...filepaths: CrunkerInputTypes[]): Promise<AudioBuffer[]>;
    /**
     * Merges (layers) multiple AudioBuffers into a single AudioBuffer.
     *
     * **Visual representation:**
     *
     * ![](https://user-images.githubusercontent.com/12958674/88806278-968f0680-d186-11ea-9cb5-8ef2606ffcc7.png)
     */
    mergeAudio(buffers: AudioBuffer[]): AudioBuffer;
    /**
     * Concatenates multiple AudioBuffers into a single AudioBuffer.
     *
     * **Visual representation:**
     *
     * ![](https://user-images.githubusercontent.com/12958674/88806297-9d1d7e00-d186-11ea-8cd2-c64cb0324845.png)
     */
    concatAudio(buffers: AudioBuffer[]): AudioBuffer;
    /**
     * Pads a specified AudioBuffer with silence from a specified start time,
     * for a specified length of time.
     *
     * Accepts float values as well as whole integers.
     *
     * @param buffer AudioBuffer to pad
     * @param padStart Time to start padding (in seconds)
     * @param seconds Duration to pad for (in seconds)
     */
    padAudio(buffer: AudioBuffer, padStart?: number, seconds?: number): AudioBuffer;
    /**
     * Slices an AudioBuffer from the specified start time to the end time, with optional fade in and out.
     *
     * @param buffer AudioBuffer to slice
     * @param start Start time (in seconds)
     * @param end End time (in seconds)
     * @param fadeIn Fade in duration (in seconds, default is 0)
     * @param fadeOut Fade out duration (in seconds, default is 0)
     */
    sliceAudio(buffer: AudioBuffer, start: number, end: number, fadeIn?: number, fadeOut?: number): AudioBuffer;
    /**
     * Plays the provided AudioBuffer in an AudioBufferSourceNode.
     */
    play(buffer: AudioBuffer): AudioBufferSourceNode;
    /**
     * Exports the specified AudioBuffer to a Blob, Object URI and HTMLAudioElement.
     *
     * Note that changing the MIME type does not change the actual file format. The
     * file format will **always** be a WAVE file due to how audio is stored in the
     * browser.
     *
     * @param buffer Buffer to export
     * @param type MIME type (default: `audio/wav`)
     */
    export(buffer: AudioBuffer, type?: string): ExportedCrunkerAudio;
    /**
     * Downloads the provided Blob.
     *
     * @param blob Blob to download
     * @param filename An optional file name to use for the download (default: `crunker`)
     */
    download(blob: Blob, filename?: string): HTMLAnchorElement;
    /**
     * Executes a callback if the browser does not support the Web Audio API.
     *
     * Returns the result of the callback, or `undefined` if the Web Audio API is supported.
     *
     * @param callback callback to run if the browser does not support the Web Audio API
     */
    notSupported<T>(callback: () => T): T | undefined;
    /**
     * Closes Crunker's internal AudioContext.
     */
    close(): this;
    /**
     * Returns the largest duration of the longest AudioBuffer.
     *
     * @internal
     */
    private _maxDuration;
    /**
     * Returns the largest number of channels in an array of AudioBuffers.
     *
     * @internal
     */
    private _maxNumberOfChannels;
    /**
     * Returns the sum of the lengths of an array of AudioBuffers.
     *
     * @internal
     */
    private _totalLength;
    /**
     * Returns whether the browser supports the Web Audio API.
     *
     * @internal
     */
    private _isSupported;
    /**
     * Writes the WAV headers for the specified Float32Array.
     *
     * Returns a DataView containing the WAV headers and file content.
     *
     * @internal
     */
    private _writeHeaders;
    /**
     * Converts a Float32Array to 16-bit PCM.
     *
     * @internal
     */
    private _floatTo16BitPCM;
    /**
     * Writes a string to a DataView at the specified offset.
     *
     * @internal
     */
    private _writeString;
    /**
     * Converts an AudioBuffer to a Float32Array.
     *
     * @internal
     */
    private _interleave;
    /**
     * Creates an HTMLAudioElement whose source is the specified Blob.
     *
     * @internal
     */
    private _renderAudioElement;
    /**
     * Creates an Object URL for the specified Blob.
     *
     * @internal
     */
    private _renderURL;
 }
@@ -0,0 +1,2 @@
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 /*! howler.js v2.2.4 | (c) 2013-2020, James Simpson of GoldFire Studios | MIT License | howlerjs.com */
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codecs="opus"').replace(/^no$/,""),ogg:!!o.canPlayType('audio/ogg; codecs="vorbis"').replace(/^no$/,""),oga:!!o.canPlayType('audio/ogg; codecs="vorbis"').replace(/^no$/,""),wav:!!(o.canPlayType('audio/wav; codecs="1"')||o.canPlayType("audio/wav")).replace(/^no$/,""),aac:!!o.canPlayType("audio/aac;").replace(/^no$/,""),caf:!!o.canPlayType("audio/x-caf;").replace(/^no$/,""),m4a:!!(o.canPlayType("audio/x-m4a;")||o.canPlayType("audio/m4a;")||o.canPlayType("audio/aac;")).replace(/^no$/,""),m4b:!!(o.canPlayType("audio/x-m4b;")||o.canPlayType("audio/m4b;")||o.canPlayType("audio/aac;")).replace(/^no$/,""),mp4:!!(o.canPlayType("audio/x-mp4;")||o.canPlayType("audio/mp4;")||o.canPlayType("audio/aac;")).replace(/^no$/,""),weba:!(_||!o.canPlayType('audio/webm; codecs="vorbis"').replace(/^no$/,"")),webm:!(_||!o.canPlayType('audio/webm; codecs="vorbis"').replace(/^no$/,"")),dolby:!!o.canPlayType('audio/mp4; codecs="ec-3"').replace(/^no$/,""),flac:!!(o.canPlayType("audio/x-flac;")||o.canPlayType("audio/flac;")).replace(/^no$/,"")},e},_unlockAudio:function(){var e=this||n;if(!e._audioUnlocked&&e.ctx){e._audioUnlocked=!1,e.autoUnlock=!1,e._mobileUnloaded||44100===e.ctx.sampleRate||(e._mobileUnloaded=!0,e.unload()),e._scratchBuffer=e.ctx.createBuffer(1,1,22050);var o=function(n){for(;e._html5AudioPool.length<e.html5PoolSize;)try{var t=new Audio;t._unlocked=!0,e._releaseHtml5Audio(t)}catch(n){e.noAudio=!0;break}for(var r=0;r<e._howls.length;r++)if(!e._howls[r]._webAudio)for(var a=e._howls[r]._getSoundIds(),u=0;u<a.length;u++){var d=e._howls[r]._soundById(a[u]);d&&d._node&&!d._node._unlocked&&(d._node._unlocked=!0,d._node.load())}e._autoResume();var i=e.ctx.createBufferSource();i.buffer=e._scratchBuffer,i.connect(e.ctx.destination),void 0===i.start?i.noteOn(0):i.start(0),"function"==typeof e.ctx.resume&&e.ctx.resume(),i.onended=function(){i.disconnect(0),e._audioUnlocked=!0,document.removeEventListener("touchstart",o,!0),document.removeEventListener("touchend",o,!0),document.removeEventListener("click",o,!0),document.removeEventListener("keydown",o,!0);for(var n=0;n<e._howls.length;n++)e._howls[n]._emit("unlock")}};return document.addEventListener("touchstart",o,!0),document.addEventListener("touchend",o,!0),document.addEventListener("click",o,!0),document.addEventListener("keydown",o,!0),e}},_obtainHtml5Audio:function(){var e=this||n;if(e._html5AudioPool.length)return e._html5AudioPool.pop();var o=(new Audio).play();return o&&"undefined"!=typeof Promise&&(o instanceof Promise||"function"==typeof o.then)&&o.catch(function(){console.warn("HTML5 Audio pool eLine truncated
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