Merge pull request #31 from erew123/dev

3x new API endpoints & Play audio at command prompt/terminal

README.md

@@ -21,22 +21,27 @@ AllTalk is an updated version of the Coqui_tts extension for Text Generation web
 - 🟨 [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
-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.
+**Dec 28th**- Finetuning has been updated to compact models and make the final steps easier (buttons basically). Narrator has been updated. If you wish to compact existing finetuned models, pre the update please see [here](https://github.com/erew123/alltalk_tts/issues/28)
 
-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).
+**Dec 25th** - Applied a small update to avoid a possible race condition on file naming with small sentences when generating narrator/character speech. Please update if you are experiencing missing small bits of missing audio on narrator/character.
+
+####     🔄 **Minor updates/bug fixes list** can be found [here](https://github.com/erew123/alltalk_tts/issues/25)
 
 ## 🟩 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`
@@ -47,17 +52,17 @@ 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 that are correct for your machine:<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>
 **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.
@@ -139,12 +144,13 @@ 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/35898566/548619c8-5f1b-47d0-a73d-54d2fee3f3db) |
+|![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/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>
@@ -203,6 +209,19 @@ Other 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>
@@ -254,17 +273,23 @@ I would suggest that if its in an interview format, you cut out the interviewer
 #### ⚫ 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)
-- When you run the installation, select **Custom Advanced** as your installation type. Uncheck `CUDA`, `Other Components` and `Driver Components` at the top then expand `CUDA` > `Development` > `Compiler` > and select `nvcc` then expand `Libraries` and select `CUBLAS`
+- Run the installer. At minimum, you need to [minimally] install the `nvcc` compiler and the `CUBLAS` development and runtime libraries:
-- Back at the top of `CUDA` expand `Runtime` > `Libraries` and select `CUBLAS`. You can now next through the install.
+  - 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 an Linux, you will 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.<br><br>
+- 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`<br><br>
+  - **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:<br>
+  - **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<br>
+    - `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`<br>
+    - `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.<br><br>
+    - 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 and `nvcc --version`. It should report back `Cuda compilation tools, release 11.8.` at which point, you are good to go.
+- 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 doesnt report that, check you have correctly set the search environment paths, dont have overlapping other versions of cuda paths etc.
+- 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. 
@@ -445,13 +470,96 @@ 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/)
+
+#### 🟦 (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.
 
-- URL: `http://127.0.0.1:7851/api/tts-generate`<br>
+#### 🟠 Ready Endpoint<br>
-- Method: `POST`<br>
+Check if the Text-to-Speech (TTS) service is ready to accept requests.
-- Content-Type: `application/x-www-form-urlencoded`<br>
+
+- 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.
+
+   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>
@@ -508,22 +616,22 @@ Example:
 
 🟠 **language**: Choose the language for TTS. Options:
 
-`ar Arabic`<br>
+`ar` Arabic<br>
-`zh-cn Chinese (Simplified)`<br>
+`zh-cn` Chinese (Simplified)<br>
-`cs Czech`<br>
+`cs` Czech<br>
-`nl Dutch`<br>
+`nl` Dutch<br>
-`en English`<br>
+`en` English<br>
-`fr French`<br>
+`fr` French<br>
-`de German`<br>
+`de` German<br>
-`hu Hungarian`<br>
+`hu` Hungarian<br>
-`it Italian`<br>
+`it` Italian<br>
-`ja Japanese`<br>
+`ja` Japanese<br>
-`ko Korean`<br>
+`ko` Korean<br>
-`pl Polish`<br>
+`pl` Polish<br>
-`pt Portuguese`<br>
+`pt` Portuguese<br>
-`ru Russian`<br>
+`ru` Russian<br>
-`es Spanish`<br>
+`es` Spanish<br>
-`tr Turkish`<br>
+`tr` Turkish<br>
 
 `-d "language=en"`<br>
 
@@ -536,12 +644,12 @@ Example:
 `-d "output_file_timestamp=true"`<br>
 `-d "output_file_timestamp=false"`
 
-🟠 **autoplay**: Feature not yet available. Enable or disable autoplay. Still needs to be specified in the JSON request.
+🟠 **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**: Feature not yet available. Set the autoplay volume. Should be between 0.1 and 1.0. Still needs to be specified in the JSON request.
+🟠 **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"`
 
@@ -556,29 +664,6 @@ 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"}`
 
-🟠 **Switching Model**<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.
-
-JSON return `{"status": "model-success"}`
-
-🟠 **Switch DeepSpeed**<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**<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"}`
-
 ### 🔴 Future to-do list
 - Voice output within the command prompt/terminal (TBD).
 - Correct a few spelling mistakes in the documentation.

diagnostics.py

@@ -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())

finetune.py

@@ -14,6 +14,7 @@ import gc
 import time
 import shutil
 import pandas
+import glob
 import json
 from pathlib import Path
 from tqdm import tqdm
@@ -40,6 +41,7 @@ if modeldownload_config_file_path.exists():
     # Extract settings from the loaded JSON
     base_path = Path(settings.get("base_path", ""))
     model_path = Path(settings.get("model_path", ""))
+    base_model_path = Path(settings.get("model_path", ""))
     files_to_download = settings.get("files_to_download", {})
 else:
     # Default settings if the JSON file doesn't exist or is empty
@@ -495,7 +497,114 @@ xtts_config_files = find_jsons(main_directory, "config.json")
 # XTTS vocab files (vocab.json)
 xtts_vocab_files = find_jsons(main_directory, "vocab.json")
 
+##########################
+#### STEP 4 AND OTHER ####
+##########################
 
+def find_latest_best_model(folder_path):
+    search_path = folder_path / "XTTS_FT-*" / "best_model.pth"
+    files = glob.glob(str(search_path), recursive=True)
+    latest_file = max(files, key=os.path.getctime, default=None)
+    return latest_file
+
+def compact_model():
+    this_dir = Path(__file__).parent.resolve()
+
+    best_model_path_str = find_latest_best_model(this_dir / "finetune" / "tmp-trn" / "training")
+
+    # Check if the best model file exists
+    if best_model_path_str is None:
+        print("No trained model was found.")
+        return "No trained model was found."
+
+    # Convert model_path_str to Path
+    best_model_path = Path(best_model_path_str)
+
+    # Attempt to load the model
+    try:
+        checkpoint = torch.load(best_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]
+
+    # Define the target directory
+    target_dir = this_dir / "models" / "trainedmodel"
+
+    # Create the target directory if it doesn't exist
+    target_dir.mkdir(parents=True, exist_ok=True)
+
+    # Save the modified checkpoint in the target directory
+    torch.save(checkpoint, target_dir / "model.pth")
+
+    # Specify the files you want to copy
+    files_to_copy = ["vocab.json", "config.json", "dvae.pth", "mel_stats.pth"]
+
+    for file_name in files_to_copy:
+        src_path = this_dir / base_path / base_model_path / file_name
+        dest_path = target_dir / file_name
+        shutil.copy(str(src_path), str(dest_path))
+
+    source_wavs_dir = this_dir / "finetune" / "tmp-trn" / "wavs"
+    target_wavs_dir = target_dir / "wavs"
+    target_wavs_dir.mkdir(parents=True, exist_ok=True)
+
+    # Iterate through files in the source directory
+    for file_path in source_wavs_dir.iterdir():
+        # Check if it's a file and larger than 1000 KB
+        if file_path.is_file() and file_path.stat().st_size > 1000 * 1024:
+            # Copy the file to the target directory
+            shutil.copy(str(file_path), str(target_wavs_dir / file_path.name))
+    
+    print("[FINETUNE] Model copied to '/models/trainedmodel/'")
+    return "Model copied to '/models/trainedmodel/'"
+
+
+def delete_training_data():
+    # Define the folder to be deleted
+    folder_to_delete = Path(this_dir / "finetune" / "tmp-trn")
+
+    # Check if the folder exists before deleting
+    if folder_to_delete.exists():
+        # Delete the folder and its contents
+        shutil.rmtree(folder_to_delete)
+        print(f"[FINETUNE] Folder {folder_to_delete} and its contents deleted successfully.")
+        return "Folder '/finetune/tmp-trn/' and its contents deleted successfully."
+    else:
+        print(f"[FINETUNE] Folder {folder_to_delete} does not exist.")
+        return "Folder '/finetune/tmp-trn/' does not exist."
+
+def delete_voice_sample_contents():
+    # Define the folder to be cleared
+    folder_to_clear = Path(this_dir / "finetune" / "put-voice-samples-in-here")
+
+    # Check if the folder exists before clearing its contents
+    if folder_to_clear.exists() and folder_to_clear.is_dir():
+        # List all files and subdirectories in the folder
+        for item in os.listdir(folder_to_clear):
+            item_path = folder_to_clear / item
+            if item_path.is_file():
+                # If it's a file, remove it
+                os.remove(item_path)
+            elif item_path.is_dir():
+                # If it's a subdirectory, remove it recursively
+                shutil.rmtree(item_path)
+
+        print(f"[FINETUNE] Contents of {folder_to_clear} deleted successfully.")
+        return f"Contents of 'put-voice-samples-in-here deleted' successfully."
+    else:
+        print(f"[FINETUNE] Folder {folder_to_clear} does not exist.")
+        return f"Folder 'put-voice-samples-in-here' does not exist."
+
+
+#######################
+#### OTHER Generic ####
+#######################
 # define a logger to redirect 
 class Logger:
     def __init__(self, filename="finetune.log"):
@@ -744,6 +853,7 @@ if __name__ == "__main__":
 
                 print("[FINETUNE] Dataset Generated. Move to Step 2")
                 return "Dataset Generated. Move to Step 2", train_meta, eval_meta
+            
 #######################
 #### GRADIO STEP 2 ####
 #######################
@@ -941,22 +1051,25 @@ if __name__ == "__main__":
                 f"""
                 ## <u>What to do next</u><br>
                 ### 🟦 <u>What you need to do</u>
-                #### &nbsp;&nbsp;&nbsp;&nbsp; 🟦 The wav(s) you liked from <span style="color: #3366ff;">Speaker Reference Audios</span> are in <span style="color: #3366ff;">/finetune/tmp-trn/wavs/</span> so copy the one(s) you selected to your <span style="color: #3366ff;">/alltalk_tts/voices/</span> samples folder.
+                #### &nbsp;&nbsp;&nbsp;&nbsp; 🟦 There are 3x buttons below:
-                #### &nbsp;&nbsp;&nbsp;&nbsp; 🟦 You can delete your original samples from inside of the <span style="color: #3366ff;">/finetune/put-voice-samples-in-here/</span> folder.
+                #### &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 🔹 Compact &amp; move model. This will compress the trained model and move it, along with any large enough wav files created to <span style="color: #3366ff;">/models/trainedmodel/</span>. You can use the wav files as sample voices..
-                #### &nbsp;&nbsp;&nbsp;&nbsp; 🟦 In the folder <span style="color: #3366ff;">/finetune/tmp-trn/training/XTTS_FT(date here)/</span> you will find your <span style="color: #3366ff;">best_model.pth</span>, <span style="color: #3366ff;">config.json</span> and <span style="color: #3366ff;">vocab.json</span> (also the last epoch training best_model_xxx.pth)
+                #### &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 🔹 Delete Generated Training data. This will delete the finetuned model and any other training data generated during this process. You will more than likely want to do this after you have Compacted &amp; moved the model.
-                #### &nbsp;&nbsp;&nbsp;&nbsp; 🟦 You can delete the last epoch training model file <span style="color: #3366ff;">best_model_xxx.pth</span> (the one with the numbers).
+                #### &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 🔹 Delete original voice samples. This will delete the voice samples you placed in put-voice-samples-in-here (if you no longer have a use for them).
-                #### &nbsp;&nbsp;&nbsp;&nbsp; 🟦 You will need to rename <span style="color: #3366ff;">best_model.pth</span> to <span style="color: #3366ff;">model.pth</span>.
+                #### &nbsp;&nbsp;&nbsp;&nbsp; 🟦 I will at some point add an option within AllTalk to load a finetuned model as a seperate model. However, for now, you will have to copy it over the model in the <span style="color: #3366ff;">/models/xttsv2_2.0.2/</span> model, if you wish to use it.
-                #### &nbsp;&nbsp;&nbsp;&nbsp; 🟦 You will close the Finetuning application and copy your 3 files listed above over the top of the existing model files inside your <span style="color: #3366ff;">/alltalk_tts/models/xttsv2_2.0.2/</span> folder. 
+                #### &nbsp;&nbsp;&nbsp;&nbsp; 🟦 If you wish to further train this model, you will also need to copy it over the model in the <span style="color: #3366ff;">/models/xttsv2_2.0.2/</span> model folder.. 
-                #### &nbsp;&nbsp;&nbsp;&nbsp; 🟦 Start up Alltalk and you should be off and running. Preferably use the <span style="color: #3366ff;">XTTS Local</span> method for best results. 
                 ### 🟨 <u>Clearing up disk space</u>
-                #### &nbsp;&nbsp;&nbsp;&nbsp; 🟨 When you are happy with everything, you can delete the <span style="color: #3366ff;">/alltalk_tts/finetune/tmp-trn/</span> folder. This will delete all training data that was generated.
                 #### &nbsp;&nbsp;&nbsp;&nbsp; 🟨 If you are not going to train anything again, you can delete the whisper model from inside of your huggingface cache (3GB approx) 
                 #### &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Linux <span style="color: #3366ff;">~/.cache/huggingface/hub/(folder-here)</span>
                 #### &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Windows <span style="color: #3366ff;">C:&bsol;users&lpar;your-username&rpar;&bsol;.cache&bsol;huggingface&bsol;hub&bsol;(folder-here)</span>.
                 #### &nbsp;&nbsp;&nbsp;&nbsp; 🟨 You can also uninstall the Nvidia CUDA 11.8 Toolkit if you wish and remove your environment variable entries.
                 """
             )
-
+            final_progress_data = gr.Label(
+                label="Progress:"
+            )
+            compact_btn = gr.Button(value="Compact and move model to '/models/trainedmodel/' (THIS WILL OVER-WRITE ANY MODEL IN THAT LOCATION)")
+            delete_training_btn = gr.Button(value="Delete generated training data")
+            delete_voicesamples_btn = gr.Button(value="Delete original voice samples")
 
             prompt_compute_btn.click(
                 fn=preprocess_dataset,
@@ -1008,6 +1121,19 @@ if __name__ == "__main__":
                 outputs=[progress_gen, tts_output_audio, reference_audio],
             )
             
+            compact_btn.click(
+                fn=compact_model,
+                outputs=[final_progress_data],
+            )
+            delete_training_btn.click(
+                fn=delete_training_data,
+                outputs=[final_progress_data],
+            )
+            delete_voicesamples_btn.click(
+                fn=delete_voice_sample_contents,
+                outputs=[final_progress_data],
+            )
+
     demo.queue().launch(
         show_api=False,
         inbrowser=True,

finetune/compact.py

@@ -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.")

modeldownload.json

@@ -8,6 +8,7 @@
         "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"
     }
 }

requirements_nvidia.txt

@@ -11,3 +11,5 @@ 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

requirements_other.txt

@@ -11,3 +11,5 @@ 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

script.py

@@ -252,7 +252,7 @@ else:
 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:
@@ -264,7 +264,7 @@ while time.time() - start_time < timeout:
         print(
             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."
@@ -483,6 +483,9 @@ 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 ####
 #################################
@@ -491,6 +494,7 @@ def output_modifier(string, state):
     if not params["activate"]:
         return string
     original_string = string
+    #print("ORGINAL STRING: ", original_string)
     cleaned_string = before_audio_generation(string, params)
     if cleaned_string is None:
         return
@@ -508,25 +512,28 @@ def output_modifier(string, state):
                     .replace("***", "*")
                     .replace("**", "*")
                     .replace("\n\n", "\n")
-                )
-                # Clean up two asterisks (narrators) being made between a newline, making it one sentence.
-                processed_string = re.sub(r'\.\*\n\*', '. ', processed_string)
-                # Clean up a few other bits.
-                processed_string = (
-                    processed_string
-                    .replace("&#x27;", "'")
                     .replace("\n", "")
-                    # Add special characters to the quote so that we can use it to identify things later after its been split
-                    .replace('&quot;', '&quot;<')
-                    # Capture new conversations which wont have things like &quote in them
-                    .replace('"', '&quot;<')
                 )
-                #capturing another outlier in inital character paragraph
+                processed_string = re.sub(r'\.\*\n\*', '. ', processed_string)
-                # print("processed string 1 is:", processed_string)
+                processed_string = (processed_string .replace('&quot;\n\n*', '&quot;<*'))
+                processed_string = (processed_string .replace('&quot;\n', '< '))
+                processed_string = (processed_string .replace("&#x27;", "'"))
+                processed_string = (processed_string .replace("\n", " "))
+                processed_string = (processed_string .replace('&quot;', '&quot;<'))
+                processed_string = (processed_string .replace('"', '&quot;<'))
+                #pattern = re.compile(r'(?<=[a-zA-Z!])&quot;<(?=[a-zA-Z])')
+                pattern = re.compile(r'(?<=[a-zA-Z!?\.])&quot;<(?=[a-zA-Z])')
+                processed_string = pattern.sub('&quot; ', processed_string)
+                pattern = re.compile(r'(?<=[a-zA-Z])\*(?=[a-zA-Z])')
+                processed_string = pattern.sub('*&quot;', 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 *
@@ -534,7 +541,7 @@ 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
@@ -576,9 +583,14 @@ def output_modifier(string, state):
                 )
                 cleaned_part = html.unescape(processed_string)                
                 # Process the part and give it a non-character name if being used vai API or standalone.
-                output_filename = get_output_filename(state)
+                if "character_menu" in state:
+                    output_file = Path(f'{params["output_folder_wav"]}/{state["character_menu"]}_{int(time.time())}.wav')
+                else:
+                    output_file = Path(f'{params["output_folder_wav"]}/TTSOUT_{int(time.time())}.wav')
+                output_file_str = output_file.as_posix()
+                output_file = get_output_filename(state)
                 generate_response = send_generate_request(
-                    cleaned_part, params["voice"], language_code, output_filename
+                    cleaned_part, params["voice"], language_code, output_file_str
                 )
                 audio_path = generate_response.get("data", {}).get("audio_path")
                 final_output_file = audio_path
@@ -618,11 +630,10 @@ def output_modifier(string, state):
 
 
 def get_output_filename(state):
-     # Check if character name exists and if not, just call it TTSOUT_
     if "character_menu" in state:
-        return Path(f'{params["output_folder_wav"]}/{state["character_menu"]}_{int(time.time())}.wav').as_posix()
+        return Path(f'{params["output_folder_wav"]}/{state["character_menu"]}_{str(uuid.uuid4())[:8]}.wav').as_posix()
     else:
-        return Path(f'{params["output_folder_wav"]}/TTSOUT_{int(time.time())}.wav').as_posix()
+        return Path(f'{params["output_folder_wav"]}/TTSOUT_{str(uuid.uuid4())[:8]}.wav').as_posix()
 
 
 ###############################################
@@ -782,7 +793,7 @@ def ui():
             )
             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():

tts_server.py

@@ -619,16 +619,84 @@ 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
@@ -802,7 +870,7 @@ async def tts_generate(
                     print("ELSE - NARRATOR\n")
                     cleaned_part = html.unescape(part.replace('< ', '').replace('<  ', '').replace('<  ', ''))
                     voice_to_use = narrator_voice_gen
-                output_file = this_dir / "outputs" / f"{output_file_name}_{int(time.time())}_{i}.wav"
+                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
@@ -826,6 +894,10 @@ async def tts_generate(
             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)
@@ -1052,6 +1124,12 @@ 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>
@@ -1151,7 +1229,7 @@ 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>
@@ -1666,6 +1744,33 @@ simple_webpage = """
 <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>
@@ -1710,10 +1815,20 @@ 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)