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Updated Docs & config file

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Had to update a variable due to the latest version of pydantic using a similar variable and causing a potential clash. As such, I have had to use a new configuration file (simplest method). Peoples base settings will be reset on next update. Added a option in the config file for standalone mode output.
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erew123 authored and GitHub committed 2023-12-17 11:02:32 +00:00
1 parent ff911ee73d
commit 9306b31c12
7 files changed
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confignew.json
+1
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@@ -0,0 +1 @@
{"activate": true, "autoplay": true, "branding": "AllTalk ", "narrator_enabled": false, "deepspeed_activate": false, "delete_output_wavs": "Disabled", "ip_address": "127.0.0.1", "language": "English", "low_vram": false, "local_temperature": "0.7", "local_repetition_penalty": "10.0", "tts_model_loaded": true, "tts_model_name": "tts_models/multilingual/multi-dataset/xtts_v2", "narrator_voice": "female_01.wav", "output_folder_wav": "extensions/alltalk_tts/outputs/", "output_folder_wav_standalone": "outputs/", "port_number": "7851", "remove_trailing_dots": false, "show_text": true, "tts_method_api_local": false, "tts_method_api_tts": false, "tts_method_xtts_local": true, "voice": "female_01.wav"}
modeldownload.py
+4 -4
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@@ -6,9 +6,9 @@ import importlib.metadata as metadata
import json
from packaging import version
##############################################################
#### LOAD PARAMS FROM CONFIG.JSON - REQUIRED FOR BRANDING ####
##############################################################
#################################################################
#### LOAD PARAMS FROM confignew.json - REQUIRED FOR BRANDING ####
#################################################################
# STARTUP VARIABLE - Create "this_dir" variable as the current script directory
this_dir = Path(__file__).parent.resolve()
@@ -20,7 +20,7 @@ def load_config(file_path):
return config
config_file_path = this_dir / "config.json"
config_file_path = this_dir / "confignew.json"
params = load_config(config_file_path)
# Define the path to the modeldownload config file file
requirements_nvidia.txt
+1 -1
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@@ -1,7 +1,7 @@
numpy>=1.22.0
soundfile>=0.12.1
uvicorn>=0.24.0.post1
TTS>=0.21.3
TTS>=0.22.0
torch>=2.1.0+cu118
torchaudio>=2.1.0+cu118
fastapi>=0.104.1
requirements_other.txt
+1 -1
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@@ -1,7 +1,7 @@
numpy>=1.22.0
soundfile>=0.12.1
uvicorn>=0.24.0.post1
TTS>=0.21.3
TTS>=0.22.0
torch>=2.1.0
torchaudio>=2.1.0
fastapi>=0.104.1
script.py
+17 -17
View File
@@ -16,9 +16,9 @@ import numpy as np
import soundfile as sf
import uuid
##############################################################
#### LOAD PARAMS FROM CONFIG.JSON - REQUIRED FOR BRANDING ####
##############################################################
#################################################################
#### LOAD PARAMS FROM confignew.json - REQUIRED FOR BRANDING ####
#################################################################
# STARTUP VARIABLE - Create "this_dir" variable as the current script directory
this_dir = Path(__file__).parent.resolve()
@@ -28,8 +28,8 @@ def load_config(file_path):
config = json.load(config_file)
return config
config_file_path = this_dir / "config.json"
# Load the params dictionary from the config.json file
config_file_path = this_dir / "confignew.json"
# Load the params dictionary from the confignew.json file
params = load_config(config_file_path)
# Required for sentence splitting
@@ -143,9 +143,9 @@ def check_required_files():
check_required_files()
#################################################
#### SET GRADIO BUTTONS BASED ON CONFIG.JSON ####
#################################################
####################################################
#### SET GRADIO BUTTONS BASED ON confignew.json ####
####################################################
if params["tts_method_api_tts"] == True:
gr_modelchoice = "API TTS"
@@ -277,7 +277,7 @@ else:
# MODEL - Swap model based on Gradio selection API TTS, API Local, XTTSv2 Local
def send_reload_request(tts_method):
try:
params["model_loaded"] = False
params["tts_model_loaded"] = False
url = f"{base_url}/api/reload"
payload = {"tts_method": tts_method}
response = requests.post(url, params=payload)
@@ -285,8 +285,8 @@ def send_reload_request(tts_method):
json_response = response.json()
# Check if the reload operation was successful
if json_response.get("status") == "model-success":
# Update model_loaded to True if the reload was successful
params["model_loaded"] = True
# Update tts_tts_model_loaded to True if the reload was successful
params["tts_model_loaded"] = True
# Update local script parameters based on the tts_method
if tts_method == "API TTS":
params["tts_method_api_local"] = False
@@ -319,7 +319,7 @@ def send_reload_request(tts_method):
# LOW VRAM - Gradio Checkbox handling
def send_lowvram_request(low_vram):
try:
params["model_loaded"] = False
params["tts_model_loaded"] = False
if low_vram:
audio_path = this_dir / "templates" / "lowvramenabled.wav"
else:
@@ -332,7 +332,7 @@ def send_lowvram_request(low_vram):
# Check if the low VRAM request was successful
if json_response.get("status") == "lowvram-success":
# Update any relevant variables or perform other actions on success
params["model_loaded"] = True
params["tts_model_loaded"] = True
return f'<audio src="file/{audio_path}" controls autoplay></audio>'
except requests.exceptions.RequestException as e:
# Handle the HTTP request error
@@ -348,7 +348,7 @@ def send_lowvram_request(low_vram):
# DEEPSPEED - Reload the model when DeepSpeed checkbox is enabled/disabled
def send_deepspeed_request(deepspeed_param):
try:
params["model_loaded"] = False
params["tts_model_loaded"] = False
if deepspeed_param:
audio_path = this_dir / "templates" / "deepspeedenabled.wav"
else:
@@ -362,7 +362,7 @@ def send_deepspeed_request(deepspeed_param):
# Check if the deepspeed request was successful
if json_response.get("status") == "deepspeed-success":
# Update any relevant variables or perform other actions on success
params["model_loaded"] = True
params["tts_model_loaded"] = True
return f'<audio src="file/{audio_path}" controls autoplay></audio>'
except requests.exceptions.RequestException as e:
# Handle the HTTP request error
@@ -400,7 +400,7 @@ Synthesizer.split_into_sentences = new_split_into_sentences
# Check model is loaded and string isnt empty, before sending a TTS request.
def before_audio_generation(string, params):
# Check Model is loaded into cuda or cpu and error if not
if not params["model_loaded"]:
if not params["tts_model_loaded"]:
print(
f"[{params['branding']}Model] \033[91mWarning\033[0m Model is still loading, please wait before trying to generate TTS"
)
@@ -789,7 +789,7 @@ def ui():
)
tts_radio_buttons_play = gr.HTML(visible=False)
explanation_text = gr.HTML(
f"<p>NOTE: Switching Model Type, Low VRAM & DeepSpeed takes 15 seconds. Each TTS generation method has a slightly different sound. DeepSpeed checkbox is only visible if DeepSpeed is present. Readme & Settings: <a href='http://{params['ip_address']}:{params['port_number']}'>http://{params['ip_address']}:{params['port_number']}</a>"
f"<p>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>"
)
with gr.Row():
templates/generate_form.html
+3 -3
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@@ -201,12 +201,12 @@
value="{{ data.output_folder_wav }}" />
<input type="hidden" id="model_loaded" name="model_loaded" value="{{ data.model_loaded }}" />
<input type="hidden" id="tts_model_loaded" name="tts_model_loaded" value="{{ data.tts_model_loaded }}" />
<!-- Continue updating other dropdowns and inputs in a similar manner -->
<label for="model_name" style="color: red;"> API TTS Model Name:</label>
<input id="model_name" name="model_name" required="" type="text" value="{{ data.model_name }}" />
<label for="tts_model_name" style="color: red;"> API TTS Model Name:</label>
<input id="tts_model_name" name="tts_model_name" required="" type="text" value="{{ data.tts_model_name }}" />
<label for="model_version"
style="color: red; font-size: 16px; line-height: 1; vertical-align: bottom; margin-bottom: 0;">&nbsp;
tts_server.py
+28 -28
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@@ -35,9 +35,9 @@ with open(this_dir / "languages.json", encoding="utf8") as f:
languages = json.load(f)
##############################################################
#### LOAD PARAMS FROM CONFIG.JSON - REQUIRED FOR BRANDING ####
##############################################################
#################################################################
#### LOAD PARAMS FROM confignew.json - REQUIRED FOR BRANDING ####
#################################################################
# Load config file and get settings
def load_config(file_path):
with open(file_path, "r") as configfile_path:
@@ -45,10 +45,10 @@ def load_config(file_path):
return configfile_data
# Define the path to the config.json file
configfile_path = this_dir / "config.json"
# Define the path to the confignew.json file
configfile_path = this_dir / "confignew.json"
# Load config.json and assign it to a different variable (config_data)
# Load confignew.json and assign it to a different variable (config_data)
params = load_config(configfile_path)
# check someone hasnt enabled lowvram on a system thats not cuda enabled
params["low_vram"] = "false" if not torch.cuda.is_available() else params["low_vram"]
@@ -131,7 +131,7 @@ async def setup():
# Start loading the correct model as set by "tts_method_api_tts", "tts_method_api_local" or "tts_method_xtts_local" being True/False
if params["tts_method_api_tts"]:
print(
f"[{params['branding']}Model] \033[94mAPI TTS Loading\033[0m {params['model_name']} \033[94minto\033[93m",
f"[{params['branding']}Model] \033[94mAPI TTS Loading\033[0m {params['tts_model_name']} \033[94minto\033[93m",
device,
"\033[0m",
)
@@ -158,8 +158,8 @@ async def setup():
print(
f"[{params['branding']}Model] \033[94mModel Loaded in \033[93m{generate_elapsed_time:.2f} seconds.\033[0m"
)
# Set "model_loaded" to true
params["model_loaded"] = True
# 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)
@@ -167,7 +167,7 @@ async def setup():
# MODEL LOADER For "API TTS"
async def api_load_model():
global model
model = TTS(params["model_name"]).to(device)
model = TTS(params["tts_model_name"]).to(device)
return model
@@ -227,7 +227,7 @@ async def unload_model(model):
del model
if torch.cuda.is_available():
torch.cuda.empty_cache()
params["model_loaded"] = False
params["tts_model_loaded"] = False
return None
@@ -520,7 +520,7 @@ templates = Jinja2Templates(directory=this_dir / "templates")
# Create a dependency to get the current JSON data
def get_json_data():
with open(this_dir / "config.json", "r") as json_file:
with open(this_dir / "confignew.json", "r") as json_file:
data = json.load(json_file)
return data
@@ -555,8 +555,8 @@ async def update_settings(
local_temperature: str = Form(...),
local_repetition_penalty: str = Form(...),
low_vram: bool = Form(...),
model_loaded: bool = Form(...),
model_name: str = Form(...),
tts_model_loaded: bool = Form(...),
tts_model_name: str = Form(...),
narrator_enabled: bool = Form(...),
narrator_voice: str = Form(...),
output_folder_wav: str = Form(...),
@@ -577,8 +577,8 @@ async def update_settings(
data["local_temperature"] = local_temperature
data["local_repetition_penalty"] = local_repetition_penalty
data["low_vram"] = low_vram
data["model_loaded"] = model_loaded
data["model_name"] = model_name
data["tts_model_loaded"] = tts_model_loaded
data["tts_model_name"] = tts_model_name
data["narrator_enabled"] = narrator_enabled
data["narrator_voice"] = narrator_voice
data["output_folder_wav"] = output_folder_wav
@@ -591,7 +591,7 @@ async def update_settings(
data["voice"] = voice
# Save the updated settings back to the JSON file
with open(this_dir / "config.json", "w") as json_file:
with open(this_dir / "confignew.json", "w") as json_file:
json.dump(data, json_file)
# Redirect to the settings page to display the updated settings
@@ -914,7 +914,7 @@ simple_webpage = """
<p>The temperature has been set at 0.70 here though, as it often produces a slightly better result (in my estimation).</p>
<p>The default settings for any model are usually provided in the config.json file that comes wtih the model and this file can be found within the folder where the model is stored.</p>
<p>The default settings for any model are usually provided in the confignew.json file that comes wtih the model and this file can be found within the folder where the model is stored.</p>
<p>These default values are carefully chosen to offer a reasonable starting point for users, and adjustments can be made based on individual preferences and use cases. However, it's important to note that changing these settings or setting them to extremes may result in unexpected outcomes. Setting extremely high or low values, especially without a good understanding of their effects, may lead to flat-sounding output or very strange-sounding output. It's advisable to experiment with adjustments incrementally and observe the impact on the generated speech to find a balance that suits your desired outcome.</p>
<p><a href="#toc">Back to top of page</a></p>
@@ -989,20 +989,20 @@ simple_webpage = """
<p>Currently/Officially only DeepSpeed v8.3 is installing on Windows, due to the broken installation routine by Microsoft, however, between myself and <a href="https://github.com/S95Sedan" target="_blank">S95Sedan</a> its now possible to install DeepSpeed v11.1 or v11.2 on Windows.</p>
<h4>DeepSpeed on Windows - <span class="option-a">Option A</span></h4>
<p>This is to use the pre built DeepSpeed v11.1 wheel file. This is quite a quick process and should work for 99&percnt; of people.</p>
<p>This is to use the pre built DeepSpeed v11.2 wheel file. This is quite a quick process and should work for 99&percnt; of people.</p>
<p><strong>Note:</strong> In my tests, with this method you will <strong>not</strong> need to install the Nvidia CUDA toolkit to make this work, but AllTalk may warn you when starting DeepSpeed that it doesn't see the CUDA Toolkit; however, it works fine for TTS purposes.</p>
<ol>
<li>Download the file <a href="https://drive.google.com/file/d/1PFsf6uSPY5Cb4o9VxiZ7DLv-j35L7Y41/view?usp=sharing" target="_blank">deepspeed-0.11.1+e9503fe-cp311-cp311-win_amd64.whl</a> by clicking the <strong>download</strong> icon at the top right of the screen and save the file it inside your <strong>text-generation-webui</strong> folder.</li>
<li>Download the correct wheel version for your CUDA and Python version file <a href="https://github.com/erew123/alltalk_tts/releases/tag/deepspeed" target="_blank">from here</a> and save the file it inside your <strong>text-generation-webui</strong> folder.</li>
<li>At a command prompt window, move into your <strong>text-generation-webui folder</strong>, you can now start the Python environment for text-generation-webui:
<br><code>cmd_windows.bat</code></li>
<li>At a command prompt window, move into your <strong>text-generation-webui folder</strong>, you can now start the Python environment for text-generation-webui:<br>
<br><code>cmd_windows.bat</code></li><br>
<li>With the file that you saved in the <strong>text-generation-webui folder</strong>, you now type the following:
<br><code>pip install "deepspeed-0.11.1+e9503fe-cp311-cp311-win_amd64.whl"</code></li>
<li>With the file that you saved in the <strong>text-generation-webui folder</strong>, you now type the following:<br>
<br><code>pip install "deepspeed-0.11.2+<b>yourversionhere</b>-win_amd64.whl"</code></li><br>
<li>This should install through cleanly and you should now have DeepSpeed v11.1 installed within the Python 3.11 environment of text-generation-webui.</li>
<li>This should install through cleanly and you should now have DeepSpeed v11.2 installed within the Python 3.11 environment of text-generation-webui.</li>
<li>When you start up text-generation-webui, and AllTalk starts, you should see <strong>[AllTalk Startup] DeepSpeed Detected</strong></li>
@@ -1138,7 +1138,7 @@ simple_webpage = """
<p><a href="#toc">Back to top of page</a></p>
<h3 id="configuration-details"><strong>Configuration Details</strong></h3>
<p>Explanation of the <b>config.json</b> file:</p>
<p>Explanation of the <b>confignew.json</b> file:</p>
<code><span class="key">"activate:"</span> <span class="value">true</span>,</code><span class="key"> Used within the code, do not change.</span><br>
<code><span class="key">"autoplay:"</span> <span class="value">true</span>,</code><span class="key"> Controls whether the TTS audio plays automatically within Text generation webUI.</span><br>
@@ -1150,8 +1150,8 @@ simple_webpage = """
<code><span class="key">"low_vram:"</span> <span class="value">false</span>,</code><span class="key"> Controls whether the Low VRAM option is enabled or disabled.</span><br>
<code><span class="key">"local_temperature:"</span> <span class="value">"0.70"</span>,</code><span class="key"> Sets the temperature to use with the API Local and XTTSv2 Local methods.</span><br>
<code><span class="key">"local_repetition_penalty:"</span> <span class="value">"10.0"</span>,</code><span class="key"> Sets the repetition penalty to use with the API Local and XTTSv2 Local methods.</span><br>
<code><span class="key">"model_loaded:"</span> <span class="value">true</span>,</code><span class="key"> Used within the code, do not change.</span><br>
<code><span class="key">"model_name:"</span> <span class="value">"tts_models/multilingual/multi-dataset/xtts_v2"</span>,</code><span class="key"> Specifies the model that the "API TTS" method will use for TTS generation.</span><br>
<code><span class="key">"tts_model_loaded:"</span> <span class="value">true</span>,</code><span class="key"> Used within the code, do not change.</span><br>
<code><span class="key">"tts_model_name:"</span> <span class="value">"tts_models/multilingual/multi-dataset/xtts_v2"</span>,</code><span class="key"> Specifies the model that the "API TTS" method will use for TTS generation.</span><br>
<code><span class="key">"narrator_enabled:"</span> <span class="value">"female_02.wav"</span>,</code><span class="key"> Specifies the default narrator voice to use for TTS.</span><br>
<code><span class="key">"narrator_voice:"</span> <span class="value">"false"</span>,</code><span class="key"> Enables and disables the narrator function.</span><br>
<code><span class="key">"port_number:"</span> <span class="value">"7851"</span>,</code><span class="key"> Specifies the default port number for the web server.</span><br>