Additional note in finetune re multiple GPU support

Merge pull request #34 from erew123/dev
Dev
2023-12-30 14:45:42 +00:00 · 2023-12-30 14:23:22 +00:00 · 2023-12-30 14:12:41 +00:00 · 2023-12-30 14:00:36 +00:00 · 2023-12-30 13:31:41 +00:00 · 2023-12-30 13:30:16 +00:00
13 changed files with 2383 additions and 88 deletions
@@ -1,6 +1,7 @@
 voices/*.*
 models/*.*
 outputs/*.*
 finetune/*.*
 config.json
 confignew.json
 models.json
@@ -2,14 +2,16 @@
 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)
- **Narrarator:** Use different voices for main character and narration. [Example Narration](https://vocaroo.com/18fYWVxiQpk1)
+- **Narrarator:** Use different voices for main character and narration. [Example Narration](https://vocaroo.com/18nrv7FR6wuA)
 - **Low VRAM mode:** Great for people with small GPU memory or 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)
 - **Finetuning** Train the model specifically on a voice of your choosing for better reproduction.
 - **Documentation:** Fully documented with a built in webpage. [Screenshot](https://github.com/erew123/alltalk_tts#screenshots)
 - **Console output** Clear command line output for any warnings or issues.
- **Standalone/3rd Party support via JSON calls** Can be used with 3rd party applications via JSON calls.
+- **API Suite and 3rd Party support via JSON calls** Can be used with 3rd party applications via JSON calls.
 - **Can be run as a standalone app** Not just inside of text-generation-webui.
 ## Index
@@ -17,22 +19,26 @@ AllTalk is an updated version of the Coqui_tts extension for Text Generation web
 - 🟪 [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)
 - 🟦 [Running AllTalk as a standalone app](https://github.com/erew123/alltalk_tts?#-running-alltalk-as-a-standalone-app)
 - 🟠 [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)
-#### Updates
+## 🔄 Updates
-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. It does however mean you need to ensure your character card is set up correctly if using the narrator function. Details are below in the installation notes.
+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)
 DeepSpeed **v11.2** can be installed within the **default text-generation-webui Python 3.11 environment**. Installs in custom Python environments are possible, but can be more complicated. Instructions [here](https://github.com/erew123/alltalk_tts##deepspeed-installation-options) (or scroll down).
 ## 🟩 Installation on Text generation web UI
 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) 
 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:<br><br>
+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`
+`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)
 3) Move into your extensions folder:<br><br>
 `cd extensions`
@@ -43,17 +49,17 @@ This has been tested on the current Dec 2023 release of Text generation webUI. I
 5) Move into the **alltalk_tts** folder:<br><br>
 `cd alltalk_tts`
-6) Install the requirements:<br><br>
+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>
+**Nvidia graphics card machines** - `pip install -r requirements_nvidia.txt`<br><br>
-*Other machines (mac, amd etc)* - `pip install -r requirements_other.txt`
+**Other machines (mac, amd etc)** - `pip install -r requirements_other.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`.
-8) 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.
+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 $\textcolor{red}{\textsf{VERY IMPORTANT}}$.
-9) 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#the-one-thing-i-cant-easily-work-around)
+10) 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#the-one-thing-i-cant-easily-work-around)
-10) Some extra voices downloadable [here](https://drive.google.com/file/d/1bYdZdr3L69kmzUN3vSiqZmLRD7-A3M47/view?usp=drive_link)
+11) Some extra voices downloadable [here](https://drive.google.com/file/d/1bYdZdr3L69kmzUN3vSiqZmLRD7-A3M47/view?usp=drive_link)
 #### 🟩 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.
@@ -81,9 +87,9 @@ This is pretty much a repeat of the installation process.
 3) At the command prompt/terminal, type:<br><br>
 `git pull`
-4) Install the requirements:<br><br>
+4) Install the correct requirements for your machine:<br><br>
-*Nvidia graphics card machines* - `pip install -r requirements_nvidia.txt`<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`
+**Other machines (mac, amd etc)** - `pip install -r requirements_other.txt`
 #### 🟪 Updating "git pull" error
@@ -95,6 +101,7 @@ I did leave a mistake in the `/extensions/alltalk_tts/.gitignore` file at one po
 voices/*.*
 models/*.*
 outputs/*.*
 finetune/*.*
 config.json
 confignew.json
 models.json
@@ -123,9 +130,9 @@ This will download a fresh installation.
 3) Move into the **alltalk_tts** folder:<br><br>
 `cd alltalk_tts`
-4) Install the requirements:<br><br>
+4) Install the correct requirements for your machine:<br><br>
-*Nvidia graphics card machines* - `pip install -r requirements_nvidia.txt`<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`
+**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.
@@ -135,11 +142,13 @@ Assuming its all working fine and you are happy, you can delete the old alltalk_
 </details>
 ## 🟫 Screenshots
-|![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/35898566/15c6ba0b-e6b0-4570-8253-b920dd76174d) | ![image](https://github.com/erew123/alltalk_tts/assets/35898566/548619c8-5f1b-47d0-a73d-54d2fee3f3db) |
 |:---:|:---:|
-|![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) |
+|![image](https://github.com/erew123/alltalk_tts/assets/35898566/b0e13dba-c6b1-4ab7-845d-244ac1158330) |  ![image](https://github.com/erew123/alltalk_tts/assets/35898566/e35e987c-543a-486b-b4fb-ee6ebe6f59c6) |
 |![image](https://github.com/erew123/alltalk_tts/assets/35898566/68edc968-bdd2-4f98-9d56-b9ca40decf26) | ![image](https://github.com/erew123/alltalk_tts/assets/35898566/eb5e617b-2345-418d-8267-a9d30f705a10) |
 ## 🟨 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
 <details>
@@ -160,7 +169,7 @@ Assuming its all working fine and you are happy, you can delete the old alltalk_
 <br><br></details>
-#### 🟨 [AllTalk Startup] Warning TTS Subprocess has NOT started up yet, Will keep trying for 60 seconds maximum. Please wait. It times out after 60 seconds.
+#### 🟨 [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>
@@ -169,9 +178,11 @@ Assuming its all working fine and you are happy, you can delete the old alltalk_
 **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.
-Possibilities for this issue are:
+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.
@@ -196,6 +207,19 @@ Possibilities for this issue are:
 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>
@@ -230,7 +254,101 @@ I would suggest following [Problems Updating](https://github.com/erew123/alltalk
 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).
 #### ⚫ 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. 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.
 #### ⚫ 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>
@@ -381,10 +499,206 @@ def get_shm_size():
 **Removal** - If it became necessary to uninstall DeepSpeed, you can do so with `cmd_windows.bat` and then `pip uninstall deepspeed`<br><br>
 </details>
 ## 🟦 Running AllTalk as a standalone app
 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. 
 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.
 #### 🟦 (Option 1) I already have AllTalk installed as an extension of Text-generation-webui
 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.
 #### 🟦 (Option 2) I wish to do a custom install of AllTalk
 1) In your chosen disk location git clone this repository:<br><br>
 `git clone https://github.com/erew123/alltalk_tts`
 2) Move into the **alltalk_tts** folder:<br><br>
 `cd alltalk_tts`
 3) If you have a custom Python environment, now is the time to load it!
 4) 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`
 5) Start AllTalk with `python script.py`
 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.
 ## 🟠 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"]}`
 #### 🟠 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
 - 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 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.<br>
 Example JSON TTS Generation Response:
 `{"status": "generate-success", "output_file_path": "C:\text-generation-webui\extensions\alltalk_tts\outputs\myoutputfile_1703149973.wav", "output_file_url": "http://127.0.0.1:7851/audio/myoutputfile_1703149973.wav"}`
 ### 🔴 Future to-do list
 - Complete & document the new/full standalone mode API.
 - Voice output within the command prompt/terminal (TBD).
- Correct an issue on incorrect output folder path when running as a standalone app.
+- Correct a few spelling mistakes in the documentation.
 - Correct a few spelling mistakes in the documnentation.
 - Possibly add some additional TTS engines (TBD).
 - Have a break!
@@ -6,6 +6,7 @@ try:
    import torch
    import os  # Import the os module
    import re
    import sys
    import glob
    import textwrap
    import packaging.version
@@ -17,7 +18,7 @@ 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[94mand then try running the diagnostics again.\033[0m")
+    print("\033[94mfrom the text-generation-webui directory, and then try running the diagnostics again.\033[0m")
    exit(1)
 try:
@@ -110,6 +111,18 @@ def log_system_info():
    # 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:
@@ -134,14 +147,24 @@ def log_system_info():
    # Log and print information
    logging.info(f"OS Version: {os_version}")
-    logging.info(f"Note: Windows 11 build is 10.x.22xxx")
+    logging.info(f"Note: Windows 11 will list as build is 10.x.22xxx")
    logging.info(f"Python Version: {python_version}")
    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("Package Versions:")
+        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')
@@ -153,12 +176,22 @@ def log_system_info():
    # 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[92mWindows 11 build is 10.x.22xxx\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{python_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())
@@ -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"
    }
 }
@@ -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
@@ -1,7 +1,7 @@
 numpy>=1.22.0
 soundfile>=0.12.1
 uvicorn>=0.24.0.post1
-TTS>=0.22.0
+TTS>=0.21.3
 torch>=2.1.0+cu118
 torchaudio>=2.1.0+cu118
 fastapi>=0.104.1
@@ -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
@@ -1,7 +1,7 @@
 numpy>=1.22.0
 soundfile>=0.12.1
 uvicorn>=0.24.0.post1
-TTS>=0.22.0
+TTS>=0.21.3
 torch>=2.1.0
 torchaudio>=2.1.0
 fastapi>=0.104.1
@@ -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
@@ -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
@@ -138,10 +141,23 @@ 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 confignew.json ####
@@ -248,10 +264,10 @@ 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 +277,9 @@ 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."
@@ -271,11 +287,13 @@ 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["tts_model_loaded"] = False
        url = f"{base_url}/api/reload"
@@ -294,17 +312,26 @@ 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
@@ -482,6 +509,9 @@ def voice_preview(string):
        return f"[{params['branding']}Server] Audio generation failed. Status: {generate_response.get('status')}"
 def replace_asterisk(match):
    return match.group(0) + '&quot;<*'
 #################################
 #### TTS STANDARD GENERATION ####
 #################################
@@ -500,32 +530,34 @@ def output_modifier(string, state):
    if process_lock.acquire(blocking=False):
        try:
            if params["narrator_enabled"]:
                # print(original_string)
                # Do Some basic stripping and remove any double CR's
                processed_string = (
                    original_string
                    .replace("***", "*")
                    .replace("**", "*")
                    .replace("\n\n", "\n")
                    .replace("\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('&quot;\n\n*', '&quot;<*'))
-                processed_string = (
+                processed_string = (processed_string .replace('&quot;\n', '< '))
-                    processed_string
+                processed_string = (processed_string .replace("&#x27;", "'"))
-                    .replace("&#x27;", "'")
+                processed_string = (processed_string .replace("\n", " "))
-                    .replace("\n", " ")
+                processed_string = (processed_string .replace('&quot;', '&quot;<'))
-                    # Add special characters to the quote so that we can use it to identify things later after its been split
+                processed_string = (processed_string .replace('"', '&quot;<'))
-                    .replace('&quot;', '&quot;<')
+                #pattern = re.compile(r'(?<=[a-zA-Z!])&quot;<(?=[a-zA-Z])')
-                    # Capture new conversations which wont have things like &quote in them
+                pattern = re.compile(r'(?<=[a-zA-Z!?\.])&quot;<(?=[a-zA-Z])')
-                    .replace('"', '&quot;<')
+                processed_string = pattern.sub('&quot; ', processed_string)
-                )
+                pattern = re.compile(r'(?<=[a-zA-Z])\*(?=[a-zA-Z])')
-                #capturing another outlier in inital character paragraph
+                processed_string = pattern.sub('*&quot;', processed_string)
                # 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)
+                processed_string = processed_string.replace('! *', '&quot;< *')
                processed_string = processed_string.replace('? *', '< *')
                processed_string = processed_string.replace('* ', '* &quot;<')
                processed_string = processed_string.replace('*. ', '* &quot;<')
                processed_string = re.sub(r'\*(?=[a-zA-Z])', replace_asterisk, 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 *
@@ -533,7 +565,7 @@ def output_modifier(string, state):
                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
@@ -551,15 +583,10 @@ def output_modifier(string, state):
                    else:
                        cleaned_part = html.unescape(part.replace('< ', '').replace('<  ', '').replace('<  ', ''))
                        voice_to_use = params["narrator_voice"]
                    # Check if character name exists and if not, just call it TTSOUT_
                    if "character_menu" in state:
                        output_file = Path(f'{params["output_folder_wav"]}/{state["character_menu"]}_{int(time.time())}_{i}.wav')
                    else:
                        output_file = Path(f'{params["output_folder_wav"]}/TTSOUT_{int(time.time())}_{i}.wav')
                    # Generate that TTS and output to a file
-                    output_file_str = output_file.as_posix()
+                    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)
@@ -627,9 +654,10 @@ 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()
 ###############################################
@@ -782,14 +810,17 @@ def ui():
            deepspeed_checkbox_play = gr.HTML(visible=False)
        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)",
                value=gr_modelchoice,  # Set the default value
            )
            tts_radio_buttons_play = gr.HTML(visible=False)
            explanation_text = gr.HTML(
-                f"<p>NOTE: Switching Model Type, Low VRAM & DeepSpeed, each 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']}'>Click here for the Settings page, help & instructions</a><a href='http://{params['ip_address']}:{params['port_number']}'></a>⚙️<br>NOTE: Switching Model Type, Low VRAM & DeepSpeed, each takes 15 seconds. Each TTS generation method has a slightly different sound. DeepSpeed checkbox is only visible if DeepSpeed is installed on your system."
            )
        with gr.Row():
@@ -33,7 +33,8 @@ device = "cuda" if torch.cuda.is_available() else "cpu"
 # STARTUP VARIABLE - Import languges file for Gradio to be able to display them in the interface
 with open(this_dir / "languages.json", encoding="utf8") as f:
    languages = json.load(f)
-
+# Base setting for a possible FineTuned model existing and the loader being available
 tts_method_xtts_ft = False
 #################################################################
 #### LOAD PARAMS FROM confignew.json - REQUIRED FOR BRANDING ####
@@ -123,7 +124,7 @@ app = FastAPI(lifespan=startup_shutdown)
 #####################################
 #### MODEL LOADING AND UNLOADING ####
 #####################################
-# MODEL LOADERS Picker For API TTS, API Local, XTTSv2 Local
+# MODEL LOADERS Picker For API TTS, API Local, XTTSv2 Local, XTTSv2 FT
 async def setup():
    global device
    # Set a timer to calculate load times
@@ -150,6 +151,13 @@ async def setup():
            "\033[0m",
        )
        model = await xtts_manual_load_model()
    elif tts_method_xtts_ft:
        print(
            f"[{params['branding']}Model] \033[94mXTTSv2 FT Loading\033[0m /models/fintuned/model.pth \033[94minto\033[93m",
            device,
            "\033[0m",
        )
        model = await xtts_ft_manual_load_model()
    # Create an end timer for calculating load times
    generate_end_time = time.time()
    # Calculate start time minus end time
@@ -161,7 +169,9 @@ async def setup():
    # Set "tts_model_loaded" to true
    params["tts_model_loaded"] = True
    # Set the output path for wav files
-    Path(f'{params["output_folder_wav"]}').mkdir(parents=True, exist_ok=True)
+    output_directory = this_dir / params["output_folder_wav_standalone"]
    output_directory.mkdir(parents=True, exist_ok=True)
    #Path(f'this_folder/outputs/').mkdir(parents=True, exist_ok=True)
 # MODEL LOADER For "API TTS"
@@ -220,6 +230,23 @@ async def xtts_manual_load_model():
    model.to(device)
    return model
 # MODEL LOADER For "XTTSv2 FT"
 async def xtts_ft_manual_load_model():
    global model
    config = XttsConfig()
    config_path = this_dir / "models" / "trainedmodel" / "config.json"
    vocab_path_dir = this_dir / "models" / "trainedmodel" / "vocab.json"
    checkpoint_dir = this_dir / "models" / "trainedmodel"
    config.load_json(str(config_path))
    model = Xtts.init_from_config(config)
    model.load_checkpoint(
        config,
        checkpoint_dir=str(checkpoint_dir),
        vocab_path=str(vocab_path_dir),
        use_deepspeed=params["deepspeed_activate"],
    )
    model.to(device)
    return model
 # MODEL UNLOADER
 async def unload_model(model):
@@ -234,6 +261,7 @@ async def unload_model(model):
 # MODEL - Swap model based on Gradio selection API TTS, API Local, XTTSv2 Local
 async def handle_tts_method_change(tts_method):
    global model
    global tts_method_xtts_ft
    # Update the params dictionary based on the selected radio button
    print(
        f"[{params['branding']}Model] \033[94mChanging model \033[92m(Please wait 15 seconds)\033[0m"
@@ -244,15 +272,23 @@ async def handle_tts_method_change(tts_method):
        params["tts_method_xtts_local"] = False
        params["tts_method_api_tts"] = True
        params["deepspeed_activate"] = False
        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
        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
        tts_method_xtts_ft = False
    elif tts_method == "XTTSv2 FT":
        tts_method_xtts_ft = True
        params["tts_method_api_tts"] = False
        params["tts_method_api_local"] = False
        params["tts_method_xtts_local"] = False
    # Unload the current model
    model = await unload_model(model)
@@ -265,7 +301,7 @@ async def handle_tts_method_change(tts_method):
@app.route("/api/reload", methods=["POST"])
 async def reload(request: Request):
    tts_method = request.query_params.get("tts_method")
-    if tts_method not in ["API TTS", "API Local", "XTTSv2 Local"]:
+    if tts_method not in ["API TTS", "API Local", "XTTSv2 Local", "XTTSv2 FT"]:
        return {"status": "error", "message": "Invalid TTS method specified"}
    await handle_tts_method_change(tts_method)
    return Response(
@@ -422,8 +458,8 @@ async def generate_audio(text, voice, language, output_file):
    if params["low_vram"] and device == "cpu":
        await switch_device()
    generate_start_time = time.time()  # Record the start time of generating TTS
-    # XTTSv2 LOCAL Method
+    # XTTSv2 LOCAL & Xttsv2 FT Method
-    if params["tts_method_xtts_local"]:
+    if params["tts_method_xtts_local"] or tts_method_xtts_ft:
        print(f"[{params['branding']}TTSGen] {text}")
        gpt_cond_latent, speaker_embedding = model.get_conditioning_latents(
            audio_path=[f"{this_dir}/voices/{voice}"],
@@ -617,6 +653,277 @@ async def get_audio(filename: str):
    audio_path = this_dir / "outputs" / filename
    return FileResponse(audio_path)
 #########################
 #### VOICES LIST API ####
 #########################
 # Define the new endpoint
@app.get("/api/voices")
 async def get_voices():
    wav_files = list_files(this_dir / "voices")
    return {"voices": wav_files}
 ###########################
 #### PREVIEW VOICE API ####
 ###########################
@app.post("/api/previewvoice/", response_class=JSONResponse)
 async def preview_voice(request: Request, voice: str = Form(...)):
    try:
        # Hardcoded settings
        language = "en"
        output_file_name = "api_preview_voice"
        # Clean the voice filename for inclusion in the text
        clean_voice_filename = re.sub(r'\.wav$', '', voice.replace(' ', '_'))
        clean_voice_filename = re.sub(r'[^a-zA-Z0-9]', ' ', clean_voice_filename)
        # Generate the audio
        text = f"Hello, this is a preview of voice {clean_voice_filename}."
        # Generate the audio
        output_file_path = this_dir / "outputs" / f"{output_file_name}.wav"
        await generate_audio(text, voice, language, output_file_path)
        # Generate the URL
        output_file_url = f'http://{params["ip_address"]}:{params["port_number"]}/audio/{output_file_name}.wav'
        # Return the response with both local file path and URL
        return JSONResponse(
            content={
                "status": "generate-success",
                "output_file_path": str(output_file_path),
                "output_file_url": str(output_file_url),
            },
            status_code=200,
        )
    except Exception as e:
        print(f"An error occurred: {e}")
        return JSONResponse(content={"error": "An error occurred"}, status_code=500)
 ########################
 #### GENERATION API ####
 ########################
 import html
 import re
 import uuid
 import numpy as np
 import soundfile as sf
 import sys
 # Check for PortAudio library on Linux
 try:
    import sounddevice as sd
    sounddevice_installed=True
 except OSError:
    print(f"[{params['branding']}Startup] \033[91mInfo\033[0m PortAudio library not found. If you wish to play TTS in standalone mode through the API suite")
    print(f"[{params['branding']}Startup] \033[91mInfo\033[0m please install PortAudio. This will not affect any other features or use of Alltalk.")
    print(f"[{params['branding']}Startup] \033[91mInfo\033[0m If you don't know what the API suite is, then this message is nothing to worry about.")
    sounddevice_installed=False
    if sys.platform.startswith('linux'):
        print(f"[{params['branding']}Startup] \033[91mInfo\033[0m On Linux, you can use the following command to install PortAudio:")
        print(f"[{params['branding']}Startup] \033[91mInfo\033[0m sudo apt-get install portaudio19-dev")
 from typing import Union, Dict
 from pydantic import BaseModel, ValidationError, Field
 def play_audio(file_path, volume):
    data, fs = sf.read(file_path)
    sd.play(volume * data, fs)
    sd.wait()
 class Request(BaseModel):
    # Define the structure of the 'Request' class if needed
    pass
 class JSONInput(BaseModel):
    text_input: str = Field(..., max_length=1000, description="text_input needs to be 1000 characters or less.")
    text_filtering: str = Field(..., pattern="^(none|standard|html)$", description="text_filtering needs to be 'none', 'standard' or 'html'.")
    character_voice_gen: str = Field(..., pattern="^.*\.wav$", description="character_voice_gen needs to be the name of a wav file e.g. mysample.wav.")
    narrator_enabled: bool = Field(..., description="narrator_enabled needs to be true or false.")
    narrator_voice_gen: str = Field(..., pattern="^.*\.wav$", description="narrator_voice_gen needs to be the name of a wav file e.g. mysample.wav.")
    text_not_inside: str = Field(..., pattern="^(character|narrator)$", description="text_not_inside needs to be 'character' or 'narrator'.")
    language: str = Field(..., pattern="^(ar|zh-cn|cs|nl|en|fr|de|hu|it|ja|ko|pl|pt|ru|es|tr)$", description="language needs to be one of the following ar|zh-cn|cs|nl|en|fr|de|hu|it|ja|ko|pl|pt|ru|es|tr.")
    output_file_name: str = Field(..., pattern="^[a-zA-Z0-9_]+$", description="output_file_name needs to be the name without any special characters or file extension e.g. 'filename'")
    output_file_timestamp: bool = Field(..., description="output_file_timestamp needs to be true or false.")
    autoplay: bool = Field(..., description="autoplay needs to be a true or false value.")
    autoplay_volume: float = Field(..., ge=0.1, le=1.0, description="autoplay_volume needs to be from 0.1 to 1.0")
    @classmethod
    def validate_autoplay_volume(cls, value):
        if not (0.1 <= value <= 1.0):
            raise ValueError("Autoplay volume must be between 0.1 and 1.0")
        return value
 class TTSGenerator:
    @staticmethod
    def validate_json_input(json_data: Union[Dict, str]) -> Union[None, str]:
        try:
            if isinstance(json_data, str):
                json_data = json.loads(json_data)
            JSONInput(**json_data)
            return None  # JSON is valid
        except ValidationError as e:
            return str(e)
 def standard_filtering(text_input):
    text_output = (text_input
                        .replace("***", "")
                        .replace("**", "")
                        .replace("*", "")
                        .replace("\n\n", "\n")
                        .replace("&#x27;", "'")
                        )
    return text_output
 def narrator_filtering(narrator_text_input):
    processed_string = re.sub(r'\.\*\n\*', '. ', narrator_text_input)
    processed_string = (
        processed_string
        .replace("\n", " ")
        .replace('&quot;', '&quot;<')
        .replace('"', '&quot;<')
    )
    processed_string = processed_string.replace('&quot;<. *', '&quot;< *"')
    processed_string = processed_string.replace('< *"', '< *')
    processed_string = processed_string.replace('. *', '< *')
    text_output = html.unescape(processed_string)
    return text_output
 def combine(output_file_timestamp, output_file_name, audio_files):
    audio = np.array([])
    sample_rate = None
    try:
        for audio_file in audio_files:
            audio_data, current_sample_rate = sf.read(audio_file)
            if audio.size == 0:
                audio = audio_data
                sample_rate = current_sample_rate
            elif sample_rate == current_sample_rate:
                audio = np.concatenate((audio, audio_data))
            else:
                raise ValueError("Sample rates of input files are not consistent.")
    except Exception as e:
        # Handle exceptions (e.g., file not found, invalid audio format)
        return None, None
    if output_file_timestamp:
        timestamp = int(time.time())
        output_file_path = os.path.join(this_dir / "outputs" / f'{output_file_name}_{timestamp}_combined.wav')
        output_file_url = f'http://{params["ip_address"]}:{params["port_number"]}/audio/{output_file_name}_{timestamp}_combined.wav'
    else:
        output_file_path = os.path.join(this_dir / "outputs" / f'{output_file_name}_combined.wav')
        output_file_url = f'http://{params["ip_address"]}:{params["port_number"]}/audio/{output_file_name}.wav'
    try:
        sf.write(output_file_path, audio, samplerate=sample_rate)
        # Clean up unnecessary files
        for audio_file in audio_files:
            os.remove(audio_file)
    except Exception as e:
        # Handle exceptions (e.g., failed to write output file)
        return None, None
    return output_file_path, output_file_url
 # Generation API (separate from text-generation-webui)
@app.post("/api/tts-generate", response_class=JSONResponse)
 async def tts_generate(
    text_input: str = Form(...),
    text_filtering: str = Form(...),
    character_voice_gen: str = Form(...),
    narrator_enabled: bool = Form(...),
    narrator_voice_gen: str = Form(...),
    text_not_inside: str = Form(...),
    language: str = Form(...),
    output_file_name: str = Form(...),
    output_file_timestamp: bool = Form(...),
    autoplay: bool = Form(...),
    autoplay_volume: float = Form(...),
 ):
    try:
        json_input_data = {
            "text_input": text_input,
            "text_filtering": text_filtering,
            "character_voice_gen": character_voice_gen,
            "narrator_enabled": narrator_enabled,
            "narrator_voice_gen": narrator_voice_gen,
            "text_not_inside": text_not_inside,
            "language": language,
            "output_file_name": output_file_name,
            "output_file_timestamp": output_file_timestamp,
            "autoplay": autoplay,
            "autoplay_volume": autoplay_volume,
        }
        JSONresult = TTSGenerator.validate_json_input(json_input_data)
        if JSONresult is None:
            pass
        else:
            return JSONResponse(content={"error": JSONresult}, status_code=400)
        if narrator_enabled:
            #print("ORIGINAL UNTOUCHED STRING IS:", text_input,"\n")
            if text_filtering in ["standard", "none"]:
                    cleaned_string = (
                        text_input
                        .replace('"', '"<')
                        .replace('*', '<*')
                    )
                    parts = re.split(r'(?<=<\*\s)|(?<=\.\s)|(?<=\."\<)|(?<=\."<)', cleaned_string)
                    parts = list(filter(lambda x: x.strip(), parts))
            elif text_filtering == "html":
                cleaned_string = standard_filtering(text_input)
                cleaned_string = narrator_filtering(cleaned_string)
                parts = re.split(r'&quot;|\.\*', cleaned_string)
            audio_files_all_paragraphs = []
            audio_files_paragraph = []
            for i, part in enumerate(parts):
                if len(part.strip()) <= 1:
                    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
                if '<' in part and '<*' not in part and '< *' not in part and '<  *' not in part and '< ' not in part and '<  ' not in part:
                    cleaned_part = html.unescape(part.replace('<', ''))
                    voice_to_use = character_voice_gen
                #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('*', '').replace('<. ', '')) 
                    voice_to_use = narrator_voice_gen
                #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
                elif text_not_inside == "character":
                    cleaned_part = html.unescape(part.replace('< ', '').replace('<  ', '').replace('<  ', ''))
                    voice_to_use = character_voice_gen
                elif text_not_inside == "narrator":
                    cleaned_part = html.unescape(part.replace('< ', '').replace('<  ', '').replace('<  ', ''))
                    voice_to_use = narrator_voice_gen
                output_file = this_dir / "outputs" / f"{output_file_name}_{uuid.uuid4()}_{int(time.time())}_{i}.wav"
                output_file_str = output_file.as_posix()
                await generate_audio(cleaned_part, voice_to_use, language, output_file_str)
                audio_path = output_file_str
                audio_files_paragraph.append(audio_path)
            # Accumulate audio files within the paragraph
            audio_files_all_paragraphs.extend(audio_files_paragraph)
            # Combine audio files across paragraphs
            output_file_path, output_file_url = combine(output_file_timestamp, output_file_name, audio_files_all_paragraphs)
        else:
            if output_file_timestamp:
                timestamp = int(time.time())
                output_file_path = this_dir / "outputs" / f"{output_file_name}_{timestamp}.wav"
                output_file_url = f'http://{params["ip_address"]}:{params["port_number"]}/audio/{output_file_name}_{timestamp}.wav'
            else:
                output_file_path = this_dir / "outputs" / f"{output_file_name}.wav"
                output_file_url = f'http://{params["ip_address"]}:{params["port_number"]}/audio/{output_file_name}.wav'
            if text_filtering == "html":
                cleaned_string = html.unescape(standard_filtering(text_input))
            elif text_filtering == "standard":
                cleaned_string = standard_filtering(text_input)
            else:
                cleaned_string = text_input
            await generate_audio(cleaned_string, character_voice_gen, language, output_file_path)
        if sounddevice_installed == False:
            autoplay = False
        if autoplay:
            play_audio(output_file_path, autoplay_volume)
        return JSONResponse(content={"status": "generate-success", "output_file_path": str(output_file_path), "output_file_url": str(output_file_url)}, status_code=200)
    except Exception as e:
        return JSONResponse(content={"status": "generate-failure", "error": "An error occurred"}, status_code=500)
 #############################################################
 #### DOCUMENTATION - README ETC - PRESENTED AS A WEBPAGE ####
 #############################################################
@@ -818,6 +1125,7 @@ simple_webpage = """
 <li><a href="#using-voice-samples">Using Voice Samples</a></li>
 <li><a href="#text-not-inside">Text Not inside</a></li>
 <li><a href="#low-vram">Low VRAM</a></li>
 <li><a href="#finetune">Finetuning (Training the model)</a></li>
 <li><a href="#deepspeed">DeepSpeed</a>
 <ul>
 <li><a href="#deepspeed-linux">DeepSpeed Setup Linux</a></li>
@@ -838,6 +1146,12 @@ simple_webpage = """
 <p style="padding-left: 30px; text-align: justify;">AllTalk is a web interface, based around the Coqui TTS voice cloning/speech generation system. To generate TTS, you can use the provided gradio interface or interact with the server using JSON/CURL commands.&nbsp;</p>
 <p style="padding-left: 30px; text-align: justify;"><span style="color: #ff0000;">Note:</span> When loading up a new character in Text generation webUI it may look like nothing is happening for 20-30 seconds. Its actually processing the introduction section (greeting message) of the text and once that is completed, it will appear. You can see the activity occuring in the console window. Refreshing the page multiple times will try force the TTS engine to keep re-generating the text, so please just wait and check the console if needed.</p>
 <p style="padding-left: 30px; text-align: justify;"><span style="color: #ff0000;">Note: </span>Ensure that your RP character card has asterisks around anything for the narration and double quotes around anything spoken. There is a complication ONLY with the greeting card so, ensuring it has the correct use of quotes and asterisks will help make sure that the greeting card sounds correct. I will aim to address this issue in a future update. In Text-generation-webUI <span style="color: #3366ff;">parameters menu</span> &gt; <span style="color: #3366ff;">character tab</span> &gt; <span style="color: #3366ff;">greeting</span>&nbsp;make sure that anything in there that is the narrator is in asterisks and anything spoken is in double quotes, then hit the <span style="color: #3366ff;">save</span> (💾) button.</p>
 <p style="padding-left: 30px;"><span style="text-decoration: underline;"><strong>AllTalk <span style="color: #ff0000; text-decoration: underline;">Minor Bug Fixes Changelog &amp; Known issues</span></strong></span></p>
 <p style="padding-left: 30px;">If I squash any minor bugs or find any issues, I will try to apply an update asap. If you think something isnt working correctly or you have a problem, check these two links below first.</p>
 <ul>
 <li>Minor bug fixes changelog&nbsp;<a href="https://github.com/erew123/alltalk_tts/issues/25" target="_blank" rel="noopener">link here</a>.</li>
 <li>Help and known issues <a href="https://github.com/erew123/alltalk_tts?#-help-with-problems" target="_blank" rel="noopener">link here</a>.</li>
 </ul>
 <p style="padding-left: 30px;"><span style="text-decoration: underline;"><strong>AllTalk</strong></span> <br />Github <a href="https://github.com/erew123/alltalk_tts" target="_blank" rel="noopener">link here</a><br />Update instructions <a href="https://github.com/erew123/alltalk_tts?#-updating" target="_blank" rel="noopener">link here</a><br />Help and issues <a href="https://github.com/erew123/alltalk_tts?#-help-with-problems" target="_blank" rel="noopener">link here<br /><br /></a><span style="text-decoration: underline;"><strong>Text generation webUI</strong></span> <br />Web interface&nbsp;<a href="http://{{ params["ip_address"] }}:7860" target="_blank" rel="noopener">link here</a> <br />Documentation <a href="https://github.com/oobabooga/text-generation-webui/wiki" target="_blank" rel="noopener">link here</a></p>
 <p style="padding-left: 30px;"><a href="#toc">Back to top of page</a></p>
 <h2 id="server-information">Server Information</h2>
@@ -937,7 +1251,7 @@ simple_webpage = """
 <p style="padding-left: 30px; text-align: justify;">Save your generated wav file in the&nbsp;<span style="color: #3366ff;">/alltalk_tts/voices/ <span style="color: #808080;">folder.</span></span></p>
 <p style="padding-left: 30px; text-align: justify;">Its worth mentioning that using AI generated audio clips may introduce unwanted sounds as its already a copy/simulation of a voice.</p>
 <h4>Why doesnt it sound like XXX Person?</h4>
-<p style="padding-left: 30px; text-align: justify;">The reasons can be that you:</p>
+<p style="padding-left: 30px; text-align: justify;">Maybe you might be interested in trying <a href="#finetune">Finetuning of the model</a>. Otherwise, the reasons can be that you:</p>
 <ul style="text-align: justify;">
 <li>Didn't downsample it as above.</li>
 <li>Have a bad quality voice sample.</li>
@@ -967,6 +1281,82 @@ simple_webpage = """
 <p style="padding-left: 30px;"><a href="#toc">Back to top of page</a></p>
 <h2 id="finetune"><strong>Finetuning (Training the model)</strong></h2>
 <p style="margin-left:40px; text-align:justify">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 &quot;XTTSv2 local&quot; model <span style="color:#3366ff">(stored in /alltalk_tts/models/xxxxx/)</span> on a specific voice. For this you will need:</p>
 <ul style="margin-left:40px">
 	<li>An Nvidia graphics card To install a few portions of the Nvidia CUDA <strong>11.8</strong> Toolkit (this will not impact text-generation-webui&#39;s cuda setup.</li>
 	<li>18GB of disk space free (most of this is used temporarily)</li>
 	<li>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).</li>
 </ul>
 <h4>How will this work/How complicated is it?</h4>
 <p style="margin-left:40px; text-align:justify">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&#39;s more complicated end you will clean up the audio a little beforehand, but its still only 4x buttons and copying a few files.</p>
 <h4>The audio you will use:</h4>
 <p style="margin-left:40px; text-align:justify">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 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.</p>
 <h4>Important requirements CUDA 11.8:</h4>
 <p style="margin-left:40px; text-align:justify">As mentioned you must have a small portion of the <span style="color:#3366ff">Nvidia CUDA Toolkit&nbsp;<strong>11.8</strong></span>&nbsp;installed. Not higher or lower versions. Specifically&nbsp;<strong>11.8</strong>. You do not have to uninstall any other versions, change any graphics drivers, reinstall torch or anything like that. There are instructions within the finetuning interface on doing this or you can also find them on this link&nbsp;<a href="https://github.com/erew123/alltalk_tts#-important-requirements-cuda-118">here</a></p>
 <h4>Starting Finetuning:</h4>
 <p style="margin-left:40px"><strong>Ensure</strong> you have followed the instructions on setting up the Nvidia CUDA Toolkit 11.8 <a href="https://github.com/erew123/alltalk_tts#-important-requirements-cuda-118">here</a>&nbsp;or the below procedure will fail.</p>
 <p style="margin-left:40px">The below instructions are also available online&nbsp;<a href="https://github.com/erew123/alltalk_tts#-finetuning-a-model">here</a></p>
 <ol>
 	<li>
 	<p>Close all other applications that are using your GPU/VRAM and copy your audio samples into:<br />
 	<br />
 	<span style="color:#3366ff">/alltalk_tts/finetune/put-voice-samples-in-here/</span></p>
 	</li>
 	<li>
 	<p>In a command prompt/terminal window you need to move into your Text generation webUI folder:<br />
 	<br />
 	<span style="color:#3366ff">cd text-generation-webui</span></p>
 	</li>
 	<li>
 	<p>Start the Text generation webUI Python environment for your OS:<br />
 	<br />
 	<span style="color:#3366ff">cmd_windows.bat,&nbsp;./cmd_linux.sh,&nbsp;cmd_macos.sh&nbsp;or&nbsp;cmd_wsl.bat</span></p>
 	</li>
 	<li>
 	<p>You can double check your search path environment still works correctly with&nbsp;<span style="color:#3366ff">nvcc --version</span>. It should report back <span style="color:#3366ff">11.8</span>:<br />
 	<br />
 	<span style="color:#3366ff">Cuda compilation tools, release 11.8.</span></p>
 	</li>
 	<li>
 	<p>Move into your extensions folder:<br />
 	<br />
 	<span style="color:#3366ff">cd extensions</span></p>
 	</li>
 	<li>
 	<p>Move into the&nbsp;<span style="color:#3366ff">alltalk_tts</span>&nbsp;folder:<br />
 	<br />
 	<span style="color:#3366ff">cd alltalk_tts</span></p>
 	</li>
 	<li>
 	<p>Install the finetune requirements file:&nbsp;<span style="color:#3366ff">pip install -r requirements_finetune.txt</span></p>
 	</li>
 	<li>
 	<p>Type<span style="color:#3366ff">&nbsp;python finetune.py</span>&nbsp;and it should start up.</p>
 	</li>
 	<li>
 	<p>Follow the on-screen instructions when the web interface starts up.</p>
 	</li>
 	<li>
 	<p>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.</p>
 	</li>
 </ol>
 <p><a href="#toc">Back to top of page</a></p>
 <h2 id="deepspeed"><strong>DeepSpeed</strong></h2>
 <p style="padding-left: 30px; text-align: justify;">DeepSpeed provides a 2x-3x speed boost for Text-to-Speech and AI tasks. It's all about making AI and TTS happen faster and more efficiently.</p>
 <ul>
@@ -1258,31 +1648,156 @@ simple_webpage = """
 </table>
 <h2 id="curl-commands"><strong>JSON calls &amp; CURL Commands</strong></h2>
-<h4>Generating TTS - Linux</h4>
+
-<p style="padding-left: 30px;"><span style="color: #3366ff;">curl -X POST -H "Content-Type: application/json" -d '{"text": "<span style="color: #ff9900;">This is text to generate as TTS</span>","voice": "<span style="color: #ff9900;">female_01.wav</span>", "language": "<span style="color: #ff9900;">en</span>", "output_file": "<span style="color: #ff9900;">outputfile.wav</span>"}' "http://127.0.0.1:7851/api/generate"</span></p>
+<h3>Overview</h3>
-<h4>Generating TTS - Windows</h4>
+<p style="margin-left: 40px; text-align: justify;">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.</p>
-<p style="padding-left: 30px;"><span style="color: #3366ff;">curl -X POST -H "Content-Type: application/json" -d "{&bsol;"text&bsol;": &bsol;"<span style="color: #ff9900;">This is text to generate as TTS</span>&bsol;", &bsol;"voice&bsol;": &bsol;"<span style="color: #ff9900;">female_01.wav</span>&bsol;", &bsol;"language&bsol;": &bsol;"<span style="color: #ff9900;">en</span>&bsol;", &bsol;"output_file&bsol;": &bsol;"<span style="color: #ff9900;">outputfile.wav</span>&bsol;"}" http://127.0.0.1:7851/api/generate</span></p>
+<h3>TTS Generation Endpoint</h3>
-<h4>Generating TTS - Notes</h4>
+<ul>
-<p style="padding-left: 30px;">Replace <span style="color: #ff9900;">This is text to generate as TTS</span> with whatever you want it to say. <span style="color: #ff9900;">female_01.wav</span> with the voice sample you want to use. <span style="color: #ff9900;">output_file.wav</span> with the file name you want it to create.</p>
+<li><strong>URL</strong>: <span style="color: #3366ff;">http://127.0.0.1:7851/api/tts-generate</span></li>
-<p style="padding-left: 30px;">JSON return <span style="color: #339966;">{"status":"generate-success","data":{"audio_path":"outputfile.wav"}}</span></p>
+<li><strong>Method</strong>: <span style="color: #3366ff;">POST</span></li>
 <li><strong>Content-Type</strong>: <span style="color: #3366ff;">application/x-www-form-urlencoded</span></li>
 </ul>
 <h3>Example command line</h3>
 <p style="padding-left: 30px;">Standard TTS speech Example (standard text) generating a time-stamped file</p>
 <p style="padding-left: 30px;"><span style="color: #3366ff;">curl -X POST "http://127.0.0.1:7851/api/tts-generate" -d "text_input=</span><span style="color: #ff9900;">All of this is text spoken by the character. This is text not inside quotes, though that doesnt matter in the slightest</span><span style="color: #3366ff;">" -d "text_filtering=</span><span style="color: #339966;">standard</span><span style="color: #3366ff;">" -d "character_voice_gen=</span><span style="color: #ff9900;">female_01.wav</span><span style="color: #3366ff;">" -d "narrator_enabled=</span><span style="color: #339966;">false</span><span style="color: #3366ff;">" -d "narrator_voice_gen=male_01.wav" -d "text_not_inside=character" -d "language=en" -d "output_file_name=</span><span style="color: #ff9900;">myoutputfile</span><span style="color: #3366ff;">" -d "output_file_timestamp=</span><span style="color: #ff9900;">true</span><span style="color: #3366ff;">" -d "autoplay=true" -d "autoplay_volume=0.8"</span></p>
 <p style="padding-left: 30px;">Narrator Example (standard text)&nbsp;generating a time-stamped file</p>
 <p style="padding-left: 30px;"><span style="color: #3366ff;">curl -X POST "http://127.0.0.1:7851/api/tts-generate" -d "text_input=</span><span style="color: #ff9900;">*This is text spoken by the narrator* &bsol;"This is text spoken by the character&bsol;". This is text not inside quotes.</span><span style="color: #3366ff;">" -d "text_filtering=</span><span style="color: #339966;">standard</span><span style="color: #3366ff;">" -d "character_voice_gen=</span><span style="color: #ff9900;">female_01.wav</span><span style="color: #3366ff;">" -d "narrator_enabled=</span><span style="color: #339966;">true</span><span style="color: #3366ff;">" -d "narrator_voice_gen=</span><span style="color: #339966;">male_01.wav</span><span style="color: #3366ff;">" -d "text_not_inside=</span><span style="color: #339966;">character</span><span style="color: #3366ff;">" -d "language=en" -d "output_file_name=</span><span style="color: #ff9900;">myoutputfile</span><span style="color: #3366ff;">" -d "output_file_timestamp=</span><span style="color: #ff9900;">true</span><span style="color: #3366ff;">" -d "autoplay=true" -d "autoplay_volume=0.8"</span></p>
 <p style="padding-left: 30px; text-align: justify;"><strong><span style="color: #ff0000;">Note</span></strong> that if your text that needs to be generated contains double quotes you will need to escape them with&nbsp;&bsol;" (Please see the narrator example).</p>
 <h3>&nbsp;Request Parameters</h3>
 <ul>
 <li>
 <p style="text-align: justify;"><strong>text_input</strong>: 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:</p>
 <p>-<span style="color: #3366ff;">d "text_input=*This is text spoken by the narrator* &bsol;"This is text spoken by the character&bsol;". This is text not inside quotes." </span></p>
 </li>
 <li>
 <p><strong>text_filtering</strong>: Filter for text. Options:</p>
 <ul>
 <li style="text-align: justify;"><span style="color: #3366ff;">none</span>&nbsp;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.</li>
 <li><span style="color: #3366ff;">standard</span>&nbsp;Human-readable text and a basic level of filtering, just to clean up some special characters.</li>
 <li><span style="color: #3366ff;">html</span>&nbsp;HTML content. Where you are using HTML entity's like &amp;quot;</li>
 </ul>
 <p><span style="color: #3366ff;">-d "text_filtering=none" </span><br /><span style="color: #3366ff;">-d "text_filtering=standard" </span><br /><span style="color: #3366ff;">-d "text_filtering=html"</span></p>
 <p><strong>Example:</strong></p>
 <ul>
 <li>Standard Example: <span style="color: #3366ff;">*This is text spoken by the narrator* "This is text spoken by the character" This is text not inside quotes.</span></li>
 <li>HTML Example:<span style="color: #3366ff;"> *This is text spoken by the narrator*&nbsp;&amp;quot;This is text spoken by the character&amp;quot;&nbsp;This is text not inside quotes.</span></li>
 <li>None will just pass whatever characters/text you send at it.</li>
 </ul>
 </li>
 <li>
 <p><strong>character_voice_gen</strong>: The WAV file name for the character's voice.</p>
 <p><span style="color: #3366ff;">-d "character_voice_gen=female_01.wav" </span></p>
 </li>
 <li>
 <p><strong>narrator_enabled</strong>: 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.</p>
 <p><span style="color: #3366ff;">-d "narrator_enabled=true"<br />-d "narrator_enabled=false" </span><span style="font-family: Verdana, Arial, Helvetica, sans-serif;">&nbsp;</span></p>
 </li>
 <li>
 <p><strong>narrator_voice_gen</strong>: The WAV file name for the narrator's voice.</p>
 <p><span style="color: #3366ff;">-d "narrator_voice_gen=male_01.wav"</span></p>
 </li>
 <li>
 <p><strong>text_not_inside</strong>: Specify the handling of lines not inside double quotes or asterisks, for the narrator feature. Options:</p>
 <ul>
 <li><span style="color: #3366ff;">character</span>: Treat as character speech.</li>
 <li><span style="color: #3366ff;">narrator</span>: Treat as narrator speech.</li>
 </ul>
 <p><span style="color: #3366ff;">-d "text_not_inside=character" </span><br /><span style="color: #3366ff;">-d "text_not_inside=narrator"</span></p>
 </li>
 <li>
 <p><strong>language</strong>: Choose the language for TTS. Options:</p>
 <ul>
 <li><span style="color: #3366ff;">ar</span>&nbsp;Arabic</li>
 <li><span style="color: #3366ff;">zh-cn</span>&nbsp;Chinese (Simplified)</li>
 <li><span style="color: #3366ff;">cs</span>&nbsp;Czech</li>
 <li><span style="color: #3366ff;">nl</span> Dutch</li>
 <li><span style="color: #3366ff;">en</span> English</li>
 <li><span style="color: #3366ff;">fr</span> French</li>
 <li><span style="color: #3366ff;">de</span> German</li>
 <li><span style="color: #3366ff;">hu</span> Hungarian</li>
 <li><span style="color: #3366ff;">it</span> Italian</li>
 <li><span style="color: #3366ff;">ja</span> Japanese</li>
 <li><span style="color: #3366ff;">ko</span> Korean</li>
 <li><span style="color: #3366ff;">pl</span> Polish</li>
 <li><span style="color: #3366ff;">pt</span> Portuguese</li>
 <li><span style="color: #3366ff;">ru </span>Russian</li>
 <li><span style="color: #3366ff;">es</span> Spanish</li>
 <li><span style="color: #3366ff;">tr</span> Turkish</li>
 </ul>
 <p><span style="color: #3366ff;">-d "language=en"</span></p>
 </li>
 <li>
 <p><strong>output_file_name</strong>: The name of the output file (excluding the .wav extension).</p>
 <p><span style="color: #3366ff;">-d "output_file_name=myoutputfile" </span></p>
 </li>
 <li>
 <p><strong>output_file_timestamp</strong>: 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.</p>
 <p><span style="color: #3366ff;">-d "output_file_timestamp=true" <br />-d "output_file_timestamp=false" </span></p>
 </li>
 <li>
 <p><strong>autoplay</strong>: <span style="color: #ff0000;">Feature not yet available</span>. Enable or disable autoplay. Still needs to be specified in the JSON request.</p>
 <p><span style="color: #3366ff;">-d "autoplay=true" <br />-d "autoplay=false"</span></p>
 </li>
 <li>
 <p><strong>autoplay_volume</strong>: <span style="color: #ff0000;">Feature not yet available</span>. Set the autoplay volume. Should be between 0.1 and 1.0.&nbsp;Still needs to be specified in the JSON request.</p>
 <p><span style="color: #3366ff;">-d "autoplay_volume=0.8" </span></p>
 </li>
 </ul>
 <h3>TTS Generation Response</h3>
 <p style="padding-left: 30px;">The API returns a JSON object with the following properties:</p>
 <ul>
 <li><span style="color: #3366ff;"><strong>status</strong></span>&nbsp;Indicates whether the generation was successful (<span style="color: #3366ff;">generate-success</span>) or failed (<span style="color: #3366ff;">generate-failure</span>).</li>
 <li><span style="color: #3366ff;"><strong>output_file_path</strong></span>&nbsp;The on-disk location of the generated WAV file.</li>
 <li><span style="color: #3366ff;"><strong>output_file_url</strong></span>&nbsp;The HTTP location for accessing the generated WAV file.</li>
 </ul>
 <p><strong>Example JSON TTS Generation Response:</strong></p>
 <p style="padding-left: 30px;"><span style="color: #339966;">{"status": "generate-success", "output_file_path": "C:\\text-generation-webui\\extensions\\alltalk_tts\\outputs\\myoutputfile_1703149973.wav", "output_file_url": "http://127.0.0.1:7851/audio/myoutputfile_1703149973.wav"}</span></p>
 <h4>Switching Model</h4>
 <p style="padding-left: 30px;"><span style="color: #3366ff;">curl -X POST "http://127.0.0.1:7851/api/reload?tts_method=API%20Local"</span><br /><span style="color: #3366ff;"> curl -X POST "http://127.0.0.1:7851/api/reload?tts_method=API%20TTS"</span><br /><span style="color: #3366ff;"> curl -X POST "http://127.0.0.1:7851/api/reload?tts_method=XTTSv2%20Local"</span></p>
 <p style="padding-left: 30px;">Switch between the 3 models respectively.</p>
 <p style="padding-left: 30px;">JSON return <span style="color: #339966;">{"status": "model-success"}</span></p>
 <h4>Switch DeepSpeed</h4>
-<p style="padding-left: 30px;"><span style="color: #3366ff;">curl -X POST -H "Content-Type: application/json" "http://127.0.0.1:7851/api/deepspeed?new_deepspeed_value=True"</span></p>
+<p style="padding-left: 30px;"><span style="color: #3366ff;">curl -X POST "http://127.0.0.1:7851/api/deepspeed?new_deepspeed_value=True"</span></p>
 <p style="padding-left: 30px;">Replace True with False to disable DeepSpeed mode.</p>
 <p style="padding-left: 30px;">JSON return <span style="color: #339966;">{"status": "deepspeed-success"}</span></p>
 <h4>Switching Low VRAM</h4>
-<p style="padding-left: 30px;"><span style="color: #3366ff;">curl -X POST -H "Content-Type: application/json" "http://127.0.0.1:7851/api/lowvramsetting?new_low_vram_value=True"</span></p>
+<p style="padding-left: 30px;"><span style="color: #3366ff;">curl -X POST "http://127.0.0.1:7851/api/lowvramsetting?new_low_vram_value=True"</span></p>
 <p style="padding-left: 30px;">Replace True with False to disable Low VRAM mode.</p>
 <p style="padding-left: 30px;">JSON return <span style="color: #339966;">{"status": "lowvram-success"}</span></p>
 <h4>Ready Endpoint</strong></h4>
 <p>Check if the Text-to-Speech (TTS) service is ready to accept requests.</p>
 <ul>
  <li>URL: <span style="color: #3366ff;">http://127.0.0.1:7851/api/ready</span></li>
  <li>Method: <span style="color: #3366ff;">GET</span></li>
  <li>Response: <span style="color: #339966;">Ready</span></li>
 </ul>
 <p style="padding-left: 30px;"><span style="color: #3366ff;">curl -X GET "http://127.0.0.1:7851/api/ready"</span></p>
 <h4>Voices List Endpoint</strong></h4>
 <p>Retrieve a list of available voices for generating speech.</p>
 <ul>
  <li>URL: <span style="color: #3366ff;">http://127.0.0.1:7851/api/voices</span></li>
  <li>Method: <span style="color: #3366ff;">GET</span></li>
 </ul>
 <p style="padding-left: 30px;"><span style="color: #3366ff;">curl -X GET "http://127.0.0.1:7851/api/voices"</span></p>
 <p style="padding-left: 30px;">JSON return: <span style="color: #339966;">{"voices": ["voice1.wav", "voice2.wav", "voice3.wav"]}</span></p>
 <h4><strong>Preview Voice Endpoint</strong></h4>
 <p>Generate a preview of a specified voice with hardcoded settings.</p>
 <ul>
  <li>URL: <span style="color: #3366ff;">http://127.0.0.1:7851/api/previewvoice/</span></li>
  <li>Method: <span style="color: #3366ff;">POST</span></li>
  <li>Content-Type: <span style="color: #3366ff;">application/x-www-form-urlencoded</span></li>
 </ul>
 <p style="padding-left: 30px;"><span style="color: #3366ff;">curl -X POST "http://127.0.0.1:7851/api/previewvoice/" -F "voice=female_01.wav"</span></p>
 <p style="padding-left: 30px;">Replace <span style="color: #3366ff;">female_01.wav</span> with the name of the voice sample you want to hear.</p>
 <p style="padding-left: 30px;">JSON return: <span style="color: #339966;">{"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"}</span></p>
 <p><a href="#toc">Back to top of page<br /></a></p>
 <h2 id="debugging-and-tts-generation-information"><strong>Debugging and TTS Generation Information</strong></h2>
 <p style="padding-left: 30px; text-align: justify;">Command line outputs are more verbose to assist in understanding backend processes and debugging.</p>
-<p style="padding-left: 30px; text-align: justify;">Its possible during startup you can get a warning message such as: <br /><br /><span style="color: black;">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[AllTalk Startup]</span> <span style="color: #ff0000;">Warning</span> <span style="color: black;">TTS Subprocess has NOT started up yet, Will keep trying for 60 seconds maximum</span> <br /><br />This is normal behavior if the subprocess is taking a while to start, however, if there is an issue starting the subprocess, you may see multiples of this message and an it will time out after 60 seconds, resulting in the TTS engine not starting. Its likely that you are not in the correct python environment or one that has a TTS engine inside, if this happens, though the system will output a warning about that ahead of this message</p>
+<p style="padding-left: 30px; text-align: justify;">Its possible during startup you can get a warning message such as: <br /><br /><span style="color: black;">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[AllTalk Startup]</span> <span style="color: #ff0000;">Warning</span> <span style="color: black;">TTS Subprocess has NOT started up yet, Will keep trying for 80 seconds maximum</span> <br /><br />This is normal behavior if the subprocess is taking a while to start, however, if there is an issue starting the subprocess, you may see multiples of this message and an it will time out after 80 seconds, resulting in the TTS engine not starting. Its likely that you are not in the correct python environment or one that has a TTS engine inside, if this happens, though the system will output a warning about that ahead of this message</p>
 <p style="padding-left: 30px; text-align: justify;">Typically the command line console will output any warning or error messages. If you need to reset your default configuation, the settings are all listed above in the configuration details.</p>
 <p style="padding-left: 30px;"><a href="#toc">Back to top of page</a></p>
 <h2 id="references"><strong>Thanks &amp; References</strong></h2>
@@ -1322,10 +1837,20 @@ template = Template(simple_webpage)
 # Render the template with the dynamic values
 rendered_html = template.render(params=params)
 ###############################
 #### Internal script ready ####
 ###############################
@app.get("/ready")
 async def ready():
    return Response("Ready endpoint")
 ############################
 #### External API ready ####
 ############################
@app.get("/api/ready")
 async def ready():
    return Response("Ready")
@app.get("/")
 async def read_root():
    return HTMLResponse(content=rendered_html, status_code=200)
Author	SHA1	Message	Date
erew123	b32df6ac15	Additional note in finetune re multiple GPU support	2023-12-30 14:45:42 +00:00
erew123	b76dd3561f	Merge pull request #34 from erew123/dev Dev	2023-12-30 14:23:22 +00:00
erew123	60bfbdcabd	Update README.md	2023-12-30 14:12:41 +00:00
erew123	c128d0851b	Updated Finetune	2023-12-30 14:00:36 +00:00
erew123	2f3b7762e4	Update README.md	2023-12-30 13:31:41 +00:00
erew123	0e594f5098	Update .gitignore	2023-12-30 13:30:16 +00:00
erew123	14151d4dda	Update README.md	2023-12-30 11:27:20 +00:00
erew123	94ab21fb15	Update README.md	2023-12-30 11:26:29 +00:00
erew123	1acac3d6c6	Update README.md	2023-12-30 11:23:59 +00:00
erew123	95ec2dc9d2	Merge pull request #32 from erew123/main merge main to dev	2023-12-30 11:11:11 +00:00
erew123	6b93eb6c1e	Update README.md	2023-12-29 23:38:38 +00:00
erew123	838578a042	Update README.md	2023-12-29 23:28:47 +00:00
erew123	2f689f0438	Model loader for Finetuned models Adds a detection routine and additional loader for a finetuned model. Model has to be in /models/trainedmodel/	2023-12-29 23:15:15 +00:00
erew123	022025ded6	Update README.md	2023-12-29 20:57:28 +00:00
erew123	320a7a6aba	Update README.md	2023-12-29 20:51:45 +00:00
erew123	fa82870883	Merge pull request #31 from erew123/dev 3x new API endpoints & Play audio at command prompt/terminal	2023-12-29 20:37:20 +00:00
erew123	a094d4f9da	Completed autoplay at command line Added additional requirement. Lowered the repetition on the start-up warning when its taking a while for the model to load.	2023-12-29 20:31:49 +00:00
erew123	bb028af694	Update README.md	2023-12-29 10:54:02 +00:00
erew123	aeb225ec7c	Update README.md	2023-12-29 10:51:06 +00:00
erew123	06a632459e	Update README.md	2023-12-29 10:44:39 +00:00
erew123	221efbddb4	Supports playback at the command line prompt Added sounddevice as its currently well supported. Allows playback at the terminal/command prompt. Added speakers_xtts.pth to the modeldownload.json as it will be needed for finetuning in future updates of TTS 0.22.0+	2023-12-29 10:42:35 +00:00
erew123	e81a88938a	Completed built-in documentation update For the new API endpoints	2023-12-29 10:11:01 +00:00
erew123	65e257077c	3x new API endpoints /api/voices/ /api/previewvoice/ /api/ready/	2023-12-29 09:56:51 +00:00
erew123	95659d5b7a	Update README.md	2023-12-29 09:55:23 +00:00
erew123	ff57270286	Update README.md	2023-12-29 09:53:02 +00:00
erew123	4fc61ba99a	Merge pull request #30 from erew123/main merge main to dev	2023-12-29 09:08:07 +00:00
erew123	3cd22081f4	Update script.py	2023-12-28 21:05:59 +00:00
erew123	d20ee95e67	Delete finetune/put-voice-samples-in-here/compact.py	2023-12-28 20:38:33 +00:00
erew123	cd47f6b123	Add files via upload	2023-12-28 20:38:12 +00:00
erew123	53a2d0a65e	Update README.md	2023-12-28 19:25:59 +00:00
erew123	13318243e4	Merge pull request #27 from rbruels/patch-1 A few changes/clarifications in the fine-tuning sections	2023-12-28 18:41:06 +00:00
erew123	acc457436a	updated narrator splitting function Improved over what was before. Still more work to do in future though.	2023-12-28 18:39:01 +00:00
erew123	8d80151889	New version of Finetune Simplified the final stages of finetuning. Added model compaction. Added cleaning routines to tidy up after training.	2023-12-28 18:36:51 +00:00
erew123	8b0ade5b9f	compact routine - separate to finetune a mini compact routine for anyone who wants to compact their existing model. This is built into the new version of finetune anyway, but is here just to capture those outlier instances.	2023-12-28 18:34:49 +00:00
Ryan Bruels	9f033e4654	A few changes/clarifications in the fine-tuning sections	2023-12-28 10:28:20 -08:00
erew123	1a2b8571d0	Updated diagnostics to include Path Now includes both Python and environment variables PATH search locations.	2023-12-28 12:05:46 +00:00
erew123	9ab20be294	Update README.md updated a screenshot	2023-12-27 06:49:46 +00:00
erew123	a34cbfdd55	Made Settings link more visble Updated the visibility of the settings & documentation page within Text-gen-webui interface. Minor built in documentation update.	2023-12-27 06:43:28 +00:00
erew123	94f5b781cc	Update Standalone API - race condition fix Applies the same race condition fix for narrator/character that potentially existed, but for the standalone mode API. Will have zero effect for anyone not using the API	2023-12-27 06:08:10 +00:00
erew123	f83e7c3b4e	Update README.md	2023-12-27 06:00:30 +00:00
erew123	607dc89be5	Update README.md Added a section on Running AllTalk as a standalone	2023-12-27 04:44:44 +00:00
erew123	47758c4aeb	Updated diagnostics Pulls Conda and Python environment details.	2023-12-26 18:58:06 +00:00
erew123	26414d4925	Update README.md	2023-12-26 17:30:40 +00:00
erew123	7ad92e7f5d	Update README.md	2023-12-26 17:28:28 +00:00
erew123	e775cef5bd	Update README.md	2023-12-26 17:19:21 +00:00
erew123	ac9ce144a0	Update README.md	2023-12-26 16:47:24 +00:00
erew123	f181c06f89	Update README.md Added a video link to show people how to install AllTalk.	2023-12-26 10:02:17 +00:00
erew123	9fae4692e3	Update README.md	2023-12-26 08:03:24 +00:00
erew123	97f0d6441a	Improved links in Documentation Added links to the minor bugs/known issues on gthub	2023-12-26 07:30:30 +00:00
erew123	2ea6cb6304	Update README.md	2023-12-26 06:23:26 +00:00
erew123	5bed68a963	minor update to standard voice naming.	2023-12-25 21:53:40 +00:00
erew123	be9862d0b0	Update README.md	2023-12-25 21:15:54 +00:00
erew123	f5a811f0f8	Update README.md	2023-12-25 21:11:02 +00:00
erew123	dc9d343115	Update uuid to avoid possible race condition file naming on short sentences could possibly have a race condition. set uuid as opposed to timestamp to avoid this outcome.	2023-12-25 21:09:39 +00:00
erew123	c92aa435e5	Update README.md	2023-12-25 09:37:39 +00:00
erew123	1f425e6bac	Update README.md	2023-12-25 06:04:35 +00:00
erew123	0854544a47	Update README.md	2023-12-25 05:45:05 +00:00
erew123	52a7922e98	Add files via upload	2023-12-25 02:05:05 +00:00
erew123	558583b16f	Update README.md	2023-12-24 20:37:59 +00:00
erew123	993d065368	Few minor updates Couple of documentation spelling mistakes Set environment variable	2023-12-24 18:01:27 +00:00
erew123	d7376fa8ef	Update README.md	2023-12-24 17:01:33 +00:00
erew123	2b175b13c4	update to find mp3 and flac Forgot it was only looking for wav's!	2023-12-24 15:56:44 +00:00
erew123	da0445489e	Update requirements_other.txt	2023-12-24 14:17:07 +00:00
erew123	e4eaa760b9	Update requirements_nvidia.txt	2023-12-24 14:16:46 +00:00
erew123	de4017f385	Update README.md	2023-12-24 14:07:22 +00:00
erew123	f2119aa0f7	Merge pull request #14 from erew123/dev New Finetuning of your models New API endpoint Full documentation (online and built in) A couple of minor file updates. Small bug fix on file generation in instruct mode with no character name available (thanks to @danielwburch)	2023-12-24 13:10:18 +00:00
erew123	bb81f3f874	Update README.md	2023-12-24 13:03:26 +00:00
erew123	fae15eecb1	minor spelling mistake updating minor spelling mistake.	2023-12-24 12:54:08 +00:00
erew123	6edcc2125b	create finetune directory	2023-12-24 12:35:02 +00:00
erew123	d26909a1d6	All the updates for Finetuning Additional files to download Updated documentation Updated requirements files	2023-12-24 12:32:10 +00:00
erew123	3be6b842c4	Update README.md	2023-12-24 10:24:03 +00:00
erew123	e10dc700c3	Update README.md	2023-12-24 10:20:03 +00:00
erew123	e8e21f949c	Update README.md Detail API Suite	2023-12-24 10:00:08 +00:00
erew123	e68a7d72f2	Update README.md	2023-12-24 08:49:14 +00:00
erew123	fd26db8e8a	Updated model + added finetuning requirements file Updated modeldownload.json with finetuning requirements inside. New requirements_finetune.txt file.	2023-12-24 08:35:33 +00:00
erew123	396f1290e7	Update README.md	2023-12-24 08:30:32 +00:00
erew123	5bc7dd8692	Update README.md added finetuning details	2023-12-24 08:29:06 +00:00
erew123	b5b68ad51f	Update script.py updated timeout	2023-12-23 00:16:38 +00:00
erew123	e49ceed40c	Merge pull request #13 from danielwburch/refactor_output_filename_2 Refactor output file naming in script.py	2023-12-21 18:03:32 +00:00
Daniel Burch	598aec7f52	Refactor output file naming in script.py	2023-12-21 10:17:41 -06:00
erew123	f25d2627cd	updated timeout to 80 seconds Much older systems with low system ram are taking 70 seconds to start up (so Im told). Ive added an extra 20 seconds onto the 60 seconds for subprocess start-up. documentation updated too.	2023-12-21 12:47:53 +00:00
erew123	3e6f1bace3	Update README.md updated docs based on 80 second timeout for older systems	2023-12-21 12:45:58 +00:00
erew123	fb851ff3f0	Update README.md	2023-12-21 12:32:52 +00:00
erew123	92bf8f5de8	Update README.md	2023-12-21 12:31:56 +00:00
erew123	8f318892c2	New API endpoint adds the /api/tts-generation endpoint & documentation.	2023-12-21 11:32:59 +00:00
erew123	28a62ed39a	Merge pull request #12 from erew123/revert-9-refactor_output_filename_setting Revert "Refactor output file naming in script.py"	2023-12-21 06:27:23 +00:00
erew123	4c08927ed9	Revert "Refactor output file naming in script.py"	2023-12-21 06:26:32 +00:00
erew123	a93da39711	Merge pull request #9 from danielwburch/refactor_output_filename_setting Refactor output file naming in script.py	2023-12-21 06:14:03 +00:00
Daniel Burch	557f4b80b6	Refactor output file naming in script.py	2023-12-20 15:07:28 -06:00