Add files via upload

TTS Generator - Various interface bugs & filtering options cleaned up.
TTS Generator - TTSDiff now scans generated text and TTS for errors.
TTS Generator - TTSSRT now creates subtitle files for video production e.g. a Youtube video.
Finetune - Now uses a customised tokenizer to deal with Japanese.
Finetune - Pre flight check and warning messages.
Finetune - Extra documentation and warnings.
Entire file structure has been re-organised to simplify management and future changes.
Documentation (built in and Github) has been rewritten/tidied up.
Requirements files have been cleaned up and simplified.
ATsetup has been re-written as necessary with additional options.
DeepSpeed moved up to version 14.
Standalone Application moved to PyTorch 2.2.1.
Nvidia CUDA Toolkit installation is NO LONGER needed (other than to compile DeepSpeed on Linux)

Tested on Linux and Windows.

.github/FUNDING.yml

@@ -0,0 +1 @@
+ko_fi: erew123

.github/ISSUE_TEMPLATE/bug-report-support-request.md

@@ -1,17 +1,16 @@
 ---
-name: Bug report/Support request
+name: Support request OR Bug report
 about: Create a report to help us improve
 title: ''
 labels: ''
 assignees: ''
 
 ---
+🔴 If you have installed AllTalk in a custom Python environment, I will only be able to provide limited assistance/support. AllTalk draws on a variety of scripts and libraries that are not written or managed by myself, and they may fail, error or give strange results in custom built python environments.
 
-Please run the diagnostics and upload the diagnostics.log file. To do this, start Text-generation-webui's Python environment with "cmd_windows.bat" OR "./cmd_linux.sh" OR "cmd_macos.sh" OR "cmd_wsl.bat" and then go into the \extensions\alltalk_tts\ folder and run:
+🔴 Please generate a diagnostics report and upload the "diagnostics.log" as this helps me understand your configuration.
 
-python diagnostics.py
-
-Which will both output to the screen and create a "diagnostics.log" file.
+https://github.com/erew123/alltalk_tts/tree/main?#-how-to-make-a-diagnostics-report-file
 
 **Describe the bug**
 A clear and concise description of what the bug is.

.github/workflows/publish-docker.yml

@@ -0,0 +1,67 @@
+name: Publish Docker image
+
+on:
+  push:
+    branches: [main]
+  release:
+    types: [published]
+  workflow_dispatch:
+
+jobs:
+  build_and_push:
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        include:
+          - dockerfile: "Dockerfile"
+            platforms: "linux/amd64"
+            tag_name: "cpu"
+          - dockerfile: "nvidia.Dockerfile"
+            platforms: "linux/amd64"
+            tag_name: "cuda"
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v3
+
+      - name: Lowercase Actor and Extract Repo Name
+        run: |
+          echo "ACTOR_LOWER=$(echo ${{ github.actor }} | tr '[:upper:]' '[:lower:]')" >> $GITHUB_ENV
+          echo "REPO_NAME=$(echo ${{ github.repository }} | cut -d'/' -f 2)" >> $GITHUB_ENV
+
+      - name: Login to GitHub Container Registry
+        uses: docker/login-action@v3
+        with:
+          registry: ghcr.io
+          username: ${{ env.ACTOR_LOWER }}
+          password: ${{ secrets.GITHUB_TOKEN }}
+
+      - name: Login to DockerHub
+        uses: docker/login-action@v3
+        with:
+          username: ${{ vars.DOCKERHUB_USERNAME }}
+          password: ${{ secrets.DOCKERHUB_TOKEN }}
+
+      - name: Build and push Docker image
+        uses: docker/build-push-action@v5
+        with:
+          context: .
+          file: ./${{ matrix.dockerfile }}
+          platforms: ${{ matrix.platforms }}
+          push: true
+          tags: |
+            ghcr.io/${{ env.ACTOR_LOWER }}/${{ env.REPO_NAME }}:${{ matrix.tag_name }}-${{ github.sha }}
+            ghcr.io/${{ env.ACTOR_LOWER }}/${{ env.REPO_NAME }}:${{ matrix.tag_name }}
+            ghcr.io/${{ env.ACTOR_LOWER }}/${{ env.REPO_NAME }}:latest
+            ${{ vars.DOCKERHUB_USERNAME }}/${{ env.REPO_NAME }}:${{ matrix.tag_name }}-${{ github.sha }}
+            ${{ vars.DOCKERHUB_USERNAME }}/${{ env.REPO_NAME }}:${{ matrix.tag_name }}
+            ${{ vars.DOCKERHUB_USERNAME }}/${{ env.REPO_NAME }}:latest
+
+      - name: Docker Hub Description
+        uses: peter-evans/dockerhub-description@v3.4.2
+        with:
+          username: ${{ vars.DOCKERHUB_USERNAME }}
+          password: ${{ secrets.DOCKERHUB_TOKEN }}
+          repository: ${{ vars.DOCKERHUB_USERNAME }}/${{ env.REPO_NAME }}

.gitignore

@@ -1,6 +1,7 @@
 voices/*.*
 models/*.*
 outputs/*.*
+finetune/*.*
 config.json
 confignew.json
 models.json

.vscode/settings.json

@@ -0,0 +1,9 @@
+{
+    "files.associations": {
+        "*.html": "jinja-html"
+    },
+    "emmet.includeLanguages": {
+        "jinja-html": "html",
+        "jinja2": "html"
+    },
+}

Deepspeed-Windows/11.1/csrc/quantization/pt_binding.cpp

@@ -1,285 +0,0 @@
-// Copyright (c) Microsoft Corporation.
-// SPDX-License-Identifier: Apache-2.0
-
-// DeepSpeed Team
-
-#include <ATen/cuda/CUDAContext.h>
-#include <torch/extension.h>
-#include <cassert>
-#include <vector>
-#include "quantization.h"
-
-template <typename T>
-at::Tensor ds_quantize(at::Tensor& vals, int groups, int bits)
-{
-    auto t_size = vals.sizes();
-    int size = 1;
-    for (auto dim : t_size) size *= dim;
-
-    if ((((size / groups) - 1) / 4096 + 1) <= 256) {
-        launch_fake_quantize_kernel(
-            (T*)vals.data_ptr(), size, groups, bits, at::cuda::getCurrentCUDAStream());
-    }
-    return vals;
-}
-
-template <typename T>
-at::Tensor ds_sr_quantize(at::Tensor& vals, int groups, int bits)
-{
-    auto t_size = vals.sizes();
-    int size = 1;
-    for (auto dim : t_size) size *= dim;
-
-    if (((size / groups) / 4 / 1024) <= 256) {
-        launch_sr_fake_quantize_kernel(
-            (T*)vals.data_ptr(), size, groups, bits, at::cuda::getCurrentCUDAStream());
-    }
-    return vals;
-}
-
-template <typename T>
-at::Tensor ds_quantize_asym(at::Tensor& vals, int groups, int bits)
-{
-    auto t_size = vals.sizes();
-    int size = 1;
-    for (auto dim : t_size) size *= dim;
-
-    if ((((size / groups) - 1) / 4096 + 1) <= 256) {
-        launch_fake_quantize_kernel_asym(
-            (T*)vals.data_ptr(), size, groups, bits, at::cuda::getCurrentCUDAStream());
-    }
-    return vals;
-}
-
-template <typename T>
-at::Tensor ds_sr_quantize_asym(at::Tensor& vals, int groups, int bits)
-{
-    auto t_size = vals.sizes();
-    int size = 1;
-    for (auto dim : t_size) size *= dim;
-
-    if (((size / groups) / 4 / 1024) <= 256) {
-        launch_sr_fake_quantize_kernel_asym(
-            (T*)vals.data_ptr(), size, groups, bits, at::cuda::getCurrentCUDAStream());
-    }
-    return vals;
-}
-
-std::vector<at::Tensor> quantize_kernel(at::Tensor& input_vals,
-                                        int groups,
-                                        int numBits,
-                                        quantize::Type quantType)
-{
-    auto dtype = at::kFloat;
-    auto params_options = at::TensorOptions()
-                              .dtype(dtype)
-                              .layout(at::kStrided)
-                              .device(at::kCUDA)
-                              .requires_grad(false);
-    const int param_elems = (quantize::requires_offset(quantType)) ? 2 : 1;
-    auto params = torch::empty({groups, param_elems}, params_options);
-
-    auto output_options = at::TensorOptions()
-                              .dtype(at::kChar)
-                              .layout(at::kStrided)
-                              .device(at::kCUDA)
-                              .requires_grad(false);
-
-    auto output_sizes = input_vals.sizes().vec();
-    output_sizes[output_sizes.size() - 1] /= numBits == 8 ? 1 : 2;
-    auto output = torch::empty(output_sizes, output_options);
-
-    const int elems_per_group = at::numel(input_vals) / groups;
-
-    launch_quant((int8_t*)output.data_ptr(),
-                 (float*)params.data_ptr(),
-                 (__half*)input_vals.data_ptr(),
-                 groups,
-                 elems_per_group,
-                 numBits,
-                 quantType,
-                 at::cuda::getCurrentCUDAStream());
-
-    return {output, params};
-}
-
-template <typename T>
-at::Tensor dequantize(at::Tensor& quantized_data,
-                      at::Tensor& params,
-                      int groups,
-                      int num_bits,
-                      quantize::Type quant_type)
-{
-    auto dtype = (std::is_same<T, float>::value) ? torch::kFloat32 : torch::kFloat16;
-    auto output_options = at::TensorOptions()
-                              .dtype(dtype)
-                              .layout(at::kStrided)
-                              .device(at::kCUDA)
-                              .requires_grad(false);
-
-    auto output_sizes = quantized_data.sizes().vec();
-    output_sizes[output_sizes.size() - 1] *= num_bits == 8 ? 1 : 2;
-    auto output = torch::empty(output_sizes, output_options);
-
-    const int total_elems = at::numel(output);
-    const int elems_per_group = total_elems / groups;
-
-    launch_dequantize_kernel((T*)output.data_ptr(),
-                             (const int8_t*)quantized_data.data_ptr(),
-                             (const float*)params.data_ptr(),
-                             quant_type,
-                             num_bits,
-                             elems_per_group,
-                             total_elems,
-                             at::cuda::getCurrentCUDAStream());
-
-    return output;
-}
-
-at::Tensor dequantize_int4_to_half_experimental(at::Tensor& data_in,
-                                                at::Tensor& scale_buffer,
-                                                at::Tensor& min_val_buffer,
-                                                int num_group,
-                                                int group_size)
-{
-    auto output_options = at::TensorOptions().dtype(at::kHalf).device(at::kCUDA);
-    auto output = torch::empty({num_group, group_size}, output_options);
-
-    launch_dequantize_int4_to_half_experimental((uint8_t*)data_in.data_ptr(),
-                                                (half*)output.data_ptr(),
-                                                (half*)scale_buffer.data_ptr(),
-                                                (half*)min_val_buffer.data_ptr(),
-                                                num_group,
-                                                group_size,
-                                                at::cuda::getCurrentCUDAStream());
-
-    return output;
-}
-
-std::vector<at::Tensor> ds_swizzle_quant(at::Tensor& input_vals,
-                                         int groups,
-                                         int num_bits,
-                                         quantize::Type quant_type,
-                                         int pipeline_size,
-                                         int nodes,
-                                         int devices_per_node)
-{
-    auto scales_options = at::TensorOptions()
-                              .dtype(at::kFloat)
-                              .layout(at::kStrided)
-                              .device(at::kCUDA)
-                              .requires_grad(false);
-    const int scales_elems = (quantize::requires_offset(quant_type)) ? 2 : 1;
-    auto scales = torch::empty({groups, scales_elems}, scales_options);
-
-    auto output_options = at::TensorOptions()
-                              .dtype(at::kChar)
-                              .layout(at::kStrided)
-                              .device(at::kCUDA)
-                              .requires_grad(false);
-
-    const int quantization_scalar = 8 / num_bits;
-    const int compressed_vals = at::numel(input_vals) / quantization_scalar;
-
-    auto output = torch::empty({compressed_vals}, output_options);
-    const int elems_per_group = at::numel(input_vals) / groups;
-
-    launch_swizzled_quant((int8_t*)output.data_ptr(),
-                          (float*)scales.data_ptr(),
-                          (__half*)input_vals.data_ptr(),
-                          num_bits,
-                          quant_type,
-                          groups,
-                          elems_per_group,
-                          pipeline_size,
-                          nodes,
-                          devices_per_node,
-                          at::cuda::getCurrentCUDAStream());
-
-    return {output, scales};
-}
-
-std::vector<at::Tensor> quantized_reduction(at::Tensor& input_vals,
-                                            at::Tensor& input_scales,
-                                            int in_groups,
-                                            int out_groups,
-                                            int num_bits,
-                                            quantize::Type quant_type,
-                                            int devices_per_node)
-{
-    auto scales_options = at::TensorOptions()
-                              .dtype(at::kFloat)
-                              .layout(at::kStrided)
-                              .device(at::kCUDA)
-                              .requires_grad(false);
-    const int scales_elems = (quantize::requires_offset(quant_type)) ? 2 : 1;
-    auto scales = torch::empty({out_groups, scales_elems}, scales_options);
-
-    auto output_options = at::TensorOptions()
-                              .dtype(at::kChar)
-                              .layout(at::kStrided)
-                              .device(at::kCUDA)
-                              .requires_grad(false);
-
-     std::vector<int64_t> sz_vector(input_vals.sizes().begin(), input_vals.sizes().end());
-     sz_vector[sz_vector.size() - 1] = sz_vector.back() / devices_per_node;  // num of GPU per nodes
-     at::IntArrayRef sz(sz_vector);
-     auto output = torch::empty(sz, output_options);
-
-     const int elems_per_in_tensor = at::numel(input_vals) / devices_per_node;
-     const int elems_per_in_group = elems_per_in_tensor / (in_groups / devices_per_node);
-     const int elems_per_out_group = elems_per_in_tensor / out_groups;
-
-// old code:
-//    std::vector<long int> sz(input_vals.sizes().begin(), input_vals.sizes().end());
-//    sz[sz.size() - 1] = sz.back() / devices_per_node;  // num of GPU per nodes
-//    const int elems_per_in_tensor = at::numel(input_vals) / devices_per_node;
-//    auto output = torch::empty(sz, output_options);
-
-//    const int elems_per_in_group = elems_per_in_tensor / (in_groups / devices_per_node);
-//    const int elems_per_out_group = elems_per_in_tensor / out_groups;
-
-    launch_dequant_reduce((int8_t*)output.data_ptr(),
-                          (float*)scales.data_ptr(),
-                          (const int8_t*)input_vals.data_ptr(),
-                          (const float*)input_scales.data_ptr(),
-                          devices_per_node,
-                          num_bits,
-                          quant_type,
-                          out_groups,
-                          elems_per_out_group,
-                          elems_per_in_tensor,
-                          in_groups / devices_per_node,
-                          elems_per_in_group,
-                          at::cuda::getCurrentCUDAStream());
-    return {output, scales};
-}
-
-PYBIND11_MODULE(TORCH_EXTENSION_NAME, m)
-{
-    m.def("ds_quantize_fp32", &ds_quantize<float>, "DeepSpeed Quantize with fp32 (CUDA)");
-    m.def("ds_quantize_fp16", &ds_quantize<__half>, "DeepSpeed Quantize with fp16 (CUDA)");
-    m.def("ds_sr_quantize_fp32", &ds_sr_quantize<float>, "DeepSpeed Quantize with fp32 (CUDA)");
-    m.def("ds_sr_quantize_fp16", &ds_sr_quantize<__half>, "DeepSpeed Quantize with fp16 (CUDA)");
-    m.def("ds_quantize_asym_fp32", &ds_quantize_asym<float>, "DeepSpeed Quantize with fp32 (CUDA)");
-    m.def(
-        "ds_quantize_asym_fp16", &ds_quantize_asym<__half>, "DeepSpeed Quantize with fp16 (CUDA)");
-    m.def("ds_sr_quantize_asym_fp32",
-          &ds_sr_quantize_asym<float>,
-          "DeepSpeed Quantize with fp32 (CUDA)");
-    m.def("ds_sr_quantize_asym_fp16",
-          &ds_sr_quantize_asym<__half>,
-          "DeepSpeed Quantize with fp16 (CUDA)");
-    pybind11::enum_<quantize::Type>(m, "QuantizationType")
-        .value("Symmetric", quantize::Type::Symmetric)
-        .value("Asymmetric", quantize::Type::Asymmetric)
-        .export_values();
-    m.def("quantize", &quantize_kernel);
-    m.def("dequantize", &dequantize<__half>);
-    m.def("dequantize_fp32", &dequantize<float>);
-    m.def("dequantize_int4_to_half_experimental",
-          &dequantize_int4_to_half_experimental,
-          "Dequantize int4 to half (experimental)");
-    m.def("swizzle_quant", &ds_swizzle_quant);
-    m.def("quantized_reduction", &quantized_reduction);
-}

Deepspeed-Windows/11.1/deepspeed/env_report.py

@@ -1,160 +0,0 @@
-# Copyright (c) Microsoft Corporation.
-# SPDX-License-Identifier: Apache-2.0
-
-# DeepSpeed Team
-
-import os
-import torch
-import deepspeed
-import subprocess
-import argparse
-import psutil
-from .ops.op_builder.all_ops import ALL_OPS
-from .git_version_info import installed_ops, torch_info
-from deepspeed.accelerator import get_accelerator
-
-GREEN = '\033[92m'
-RED = '\033[91m'
-YELLOW = '\033[93m'
-END = '\033[0m'
-SUCCESS = f"{GREEN} [SUCCESS] {END}"
-OKAY = f"{GREEN}[OKAY]{END}"
-WARNING = f"{YELLOW}[WARNING]{END}"
-FAIL = f'{RED}[FAIL]{END}'
-INFO = '[INFO]'
-
-color_len = len(GREEN) + len(END)
-okay = f"{GREEN}[OKAY]{END}"
-warning = f"{YELLOW}[WARNING]{END}"
-
-
-def op_report(verbose=True):
-    max_dots = 23
-    max_dots2 = 11
-    h = ["op name", "installed", "compatible"]
-    print("-" * (max_dots + max_dots2 + len(h[0]) + len(h[1])))
-    print("DeepSpeed C++/CUDA extension op report")
-    print("-" * (max_dots + max_dots2 + len(h[0]) + len(h[1])))
-
-    print("NOTE: Ops not installed will be just-in-time (JIT) compiled at\n"
-          "      runtime if needed. Op compatibility means that your system\n"
-          "      meet the required dependencies to JIT install the op.")
-
-    print("-" * (max_dots + max_dots2 + len(h[0]) + len(h[1])))
-    print("JIT compiled ops requires ninja")
-    ninja_status = OKAY if ninja_installed() else FAIL
-    print('ninja', "." * (max_dots - 5), ninja_status)
-    print("-" * (max_dots + max_dots2 + len(h[0]) + len(h[1])))
-    print(h[0], "." * (max_dots - len(h[0])), h[1], "." * (max_dots2 - len(h[1])), h[2])
-    print("-" * (max_dots + max_dots2 + len(h[0]) + len(h[1])))
-    installed = f"{GREEN}[YES]{END}"
-    no = f"{YELLOW}[NO]{END}"
-    for op_name, builder in ALL_OPS.items():
-        dots = "." * (max_dots - len(op_name))
-        is_compatible = OKAY if builder.is_compatible(verbose) else no
-        is_installed = installed if installed_ops.get(op_name, False) else no
-        dots2 = '.' * ((len(h[1]) + (max_dots2 - len(h[1]))) - (len(is_installed) - color_len))
-        print(op_name, dots, is_installed, dots2, is_compatible)
-    print("-" * (max_dots + max_dots2 + len(h[0]) + len(h[1])))
-
-
-def ninja_installed():
-    try:
-        import ninja  # noqa: F401 # type: ignore
-    except ImportError:
-        return False
-    return True
-
-
-def nvcc_version():
-    import torch.utils.cpp_extension
-    cuda_home = torch.utils.cpp_extension.CUDA_HOME
-    if cuda_home is None:
-        return f"{RED} [FAIL] cannot find CUDA_HOME via torch.utils.cpp_extension.CUDA_HOME={torch.utils.cpp_extension.CUDA_HOME} {END}"
-    try:
-        output = subprocess.check_output([cuda_home + "/bin/nvcc", "-V"], universal_newlines=True)
-    except FileNotFoundError:
-        return f"{RED} [FAIL] nvcc missing {END}"
-    output_split = output.split()
-    release_idx = output_split.index("release")
-    release = output_split[release_idx + 1].replace(',', '').split(".")
-    return ".".join(release)
-
-
-def get_shm_size():
-    try:
-        temp_dir = os.getenv('TEMP') or os.getenv('TMP') or os.path.join(os.path.expanduser('~'), 'tmp')
-        shm_stats = psutil.disk_usage(temp_dir)
-        shm_size = shm_stats.total
-        shm_hbytes = human_readable_size(shm_size)
-        warn = []
-        if shm_size < 512 * 1024**2:
-            warn.append(
-                f" {YELLOW} [WARNING] Shared memory size might be too small, consider increasing it. {END}"
-            )
-            # Add additional warnings specific to your use case if needed.
-        return shm_hbytes, warn
-    except Exception as e:
-        return "UNKNOWN", [f"Error getting shared memory size: {e}"]
-
-def human_readable_size(size):
-    units = ['B', 'KB', 'MB', 'GB', 'TB']
-    i = 0
-    while size >= 1024 and i < len(units) - 1:
-        size /= 1024
-        i += 1
-    return f'{size:.2f} {units[i]}'
-
-
-def debug_report():
-    max_dots = 33
-
-    report = [("torch install path", torch.__path__), ("torch version", torch.__version__),
-              ("deepspeed install path", deepspeed.__path__),
-              ("deepspeed info", f"{deepspeed.__version__}, {deepspeed.__git_hash__}, {deepspeed.__git_branch__}")]
-    if get_accelerator().device_name() == 'cuda':
-        hip_version = getattr(torch.version, "hip", None)
-        report.extend([("torch cuda version", torch.version.cuda), ("torch hip version", hip_version),
-                       ("nvcc version", (None if hip_version else nvcc_version())),
-                       ("deepspeed wheel compiled w.", f"torch {torch_info['version']}, " +
-                        (f"hip {torch_info['hip_version']}" if hip_version else f"cuda {torch_info['cuda_version']}"))
-                       ])
-    else:
-        report.extend([("deepspeed wheel compiled w.", f"torch {torch_info['version']} ")])
-
-    report.append(("shared memory (/dev/shm) size", get_shm_size()))
-
-    print("DeepSpeed general environment info:")
-    for name, value in report:
-        warns = []
-        if isinstance(value, tuple):
-            value, warns = value
-        print(name, "." * (max_dots - len(name)), value)
-        if warns:
-            for warn in warns:
-                print(warn)
-
-
-def parse_arguments():
-    parser = argparse.ArgumentParser()
-    parser.add_argument('--hide_operator_status',
-                        action='store_true',
-                        help='Suppress display of installation and compatibility statuses of DeepSpeed operators. ')
-    parser.add_argument('--hide_errors_and_warnings', action='store_true', help='Suppress warning and error messages.')
-    args = parser.parse_args()
-    return args
-
-
-def main(hide_operator_status=False, hide_errors_and_warnings=False):
-    if not hide_operator_status:
-        op_report(verbose=not hide_errors_and_warnings)
-    debug_report()
-
-
-def cli_main():
-    args = parse_arguments()
-    main(hide_operator_status=args.hide_operator_status, hide_errors_and_warnings=args.hide_errors_and_warnings)
-
-
-if __name__ == "__main__":
-    main()

Deepspeed-Windows/11.2/csrc/quantization/pt_binding.cpp

@@ -1,299 +0,0 @@
-// Copyright (c) Microsoft Corporation.
-// SPDX-License-Identifier: Apache-2.0
-
-// DeepSpeed Team
-
-#include <ATen/cuda/CUDAContext.h>
-#include <torch/extension.h>
-#include <cassert>
-#include <vector>
-#include "quantization.h"
-
-template <typename T>
-at::Tensor ds_quantize(at::Tensor& vals, int groups, int bits)
-{
-    auto t_size = vals.sizes();
-    int size = 1;
-    for (auto dim : t_size) size *= dim;
-
-    if ((((size / groups) - 1) / 4096 + 1) <= 256) {
-        launch_fake_quantize_kernel(
-            (T*)vals.data_ptr(), size, groups, bits, at::cuda::getCurrentCUDAStream());
-    }
-    return vals;
-}
-
-template <typename T>
-at::Tensor ds_sr_quantize(at::Tensor& vals, int groups, int bits)
-{
-    auto t_size = vals.sizes();
-    int size = 1;
-    for (auto dim : t_size) size *= dim;
-
-    if (((size / groups) / 4 / 1024) <= 256) {
-        launch_sr_fake_quantize_kernel(
-            (T*)vals.data_ptr(), size, groups, bits, at::cuda::getCurrentCUDAStream());
-    }
-    return vals;
-}
-
-template <typename T>
-at::Tensor ds_quantize_asym(at::Tensor& vals, int groups, int bits)
-{
-    auto t_size = vals.sizes();
-    int size = 1;
-    for (auto dim : t_size) size *= dim;
-
-    if ((((size / groups) - 1) / 4096 + 1) <= 256) {
-        launch_fake_quantize_kernel_asym(
-            (T*)vals.data_ptr(), size, groups, bits, at::cuda::getCurrentCUDAStream());
-    }
-    return vals;
-}
-
-template <typename T>
-at::Tensor ds_sr_quantize_asym(at::Tensor& vals, int groups, int bits)
-{
-    auto t_size = vals.sizes();
-    int size = 1;
-    for (auto dim : t_size) size *= dim;
-
-    if (((size / groups) / 4 / 1024) <= 256) {
-        launch_sr_fake_quantize_kernel_asym(
-            (T*)vals.data_ptr(), size, groups, bits, at::cuda::getCurrentCUDAStream());
-    }
-    return vals;
-}
-
-std::vector<at::Tensor> quantize_kernel(at::Tensor& input_vals,
-                                        int groups,
-                                        int numBits,
-                                        quantize::Type quantType)
-{
-    auto dtype = at::kFloat;
-    auto params_options = at::TensorOptions()
-                              .dtype(dtype)
-                              .layout(at::kStrided)
-                              .device(at::kCUDA)
-                              .requires_grad(false);
-    const int param_elems = (quantize::requires_offset(quantType)) ? 2 : 1;
-    auto params = torch::empty({groups, param_elems}, params_options);
-
-    auto output_options = at::TensorOptions()
-                              .dtype(at::kChar)
-                              .layout(at::kStrided)
-                              .device(at::kCUDA)
-                              .requires_grad(false);
-
-    auto output_sizes = input_vals.sizes().vec();
-    output_sizes[output_sizes.size() - 1] /= numBits == 8 ? 1 : 2;
-    auto output = torch::empty(output_sizes, output_options);
-
-    const int elems_per_group = at::numel(input_vals) / groups;
-
-    launch_quant((int8_t*)output.data_ptr(),
-                 (float*)params.data_ptr(),
-                 (__half*)input_vals.data_ptr(),
-                 groups,
-                 elems_per_group,
-                 numBits,
-                 quantType,
-                 at::cuda::getCurrentCUDAStream());
-
-    return {output, params};
-}
-
-template <typename T>
-at::Tensor dequantize(at::Tensor& quantized_data,
-                      at::Tensor& params,
-                      int groups,
-                      int num_bits,
-                      quantize::Type quant_type)
-{
-    auto dtype = (std::is_same<T, float>::value) ? torch::kFloat32 : torch::kFloat16;
-    auto output_options = at::TensorOptions()
-                              .dtype(dtype)
-                              .layout(at::kStrided)
-                              .device(at::kCUDA)
-                              .requires_grad(false);
-
-    auto output_sizes = quantized_data.sizes().vec();
-    output_sizes[output_sizes.size() - 1] *= num_bits == 8 ? 1 : 2;
-    auto output = torch::empty(output_sizes, output_options);
-
-    const int total_elems = at::numel(output);
-    const int elems_per_group = total_elems / groups;
-
-    launch_dequantize_kernel((T*)output.data_ptr(),
-                             (const int8_t*)quantized_data.data_ptr(),
-                             (const float*)params.data_ptr(),
-                             quant_type,
-                             num_bits,
-                             elems_per_group,
-                             total_elems,
-                             at::cuda::getCurrentCUDAStream());
-
-    return output;
-}
-
-at::Tensor dequantize_int4_to_half_experimental(at::Tensor& data_in,
-                                                at::Tensor& scale_buffer,
-                                                at::Tensor& min_val_buffer,
-                                                int num_group,
-                                                int group_size)
-{
-    auto output_options = at::TensorOptions().dtype(at::kHalf).device(at::kCUDA);
-    auto output = torch::empty({num_group, group_size}, output_options);
-
-    launch_dequantize_int4_to_half_experimental((uint8_t*)data_in.data_ptr(),
-                                                (half*)output.data_ptr(),
-                                                (half*)scale_buffer.data_ptr(),
-                                                (half*)min_val_buffer.data_ptr(),
-                                                num_group,
-                                                group_size,
-                                                at::cuda::getCurrentCUDAStream());
-
-    return output;
-}
-
-at::Tensor dequantize_int8_to_half_experimental(at::Tensor& data_in,
-                                                at::Tensor& scale_buffer,
-                                                at::Tensor& min_val_buffer,
-                                                int num_group,
-                                                int group_size)
-{
-    auto output_options = at::TensorOptions().dtype(at::kHalf).device(at::kCUDA);
-    auto output = torch::empty({num_group, group_size}, output_options);
-
-    launch_dequantize_int8_to_half_experimental((uint8_t*)data_in.data_ptr(),
-                                                (half*)output.data_ptr(),
-                                                (half*)scale_buffer.data_ptr(),
-                                                (half*)min_val_buffer.data_ptr(),
-                                                num_group,
-                                                group_size,
-                                                at::cuda::getCurrentCUDAStream());
-
-    return output;
-}
-
-std::vector<at::Tensor> ds_swizzle_quant(at::Tensor& input_vals,
-                                         int groups,
-                                         int num_bits,
-                                         quantize::Type quant_type,
-                                         int pipeline_size,
-                                         int nodes,
-                                         int devices_per_node)
-{
-    auto scales_options = at::TensorOptions()
-                              .dtype(at::kFloat)
-                              .layout(at::kStrided)
-                              .device(at::kCUDA)
-                              .requires_grad(false);
-    const int scales_elems = (quantize::requires_offset(quant_type)) ? 2 : 1;
-    auto scales = torch::empty({groups, scales_elems}, scales_options);
-
-    auto output_options = at::TensorOptions()
-                              .dtype(at::kChar)
-                              .layout(at::kStrided)
-                              .device(at::kCUDA)
-                              .requires_grad(false);
-
-    const int quantization_scalar = 8 / num_bits;
-    const int compressed_vals = at::numel(input_vals) / quantization_scalar;
-
-    auto output = torch::empty({compressed_vals}, output_options);
-    const int elems_per_group = at::numel(input_vals) / groups;
-
-    launch_swizzled_quant((int8_t*)output.data_ptr(),
-                          (float*)scales.data_ptr(),
-                          (__half*)input_vals.data_ptr(),
-                          num_bits,
-                          quant_type,
-                          groups,
-                          elems_per_group,
-                          pipeline_size,
-                          nodes,
-                          devices_per_node,
-                          at::cuda::getCurrentCUDAStream());
-
-    return {output, scales};
-}
-
-std::vector<at::Tensor> quantized_reduction(at::Tensor& input_vals,
-                                            at::Tensor& input_scales,
-                                            int in_groups,
-                                            int out_groups,
-                                            int num_bits,
-                                            quantize::Type quant_type,
-                                            int devices_per_node)
-{
-    auto scales_options = at::TensorOptions()
-                              .dtype(at::kFloat)
-                              .layout(at::kStrided)
-                              .device(at::kCUDA)
-                              .requires_grad(false);
-    const int scales_elems = (quantize::requires_offset(quant_type)) ? 2 : 1;
-    auto scales = torch::empty({out_groups, scales_elems}, scales_options);
-
-    auto output_options = at::TensorOptions()
-                              .dtype(at::kChar)
-                              .layout(at::kStrided)
-                              .device(at::kCUDA)
-                              .requires_grad(false);
-
-    std::vector<int64_t> sz_vector(input_vals.sizes().begin(), input_vals.sizes().end());
-    sz_vector[sz_vector.size() - 1] = sz_vector.back() / devices_per_node;  // num of GPU per nodes
-    at::IntArrayRef sz(sz_vector);
-    auto output = torch::empty(sz, output_options);
-
-    const int elems_per_in_tensor = at::numel(input_vals) / devices_per_node;
-    const int elems_per_in_group = elems_per_in_tensor / (in_groups / devices_per_node);
-    const int elems_per_out_group = elems_per_in_tensor / out_groups;
-
-    launch_dequant_reduce((int8_t*)output.data_ptr(),
-                          (float*)scales.data_ptr(),
-                          (const int8_t*)input_vals.data_ptr(),
-                          (const float*)input_scales.data_ptr(),
-                          devices_per_node,
-                          num_bits,
-                          quant_type,
-                          out_groups,
-                          elems_per_out_group,
-                          elems_per_in_tensor,
-                          in_groups / devices_per_node,
-                          elems_per_in_group,
-                          at::cuda::getCurrentCUDAStream());
-    return {output, scales};
-}
-
-PYBIND11_MODULE(TORCH_EXTENSION_NAME, m)
-{
-    m.def("ds_quantize_fp32", &ds_quantize<float>, "DeepSpeed Quantize with fp32 (CUDA)");
-    m.def("ds_quantize_fp16", &ds_quantize<__half>, "DeepSpeed Quantize with fp16 (CUDA)");
-    m.def("ds_sr_quantize_fp32", &ds_sr_quantize<float>, "DeepSpeed Quantize with fp32 (CUDA)");
-    m.def("ds_sr_quantize_fp16", &ds_sr_quantize<__half>, "DeepSpeed Quantize with fp16 (CUDA)");
-    m.def("ds_quantize_asym_fp32", &ds_quantize_asym<float>, "DeepSpeed Quantize with fp32 (CUDA)");
-    m.def(
-        "ds_quantize_asym_fp16", &ds_quantize_asym<__half>, "DeepSpeed Quantize with fp16 (CUDA)");
-    m.def("ds_sr_quantize_asym_fp32",
-          &ds_sr_quantize_asym<float>,
-          "DeepSpeed Quantize with fp32 (CUDA)");
-    m.def("ds_sr_quantize_asym_fp16",
-          &ds_sr_quantize_asym<__half>,
-          "DeepSpeed Quantize with fp16 (CUDA)");
-    pybind11::enum_<quantize::Type>(m, "QuantizationType")
-        .value("Symmetric", quantize::Type::Symmetric)
-        .value("Asymmetric", quantize::Type::Asymmetric)
-        .export_values();
-    m.def("quantize", &quantize_kernel);
-    m.def("dequantize", &dequantize<__half>);
-    m.def("dequantize_fp32", &dequantize<float>);
-    m.def("dequantize_int4_to_half_experimental",
-          &dequantize_int4_to_half_experimental,
-          "Dequantize int4 to half (experimental)");
-    m.def("dequantize_int8_to_half_experimental",
-          &dequantize_int8_to_half_experimental,
-          "Dequantize int8 to half (experimental)");
-    m.def("swizzle_quant", &ds_swizzle_quant);
-    m.def("quantized_reduction", &quantized_reduction);
-}

Deepspeed-Windows/11.2/deepspeed/env_report.py

@@ -1,161 +0,0 @@
-# Copyright (c) Microsoft Corporation.
-# SPDX-License-Identifier: Apache-2.0
-
-# DeepSpeed Team
-
-import os
-import torch
-import deepspeed
-import subprocess
-import argparse
-import psutil
-from .ops.op_builder.all_ops import ALL_OPS
-from .git_version_info import installed_ops, torch_info
-from deepspeed.accelerator import get_accelerator
-
-GREEN = '\033[92m'
-RED = '\033[91m'
-YELLOW = '\033[93m'
-END = '\033[0m'
-SUCCESS = f"{GREEN} [SUCCESS] {END}"
-OKAY = f"{GREEN}[OKAY]{END}"
-WARNING = f"{YELLOW}[WARNING]{END}"
-FAIL = f'{RED}[FAIL]{END}'
-INFO = '[INFO]'
-
-color_len = len(GREEN) + len(END)
-okay = f"{GREEN}[OKAY]{END}"
-warning = f"{YELLOW}[WARNING]{END}"
-
-
-def op_report(verbose=True):
-    max_dots = 23
-    max_dots2 = 11
-    h = ["op name", "installed", "compatible"]
-    print("-" * (max_dots + max_dots2 + len(h[0]) + len(h[1])))
-    print("DeepSpeed C++/CUDA extension op report")
-    print("-" * (max_dots + max_dots2 + len(h[0]) + len(h[1])))
-
-    print("NOTE: Ops not installed will be just-in-time (JIT) compiled at\n"
-          "      runtime if needed. Op compatibility means that your system\n"
-          "      meet the required dependencies to JIT install the op.")
-
-    print("-" * (max_dots + max_dots2 + len(h[0]) + len(h[1])))
-    print("JIT compiled ops requires ninja")
-    ninja_status = OKAY if ninja_installed() else FAIL
-    print('ninja', "." * (max_dots - 5), ninja_status)
-    print("-" * (max_dots + max_dots2 + len(h[0]) + len(h[1])))
-    print(h[0], "." * (max_dots - len(h[0])), h[1], "." * (max_dots2 - len(h[1])), h[2])
-    print("-" * (max_dots + max_dots2 + len(h[0]) + len(h[1])))
-    installed = f"{GREEN}[YES]{END}"
-    no = f"{YELLOW}[NO]{END}"
-    for op_name, builder in ALL_OPS.items():
-        dots = "." * (max_dots - len(op_name))
-        is_compatible = OKAY if builder.is_compatible(verbose) else no
-        is_installed = installed if installed_ops.get(op_name, False) else no
-        dots2 = '.' * ((len(h[1]) + (max_dots2 - len(h[1]))) - (len(is_installed) - color_len))
-        print(op_name, dots, is_installed, dots2, is_compatible)
-    print("-" * (max_dots + max_dots2 + len(h[0]) + len(h[1])))
-
-
-def ninja_installed():
-    try:
-        import ninja  # noqa: F401 # type: ignore
-    except ImportError:
-        return False
-    return True
-
-
-def nvcc_version():
-    import torch.utils.cpp_extension
-    cuda_home = torch.utils.cpp_extension.CUDA_HOME
-    if cuda_home is None:
-        return f"{RED} [FAIL] cannot find CUDA_HOME via torch.utils.cpp_extension.CUDA_HOME={torch.utils.cpp_extension.CUDA_HOME} {END}"
-    try:
-        output = subprocess.check_output([cuda_home + "/bin/nvcc", "-V"], universal_newlines=True)
-    except FileNotFoundError:
-        return f"{RED} [FAIL] nvcc missing {END}"
-    output_split = output.split()
-    release_idx = output_split.index("release")
-    release = output_split[release_idx + 1].replace(',', '').split(".")
-    return ".".join(release)
-
-
-def get_shm_size():
-    try:
-        temp_dir = os.getenv('TEMP') or os.getenv('TMP') or os.path.join(os.path.expanduser('~'), 'tmp')
-        shm_stats = psutil.disk_usage(temp_dir)
-        shm_size = shm_stats.total
-        shm_hbytes = human_readable_size(shm_size)
-        warn = []
-        if shm_size < 512 * 1024**2:
-            warn.append(
-                f" {YELLOW} [WARNING] Shared memory size might be too small, consider increasing it. {END}"
-            )
-            # Add additional warnings specific to your use case if needed.
-        return shm_hbytes, warn
-    except Exception as e:
-        return "UNKNOWN", [f"Error getting shared memory size: {e}"]
-
-
-def human_readable_size(size):
-    units = ['B', 'KB', 'MB', 'GB', 'TB']
-    i = 0
-    while size >= 1024 and i < len(units) - 1:
-        size /= 1024
-        i += 1
-    return f'{size:.2f} {units[i]}'
-
-
-def debug_report():
-    max_dots = 33
-
-    report = [("torch install path", torch.__path__), ("torch version", torch.__version__),
-              ("deepspeed install path", deepspeed.__path__),
-              ("deepspeed info", f"{deepspeed.__version__}, {deepspeed.__git_hash__}, {deepspeed.__git_branch__}")]
-    if get_accelerator().device_name() == 'cuda':
-        hip_version = getattr(torch.version, "hip", None)
-        report.extend([("torch cuda version", torch.version.cuda), ("torch hip version", hip_version),
-                       ("nvcc version", (None if hip_version else nvcc_version())),
-                       ("deepspeed wheel compiled w.", f"torch {torch_info['version']}, " +
-                        (f"hip {torch_info['hip_version']}" if hip_version else f"cuda {torch_info['cuda_version']}"))
-                       ])
-    else:
-        report.extend([("deepspeed wheel compiled w.", f"torch {torch_info['version']} ")])
-
-    report.append(("shared memory (/dev/shm) size", get_shm_size()))
-
-    print("DeepSpeed general environment info:")
-    for name, value in report:
-        warns = []
-        if isinstance(value, tuple):
-            value, warns = value
-        print(name, "." * (max_dots - len(name)), value)
-        if warns:
-            for warn in warns:
-                print(warn)
-
-
-def parse_arguments():
-    parser = argparse.ArgumentParser()
-    parser.add_argument('--hide_operator_status',
-                        action='store_true',
-                        help='Suppress display of installation and compatibility statuses of DeepSpeed operators. ')
-    parser.add_argument('--hide_errors_and_warnings', action='store_true', help='Suppress warning and error messages.')
-    args = parser.parse_args()
-    return args
-
-
-def main(hide_operator_status=False, hide_errors_and_warnings=False):
-    if not hide_operator_status:
-        op_report(verbose=not hide_errors_and_warnings)
-    debug_report()
-
-
-def cli_main():
-    args = parse_arguments()
-    main(hide_operator_status=args.hide_operator_status, hide_errors_and_warnings=args.hide_errors_and_warnings)
-
-
-if __name__ == "__main__":
-    main()

Deepspeed-Windows/DeepSpeed readme.txt

@@ -1,18 +0,0 @@
-These are the modified files you would need for a MANUAL build of DeepSpeed 11.1 or 11.2.
-
-They were created by a mix of instructions from erew123 and S95Sedan.
-
-
-- You still have to download the DeepSpeed v11.1 or v11.2 installation files from Microsoft to use these files.
-
-https://github.com/microsoft/DeepSpeed/releases/tag/v0.11.2
-
-
-- These files were provided by S95Sedan here: 
-
-https://github.com/S95Sedan/Deepspeed-Windows
-
-
-- They are related to the manual build of DeepSpeed for AllTalk, which is linked here: 
-
-https://github.com/erew123/alltalk_tts/tree/main?tab=readme-ov-file#-option-2---a-bit-more-complicated

Dockerfile

@@ -0,0 +1,12 @@
+FROM ubuntu:22.04
+ENV HOST 0.0.0.0
+RUN apt-get update && apt-get upgrade -y \
+    && apt-get install -y git build-essential portaudio19-dev \
+    python3 python3-pip gcc wget \
+    && ln -s /usr/bin/python3 /usr/bin/python
+WORKDIR /app
+COPY . .
+RUN pip install --no-cache-dir -r requirements_other.txt
+EXPOSE 7851
+RUN chmod +x launch.sh
+ENTRYPOINT ["sh", "-c", "./launch.sh"]

atsetup.bat

@@ -0,0 +1,638 @@
+@echo off
+cd /D "%~dp0"
+
+set PATH=%PATH%;%SystemRoot%\system32
+
+:: Generate the ESC character
+for /F %%a in ('echo prompt $E ^| cmd') do set "ESC=%%a"
+
+:: Standard Colors
+set "BLACK=%ESC%[30m"
+set "RED=%ESC%[31m"
+set "GREEN=%ESC%[32m"
+set "YELLOW=%ESC%[33m"
+set "BLUE=%ESC%[34m"
+set "MAGENTA=%ESC%[35m"
+set "CYAN=%ESC%[36m"
+set "WHITE=%ESC%[37m"
+set "L_BLACK=%ESC%[90m"
+set "L_RED=%ESC%[91m"
+set "L_GREEN=%ESC%[92m"
+set "L_YELLOW=%ESC%[93m"
+set "L_BLUE=%ESC%[94m"
+set "L_MAGENTA=%ESC%[95m"
+set "L_CYAN=%ESC%[96m"
+set "L_WHITE=%ESC%[97m"
+set "RESET=%ESC%[0m"
+
+@rem Check if curl is available
+curl --version >nul 2>&1
+if "%ERRORLEVEL%" NEQ "0" (
+    echo curl is not available on this system. Please install curl then re-run the script https://curl.se/ 
+	echo or perform a manual installation of a Conda Python environment.
+    goto end
+)
+
+:MainMenu
+cls
+echo.
+echo    %L_BLUE%ALLTALK WINDOWS SETUP UTILITY%RESET%
+echo.
+echo    INSTALLATION TYPE
+echo    1) I am using AllTalk as part of %L_GREEN%Text-generation-webui%RESET%
+echo    2) I am using AllTalk as a %L_GREEN%Standalone Application%RESET%
+echo.
+echo    9) %L_RED%Exit/Quit%RESET%
+echo.
+set /p UserOption="    Enter your choice: "
+
+if "%UserOption%"=="1" goto WebUIMenu
+if "%UserOption%"=="2" goto StandaloneMenu
+if "%UserOption%"=="9" goto End
+goto MainMenu
+
+:WebUIMenu
+cls
+echo.
+echo    %L_BLUE%TEXT-GENERATION-WEBUI SETUP%RESET%
+echo.
+echo    Please ensure you have started your Text-generation-webui Python 
+echo    environment. If you have NOT done this, please run %L_GREEN%cmd_windows.bat%RESET% 
+echo    in the %L_GREEN%text-generation-webui%RESET% folder and then re-run this script.
+echo.
+echo    BASE REQUIREMENTS
+echo    1) Apply/Re-Apply the requirements for %L_GREEN%Text-generation-webui%RESET%.
+echo.
+echo    OPTIONAL
+echo    2) Git Pull the latest AllTalk updates from Github
+echo.
+echo    DEEPSPEED FOR %L_YELLOW=%PyTorch 2.1.x%RESET%
+echo    4) Install DeepSpeed v11.2 for CUDA %L_GREEN%11.8%RESET% and Python-3.11.x and %L_YELLOW%PyTorch 2.1.x%RESET%.
+echo    5) Install DeepSpeed v11.2 for CUDA %L_GREEN%12.1%RESET% and Python-3.11.x and %L_YELLOW%PyTorch 2.1.x%RESET%.
+echo.
+echo    DEEPSPEED FOR %L_YELLOW=%PyTorch 2.2.x%RESET% (March 2024 builds of Text-gen-webui and later)
+echo    6) Install DeepSpeed v14.0 for CUDA %L_GREEN%12.1%RESET% and Python-3.11.x and %L_YELLOW%PyTorch 2.2.x%RESET%.
+echo    7) Install DeepSpeed v14.0 for CUDA %L_GREEN%11.8%RESET% and Python-3.11.x and %L_YELLOW%PyTorch 2.2.x%RESET%.
+echo.
+echo    U) Uninstall DeepSpeed.
+echo.
+echo.   OTHER
+echo    8) Generate a diagnostics file.
+echo.
+echo    9) %L_RED%Exit/Quit%RESET%
+echo.
+set /p WebUIOption="Enter your choice: "
+if "%WebUIOption%"=="1" goto InstallNvidiaTextGen
+if "%WebUIOption%"=="2" goto TGGitpull
+if "%WebUIOption%"=="4" goto InstallDeepSpeed118TextGen
+if "%WebUIOption%"=="5" goto InstallDeepSpeed121TextGen
+if "%WebUIOption%"=="6" goto InstallDeepSpeed121TextGenPytorch221
+if "%WebUIOption%"=="7" goto InstallDeepSpeed118TextGenPytorch221
+if "%WebUIOption%"=="U" goto UnInstallDeepSpeed
+if "%WebUIOption%"=="u" goto UnInstallDeepSpeed
+if "%WebUIOption%"=="8" goto GenerateDiagsTextGen
+if "%WebUIOption%"=="9" goto End
+goto WebUIMenu
+
+:StandaloneMenu
+cls
+echo.
+echo    %L_BLUE%ALLTALK STANDALONE APPLICATION SETUP%RESET%
+echo.
+echo    BASE REQUIREMENTS
+echo    1) Install AllTalk as a Standalone Application
+echo.
+echo    OPTIONAL
+echo    2) Git Pull the latest AllTalk updates from Github
+echo    3) Re-Apply/Update the requirements file
+echo    4) Delete AllTalk's custom Python environment
+echo    5) Purge the PIP cache
+echo.
+echo.   OTHER
+echo    8) Generate a diagnostics file
+echo.
+echo    9) %L_RED%Exit/Quit%RESET%
+echo.
+set /p StandaloneOption="Enter your choice: "
+if "%StandaloneOption%"=="1" goto InstallCustomStandalone
+if "%StandaloneOption%"=="2" goto STGitpull
+if "%StandaloneOption%"=="3" goto STReapplyrequirements
+if "%StandaloneOption%"=="4" goto STDeleteCustomStandalone
+if "%StandaloneOption%"=="5" goto STPurgepipcache
+if "%StandaloneOption%"=="8" goto GenerateDiagsStandalone
+if "%StandaloneOption%"=="9" goto End
+goto StandaloneMenu
+
+:InstallNvidiaTextGen
+pip install -r system\requirements\requirements_textgen.txt
+if %ERRORLEVEL% neq 0 (
+    echo.
+    echo    There was an error installing the requirements.
+    echo    Press any key to return to the menu.
+    echo.
+    pause
+    goto WebUIMenu
+)
+Echo.
+echo.
+Echo    Requirements installed successfully.
+Echo. 
+pause
+goto WebUIMenu
+
+:TGGitpull
+git pull
+if %ERRORLEVEL% neq 0 (
+    echo.
+    echo    There was an error pulling from Github.
+    echo    Press any key to return to the menu.
+    echo.
+    pause
+    goto WebUIMenu
+)
+Echo.
+echo     AllTalk Updated from Github. Please re-apply
+echo     the latest requirements file. Option 1
+Echo. 
+pause
+goto WebUIMenu
+
+:InstallDeepSpeed118TextGen
+echo Downloading DeepSpeed...
+curl -LO https://github.com/erew123/alltalk_tts/releases/download/deepspeed/deepspeed-0.11.2+cuda118-cp311-cp311-win_amd64.whl
+if %ERRORLEVEL% neq 0 (
+    echo.
+    echo    Failed to download DeepSpeed wheel file.
+    echo    Please check your internet connection or try again later.
+    echo    Press any key to return to the menu.
+    echo.
+    pause
+    goto WebUIMenu
+)
+echo DeepSpeed wheel file downloaded successfully.
+echo Installing DeepSpeed...
+pip install deepspeed-0.11.2+cuda118-cp311-cp311-win_amd64.whl
+if %ERRORLEVEL% neq 0 (
+    echo. 
+    echo    Failed to install DeepSpeed.
+    echo    Please check if the wheel file is compatible with your system.
+    echo    Press any key to return to the menu.
+    echo.
+    pause
+    goto WebUIMenu
+)
+Echo.
+echo.
+Echo    DeepSpeed installed successfully.
+Echo. 
+del deepspeed-0.11.2+cuda118-cp311-cp311-win_amd64.whl
+pause
+goto WebUIMenu
+
+:InstallDeepSpeed121TextGen
+echo Downloading DeepSpeed...
+curl -LO https://github.com/erew123/alltalk_tts/releases/download/deepspeed/deepspeed-0.11.2+cuda121-cp311-cp311-win_amd64.whl
+if %ERRORLEVEL% neq 0 (
+    echo.
+    echo    Failed to download DeepSpeed wheel file.
+    echo    Please check your internet connection or try again later.
+    echo    Press any key to return to the menu.
+    echo.
+    pause
+    goto WebUIMenu
+)
+echo    DeepSpeed wheel file downloaded successfully.
+echo    Installing DeepSpeed...
+pip install deepspeed-0.11.2+cuda121-cp311-cp311-win_amd64.whl
+if %ERRORLEVEL% neq 0 (
+    echo. 
+    echo    Failed to install DeepSpeed.
+    echo    Please check if the wheel file is compatible with your system.
+    echo    Press any key to return to the menu.
+    echo.
+    pause
+    goto WebUIMenu
+)
+Echo.
+echo.
+Echo    DeepSpeed installed successfully.
+Echo. 
+del deepspeed-0.11.2+cuda121-cp311-cp311-win_amd64.whl
+pause
+goto WebUIMenu
+
+:InstallDeepSpeed121TextGenPytorch221
+echo Downloading DeepSpeed...
+curl -LO https://github.com/erew123/alltalk_tts/releases/download/DeepSpeed-14.0/deepspeed-0.14.0+ce78a63-cp311-cp311-win_amd64.whl
+if %ERRORLEVEL% neq 0 (
+    echo.
+    echo    Failed to download DeepSpeed wheel file.
+    echo    Please check your internet connection or try again later.
+    echo    Press any key to return to the menu.
+    echo.
+    pause
+    goto WebUIMenu
+)
+echo    DeepSpeed wheel file downloaded successfully.
+echo    Installing DeepSpeed...
+pip install deepspeed-0.14.0+ce78a63-cp311-cp311-win_amd64.whl
+if %ERRORLEVEL% neq 0 (
+    echo. 
+    echo    Failed to install DeepSpeed.
+    echo    Please check if the wheel file is compatible with your system.
+    echo    Press any key to return to the menu.
+    echo.
+    pause
+    goto WebUIMenu
+)
+Echo.
+echo.
+Echo    DeepSpeed installed successfully.
+Echo. 
+del deepspeed-0.14.0+ce78a63-cp311-cp311-win_amd64.whl
+pause
+goto WebUIMenu
+
+:InstallDeepSpeed118TextGenPytorch221
+echo Downloading DeepSpeed...
+curl -LO https://github.com/erew123/alltalk_tts/releases/download/DeepSpeed-14.0/deepspeed-0.14.0+cu118-cp311-cp311-win_amd64.whl
+if %ERRORLEVEL% neq 0 (
+    echo.
+    echo    Failed to download DeepSpeed wheel file.
+    echo    Please check your internet connection or try again later.
+    echo    Press any key to return to the menu.
+    echo.
+    pause
+    goto WebUIMenu
+)
+echo    DeepSpeed wheel file downloaded successfully.
+echo    Installing DeepSpeed...
+pip install deepspeed-0.14.0+cu118-cp311-cp311-win_amd64.whl
+if %ERRORLEVEL% neq 0 (
+    echo. 
+    echo    Failed to install DeepSpeed.
+    echo    Please check if the wheel file is compatible with your system.
+    echo    Press any key to return to the menu.
+    echo.
+    pause
+    goto WebUIMenu
+)
+Echo.
+echo.
+Echo    DeepSpeed installed successfully.
+Echo. 
+del deepspeed-0.14.0+cu118-cp311-cp311-win_amd64.whl
+pause
+goto WebUIMenu
+
+:UnInstallDeepSpeed
+pip uninstall deepspeed
+if %ERRORLEVEL% neq 0 (
+    echo. 
+    echo    There was an error uninstalling DeepSpeed.
+    echo    Press any key to return to the menu.
+    echo.
+    pause
+    goto WebUIMenu
+)
+echo.
+Echo    DeepSpeed uninstalled successfully.
+Echo. 
+pause
+goto WebUIMenu
+
+:GenerateDiagsTextGen
+Python diagnostics.py
+if %ERRORLEVEL% neq 0 (
+    echo.
+    echo    There was an error running diagnostics. Have you correctly started your 
+    echo    Text-generation-webui Python environment with %L_GREEN%cmd_windows.bat%RESET%?
+    echo.
+    pause
+    goto WebUIMenu
+)
+Echo.
+echo.
+Echo    Diagnostics.log generated. Please scroll up to look over the log.
+Echo. 
+pause
+goto WebUIMenu
+
+:InstallCustomStandalone
+set PATH=%PATH%;%SystemRoot%\system32
+
+@rem Check if curl is available
+curl --version >nul 2>&1
+if "%ERRORLEVEL%" NEQ "0" (
+    echo curl is not available on this system. Please install curl then re-run the script https://curl.se/ 
+	echo or perform a manual installation of a Conda Python environment.
+    goto end
+)
+echo "%CD%"| findstr /C:" " >nul && echo This script relies on Miniconda which can not be silently installed under a path with spaces. Please correct your folder names and re-try installation. && goto exit
+
+@rem Check for special characters in installation path
+set "SPCHARMESSAGE=WARNING: Special characters were detected in the installation path! This can cause the installation to fail!"
+echo "%CD%"| findstr /R /C:"[!#\$%&()\*+,;<=>?@\[\]\^`{|}~]" >nul && (
+    call :PrintBigMessage %SPCHARMESSAGE%
+)
+set SPCHARMESSAGE=
+
+@rem fix failed install when installing to a separate drive
+set TMP=%cd%\alltalk_environment
+set TEMP=%cd%\alltalk_environment
+
+@rem deactivate existing conda envs as needed to avoid conflicts
+(call conda deactivate && call conda deactivate && call conda deactivate) 2>nul
+
+@rem config
+set INSTALL_DIR=%cd%\alltalk_environment
+set CONDA_ROOT_PREFIX=%cd%\alltalk_environment\conda
+set INSTALL_ENV_DIR=%cd%\alltalk_environment\env
+set MINICONDA_DOWNLOAD_URL=https://repo.anaconda.com/miniconda/Miniconda3-py310_23.3.1-0-Windows-x86_64.exe
+set conda_exists=F
+
+@rem figure out whether git and conda need to be installed
+call "%CONDA_ROOT_PREFIX%\_conda.exe" --version >nul 2>&1
+if "%ERRORLEVEL%" EQU "0" (
+    set conda_exists=T
+    call "%CONDA_ROOT_PREFIX%\condabin\conda.bat" activate "%INSTALL_ENV_DIR%"
+    goto RunScript
+)
+
+@rem download and install conda if not installed
+echo Downloading Miniconda from %MINICONDA_DOWNLOAD_URL% to %INSTALL_DIR%\miniconda_installer.exe
+mkdir "%INSTALL_DIR%"
+call curl -Lk "%MINICONDA_DOWNLOAD_URL%" > "%INSTALL_DIR%\miniconda_installer.exe" || ( echo. && echo Miniconda failed to download. && goto end )
+echo Installing Miniconda to %CONDA_ROOT_PREFIX%
+start /wait "" "%INSTALL_DIR%\miniconda_installer.exe" /InstallationType=JustMe /NoShortcuts=1 /AddToPath=0 /RegisterPython=0 /NoRegistry=1 /S /D=%CONDA_ROOT_PREFIX%
+echo Miniconda version:
+call "%CONDA_ROOT_PREFIX%\_conda.exe" --version || ( echo. && echo Miniconda not found. && goto end )
+
+@rem create the installer env
+echo Packages to install: %PACKAGES_TO_INSTALL%
+call "%CONDA_ROOT_PREFIX%\_conda.exe" create --no-shortcuts -y -k --prefix "%INSTALL_ENV_DIR%" python=3.11 || ( echo. && echo Conda environment creation failed. && goto end )
+
+@rem check if conda environment was actually created
+if not exist "%INSTALL_ENV_DIR%\python.exe" ( echo. && echo Conda environment is empty. && goto end )
+
+@rem activate installer env
+call "%CONDA_ROOT_PREFIX%\condabin\conda.bat" activate "%INSTALL_ENV_DIR%" || ( echo. && echo Miniconda hook not found. && goto end )
+
+echo.
+echo     Downloading and installing PyTorch. This step can take a long time
+echo     depending on your internet connection and hard drive speed. Please
+echo     be patient.
+echo.
+pip install torch>=2.2.1+cu121 torchaudio>=2.2.1+cu121 --extra-index-url https://download.pytorch.org/whl/cu121
+echo Installing other requirements.
+echo.
+pip install -r system\requirements\requirements_standalone.txt
+curl -LO https://github.com/erew123/alltalk_tts/releases/download/DeepSpeed-12.7/deepspeed-0.12.7+d058d4b-cp311-cp311-win_amd64.whl
+echo Installing DeepSpeed...
+pip install deepspeed-0.12.7+d058d4b-cp311-cp311-win_amd64.whl
+del deepspeed-0.12.7+d058d4b-cp311-cp311-win_amd64.whl
+
+
+@rem Create start_environment.bat to run AllTalk environment
+echo @echo off > start_environment.bat
+echo cd /D "%~dp0" >> start_environment.bat
+echo set CONDA_ROOT_PREFIX=%cd%\alltalk_environment\conda >> start_environment.bat
+echo set INSTALL_ENV_DIR=%cd%\alltalk_environment\env >> start_environment.bat
+echo call "%CONDA_ROOT_PREFIX%\condabin\conda.bat" activate "%INSTALL_ENV_DIR%" >> start_environment.bat
+@rem Create start_alltalk.bat to run AllTalk
+echo @echo off > start_alltalk.bat
+echo cd /D "%~dp0" >> start_alltalk.bat
+echo set CONDA_ROOT_PREFIX=%cd%\alltalk_environment\conda >> start_alltalk.bat
+echo set INSTALL_ENV_DIR=%cd%\alltalk_environment\env >> start_alltalk.bat
+echo call "%CONDA_ROOT_PREFIX%\condabin\conda.bat" activate "%INSTALL_ENV_DIR%" >> start_alltalk.bat
+echo call python script.py >> start_alltalk.bat
+@rem Create start_finetune.bat to run AllTalk
+echo @echo off > start_finetune.bat
+echo cd /D "%~dp0" >> start_finetune.bat
+echo set CONDA_ROOT_PREFIX=%cd%\alltalk_environment\conda >> start_finetune.bat
+echo set INSTALL_ENV_DIR=%cd%\alltalk_environment\env >> start_finetune.bat
+echo call "%CONDA_ROOT_PREFIX%\condabin\conda.bat" activate "%INSTALL_ENV_DIR%" >> start_finetune.bat
+echo call python finetune.py >> start_finetune.bat
+Echo.
+Echo    Run %L_YELLOW%start_alltalk.bat%RESET% to start AllTalk.
+Echo    Run %L_YELLOW%start_finetune.bat%RESET% to start Finetuning.
+Echo    Run %L_YELLOW%start_environment.bat%RESET% to start the AllTalk Python environment.
+Echo.
+pause
+goto StandaloneMenu
+
+:STDeleteCustomStandalone
+@rem Check if the alltalk_environment directory exists
+if not exist "%cd%\alltalk_environment\" (
+    echo.
+    echo    %L_GREEN%alltalk_environment%RESET% directory does not exist. No need to delete.
+    echo.
+    pause
+    goto StandaloneMenu
+)
+@rem Check if a Conda environment is active
+if not defined CONDA_PREFIX goto NoCondaEnvDeleteCustomStandalone
+@rem Deactivate Conda environment if it's active
+Echo    Exiting the Conda Environment. Please run %L_GREEN%atsetup.bat%RESET% again and delete the environment.
+conda deactivate
+:NoCondaEnvDeleteCustomStandalone
+echo Deleting "alltalk_environment". Please wait.
+rd /s /q "alltalk_environment"
+del start_alltalk.bat
+del start_environment.bat
+if %ERRORLEVEL% neq 0 (
+    echo.
+    echo    Failed to delete alltalk_environment folder.
+    echo    Please make sure it is not in use and try again.
+    echo.
+    pause
+    goto StandaloneMenu
+)
+echo.
+Echo.
+echo    Environment %L_GREEN%alltalk_environment%RESET% deleted. Please set up the environment again.
+Echo.
+pause
+goto StandaloneMenu
+
+:GenerateDiagsStandalone
+cd /D "%~dp0"
+set CONDA_ROOT_PREFIX=%cd%\alltalk_environment\conda
+set INSTALL_ENV_DIR=%cd%\alltalk_environment\env
+@rem Check if the Conda environment exists
+if not exist "%INSTALL_ENV_DIR%\python.exe" (
+    echo.
+    echo    The Conda environment at "%INSTALL_ENV_DIR%" does not exist.
+    echo    Please install the environment before proceeding.
+    echo. 
+    pause
+    goto StandaloneMenu
+)
+@rem Attempt to activate the Conda environment
+call "%CONDA_ROOT_PREFIX%\condabin\conda.bat" activate "%INSTALL_ENV_DIR%"
+if errorlevel 1 (
+    echo. 
+    echo    Failed to activate the Conda environment.
+    echo    Please check your installation and try again.
+    echo.
+    pause
+    goto StandaloneMenu
+)
+@rem Run diagnostics
+Python diagnostics.py
+if %ERRORLEVEL% neq 0 (
+    echo.
+    echo    There was an error running diagnostics.
+    echo    Press any key to return to the menu.
+    echo.
+    pause
+    goto StandaloneMenu
+)
+Echo.
+Echo.
+Echo    Diagnostics.log generated. Please scroll up to look over the log.
+Echo.
+pause
+goto StandaloneMenu
+
+:STReapplyrequirements
+cd /D "%~dp0"
+set CONDA_ROOT_PREFIX=%cd%\alltalk_environment\conda
+set INSTALL_ENV_DIR=%cd%\alltalk_environment\env
+@rem Check if the Conda environment exists
+if not exist "%INSTALL_ENV_DIR%\python.exe" (
+    echo.
+    echo    The Conda environment at "%INSTALL_ENV_DIR%" does not exist.
+    echo    Please install the environment before proceeding.
+    echo. 
+    pause
+    goto StandaloneMenu
+)
+@rem Attempt to activate the Conda environment
+call "%CONDA_ROOT_PREFIX%\condabin\conda.bat" activate "%INSTALL_ENV_DIR%"
+if errorlevel 1 (
+    echo. 
+    echo    Failed to activate the Conda environment.
+    echo    Please check your installation and try again.
+    echo.
+    pause
+    goto StandaloneMenu
+)
+@rem Run Reapply requirements
+echo.
+echo     Downloading and installing PyTorch. This step can take a long time
+echo     depending on your internet connection and hard drive speed. Please
+echo     be patient.
+echo.
+pip install torch>=2.2.1+cu121 torchaudio>=2.2.1+cu121 --extra-index-url https://download.pytorch.org/whl/cu121
+echo Installing other requirements.
+echo.
+pip install -r system\requirements\requirements_standalone.txt
+curl -LO https://github.com/erew123/alltalk_tts/releases/download/DeepSpeed-12.7/deepspeed-0.12.7+d058d4b-cp311-cp311-win_amd64.whl
+echo Installing DeepSpeed...
+pip install deepspeed-0.12.7+d058d4b-cp311-cp311-win_amd64.whl
+del deepspeed-0.12.7+d058d4b-cp311-cp311-win_amd64.whl
+if %ERRORLEVEL% neq 0 (
+    echo.
+    echo    There was an error.
+    echo    Press any key to return to the menu.
+    echo.
+    pause
+    goto StandaloneMenu
+)
+Echo.
+Echo.
+Echo    Requirements have been re-applied/updated.
+Echo.
+pause
+goto StandaloneMenu
+
+:STPurgepipcache
+cd /D "%~dp0"
+set CONDA_ROOT_PREFIX=%cd%\alltalk_environment\conda
+set INSTALL_ENV_DIR=%cd%\alltalk_environment\env
+@rem Check if the Conda environment exists
+if not exist "%INSTALL_ENV_DIR%\python.exe" (
+    echo.
+    echo    The Conda environment at "%INSTALL_ENV_DIR%" does not exist.
+    echo    Please install the environment before proceeding.
+    echo. 
+    pause
+    goto StandaloneMenu
+)
+@rem Attempt to activate the Conda environment
+call "%CONDA_ROOT_PREFIX%\condabin\conda.bat" activate "%INSTALL_ENV_DIR%"
+if errorlevel 1 (
+    echo. 
+    echo    Failed to activate the Conda environment.
+    echo    Please check your installation and try again.
+    echo.
+    pause
+    goto StandaloneMenu
+)
+@rem Clear the PIP cache
+echo.
+echo     Purging the PIP cache of downloaded files.
+echo.
+pip cache purge
+if %ERRORLEVEL% neq 0 (
+    echo.
+    echo    There was an error.
+    echo    Press any key to return to the menu.
+    echo.
+    pause
+    goto StandaloneMenu
+)
+Echo.
+Echo    The PIP cache has been purged.
+Echo.
+pause
+goto StandaloneMenu
+
+:STGitpull
+cd /D "%~dp0"
+set CONDA_ROOT_PREFIX=%cd%\alltalk_environment\conda
+set INSTALL_ENV_DIR=%cd%\alltalk_environment\env
+@rem Check if the Conda environment exists
+if not exist "%INSTALL_ENV_DIR%\python.exe" (
+    echo.
+    echo    The Conda environment at "%INSTALL_ENV_DIR%" does not exist.
+    echo    Please install the environment before proceeding.
+    echo. 
+    pause
+    goto StandaloneMenu
+)
+@rem Attempt to activate the Conda environment
+call "%CONDA_ROOT_PREFIX%\condabin\conda.bat" activate "%INSTALL_ENV_DIR%"
+if errorlevel 1 (
+    echo. 
+    echo    Failed to activate the Conda environment.
+    echo    Please check your installation and try again.
+    echo.
+    pause
+    goto StandaloneMenu
+)
+@rem Pull from Github
+echo.
+echo     Pulling the latest updates. Please re-apply
+echo     the latest requirements file. Option 3
+echo.
+git pull
+if %ERRORLEVEL% neq 0 (
+    echo.
+    echo    There was an error pulling from Github.
+    echo    Press any key to return to the menu.
+    echo.
+    pause
+    goto StandaloneMenu
+)
+Echo.
+echo     AllTalk Updated from Github. Please re-apply
+echo     the latest requirements file. Option 3
+Echo.
+pause
+goto StandaloneMenu
+
+:End
+echo Exiting AllTalk Setup Utility...
+exit /b

atsetup.sh

@@ -0,0 +1,486 @@
+#!/bin/bash
+
+# ANSI color codes
+RED='\033[1;31m'
+GREEN='\033[1;32m'
+YELLOW='\033[1;33m'
+BLUE='\033[1;34m'
+CYAN='\033[1;36m'
+MAGENTA='\033[1;35m'
+WHITE='\033[1;37m'
+L_RED='\033[1;91m'
+L_GREEN='\033[1;92m'
+L_YELLOW='\033[1;93m'
+L_BLUE='\033[1;94m'
+L_CYAN='\033[1;96m'
+L_MAGENTA='\033[1;95m'
+NC='\033[0m' # No Color
+
+# Navigate to the script's directory
+cd "$(dirname "$0")"
+
+# Function to check if curl is installed
+check_curl() {
+    if ! command -v curl &> /dev/null; then
+        echo "curl is not available on this system. Please install curl then re-run the script https://curl.se/"
+        echo "or perform a manual installation of a Conda Python environment."
+        exit 1
+    fi
+}
+
+# Main Menu
+main_menu() {
+    while true; do
+        clear
+        echo
+        echo -e "    ${L_BLUE}ALLTALK LINUX SETUP UTILITY${NC}"
+        echo
+        echo "    INSTALLATION TYPE"
+        echo -e "    1) I am using AllTalk as part of ${L_GREEN}Text-generation-webui${NC}"
+        echo -e "    2) I am using AllTalk as a ${L_GREEN}Standalone Application${NC}"
+        echo
+        echo -e "    9)${L_RED} Exit/Quit${NC}"
+        echo
+        read -p "    Enter your choice: " user_option
+
+        case $user_option in
+            1) webui_menu ;;
+            2) standalone_menu ;;
+            9) exit 0 ;;
+            *) echo "Invalid option"; sleep 2 ;;
+        esac
+    done
+}
+
+# Text-generation-webui Menu
+webui_menu() {
+    while true; do
+        clear
+        echo
+        echo -e "    ${L_BLUE}TEXT-GENERATION-WEBUI SETUP${NC}"
+        echo
+        echo -e "    Please ensure you have started your Text-generation-webui Python"
+        echo -e "    environment. If you have NOT done this, please run ${L_GREEN}/cmd_linux.sh${NC}"
+        echo -e "    in the ${L_GREEN}text-generation-webui${NC} folder and then re-run this script."
+        echo
+        echo "    BASE REQUIREMENTS"
+        echo -e "    1) Apply/Re-Apply the requirements for an ${L_GREEN}Text-generation-webui${NC}"
+        echo
+        echo "    OPTIONAL"
+        echo "    2) Git Pull the latest AllTalk updates from Github"
+        echo
+        echo "    DEEPSPEED"
+        echo "    4) Install DeepSpeed."
+        echo "    5) Uninstall DeepSpeed."
+        echo
+        echo "    OTHER"
+        echo "    6) Generate a diagnostics file."
+        echo
+        echo -e "    9)${L_RED} Exit/Quit${NC}"
+        echo
+        read -p "    Enter your choice: " webui_option
+
+        case $webui_option in
+            1) install_nvidia_textgen ;;
+            2) tg_gitpull ;;
+            4) install_deepspeed ;;
+            5) uninstall_deepspeed ;;
+            6) generate_diagnostics_textgen ;;
+            9) exit 0 ;;
+            *) echo "Invalid option"; sleep 2 ;;
+        esac
+    done
+}
+
+install_nvidia_textgen() {
+    local requirements_file="system/requirements/requirements_textgen.txt"
+    echo "    Installing Requirements from $requirements_file..."
+    if ! pip install -r "$requirements_file"; then
+        echo
+        echo "    There was an error pulling from Github."
+        echo "    Please check the output for details."
+        read -p "    Press any key to return to the menu. " -n 1
+        echo
+        return
+    fi
+    echo
+    echo "    Requirements installed successfully."
+    echo
+    echo -e "    To install ${L_YELLOW}DeepSpeed${NC} on Linux, there are additional"
+    echo -e "    steps required. Please see the Github or documentation on DeepSeed."
+    echo
+    read -p "    Press any key to continue. " -n 1
+    echo
+}
+
+tg_gitpull() {
+    echo
+    if ! git pull; then
+        echo
+        echo "    There was an error installing the requirements."
+        echo "    Please check the output for details."
+        echo
+        read -p "    Press any key to return to the menu. " -n 1
+        echo
+        return
+    fi
+    echo
+    echo "    AllTalk Updated from Github. Please re-apply"
+    echo "    the latest requirements file. (Option 1)"
+    echo
+    read -p "    Press any key to continue. " -n 1
+    echo
+}
+
+# Function to install DeepSpeed
+install_deepspeed() {
+    clear
+    echo
+    echo -e "    ${L_BLUE}DEEPSPEED INSTALLATION REQUIREMENTS${NC}"
+    echo
+    echo -e "    - NVIDIA CUDA Toolkit must be installed from your ${L_GREEN}Linux package manager${NC}"
+    echo -e "      or ${L_GREEN}https://developer.nvidia.com/cuda-toolkit-archive${NC}"
+    echo -e "    - The environment variable ${L_GREEN}CUDA_HOME${NC} must be set in your Python env"
+    echo -e "      e.g. export CUDA_HOME=/usr/local/cuda."
+    echo -e "    - ${L_GREEN}libaio-dev${NC} must be installed."
+    echo
+    echo -e "    See the following link for full instructions:"
+    echo -e "    ${L_GREEN}https://github.com/erew123/alltalk_tts?#-deepspeed-installation-options${NC}"
+    echo
+    echo -e "    ${L_BLUE}Please ${L_RED}confirm${L_BLUE} that you have completed these steps before continuing" 
+    echo -e "    with the DeepSpeed installation, or the install ${L_RED}will fail.${NC}"
+    echo
+    read -p "    Have you completed all the above steps? (y/n): " confirm
+
+    if [ "$confirm" != "y" ]; then
+        echo -e "    ${RED}DeepSpeed installation cannot proceed without completing the prerequisites.${NC}"
+        return
+    fi
+
+    echo -e "\n    ${GREEN}Proceeding with DeepSpeed installation...${NC}"
+    pip install deepspeed
+    if [ $? -ne 0 ]; then
+        echo -e "    ${RED}There was an error installing DeepSpeed.${NC}"
+        return
+    fi
+
+    echo -e "    ${GREEN}DeepSpeed installed successfully.${NC}"
+    read -p "    Press any key to continue. " -n 1
+    echo
+}
+
+uninstall_deepspeed() {
+    echo "Uninstalling DeepSpeed..."
+    pip uninstall -y deepspeed
+    if [ $? -ne 0 ]; then
+        echo
+        echo "    There was an error uninstalling DeepSpeed."
+        echo
+        echo "    Press any key to return to the menu."
+        read -n 1
+        return
+    fi
+    echo
+    echo "    DeepSpeed uninstalled successfully."
+    echo
+    echo "    Press any key to continue."
+    read -n 1
+}
+
+generate_diagnostics_textgen() {
+    # Run diagnostics
+    if ! python diagnostics.py; then
+        echo
+        echo "    There was an error running diagnostics."
+        echo
+        read -p "    Press any key to return to the menu. " -n 1
+        echo
+        return
+    fi
+    echo
+    echo "    Diagnostics log file generated successfully."
+    echo "    Please see diagnostics.log"
+    echo
+    read -p "    Press any key to continue. " -n 1
+    echo
+}
+
+# Standalone Menu
+standalone_menu() {
+    while true; do
+        clear
+        echo
+        echo -e "    ${L_BLUE}ALLTALK STANDALONE APPLICATION SETUP${NC}"
+        echo
+        echo "    BASE REQUIREMENTS"
+        echo "    1) Install AllTalk as a Standalone Application"
+        echo
+        echo "    OPTIONAL"
+        echo "    2) Git Pull the latest AllTalk updates from Github"
+        echo "    3) Re-Apply/Update the requirements file"
+        echo "    4) Delete AllTalk's custom Python environment"
+        echo "    5) Purge the PIP cache"
+        echo
+        echo "    DEEPSPEED"
+        echo "    6) DeepSpeed Instructions/Install"
+        echo
+        echo "    OTHER"        
+        echo "    8) Generate a diagnostics file"
+        echo
+        echo -e "    9)${L_RED} Exit/Quit${NC}"
+        echo
+        read -p "    Enter your choice: " standalone_option
+
+        case $standalone_option in
+            1) install_custom_standalone ;;
+            2) gitpull_standalone ;;
+            3) reapply_standalone ;;
+            4) delete_custom_standalone ;;
+            5) pippurge_standalone ;;
+            6) install_deepspeed ;;
+            8) generate_diagnostics_standalone ;;
+            9) exit 0 ;;
+            *) echo "Invalid option"; sleep 2 ;;
+        esac
+    done
+}
+
+
+install_custom_standalone() {
+    cd "$(dirname "${BASH_SOURCE[0]}")"
+
+    if [[ "$(pwd)" =~ " " ]]; then
+        echo "This script relies on Miniconda which can not be silently installed under a path with spaces."
+        exit
+    fi
+
+    # Deactivate existing conda envs as needed to avoid conflicts
+    { conda deactivate && conda deactivate && conda deactivate; } 2> /dev/null
+
+    OS_ARCH=$(uname -m)
+    case "${OS_ARCH}" in
+        x86_64*)    OS_ARCH="x86_64" ;;
+        arm64* | aarch64*) OS_ARCH="aarch64" ;;
+        *)          echo "Unknown system architecture: $OS_ARCH! This script runs only on x86_64 or arm64" && exit ;;
+    esac
+
+    # Config
+    INSTALL_DIR="$(pwd)/alltalk_environment"
+    CONDA_ROOT_PREFIX="${INSTALL_DIR}/conda"
+    INSTALL_ENV_DIR="${INSTALL_DIR}/env"
+    MINICONDA_DOWNLOAD_URL="https://repo.anaconda.com/miniconda/Miniconda3-py310_23.3.1-0-Linux-${OS_ARCH}.sh"
+
+    if [ ! -x "${CONDA_ROOT_PREFIX}/bin/conda" ]; then
+        echo "Downloading Miniconda from $MINICONDA_DOWNLOAD_URL to ${INSTALL_DIR}/miniconda_installer.sh"
+        mkdir -p "${INSTALL_DIR}"
+        curl -L "${MINICONDA_DOWNLOAD_URL}" -o "${INSTALL_DIR}/miniconda_installer.sh"
+        chmod +x "${INSTALL_DIR}/miniconda_installer.sh"
+        bash "${INSTALL_DIR}/miniconda_installer.sh" -b -p "${CONDA_ROOT_PREFIX}"
+        echo "Miniconda installed."
+    fi
+
+    if [ ! -d "${INSTALL_ENV_DIR}" ]; then
+        "${CONDA_ROOT_PREFIX}/bin/conda" create -y --prefix "${INSTALL_ENV_DIR}" python=3.11
+        echo "Conda environment created at ${INSTALL_ENV_DIR}."
+    fi
+
+    # Activate the environment and install requirements
+    source "${CONDA_ROOT_PREFIX}/etc/profile.d/conda.sh"
+    conda activate "${INSTALL_ENV_DIR}"
+    echo
+    echo "    Downloading and installing PyTorch. This step can take a long time"
+    echo "    depending on your internet connection and hard drive speed. Please"
+    echo "    be patient."
+    pip install torch>=2.2.1+cu121 torchaudio>=2.2.1+cu121 --extra-index-url https://download.pytorch.org/whl/cu121
+    echo
+    echo "    Installing additional requirements."
+    echo
+    pip install -r system/requirements/requirements_standalone.txt
+    # Create start_environment.sh to run AllTalk
+    cat << EOF > start_environment.sh
+#!/bin/bash
+cd "$(dirname "${BASH_SOURCE[0]}")"
+if [[ "$(pwd)" =~ " " ]]; then echo This script relies on Miniconda which can not be silently installed under a path with spaces. && exit; fi
+# deactivate existing conda envs as needed to avoid conflicts
+{ conda deactivate && conda deactivate && conda deactivate; } 2> /dev/null
+# config
+CONDA_ROOT_PREFIX="$(pwd)/alltalk_environment/conda"
+INSTALL_ENV_DIR="$(pwd)/alltalk_environment/env"
+# environment isolation
+export PYTHONNOUSERSITE=1
+unset PYTHONPATH
+unset PYTHONHOME
+export CUDA_PATH="$INSTALL_ENV_DIR"
+export CUDA_HOME="$CUDA_PATH"
+export LD_LIBRARY_PATH=`python3 -c 'import os; import nvidia.cublas.lib; import nvidia.cudnn.lib; print(os.path.dirname(nvidia.cublas.lib.__file__) + ":" + os.path.dirname(nvidia.cudnn.lib.__file__))'`
+# activate env
+bash --init-file <(echo "source \"$CONDA_ROOT_PREFIX/etc/profile.d/conda.sh\" && conda activate \"$INSTALL_ENV_DIR\"")
+EOF
+    # Create start_alltalk.sh to run AllTalk
+    cat << EOF > start_alltalk.sh
+#!/bin/bash
+export LD_LIBRARY_PATH=`python3 -c 'import os; import nvidia.cublas.lib; import nvidia.cudnn.lib; print(os.path.dirname(nvidia.cublas.lib.__file__) + ":" + os.path.dirname(nvidia.cudnn.lib.__file__))'`
+source "${CONDA_ROOT_PREFIX}/etc/profile.d/conda.sh"
+conda activate "${INSTALL_ENV_DIR}"
+python script.py
+EOF
+    # Create start_finetune.sh to run AllTalk
+    cat << EOF > start_finetune.sh
+#!/bin/bash
+export TRAINER_TELEMETRY=0
+export LD_LIBRARY_PATH=`python3 -c 'import os; import nvidia.cublas.lib; import nvidia.cudnn.lib; print(os.path.dirname(nvidia.cublas.lib.__file__) + ":" + os.path.dirname(nvidia.cudnn.lib.__file__))'`
+source "${CONDA_ROOT_PREFIX}/etc/profile.d/conda.sh"
+conda activate "${INSTALL_ENV_DIR}"
+python finetune.py
+EOF
+    chmod +x start_alltalk.sh
+    chmod +x start_environment.sh
+    chmod +x start_finetune.sh
+    echo
+    echo
+    echo -e "    Run ${L_YELLOW}./start_alltalk.sh${NC} to start AllTalk."
+    echo -e "    Run ${L_YELLOW}./start_finetune.sh${NC} to start Finetuning."
+    echo -e "    Run ${L_YELLOW}./start_environment.sh${NC} to start the AllTalk Python environment."
+    echo
+    echo -e "    To install ${L_YELLOW}DeepSpeed${NC} on Linux, there are additional"
+    echo -e "    steps required. Please see the Github or documentation on DeepSeed."
+    echo
+    read -p "    Press any key to continue. " -n 1
+}
+
+delete_custom_standalone() {
+    local env_dir="$PWD/alltalk_environment"
+    # Check if the alltalk_environment directory exists
+    if [ ! -d "$env_dir" ]; then
+        echo "    \"$env_dir\" directory does not exist. No need to delete."
+        read -p "    Press any key to continue. " -n 1
+        echo
+        return
+    fi
+    # Check if a Conda environment is active and deactivate it
+    if [ -n "$CONDA_PREFIX" ]; then
+        echo "    Exiting the Conda environment. You may need to start ./atstart.sh again"
+        conda deactivate
+    fi
+    echo "Deleting \"$env_dir\". Please wait."
+    rm -rf "$env_dir"
+    if [ -d "$env_dir" ]; then
+        echo "    Failed to delete \"$env_dir\" folder."
+        echo "    Please make sure it is not in use and try again."
+    else
+        echo "    Environment \"$env_dir\" deleted successfully."
+    fi
+    read -p "    Press any key to continue. " -n 1
+    echo
+}
+
+generate_diagnostics_standalone() {
+    local env_dir="$PWD/alltalk_environment"
+    local conda_root_prefix="${env_dir}/conda"
+    local install_env_dir="${env_dir}/env"
+    if [ ! -d "${install_env_dir}" ]; then
+        echo
+        echo "    The Conda environment at '${install_env_dir}' does not exist."
+        echo "    Please install the environment before proceeding."
+        echo
+        read -p "    Press any key to return to the menu. " -n 1
+        echo
+        return
+    fi
+    source "${conda_root_prefix}/etc/profile.d/conda.sh"
+    conda activate "${install_env_dir}"
+    if ! python diagnostics.py; then
+        echo
+        echo "    There was an error running diagnostics."
+        echo
+        read -p "    Press any key to return to the menu. " -n 1
+        echo
+        return
+    fi
+    echo
+    echo "    Diagnostics completed successfully."
+    read -p "    Press any key to continue. " -n 1
+    echo
+}
+
+gitpull_standalone() {
+    local env_dir="$PWD/alltalk_environment"
+    local conda_root_prefix="${env_dir}/conda"
+    local install_env_dir="${env_dir}/env"
+    if [ ! -d "${install_env_dir}" ]; then
+        echo
+        echo "    The Conda environment at '${install_env_dir}' does not exist."
+        echo "    Please install the environment before proceeding."
+        echo
+        read -p "    Press any key to return to the menu. " -n 1
+        echo
+        return
+    fi
+    source "${conda_root_prefix}/etc/profile.d/conda.sh"
+    conda activate "${install_env_dir}"
+    if ! git pull; then
+        echo
+        echo "    There was an error pulling from Github."
+        echo
+        read -p "    Press any key to return to the menu. " -n 1
+        echo
+        return
+    fi
+    echo
+    echo "    AllTalk Updated from Github. Please re-apply."
+    echo "    the latest requirements file. (Option 3)"
+    echo
+    read -p "    Press any key to continue. " -n 1
+    echo
+}
+
+pippurge_standalone() {
+    if ! pip cache purge; then
+        echo
+        echo "    There was an error."
+        echo
+        read -p "    Press any key to return to the menu. " -n 1
+        echo
+        return
+    fi
+    echo
+    echo "    The PIP cache has been purged."
+    echo
+    read -p "    Press any key to continue. " -n 1
+    echo
+}
+
+reapply_standalone() {
+    local env_dir="$PWD/alltalk_environment"
+    local conda_root_prefix="${env_dir}/conda"
+    local install_env_dir="${env_dir}/env"
+    if [ ! -d "${install_env_dir}" ]; then
+        echo
+        echo "    The Conda environment at '${install_env_dir}' does not exist."
+        echo "    Please install the environment before proceeding."
+        echo
+        read -p "    Press any key to return to the menu. " -n 1
+        echo
+        return
+    fi
+    source "${conda_root_prefix}/etc/profile.d/conda.sh"
+    conda activate "${install_env_dir}"
+    echo
+    echo "    Downloading and installing PyTorch. This step can take a long time"
+    echo "    depending on your internet connection and hard drive speed. Please"
+    echo "    be patient."
+    pip install torch>=2.2.1+cu121 torchaudio>=2.2.1+cu121 --extra-index-url https://download.pytorch.org/whl/cu121
+    echo
+    echo "    Installing additional requirements."
+    echo
+    pip install -r system/requirements/requirements_standalone.txt
+    echo
+    echo "    Requirements have been re-applied/updated."
+    echo
+    read -p "    Press any key to continue. " -n 1
+    echo
+}
+
+
+# Start the main menu
+main_menu

confignew.json

@@ -1 +1,25 @@
-{"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"}
+{
+    "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"
+}

diagnostics.py

@@ -2,16 +2,30 @@ try:
     import platform
     import subprocess
     import logging
-    from importlib_metadata import distribution, distributions
+    from importlib_metadata import distributions
     import torch
     import os  # Import the os module
+    import re
+    import sys
+    import glob
+    import site
+    import textwrap
+    import torch
+    import packaging.version
+    import packaging.specifiers
+    from packaging.specifiers import SpecifierSet
+    from packaging.specifiers import SpecifierSet
+    from packaging.version import parse as parse_version
+    from pathlib import Path
 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)
 
+this_dir = Path(__file__).parent
+
 try:
     import psutil
 except ImportError:
@@ -19,8 +33,31 @@ except ImportError:
     subprocess.run(['pip', 'install', 'psutil'])
     import psutil
 
-# Additional import for torch
-import torch
+def get_requirements_file():
+    this_dir = Path(__file__).parent  # Assuming 'this_dir' is defined as the script's directory
+    requirements_dir = this_dir / 'system' / 'requirements'
+    requirements_files = list(requirements_dir.glob('requirements*.txt'))  # Using pathlib for globbing
+    
+    if not requirements_files:
+        print("\033[91mNo requirements files found.\033[0m")
+        return None
+
+    print("\033[94m\nSelect a requirements file to check against (or press Enter for default 'requirements.txt'):\033[0m\n")
+    for i, file_path in enumerate(requirements_files, start=1):
+        print(f"    {i}. {file_path.name}")  # Only print the filename
+
+    choice = input("\nEnter the number of your choice: ")
+    try:
+        choice = int(choice) - 1
+        return str(requirements_files[choice])  # Return the full path as a string
+    except (ValueError, IndexError):
+        return str(requirements_dir / "requirements.txt")  # Return the default path as a string
+
+# Set up logging with filemode='w'
+logging.basicConfig(filename='diagnostics.log',
+                    filemode='w',
+                    level=logging.INFO,
+                    format='%(message)s')  # Custom format
 
 # Function to get GPU information using subprocess
 def get_gpu_info():
@@ -29,6 +66,22 @@ def get_gpu_info():
         return result.stdout
     except FileNotFoundError:
         return "NVIDIA GPU information not available"
+    
+def get_cpu_info():
+    cpu_info = {
+        'physical_cores': psutil.cpu_count(logical=False),
+        'total_cores': psutil.cpu_count(logical=True),
+        'max_frequency': psutil.cpu_freq().max
+    }
+    return cpu_info
+
+def get_disk_info():
+    disk_info = []
+    partitions = psutil.disk_partitions()
+    for p in partitions:
+        usage = psutil.disk_usage(p.mountpoint)
+        disk_info.append(f" Drive: {p.device} | Total: {usage.total / (1024 ** 3):.2f} GB | Used: {usage.used / (1024 ** 3):.2f} GB | Free: {usage.free / (1024 ** 3):.2f} GB | Type: {p.fstype}")
+    return disk_info
 
 # Function to check if a port is in use
 def is_port_in_use(port):
@@ -37,6 +90,48 @@ def is_port_in_use(port):
             return True
     return False
 
+def satisfies_wildcard(installed_version, required_version):
+    if '*' in required_version:
+        required_parts = required_version.split('.')
+        installed_parts = installed_version.split('.')
+        for req, inst in zip(required_parts, installed_parts):
+            if req != '*' and req != inst:
+                return False
+        return True
+    return False
+
+def test_cuda():
+    cuda_available = torch.cuda.is_available()
+    if cuda_available:
+        try:
+            # Attempt to create a tensor on GPU
+            torch.tensor([1.0, 2.0]).cuda()
+            return "Success - CUDA is available and working."
+        except Exception as e:
+            return f"Fail - CUDA is available but not working. Error: {e}"
+    else:
+        return "Fail - CUDA is not available."
+
+def find_files_in_path_with_wildcard(pattern):
+    # Get the site-packages directory of the current Python environment
+    site_packages_path = site.getsitepackages()
+    found_paths = []
+    # Adjust the sub-directory based on the operating system
+    sub_directory = "nvidia/cublas"
+    if platform.system() == "Linux":
+        sub_directory = os.path.join(sub_directory, "lib")
+    else:
+        sub_directory = os.path.join(sub_directory, "bin")
+    # Iterate over each site-packages directory (there can be more than one)
+    for directory in site_packages_path:
+        # Construct the search directory path
+        search_directory = os.path.join(directory, sub_directory)
+        # Use glob to find all files matching the pattern in this directory
+        for file_path in glob.glob(os.path.join(search_directory, pattern)):
+            if os.path.isfile(file_path):  # Ensure it's a file
+                found_paths.append(file_path)
+    return found_paths
+
 # Function to log and print system information
 def log_system_info():
     # System information
@@ -52,6 +147,9 @@ def log_system_info():
 
     # Torch version
     torch_version = torch.__version__
+    cuda_test_result = test_cuda()
+    cpu_info = get_cpu_info()
+    disk_info = get_disk_info()
 
     # System RAM using psutil
     try:
@@ -75,34 +173,153 @@ 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')
+
+    # Check for cublas
+    file_name = 'cublas64_11.*' if platform.system() == "Windows" else 'libcublas.so.11*'
+    found_paths = find_files_in_path_with_wildcard(file_name)
+
+    # Compare with requirements file
+    requirements_file = get_requirements_file()
+    if requirements_file:
+        required_packages = {}
+        installed_packages = {}
+
+        try:
+            with open(requirements_file, 'r') as req_file:
+                requirements = [line.strip() for line in req_file]
+                for req in requirements:
+                    # Use regular expression to parse package name and version
+                    match = re.match(r'([^\s>=]+)\s*([>=<]+)\s*([^,]+)', req)
+                    if match:
+                        package_name, operator, version_spec = match.groups()
+                        installed_version = package_versions.get(package_name, 'Not installed')
+                        if installed_version != 'Not installed':
+                            required_packages[package_name] = (operator, version_spec)
+                            installed_packages[package_name] = installed_version
+        except FileNotFoundError:
+            print(f"\n{requirements_file} not found. Skipping version checks.")
+            logging.info(f"NOTE {requirements_file} not found. Skipping version checks.")
+
     # Log and print information
-    logging.info(f"OS Version: {os_version}")
-    logging.info(f"Note: Windows 11 does call itself 10")
-    logging.info(f"Python Version: {python_version}")
-    logging.info(f"Torch Version: {torch_version}")
-    logging.info(f"System RAM: {system_ram}")
-    logging.info(f"Total System RAM: {total_ram}")
-    logging.info(f"Available System RAM: {available_ram}")
-    logging.info(f"CUDA_HOME: {cuda_home}")
-    logging.info(f"\nPort Status: {port_status}")
-    logging.info(f"GPU Information:\n{gpu_info}")
-    logging.info("Package Versions:")
+    logging.info(f"OPERATING SYSTEM:")
+    logging.info(f" OS Version: {os_version}")
+    logging.info(f" Note: Windows 11 will list as build is 10.x.22xxx")
+    logging.info(f"\nHARDWARE ENVIRONMENT:")
+    logging.info(f" CPU: Physical Cores: {cpu_info['physical_cores']}, Total Cores: {cpu_info['total_cores']}, Max Frequency: {cpu_info['max_frequency']} MHz")
+    logging.info(f" System RAM: {system_ram}")
+    logging.info(f"\nGPU INFORMATION:{gpu_info}")
+    logging.info("DISK INFORMATION:")
+    for disk in disk_info:
+        logging.info(disk)
+    logging.info("\nNETWORK PORT:")
+    logging.info(f" Port Status: {port_status}")
+    logging.info("\nCUDA:")
+    logging.info(f" CUDA Working: {cuda_test_result}")
+    logging.info(f" CUDA_HOME: {cuda_home}")
+    if found_paths:
+        logging.info(f" Cublas64_11 Path: {', '.join(found_paths)}")
+    else:
+        logging.info(f" Cublas64_11 Path: Not found in any search path directories.")
+    logging.info("\nPYTHON & PYTORCH:")
+    logging.info(f" Torch Version: {torch_version}")
+    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 SEARCHPATH ENVIRONMENT:")
+    for path in path_env.split(';'):
+        logging.info(f"  {path}")
+    if required_packages:  # Check if the dictionary is not empty
+        logging.info("\nPACKAGE VERSIONS vs REQUIREMENTS FILE:")
+        max_package_length = max(len(package) for package in required_packages.keys())
+        for package_name, (operator, required_version) in required_packages.items():
+            installed_version = installed_packages.get(package_name, 'Not installed')
+            logging.info(f" {package_name.ljust(max_package_length)}  Required: {operator} {required_version.ljust(12)}  Installed: {installed_version}")
+    logging.info("\nPYTHON PACKAGES:")
     for package, version in package_versions.items():
-        logging.info(f"{package}>= {version}")
+        logging.info(f" {package}>= {version}")
 
     # Print to screen
-    print(f"\033[94mOS Version:\033[0m \033[92m{os_version}\033[0m")
-    print(f"\033[94mNote:\033[0m \033[92mWindows 11 does call itself 10\033[0m")
-    print(f"\033[94mPython Version:\033[0m \033[92m{python_version}\033[0m")
-    print(f"\033[94mTorch Version:\033[0m \033[92m{torch_version}\033[0m")
+    print(f"\n\033[94mOS Version:\033[0m \033[92m{os_version}\033[0m")
+    print(f"\033[94mOS Ver note:\033[0m \033[92m(Windows 11 will say build is 10.x.22xxx)\033[0m")
     print(f"\033[94mSystem RAM:\033[0m \033[92m{system_ram}\033[0m")
-    print(f"\033[94mTotal System RAM:\033[0m \033[92m{total_ram}\033[0m")
-    print(f"\033[94mAvailable System RAM:\033[0m \033[92m{available_ram}\033[0m")
+    for disk in disk_info:
+        print(f"\033[94mDisk:\033[0m \033[92m{disk}\033[0m")
+    print(f"\033[94m\nGPU Information:\033[0m {gpu_info}")
+    print(f"\033[94mPort Status:\033[0m \033[92m{port_status}\033[0m\n")
+    if "Fail" in cuda_test_result:
+        print(f"\033[91mCUDA Working:\033[0m \033[91m{cuda_test_result}\033[0m")
+    else:
+        print(f"\033[94mCUDA Working:\033[0m \033[92m{cuda_test_result}\033[0m")
     print(f"\033[94mCUDA_HOME:\033[0m \033[92m{cuda_home}\033[0m")
-    print(f"\033[94mPort Status:\033[0m \033[92m{port_status}\033[0m")
+    if found_paths:
+        print(f"\033[94mCublas64_11 Path:\033[0m \033[92m{', '.join(found_paths)}\033[0m")
+    else:
+        print(f"\033[94mCublas64_11 Path:\033[0m \033[91mNot found in any search path directories.\033[0m")    
+    print(f"\033[94m\nTorch Version:\033[0m \033[92m{torch_version}\033[0m")
+    print(f"\033[94mPython Version:\033[0m \033[92m{platform.python_version()}\033[0m")
+    print(f"\033[94mPython Executable:\033[0m \033[92m{python_executable}\033[0m")
+    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}")
+    if required_packages:  # Check if the dictionary is not empty
+        print("\033[94m\nRequirements file package comparison:\033[0m")
+        max_package_length = max(len(package) for package in required_packages.keys())
+
+        for package_name, (operator, required_version) in required_packages.items():
+            installed_version = installed_packages.get(package_name, 'Not installed')
+
+            # Exclude build information (e.g., +cu118) before creating the SpecifierSet
+            required_version_no_build = required_version.split("+")[0]
+
+            if '*' in required_version:
+                condition_met = satisfies_wildcard(installed_version, required_version)
+            else:
+                # Compare versions using packaging.version
+                required_specifier = SpecifierSet(f"{operator}{required_version_no_build}")
+                installed_version = parse_version(installed_version)
+                condition_met = installed_version in required_specifier
+
+            color_required = "\033[92m" if condition_met else "\033[91m"
+            color_installed = "\033[92m" if condition_met else "\033[91m"
+
+            # Print colored output
+            print(f"  {package_name.ljust(max_package_length)}  Required: {color_required}{operator} {required_version.ljust(12)}\033[0m  Installed: {color_installed}{installed_version}\033[0m")
+
+        print("\nOn Nvidia Graphics cards machines, if your \033[92mInstalled\033[0m version of \033[92mTorch\033[0m and \033[92mTorchaudio\033[0m does")    
+        print("not have \033[92m+cu118\033[0m (Cuda 11.8) or \033[92m+cu121\033[0m (Cuda 12.1) listed after them, you do not have CUDA")
+        print("installed for Torch or Torchaudio in this Python environment. This will cause you problems")
+        print("with \033[94mAllTalk\033[0m and \033[94mFinetuning.\033[0m You may have to 'pip install' a new version of torch and")
+        print("torchaudio, using '\033[94m--upgrade --force-reinstall\033[0m' with the correct version of PyTorch for\033[0m")
+        print("your Python environment.\033[0m")
+        print("\033[94m\nRequirements file specifier meanings:\033[0m")
+        explanation = textwrap.dedent("""
+        == Exact version              != Any version except          < Less than               
+        <= Less than or equal to      >  Greater than                >= Greater than or equal to
+        ~ Compatible release          ;  Environment marker          AND Logical AND           
+        OR Logical OR
+        """)
+        print(explanation.strip())
     print("")
-    print(f"GPU Information:{gpu_info}")
-    print(f"\033[94mDiagnostic log created:\033[0m \033[92mdiagnostics.log\033[0m")
+    print(f"\033[94mDiagnostic log created:\033[0m \033[92mdiagnostics.log. \033[94mA brief summary of results is displayed above on\033[0m")
+    print(f"\033[94mscreen. Please see the log file for more detail.\033[0m")
+    print(f"\033[94m\nPlease upload the log file with any support ticket.\033[0m")
 
 if __name__ == "__main__":
     log_system_info()

docker-compose-cuda.yml

@@ -0,0 +1,20 @@
+version: '3.8'
+services:
+  alltalk-tts:
+    image: erew123/alltalk_tts:cuda
+    restart: unless-stopped
+    ports:
+      - "7851:7851"
+    volumes:
+      - ./outputs:/app/outputs/
+      - ./models:/app/models/
+      - ./voices:/app/voices/
+      - ./finetune/put-voice-samples-in-here:/app/finetune/put-voice-samples-in-here
+      - ./dockerconfig.json:/app/confignew.json
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - driver: nvidia
+              count: all
+              capabilities: [ gpu ]

docker-compose.yml

@@ -0,0 +1,13 @@
+version: '3.8'
+services:
+  alltalk-tts:
+    image: erew123/alltalk_tts:cpu
+    restart: unless-stopped
+    ports:
+      - "7851:7851"
+    volumes:
+      - ./outputs:/app/outputs/
+      - ./models:/app/models/
+      - ./voices:/app/voices/
+      - ./finetune/put-voice-samples-in-here:/app/finetune/put-voice-samples-in-here
+      - ./dockerconfig.json:/app/confignew.json

dockerconfig.json

@@ -0,0 +1,25 @@
+{
+    "activate": true,
+    "autoplay": true,
+    "branding": "AllTalk ",
+    "narrator_enabled": false,
+    "deepspeed_activate": true,
+    "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"
+}

launch.sh

@@ -0,0 +1,5 @@
+#!/bin/sh
+python modeldownload.py
+uvicorn tts_server:app --host 0.0.0.0 --port 7851 --workers 1 --proxy-headers &
+sleep 5
+python script.py

modeldownload.json

@@ -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"
     }
-}
+}

modeldownload.py

@@ -45,18 +45,18 @@ else:
     )
 
 # Read the version specifier from requirements_nvidia.txt
-with open(this_dir / "requirements_nvidia.txt", "r") as req_file:
+with open(this_dir / "system" / "requirements" / "requirements_standalone.txt", "r") as req_file:
     requirements = req_file.readlines()
 
 tts_version_required = None
 for req in requirements:
-    if req.startswith("TTS>="):
-        tts_version_required = req.strip().split(">=")[1]
+    if req.startswith("TTS=="):
+        tts_version_required = req.strip().split("==")[1]
         break
 
 if tts_version_required is None:
     raise ValueError(
-        f"[{params['branding']}Startup] \033[91mWarning\033[0m Could not find TTS version specifier in requirements_nvidia.txt"
+        f"[{params['branding']}Startup] \033[91mWarning\033[0m Could not find TTS version specifier in requirements file"
     )
 
 

nvidia.Dockerfile

@@ -0,0 +1,20 @@
+FROM nvidia/cuda:12.1.1-devel-ubuntu22.04
+ENV HOST 0.0.0.0
+RUN apt-get update && apt-get upgrade -y \
+    && apt-get install -y git build-essential portaudio19-dev \
+    python3 python3-pip gcc wget \
+    ocl-icd-opencl-dev opencl-headers clinfo \
+    libclblast-dev libopenblas-dev \
+    && mkdir -p /etc/OpenCL/vendors && echo "libnvidia-opencl.so.1" > /etc/OpenCL/vendors/nvidia.icd \
+    && ln -s /usr/bin/python3 /usr/bin/python
+WORKDIR /app
+COPY . .
+ENV CUDA_DOCKER_ARCH=all
+
+RUN pip install --no-cache-dir -r requirements_nvidia.txt && \
+    pip install --no-cache-dir -r requirements_finetune.txt && \
+    pip install --no-cache-dir -r requirements_other.txt && \
+    pip install --no-cache-dir deepspeed
+EXPOSE 7851
+RUN chmod +x launch.sh
+ENTRYPOINT ["sh", "-c", "./launch.sh"]

requirements_nvidia.txt

@@ -1,12 +0,0 @@
-numpy>=1.22.0
-soundfile>=0.12.1
-uvicorn>=0.24.0.post1
-TTS>=0.22.0
-torch>=2.1.0+cu118
-torchaudio>=2.1.0+cu118
-fastapi>=0.104.1
-Jinja2>=3.1.2
-requests>=2.31.0
-tqdm>=4.66.1
-importlib-metadata>=4.8.1
-packaging>=23.2

requirements_other.txt

@@ -1,12 +0,0 @@
-numpy>=1.22.0
-soundfile>=0.12.1
-uvicorn>=0.24.0.post1
-TTS>=0.22.0
-torch>=2.1.0
-torchaudio>=2.1.0
-fastapi>=0.104.1
-Jinja2>=3.1.2
-requests>=2.31.0
-tqdm>=4.66.1
-importlib-metadata>=4.8.1
-packaging>=23.2

script.py

@@ -16,18 +16,28 @@ import numpy as np
 import soundfile as sf
 import uuid
 
+######################################
+#### ALLTALK ALLOWED STARTUP TIME ####
+######################################
+startup_wait_time = 120
+
+# You can change the above setting to a larger number to allow AllTAlk more time to start up. The default setting is 120 seconds (2 minutes).
+# On some older systems you may need to allow AllTalk more time. So you could set it to 240 (4 minutes) which will give AllTalk more to load.
+
 #################################################################
 #### 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()
 
+
 # load config file in and get settings
 def load_config(file_path):
     with open(file_path, "r") as config_file:
         config = json.load(config_file)
     return config
 
+
 config_file_path = this_dir / "confignew.json"
 # Load the params dictionary from the confignew.json file
 params = load_config(config_file_path)
@@ -39,8 +49,8 @@ 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 Windows:\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 \\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
@@ -48,6 +58,7 @@ except ModuleNotFoundError:
 # IMPORT - Attempt Importing DeepSpeed (required for displaying Deepspeed checkbox in gradio)
 try:
     import deepspeed
+
     deepspeed_installed = True
 except ImportError:
     deepspeed_installed = False
@@ -60,9 +71,12 @@ try:
     from modules.logging_colors import logger
     from modules.ui import create_refresh_button
     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
@@ -71,15 +85,19 @@ except ModuleNotFoundError:
 #### STARTUP VARIABLES ####
 ###########################
 # 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:
+with open(this_dir / "system" / "config" / "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():
     return sorted([voice.name for voice in Path(f"{this_dir}/voices").glob("*.wav")])
 
+
 #########################
 #### LICENSE DISPLAY ####
 #########################
@@ -108,7 +126,6 @@ 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
@@ -142,6 +159,22 @@ def check_required_files():
 # 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 ####
@@ -157,6 +190,7 @@ elif params["tts_method_xtts_local"] == True:
 # Set the default for Narrated text without asterisk or quotes to be Narrator
 non_quoted_text_is = True
 
+
 ######################
 #### GRADIO STUFF ####
 ######################
@@ -214,68 +248,88 @@ def signal_handler(sig, frame):
 
 # Attach the signal handler to the SIGINT signal (Ctrl+C)
 signal.signal(signal.SIGINT, signal_handler)
-
-# Start the subprocess
-process = subprocess.Popen(["python", script_path])
-
-# Check if the subprocess has started successfully
-if process.poll() is None:
-    print(f"[{params['branding']}Startup] TTS Subprocess starting")
+# Check if we're running in docker
+if os.path.isfile("/.dockerenv"):
     print(
-        f"[{params['branding']}Startup] Readme available here:",
-        f"http://{params['ip_address']}:{params['port_number']}",
+        f"[{params['branding']}Startup] \033[94mRunning in Docker. Please wait.\033[0m"
     )
 else:
-    print(
-        f"[{params['branding']}Startup] \033[91mWarning\033[0m TTS Subprocess Webserver failing to start process"
-    )
-    print(
-        f"[{params['branding']}Startup] \033[91mWarning\033[0m It could be that you have something on port:",
-        params["port_number"],
-    )
-    print(
-        f"[{params['branding']}Startup] \033[91mWarning\033[0m Or you have not started in a Python environement with all the necesssary bits installed"
-    )
-    print(
-        f"[{params['branding']}Startup] \033[91mWarning\033[0m Check you are starting Text-generation-webui with either the start_xxxxx file or the Python environment with cmd_xxxxx file."
-    )
-    print(
-        f"[{params['branding']}Startup] \033[91mWarning\033[0m xxxxx is the type of OS you are on e.g. windows, linux or mac."
-    )
-    print(
-        f"[{params['branding']}Startup] \033[91mWarning\033[0m Alternatively, you could check no other Python processes are running that shouldnt be e.g. Restart your computer is the simple way."
-    )
-    # 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
-
-# Introduce a delay before starting the check loop
-time.sleep(25)  # Wait 25 secs before checking if the tts_server.py has started up.
-start_time = time.time()
-while time.time() - start_time < timeout:
-    try:
-        response = requests.get(f"{base_url}/ready")
-        if response.status_code == 200:
-            break
-    except requests.RequestException as e:
-        # Print the exception for debugging purposes
+    # Start the subprocess
+    process = subprocess.Popen(["python", script_path])
+    # Check if the subprocess has started successfully
+    if process.poll() is None:
+        print(f"[{params['branding']}Startup] TTS Subprocess starting")
+        print(f"[{params['branding']}Startup]")
         print(
-            f"[{params['branding']}Startup] \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[94m {params['branding']}Settings & Documentation:\033[00m",
+            f"\033[92mhttp://{params['ip_address']}:{params['port_number']}\033[00m",
         )
-    time.sleep(1)
-else:
-    print(
-        f"[{params['branding']}Startup] Startup timed out. Check the server logs for more information."
-    )
-    # Cleanly kill off this script, but allow text-generation-webui to keep running, albeit without this alltalk_tts
-    sys.exit(1)
+        print(f"[{params['branding']}Startup]")
+    else:
+        print(
+            f"[{params['branding']}Startup] \033[91mWarning\033[0m TTS Subprocess Webserver failing to start process"
+        )
+        print(
+            f"[{params['branding']}Startup] \033[91mWarning\033[0m It could be that you have something on port:",
+            params["port_number"],
+        )
+        print(
+            f"[{params['branding']}Startup] \033[91mWarning\033[0m Or you have not started in a Python environement with all the necesssary bits installed"
+        )
+        print(
+            f"[{params['branding']}Startup] \033[91mWarning\033[0m Check you are starting Text-generation-webui with either the start_xxxxx file or the Python environment with cmd_xxxxx file."
+        )
+        print(
+            f"[{params['branding']}Startup] \033[91mWarning\033[0m xxxxx is the type of OS you are on e.g. windows, linux or mac."
+        )
+        print(
+            f"[{params['branding']}Startup] \033[91mWarning\033[0m Alternatively, you could check no other Python processes are running that shouldnt be e.g. Restart your computer is the simple way."
+        )
+        # Cleanly kill off this script, but allow text-generation-webui to keep running, albeit without this alltalk_tts
+        sys.exit(1)
+
+    timeout = startup_wait_time  # Gather timeout setting from startup_wait_time
+
+    # Introduce a delay before starting the check loop
+    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:
+            response = requests.get(f"{base_url}/ready")
+            if response.status_code == 200:
+                break
+        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 {timeout} seconds maximum. Please wait."
+            )
+        time.sleep(5)
+    else:
+        print(
+            f"\n[{params['branding']}Startup] Startup timed out. Full help available here \033[92mhttps://github.com/erew123/alltalk_tts#-help-with-problems\033[0m"
+        )
+        print(
+            f"[{params['branding']}Startup] On older system you may wish to open and edit \033[94mscript.py\033[0m with a text editor and changing the"
+        )
+        print(
+            f"[{params['branding']}Startup] \033[94mstartup_wait_time = 120\033[0m setting to something like \033[94mstartup_wait_time = 240\033[0m as this will allow"
+        )
+        print(
+            f"[{params['branding']}Startup] AllTalk more time to try load the model into your VRAM. Otherise please visit the Github for"
+        )
+        print(
+            f"[{params['branding']}Startup] a list of other possible troubleshooting options."
+        )
+        # 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"
@@ -293,18 +347,27 @@ def send_reload_request(tts_method):
                 params["tts_method_xtts_local"] = False
                 params["tts_method_api_tts"] = True
                 params["deepspeed_activate"] = False
-                audio_path = this_dir / "templates" / "apitts.wav"
+                audio_path = this_dir / "system" / "at_sounds" / "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"
+                audio_path = this_dir / "system" / "at_sounds" / "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"
+                audio_path = this_dir / "system" / "at_sounds" / "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 / "system" / "at_sounds" / "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
@@ -313,6 +376,7 @@ def send_reload_request(tts_method):
         )
         return {"status": "error", "message": str(e)}
 
+
 ##################
 #### LOW VRAM ####
 ##################
@@ -321,9 +385,9 @@ def send_lowvram_request(low_vram):
     try:
         params["tts_model_loaded"] = False
         if low_vram:
-            audio_path = this_dir / "templates" / "lowvramenabled.wav"
+            audio_path = this_dir / "system" / "at_sounds" / "lowvramenabled.wav"
         else:
-            audio_path = this_dir / "templates" / "lowvramdisabled.wav"
+            audio_path = this_dir / "system" / "at_sounds" / "lowvramdisabled.wav"
         url = f"{base_url}/api/lowvramsetting?new_low_vram_value={low_vram}"
         headers = {"Content-Type": "application/json"}
         response = requests.post(url, headers=headers)
@@ -350,10 +414,10 @@ def send_deepspeed_request(deepspeed_param):
     try:
         params["tts_model_loaded"] = False
         if deepspeed_param:
-            audio_path = this_dir / "templates" / "deepspeedenabled.wav"
+            audio_path = this_dir / "system" / "at_sounds" / "deepspeedenabled.wav"
         else:
-            audio_path = this_dir / "templates" / "deepspeeddisabled.wav"
-        
+            audio_path = this_dir / "system" / "at_sounds" / "deepspeeddisabled.wav"
+
         url = f"{base_url}/api/deepspeed?new_deepspeed_value={deepspeed_param}"
         headers = {"Content-Type": "application/json"}
         response = requests.post(url, headers=headers)
@@ -427,9 +491,13 @@ def combine(audio_files, output_folder, state):
 
     # Save the combined audio to a file with a specified sample rate
     if "character_menu" in state:
-        output_file_path = os.path.join(output_folder, f'{state["character_menu"]}_{int(time.time())}_combined.wav')
+        output_file_path = os.path.join(
+            output_folder, f'{state["character_menu"]}_{int(time.time())}_combined.wav'
+        )
     else:
-        output_file_path = os.path.join(output_folder, f'TTSOUT_{int(time.time())}_combined.wav')
+        output_file_path = os.path.join(
+            output_folder, f"TTSOUT_{int(time.time())}_combined.wav"
+        )
     sf.write(output_file_path, audio, samplerate=sample_rate)
     # Clean up unnecessary files
     for audio_file in audio_files:
@@ -443,7 +511,7 @@ def combine(audio_files, output_folder, state):
 ################################
 # PREVIEW VOICE - Generate Random Sentence if Voice Preview box is empty
 def random_sentence():
-    with open(this_dir / "harvard_sentences.txt") as f:
+    with open(this_dir / "system" / "config" / "harvard_sentences.txt") as f:
         return random.choice(list(f))
 
 
@@ -460,12 +528,19 @@ def voice_preview(string):
     output_file = Path(params["output_folder_wav"]) / "voice_preview.wav"
     # Generate the audio
     language_code = languages.get(params["language"])
+    temperature = params["local_temperature"]
+    repetition_penalty = params["local_repetition_penalty"]
     # Convert the WindowsPath object to a string before using it in JSON payload
     output_file_str = output_file.as_posix()
     # Lock before making the generate request
     with process_lock:
         generate_response = send_generate_request(
-            string, params["voice"], language_code, output_file_str
+            string,
+            params["voice"],
+            language_code,
+            temperature,
+            repetition_penalty,
+            output_file_str,
         )
     # Check if lock is already acquired
     if process_lock.locked():
@@ -482,6 +557,83 @@ def voice_preview(string):
         return f"[{params['branding']}Server] Audio generation failed. Status: {generate_response.get('status')}"
 
 
+#######################
+#### TEXT CLEANING ####
+#######################
+
+def process_text(text):
+    # Normalize HTML encoded quotes
+    text = html.unescape(text)
+
+    # Replace ellipsis with a single dot
+    text = re.sub(r"\.{3,}", ".", text)
+
+    # Pattern to identify combined narrator and character speech
+    combined_pattern = r'(\*[^*"]+\*|"[^"*]+")'
+
+    # List to hold parts of speech along with their type
+    ordered_parts = []
+
+    # Track the start of the next segment
+    start = 0
+
+    # Find all matches
+    for match in re.finditer(combined_pattern, text):
+        # Add the text before the match, if any, as ambiguous
+        if start < match.start():
+            ambiguous_text = text[start : match.start()].strip()
+            if ambiguous_text:
+                ordered_parts.append(("ambiguous", ambiguous_text))
+
+        # Add the matched part as either narrator or character
+        matched_text = match.group(0)
+        if matched_text.startswith("*") and matched_text.endswith("*"):
+            ordered_parts.append(("narrator", matched_text.strip("*").strip()))
+        elif matched_text.startswith('"') and matched_text.endswith('"'):
+            ordered_parts.append(("character", matched_text.strip('"').strip()))
+        else:
+            # In case of mixed or improperly formatted parts
+            if "*" in matched_text:
+                ordered_parts.append(("narrator", matched_text.strip("*").strip('"')))
+            else:
+                ordered_parts.append(("character", matched_text.strip('"').strip("*")))
+
+        # Update the start of the next segment
+        start = match.end()
+
+    # Add any remaining text after the last match as ambiguous
+    if start < len(text):
+        ambiguous_text = text[start:].strip()
+        if ambiguous_text:
+            ordered_parts.append(("ambiguous", ambiguous_text))
+
+    return ordered_parts
+
+
+########################
+#### IMAGE CLEANING ####
+########################
+
+img_pattern = r'<img[^>]*src\s*=\s*["\'][^"\'>]+["\'][^>]*>'
+
+def extract_and_remove_images(text):
+    """
+    Extracts all image data from the text and removes it for clean TTS processing.
+    Returns the cleaned text and the extracted image data.
+    """
+    img_matches = re.findall(img_pattern, text)
+    img_info = "\n".join(img_matches)  # Store extracted image data
+    cleaned_text = re.sub(img_pattern, '', text)  # Remove images from text
+    return cleaned_text, img_info
+
+def reinsert_images(text, img_info):
+    """
+    Reinserts the previously extracted image data back into the text.
+    """
+    if img_info:  # Check if there are images to reinsert
+        text += f"\n\n{img_info}"
+    return text
+
 #################################
 #### TTS STANDARD GENERATION ####
 #################################
@@ -489,105 +641,104 @@ def voice_preview(string):
 def output_modifier(string, state):
     if not params["activate"]:
         return string
-    original_string = string
-    cleaned_string = before_audio_generation(string, params)
+    img_info = ""
+    cleaned_text, img_info = extract_and_remove_images(string)
+    # print("Cleaned STRING IS:", cleaned_text)
+    cleaned_string = before_audio_generation(cleaned_text, params)
     if cleaned_string is None:
         return
-    string = cleaned_string
     language_code = languages.get(params["language"])
+    temperature = params["local_temperature"]
+    repetition_penalty = params["local_repetition_penalty"]
     # Create a list to store generated audio paths
     audio_files = []
     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")
-                )
-                # Clean up two asterisks (narrators) being made between a newline, making it one sentence.
-                processed_string = re.sub(r'\.\*\n\*', '. ', processed_string)
-                # Clean up a few other bits.
-                processed_string = (
-                    processed_string
-                    .replace("&#x27;", "'")
-                    .replace("\n", " ")
-                    # Add special characters to the quote so that we can use it to identify things later after its been split
-                    .replace('&quot;', '&quot;<')
-                    # Capture new conversations which wont have things like &quote in them
-                    .replace('"', '&quot;<')
-                )
-                #capturing another outlier in inital character paragraph
-                # print("processed string 1 is:", processed_string)
-                processed_string = processed_string.replace('&quot;<. *', '&quot;< *"')
-                processed_string = processed_string.replace('< *"', '< *')
-                processed_string = processed_string.replace('. *', '< *')
-                # print("processed string 2 is:", processed_string)
-                # Set up a tracking of the individual wav files.
+                processed_parts = process_text(cleaned_string)
+
                 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 *
-                parts = re.split(r'&quot;|\.\*', processed_string)
-                audio_files_paragraph = []
-                for i, part in enumerate(parts):
+                for part_type, part in processed_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
-                    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 = params["voice"]
-                    #Narrator will always be an * or < with an * a position or two after it.
-                    elif '<*' in part or '< *' in part or '<  *' in part or '*' in part:
-                        cleaned_part = html.unescape(part.replace('<*', '').replace('< *', '').replace('<  *', '').replace('*', ''))
+
+                    # Determine the voice to use based on the part type
+                    if part_type == "narrator":
                         voice_to_use = params["narrator_voice"]
-                    #If the other two dont capture it, aka, the AI gave no * or &quot; on the line, use non_quoted_text_is aka user interface, user can choose Char or Narrator
-                    elif non_quoted_text_is:
-                        cleaned_part = html.unescape(part.replace('< ', '').replace('<  ', '').replace('<  ', ''))
+                        print(
+                            f"[{params['branding']}TTSGen] \033[92mNarrator\033[0m"
+                        )  # Green
+                    elif part_type == "character":
                         voice_to_use = params["voice"]
+                        print(
+                            f"[{params['branding']}TTSGen] \033[36mCharacter\033[0m"
+                        )  # Yellow
                     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()
+                        # Handle ambiguous parts based on user preference
+                        voice_to_use = (
+                            params["voice"]
+                            if non_quoted_text_is
+                            else params["narrator_voice"]
+                        )
+                        voice_description = (
+                            "\033[36mCharacter (Text-not-inside)\033[0m"
+                            if non_quoted_text_is
+                            else "\033[92mNarrator (Text-not-inside)\033[0m"
+                        )
+                        print(f"[{params['branding']}TTSGen] {voice_description}")
+
+                    # Replace multiple exclamation marks, question marks, or other punctuation with a single instance
+                    cleaned_part = re.sub(r"([!?.])\1+", r"\1", part)
+                    # Further clean to remove any other unwanted characters
+                    cleaned_part = re.sub(r'[^a-zA-Z0-9\s\.,;:!?\-\'"\u0100-\u017F\u0400-\u04FFÀ-ÿ\u0150\u0151\u0170\u0171\u4E00-\u9FFF\u3400-\u4DBF\u20000-\u2A6DF\u3000-\u303F\$]', '', cleaned_part)
+                    # Remove all newline characters (single or multiple)
+                    cleaned_part = re.sub(r"\n+", " ", cleaned_part)
+
+                    # Generate TTS and output to a file
+                    output_filename = get_output_filename(state)
                     generate_response = send_generate_request(
-                        cleaned_part, voice_to_use, language_code, output_file_str
+                        cleaned_part,
+                        voice_to_use,
+                        language_code,
+                        temperature,
+                        repetition_penalty,
+                        output_filename,
                     )
                     audio_path = generate_response.get("data", {}).get("audio_path")
-                    audio_files_paragraph.append(audio_path)
-                # Accumulate audio files within the paragraph
-                audio_files_all_paragraphs.extend(audio_files_paragraph)
+                    audio_files_all_paragraphs.append(audio_path)
+
                 # Combine audio files across paragraphs
                 final_output_file = combine(
                     audio_files_all_paragraphs, params["output_folder_wav"], state
                 )
             else:
-                processed_string = (
-                    original_string
-                    .replace("***", "")
-                    .replace("**", "")
-                    .replace("*", "")
-                    .replace("\n\n", "\n")
-                    .replace("&#x27;", "'")
-                )
-                cleaned_part = html.unescape(processed_string)                
+                # Decode HTML entities first
+                cleaned_part = html.unescape(cleaned_string)
+                # Replace multiple instances of certain punctuation marks with a single instance
+                cleaned_part = re.sub(r"([!?.])\1+", r"\1", cleaned_part)
+                # Further clean to remove any other unwanted characters
+                cleaned_part = re.sub(r'[^a-zA-Z0-9\s\.,;:!?\-\'"\u0100-\u017F\u0400-\u04FFÀ-ÿ\u0150\u0151\u0170\u0171\u4E00-\u9FFF\u3400-\u4DBF\u20000-\u2A6DF\u3000-\u303F\$]', '', cleaned_part)
+                # Remove all newline characters (single or multiple)
+                cleaned_part = re.sub(r"\n+", " ", cleaned_part)
                 # Process the part and give it a non-character name if being used vai API or standalone.
                 if "character_menu" in state:
-                    output_file = Path(f'{params["output_folder_wav"]}/{state["character_menu"]}_{int(time.time())}.wav')
+                    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 = 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_file_str
+                    cleaned_part,
+                    params["voice"],
+                    language_code,
+                    temperature,
+                    repetition_penalty,
+                    output_file_str,
                 )
                 audio_path = generate_response.get("data", {}).get("audio_path")
                 final_output_file = audio_path
@@ -606,41 +757,40 @@ def output_modifier(string, state):
         if audio_path:
             # Handle Gradio and playback
             autoplay = "autoplay" if params["autoplay"] else ""
-            string = (
-                f'<audio src="file/{final_output_file}" controls {autoplay}></audio>'
-            )
-
+            string = (f'<audio src="file/{final_output_file}" controls {autoplay}></audio>')
             if params["show_text"]:
-                string += f"\n\n{original_string}"
+                string += reinsert_images(cleaned_string, img_info)
                 shared.processing_message = "*Is typing...*"
-
             return string
         else:
-            print(
-                f"[{params['branding']}Server] \033[91mWarning\033[0m No audio path in the response."
-            )
+            print(f"[{params['branding']}Server] \033[91mWarning\033[0m No audio path in the response.")
     else:
-        print(
-            f"[{params['branding']}Server] \033[91mWarning\033[0m Audio generation failed. Status:",
-            generate_response.get("message"),
-        )
-
+        print(f"[{params['branding']}Server] \033[91mWarning\033[0m Audio generation failed. Status:", generate_response.get("message"),)
 
 def get_output_filename(state):
-    return Path(
-        f'{params["output_folder_wav"]}/{state["character_menu"]}_{str(uuid.uuid4())[:8]}.wav'
-    ).as_posix()
+    if "character_menu" in state:
+        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_{str(uuid.uuid4())[:8]}.wav'
+        ).as_posix()
 
 
 ###############################################
 #### SEND GENERATION REQUEST TO TTS ENGINE ####
 ###############################################
-def send_generate_request(text, voice, language, output_file):
+def send_generate_request(
+    text, voice, language, temperature, repetition_penalty, output_file
+):
     url = f"{base_url}/api/generate"
     payload = {
         "text": text,
         "voice": voice,
         "language": language,
+        "temperature": temperature,
+        "repetition_penalty": repetition_penalty,
         "output_file": output_file,
     }
     headers = {"Content-Type": "application/json"}
@@ -665,12 +815,14 @@ def state_modifier(state):
     state["stream"] = False
     return state
 
+
 def update_narrator_enabled(value):
     if value == "Enabled":
         params["narrator_enabled"] = True
     elif value == "Disabled":
         params["narrator_enabled"] = False
 
+
 def update_non_quoted_text_is(value):
     global non_quoted_text_is
     if value == "Narrator":
@@ -678,6 +830,7 @@ def update_non_quoted_text_is(value):
     elif value == "Char":
         non_quoted_text_is = True
 
+
 def input_modifier(string, state):
     if not params["activate"]:
         return string
@@ -685,42 +838,56 @@ def input_modifier(string, state):
     shared.processing_message = "*Is recording a voice message...*"
     return string
 
-def custom_css():
-    path_to_css = Path(f"{this_dir}/style.css")
-    return open(path_to_css, "r").read()
-
 
 def ui():
     with gr.Accordion(params["branding"] + " TTS (XTTSv2)"):
+        # Activate alltalk_tts, Enable autoplay, Show text
         with gr.Row():
-            activate = gr.Checkbox(value=params["activate"], label="Activate TTS")
-            autoplay = gr.Checkbox(
-                value=params["autoplay"], label="Play TTS automatically"
-            )
+            activate = gr.Checkbox(value=params["activate"], label="Enable TTS")
+            autoplay = gr.Checkbox(value=params["autoplay"], label="Autoplay TTS")
+            show_text = gr.Checkbox(value=params["show_text"], label="Show Text")
 
+        # Low vram enable, Deepspeed enable, Remove trailing dots
         with gr.Row():
-            show_text = gr.Checkbox(
-                value=params["show_text"], label="Show message text under audio player"
+            low_vram = gr.Checkbox(
+                value=params["low_vram"], label="Enable Low VRAM Mode"
             )
+            low_vram_play = gr.HTML(visible=False)
+            deepspeed_checkbox = gr.Checkbox(
+                value=params["deepspeed_activate"],
+                label="Enable DeepSpeed",
+                visible=deepspeed_installed,
+            )
+            deepspeed_checkbox_play = gr.HTML(visible=False)
             remove_trailing_dots = gr.Checkbox(
-                value=params["remove_trailing_dots"],
-                label='Remove trailing "." from text segments before generation',
+                value=params["remove_trailing_dots"], label='Remove trailing "."'
             )
 
+        # TTS method, Character voice selection
         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=model_loader_choices,
+                label="TTS Method (Each method sounds slightly different)",
+                value=gr_modelchoice,  # Set the default value
+            )
+            tts_radio_buttons_play = gr.HTML(visible=False)
             with gr.Row():
                 available_voices = get_available_voices()
-                default_voice = params["voice"]
-                # Check if the default voice is in the list of available voices
+                default_voice = params[
+                    "voice"
+                ]  # Check if the default voice is in the list of available voices
+
                 if default_voice not in available_voices:
-                    # Handle the case where the default voice is not in the list (choose a default value or update it)
                     default_voice = available_voices[
                         0
                     ]  # Choose the first available voice as the default
                 # Add allow_custom_value=True to the Dropdown
                 voice = gr.Dropdown(
                     available_voices,
-                    label="Default Voice",
+                    label="Character Voice",
                     value=default_voice,
                     allow_custom_value=True,
                 )
@@ -734,14 +901,11 @@ def ui():
                     "refresh-button",
                 )
 
-            language = gr.Dropdown(
-                languages.keys(),
-                label="Language",
-                allow_custom_value=True,
-                value=params["language"],
-            )
-
+        # Language, Narrator voice
         with gr.Row():
+            language = gr.Dropdown(
+                languages.keys(), label="Language", value=params["language"]
+            )
             with gr.Row():
                 narrator_voice_gr = gr.Dropdown(
                     get_available_voices(),
@@ -758,40 +922,42 @@ def ui():
                     },
                     "refresh-button",
                 )
+
+        # Temperature, Repetition Penalty
+        with gr.Row():
+            local_temperature_gr = gr.Slider(
+                minimum=0.05,
+                maximum=1,
+                step=0.05,
+                label="Temperature",
+                value=params["local_temperature"],
+            )
+            local_repetition_penalty_gr = gr.Slider(
+                minimum=0.5,
+                maximum=20,
+                step=0.5,
+                label="Repetition Penalty",
+                value=params["local_repetition_penalty"],
+            )
+
+        # Narrator enable, Non quoted text, Explanation text
+        with gr.Row():
+            with gr.Row():
                 narrator_enabled_gr = gr.Radio(
                     choices={"Enabled": "true", "Disabled": "false"},
-                    label="Narrator Activation",
+                    label="Narrator",
                     value="Enabled" if params.get("narrator_enabled") else "Disabled",
                 )
                 non_quoted_text_is_gr = gr.Radio(
-                    choices={"Char": "true", "Narrator": "false"},
-                    label='Text NOT inside of * or " is',
-                    value="Char" if non_quoted_text_is else "Narrator",
+                    choices={"Character": "true", "Narrator": "false"},
+                    label='Unmarked text NOT inside of * or " is',
+                    value="Character" if non_quoted_text_is else "Narrator",
+                )
+                explanation_text = gr.HTML(
+                    f"<p>⚙️ <a href='http://{params['ip_address']}:{params['port_number']}'>Settings and Documentation Page</a><a href='http://{params['ip_address']}:{params['port_number']}'></a>⚙️<br>- Low VRAM Mode and Deepspeed take 15 seconds to be enabled or disabled.<br>- The DeepSpeed checkbox is only visible if DeepSpeed is present.</p>"
                 )
 
-        with gr.Row():
-            low_vram = gr.Checkbox(
-                value=params["low_vram"], label="Low VRAM mode (Read NOTE)"
-            )
-            low_vram_play = gr.HTML(visible=False)
-            deepspeed_checkbox = gr.Checkbox(
-                value=params["deepspeed_activate"],
-                label="Activate DeepSpeed (Read NOTE)",
-                visible=deepspeed_installed,
-            )
-            deepspeed_checkbox_play = gr.HTML(visible=False)
-
-        with gr.Row():
-            tts_radio_buttons = gr.Radio(
-                choices=["API TTS", "API Local", "XTTSv2 Local"],
-                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>"
-            )
-
+        # Preview speech
         with gr.Row():
             preview_text = gr.Text(
                 show_label=False,
@@ -861,18 +1027,34 @@ def ui():
     autoplay.change(lambda x: params.update({"autoplay": x}), autoplay, None)
     low_vram.change(lambda x: params.update({"low_vram": x}), low_vram, None)
     low_vram.change(lambda x: send_lowvram_request(x), low_vram, low_vram_play, None)
-    tts_radio_buttons.change(send_reload_request, tts_radio_buttons, tts_radio_buttons_play, None)
-    deepspeed_checkbox.change(send_deepspeed_request, deepspeed_checkbox, deepspeed_checkbox_play, None)
+    tts_radio_buttons.change(
+        send_reload_request, tts_radio_buttons, tts_radio_buttons_play, None
+    )
+    deepspeed_checkbox.change(
+        send_deepspeed_request, deepspeed_checkbox, deepspeed_checkbox_play, None
+    )
     remove_trailing_dots.change(
         lambda x: params.update({"remove_trailing_dots": x}), remove_trailing_dots, None
     )
     voice.change(lambda x: params.update({"voice": x}), voice, None)
     language.change(lambda x: params.update({"language": x}), language, None)
 
+    # TSS Settings
+    local_temperature_gr.change(
+        lambda x: params.update({"local_temperature": x}), local_temperature_gr, None
+    )
+    local_repetition_penalty_gr.change(
+        lambda x: params.update({"local_repetition_penalty": x}),
+        local_repetition_penalty_gr,
+        None,
+    )
+
     # Narrator selection actions
     narrator_enabled_gr.change(update_narrator_enabled, narrator_enabled_gr, None)
     non_quoted_text_is_gr.change(update_non_quoted_text_is, non_quoted_text_is_gr, None)
-    narrator_voice_gr.change(lambda x: params.update({"narrator_voice": x}), narrator_voice_gr, None)
+    narrator_voice_gr.change(
+        lambda x: params.update({"narrator_voice": x}), narrator_voice_gr, None
+    )
 
     # Play preview
     preview_text.submit(voice_preview, preview_text, preview_audio)
@@ -888,4 +1070,4 @@ if running_in_standalone:
         try:
             time.sleep(1)  # Add a small delay to avoid high CPU usage
         except KeyboardInterrupt:
-            break  # Allow graceful exit on Ctrl+C
+            break  # Allow graceful exit on Ctrl+C

style.css

@@ -1,8 +0,0 @@
-.SDAP .hires_opts input[type="number"] {
-    width: 6em !important;
-}
-
-/* silero_tts preview */
-.form:has(> #silero_preview_text) {
-    min-width: 75%
-}

system/at_admin/at_settings.html

@@ -89,25 +89,25 @@
     <h3>AllTalk Startup Settings</h3><br>
     <form action="/update-settings" method="post">
 
-        <label for="activate" style="color: #33cc33;">Activate TTS:</label>
+        <label for="activate" style="color: #b273fa;">TG-webui Activate TTS:</label>
         <select id="activate" name="activate" required="">
             <option {% if data.activate %}selected{% endif %} value="true">True</option>
             <option {% if not data.activate %}selected{% endif %} value="false">False</option>
         </select>
 
-        <label for="autoplay" style="color: #33cc33;">&nbsp; &nbsp; Autoplay TTS output:</label>
+        <label for="autoplay" style="color: #b273fa;">&nbsp; &nbsp; TG-webui Autoplay TTS:</label>
         <select id="autoplay" name="autoplay" required="">
             <option {% if data.autoplay %}selected{% endif %} value="true">True</option>
             <option {% if not data.autoplay %}selected{% endif %} value="false">False</option>
         </select>
 
-        <label for="show_text" style="color: #33cc33;"> Show Text on generation:</label>
+        <label for="show_text" style="color: #b273fa;">TG-webui Show Text:</label>
         <select id="show_text" name="show_text" required="">
             <option {% if data.show_text %}selected{% endif %} value="true">True</option>
             <option {% if not data.show_text %}selected{% endif %} value="false">False</option>
         </select>
 
-        <label for="voice" style="color: #33cc33;">&nbsp; &nbsp; Default voice:</label>
+        <label for="voice" style="color: #b273fa;">&nbsp; &nbsp;  TG-webui Default voice:</label>
         <select id="voice" name="voice" required="">
             {% for file in wav_files %}
             <option value="{{ file }}" {% if data.voice==file %}selected{% endif %}>{{ file }}</option>
@@ -115,7 +115,7 @@
         </select>
 
 
-        <label for="language" style="color: #33cc33;">Default Language:</label>
+        <label for="language" style="color: #b273fa;">TG-webui Default Language:</label>
         <select id="language" name="language" required="">
             <option value="Arabic" {% if data.language=='Arabic' %}selected{% endif %}>Arabic</option>
             <option value="Chinese" {% if data.language=='Chinese' %}selected{% endif %}>Chinese</option>
@@ -135,20 +135,20 @@
             <option value="Turkish" {% if data.language=='Turkish' %}selected{% endif %}>Turkish</option>
         </select>
 
-        <label for="narrator_voice" style="color: #33cc33;">&nbsp; &nbsp; Narrator voice:</label>
+        <label for="narrator_voice" style="color: #b273fa;">&nbsp; &nbsp; TG-webui Narrator voice:</label>
         <select id="narrator_voice" name="narrator_voice" required="">
             {% for file in wav_files %}
             <option value="{{ file }}" {% if data.narrator_voice==file %}selected{% endif %}>{{ file }}</option>
             {% endfor %}
         </select>
 
-        <label for="remove_trailing_dots" style="color: #33cc33;"> Remove Trailing Dots:</label>
+        <label for="remove_trailing_dots" style="color: #b273fa;">TG-webui Remove Trailing Dots:</label>
         <select id="remove_trailing_dots" name="remove_trailing_dots" required="">
             <option {% if data.remove_trailing_dots %}selected{% endif %} value="true">True</option>
             <option {% if not data.remove_trailing_dots %}selected{% endif %} value="false">False</option>
         </select>
 
-        <label for="narrator_enabled" style="color: #33cc33;">&nbsp; &nbsp; Narrator enabled:</label>
+        <label for="narrator_enabled" style="color: #b273fa;">&nbsp; &nbsp; TG-webui Narrator enabled:</label>
         <select id="narrator_enabled" name="narrator_enabled" required="">
             <option {% if data.narrator_enabled %}selected{% endif %} value="true">True</option>
             <option {% if not data.narrator_enabled %}selected{% endif %} value="false">False</option>

system/ft_tokenizer/tokenizer.py

@@ -0,0 +1,869 @@
+import os
+import re
+import textwrap
+from functools import cached_property
+
+import pypinyin
+import torch
+from hangul_romanize import Transliter
+from hangul_romanize.rule import academic
+from num2words import num2words
+from spacy.lang.ar import Arabic
+from spacy.lang.en import English
+from spacy.lang.es import Spanish
+from spacy.lang.ja import Japanese
+from spacy.lang.zh import Chinese
+from tokenizers import Tokenizer
+
+from TTS.tts.layers.xtts.zh_num2words import TextNorm as zh_num2words
+
+
+def get_spacy_lang(lang):
+    if lang == "zh":
+        return Chinese()
+    elif lang == "ja":
+        return Japanese()
+    elif lang == "ar":
+        return Arabic()
+    elif lang == "es":
+        return Spanish()
+    else:
+        # For most languages, Enlish does the job
+        return English()
+
+
+def split_sentence(text, lang, text_split_length=250):
+    """Preprocess the input text"""
+    text_splits = []
+    if text_split_length is not None and len(text) >= text_split_length:
+        text_splits.append("")
+        nlp = get_spacy_lang(lang)
+        nlp.add_pipe("sentencizer")
+        doc = nlp(text)
+        for sentence in doc.sents:
+            if len(text_splits[-1]) + len(str(sentence)) <= text_split_length:
+                # if the last sentence + the current sentence is less than the text_split_length
+                # then add the current sentence to the last sentence
+                text_splits[-1] += " " + str(sentence)
+                text_splits[-1] = text_splits[-1].lstrip()
+            elif len(str(sentence)) > text_split_length:
+                # if the current sentence is greater than the text_split_length
+                for line in textwrap.wrap(
+                    str(sentence),
+                    width=text_split_length,
+                    drop_whitespace=True,
+                    break_on_hyphens=False,
+                    tabsize=1,
+                ):
+                    text_splits.append(str(line))
+            else:
+                text_splits.append(str(sentence))
+
+        if len(text_splits) > 1:
+            if text_splits[0] == "":
+                del text_splits[0]
+    else:
+        text_splits = [text.lstrip()]
+
+    return text_splits
+
+
+_whitespace_re = re.compile(r"\s+")
+
+# List of (regular expression, replacement) pairs for abbreviations:
+_abbreviations = {
+    "en": [
+        (re.compile("\\b%s\\." % x[0], re.IGNORECASE), x[1])
+        for x in [
+            ("mrs", "misess"),
+            ("mr", "mister"),
+            ("dr", "doctor"),
+            ("st", "saint"),
+            ("co", "company"),
+            ("jr", "junior"),
+            ("maj", "major"),
+            ("gen", "general"),
+            ("drs", "doctors"),
+            ("rev", "reverend"),
+            ("lt", "lieutenant"),
+            ("hon", "honorable"),
+            ("sgt", "sergeant"),
+            ("capt", "captain"),
+            ("esq", "esquire"),
+            ("ltd", "limited"),
+            ("col", "colonel"),
+            ("ft", "fort"),
+        ]
+    ],
+    "es": [
+        (re.compile("\\b%s\\." % x[0], re.IGNORECASE), x[1])
+        for x in [
+            ("sra", "señora"),
+            ("sr", "señor"),
+            ("dr", "doctor"),
+            ("dra", "doctora"),
+            ("st", "santo"),
+            ("co", "compañía"),
+            ("jr", "junior"),
+            ("ltd", "limitada"),
+        ]
+    ],
+    "fr": [
+        (re.compile("\\b%s\\." % x[0], re.IGNORECASE), x[1])
+        for x in [
+            ("mme", "madame"),
+            ("mr", "monsieur"),
+            ("dr", "docteur"),
+            ("st", "saint"),
+            ("co", "compagnie"),
+            ("jr", "junior"),
+            ("ltd", "limitée"),
+        ]
+    ],
+    "de": [
+        (re.compile("\\b%s\\." % x[0], re.IGNORECASE), x[1])
+        for x in [
+            ("fr", "frau"),
+            ("dr", "doktor"),
+            ("st", "sankt"),
+            ("co", "firma"),
+            ("jr", "junior"),
+        ]
+    ],
+    "pt": [
+        (re.compile("\\b%s\\." % x[0], re.IGNORECASE), x[1])
+        for x in [
+            ("sra", "senhora"),
+            ("sr", "senhor"),
+            ("dr", "doutor"),
+            ("dra", "doutora"),
+            ("st", "santo"),
+            ("co", "companhia"),
+            ("jr", "júnior"),
+            ("ltd", "limitada"),
+        ]
+    ],
+    "it": [
+        (re.compile("\\b%s\\." % x[0], re.IGNORECASE), x[1])
+        for x in [
+            # ("sig.ra", "signora"),
+            ("sig", "signore"),
+            ("dr", "dottore"),
+            ("st", "santo"),
+            ("co", "compagnia"),
+            ("jr", "junior"),
+            ("ltd", "limitata"),
+        ]
+    ],
+    "pl": [
+        (re.compile("\\b%s\\." % x[0], re.IGNORECASE), x[1])
+        for x in [
+            ("p", "pani"),
+            ("m", "pan"),
+            ("dr", "doktor"),
+            ("sw", "święty"),
+            ("jr", "junior"),
+        ]
+    ],
+    "ar": [
+        (re.compile("\\b%s\\." % x[0], re.IGNORECASE), x[1])
+        for x in [
+            # There are not many common abbreviations in Arabic as in English.
+        ]
+    ],
+    "zh": [
+        (re.compile("\\b%s\\." % x[0], re.IGNORECASE), x[1])
+        for x in [
+            # Chinese doesn't typically use abbreviations in the same way as Latin-based scripts.
+        ]
+    ],
+    "cs": [
+        (re.compile("\\b%s\\." % x[0], re.IGNORECASE), x[1])
+        for x in [
+            ("dr", "doktor"),  # doctor
+            ("ing", "inženýr"),  # engineer
+            ("p", "pan"),  # Could also map to pani for woman but no easy way to do it
+            # Other abbreviations would be specialized and not as common.
+        ]
+    ],
+    "ru": [
+        (re.compile("\\b%s\\b" % x[0], re.IGNORECASE), x[1])
+        for x in [
+            ("г-жа", "госпожа"),  # Mrs.
+            ("г-н", "господин"),  # Mr.
+            ("д-р", "доктор"),  # doctor
+            # Other abbreviations are less common or specialized.
+        ]
+    ],
+    "nl": [
+        (re.compile("\\b%s\\." % x[0], re.IGNORECASE), x[1])
+        for x in [
+            ("dhr", "de heer"),  # Mr.
+            ("mevr", "mevrouw"),  # Mrs.
+            ("dr", "dokter"),  # doctor
+            ("jhr", "jonkheer"),  # young lord or nobleman
+            # Dutch uses more abbreviations, but these are the most common ones.
+        ]
+    ],
+    "tr": [
+        (re.compile("\\b%s\\." % x[0], re.IGNORECASE), x[1])
+        for x in [
+            ("b", "bay"),  # Mr.
+            ("byk", "büyük"),  # büyük
+            ("dr", "doktor"),  # doctor
+            # Add other Turkish abbreviations here if needed.
+        ]
+    ],
+    "hu": [
+        (re.compile("\\b%s\\." % x[0], re.IGNORECASE), x[1])
+        for x in [
+            ("dr", "doktor"),  # doctor
+            ("b", "bácsi"),  # Mr.
+            ("nőv", "nővér"),  # nurse
+            # Add other Hungarian abbreviations here if needed.
+        ]
+    ],
+    "ko": [
+        (re.compile("\\b%s\\." % x[0], re.IGNORECASE), x[1])
+        for x in [
+            # Korean doesn't typically use abbreviations in the same way as Latin-based scripts.
+        ]
+    ],
+    "ja": [
+        (re.compile("\\b%s\\b" % x[0]), x[1])
+        for x in [
+            ("氏", "さん"),  # Mr.
+            ("夫人", "おんなのひと"),  # Mrs.
+            ("博士", "はかせ"),  # Doctor or PhD
+            ("株", "株式会社"),  # Corporation
+            ("有", "有限会社"),  # Limited company
+            ("大学", "だいがく"),   # University
+            ("先生", "せんせい"),   # Teacher/Professor/Master
+            ("君", "くん")   # Used at the end of boys' names to express familiarity or affection.
+        ]
+    ],
+}
+
+
+def expand_abbreviations_multilingual(text, lang="en"):
+    for regex, replacement in _abbreviations[lang]:
+        text = re.sub(regex, replacement, text)
+    return text
+
+
+_symbols_multilingual = {
+    "en": [
+        (re.compile(r"%s" % re.escape(x[0]), re.IGNORECASE), x[1])
+        for x in [
+            ("&", " and "),
+            ("@", " at "),
+            ("%", " percent "),
+            ("#", " hash "),
+            ("$", " dollar "),
+            ("£", " pound "),
+            ("°", " degree "),
+        ]
+    ],
+    "es": [
+        (re.compile(r"%s" % re.escape(x[0]), re.IGNORECASE), x[1])
+        for x in [
+            ("&", " y "),
+            ("@", " arroba "),
+            ("%", " por ciento "),
+            ("#", " numeral "),
+            ("$", " dolar "),
+            ("£", " libra "),
+            ("°", " grados "),
+        ]
+    ],
+    "fr": [
+        (re.compile(r"%s" % re.escape(x[0]), re.IGNORECASE), x[1])
+        for x in [
+            ("&", " et "),
+            ("@", " arobase "),
+            ("%", " pour cent "),
+            ("#", " dièse "),
+            ("$", " dollar "),
+            ("£", " livre "),
+            ("°", " degrés "),
+        ]
+    ],
+    "de": [
+        (re.compile(r"%s" % re.escape(x[0]), re.IGNORECASE), x[1])
+        for x in [
+            ("&", " und "),
+            ("@", " at "),
+            ("%", " prozent "),
+            ("#", " raute "),
+            ("$", " dollar "),
+            ("£", " pfund "),
+            ("°", " grad "),
+        ]
+    ],
+    "pt": [
+        (re.compile(r"%s" % re.escape(x[0]), re.IGNORECASE), x[1])
+        for x in [
+            ("&", " e "),
+            ("@", " arroba "),
+            ("%", " por cento "),
+            ("#", " cardinal "),
+            ("$", " dólar "),
+            ("£", " libra "),
+            ("°", " graus "),
+        ]
+    ],
+    "it": [
+        (re.compile(r"%s" % re.escape(x[0]), re.IGNORECASE), x[1])
+        for x in [
+            ("&", " e "),
+            ("@", " chiocciola "),
+            ("%", " per cento "),
+            ("#", " cancelletto "),
+            ("$", " dollaro "),
+            ("£", " sterlina "),
+            ("°", " gradi "),
+        ]
+    ],
+    "pl": [
+        (re.compile(r"%s" % re.escape(x[0]), re.IGNORECASE), x[1])
+        for x in [
+            ("&", " i "),
+            ("@", " małpa "),
+            ("%", " procent "),
+            ("#", " krzyżyk "),
+            ("$", " dolar "),
+            ("£", " funt "),
+            ("°", " stopnie "),
+        ]
+    ],
+    "ar": [
+        # Arabic
+        (re.compile(r"%s" % re.escape(x[0]), re.IGNORECASE), x[1])
+        for x in [
+            ("&", " و "),
+            ("@", " على "),
+            ("%", " في المئة "),
+            ("#", " رقم "),
+            ("$", " دولار "),
+            ("£", " جنيه "),
+            ("°", " درجة "),
+        ]
+    ],
+    "zh": [
+        # Chinese
+        (re.compile(r"%s" % re.escape(x[0]), re.IGNORECASE), x[1])
+        for x in [
+            ("&", " 和 "),
+            ("@", " 在 "),
+            ("%", " 百分之 "),
+            ("#", " 号 "),
+            ("$", " 美元 "),
+            ("£", " 英镑 "),
+            ("°", " 度 "),
+        ]
+    ],
+    "cs": [
+        # Czech
+        (re.compile(r"%s" % re.escape(x[0]), re.IGNORECASE), x[1])
+        for x in [
+            ("&", " a "),
+            ("@", " na "),
+            ("%", " procento "),
+            ("#", " křížek "),
+            ("$", " dolar "),
+            ("£", " libra "),
+            ("°", " stupně "),
+        ]
+    ],
+    "ru": [
+        # Russian
+        (re.compile(r"%s" % re.escape(x[0]), re.IGNORECASE), x[1])
+        for x in [
+            ("&", " и "),
+            ("@", " собака "),
+            ("%", " процентов "),
+            ("#", " номер "),
+            ("$", " доллар "),
+            ("£", " фунт "),
+            ("°", " градус "),
+        ]
+    ],
+    "nl": [
+        # Dutch
+        (re.compile(r"%s" % re.escape(x[0]), re.IGNORECASE), x[1])
+        for x in [
+            ("&", " en "),
+            ("@", " bij "),
+            ("%", " procent "),
+            ("#", " hekje "),
+            ("$", " dollar "),
+            ("£", " pond "),
+            ("°", " graden "),
+        ]
+    ],
+    "tr": [
+        (re.compile(r"%s" % re.escape(x[0]), re.IGNORECASE), x[1])
+        for x in [
+            ("&", " ve "),
+            ("@", " at "),
+            ("%", " yüzde "),
+            ("#", " diyez "),
+            ("$", " dolar "),
+            ("£", " sterlin "),
+            ("°", " derece "),
+        ]
+    ],
+    "hu": [
+        (re.compile(r"%s" % re.escape(x[0]), re.IGNORECASE), x[1])
+        for x in [
+            ("&", " és "),
+            ("@", " kukac "),
+            ("%", " százalék "),
+            ("#", " kettőskereszt "),
+            ("$", " dollár "),
+            ("£", " font "),
+            ("°", " fok "),
+        ]
+    ],
+    "ko": [
+        # Korean
+        (re.compile(r"%s" % re.escape(x[0]), re.IGNORECASE), x[1])
+        for x in [
+            ("&", " 그리고 "),
+            ("@", " 에 "),
+            ("%", " 퍼센트 "),
+            ("#", " 번호 "),
+            ("$", " 달러 "),
+            ("£", " 파운드 "),
+            ("°", " 도 "),
+        ]
+    ],
+    "ja": [
+        (re.compile(r"%s" % re.escape(x[0])), x[1])
+        for x in [
+            ("&", " と "),
+            ("@", " アットマーク "),
+            ("%", " パーセント "),
+            ("#", " ナンバー "),
+            ("$", " ドル "),
+            ("£", " ポンド "),
+            ("°", " 度"),
+            ]
+    ],
+}
+
+
+def expand_symbols_multilingual(text, lang="en"):
+    for regex, replacement in _symbols_multilingual[lang]:
+        text = re.sub(regex, replacement, text)
+        text = text.replace("  ", " ")  # Ensure there are no double spaces
+    return text.strip()
+
+
+_ordinal_re = {
+    "en": re.compile(r"([0-9]+)(st|nd|rd|th)"),
+    "es": re.compile(r"([0-9]+)(º|ª|er|o|a|os|as)"),
+    "fr": re.compile(r"([0-9]+)(º|ª|er|re|e|ème)"),
+    "de": re.compile(r"([0-9]+)(st|nd|rd|th|º|ª|\.(?=\s|$))"),
+    "pt": re.compile(r"([0-9]+)(º|ª|o|a|os|as)"),
+    "it": re.compile(r"([0-9]+)(º|°|ª|o|a|i|e)"),
+    "pl": re.compile(r"([0-9]+)(º|ª|st|nd|rd|th)"),
+    "ar": re.compile(r"([0-9]+)(ون|ين|ث|ر|ى)"),
+    "cs": re.compile(r"([0-9]+)\.(?=\s|$)"),  # In Czech, a dot is often used after the number to indicate ordinals.
+    "ru": re.compile(r"([0-9]+)(-й|-я|-е|-ое|-ье|-го)"),
+    "nl": re.compile(r"([0-9]+)(de|ste|e)"),
+    "tr": re.compile(r"([0-9]+)(\.|inci|nci|uncu|üncü|\.)"),
+    "hu": re.compile(r"([0-9]+)(\.|adik|edik|odik|edik|ödik|ödike|ik)"),
+    "ko": re.compile(r"([0-9]+)(번째|번|차|째)"),
+    "ja": re.compile(r"([0-9]+)(番|回|つ|目|等|位)")
+}
+_number_re = re.compile(r"[0-9]+")
+_currency_re = {
+    "USD": re.compile(r"((\$[0-9\.\,]*[0-9]+)|([0-9\.\,]*[0-9]+\$))"),
+    "GBP": re.compile(r"((£[0-9\.\,]*[0-9]+)|([0-9\.\,]*[0-9]+£))"),
+    "EUR": re.compile(r"(([0-9\.\,]*[0-9]+€)|((€[0-9\.\,]*[0-9]+)))"),
+}
+
+_comma_number_re = re.compile(r"\b\d{1,3}(,\d{3})*(\.\d+)?\b")
+_dot_number_re = re.compile(r"\b\d{1,3}(.\d{3})*(\,\d+)?\b")
+_decimal_number_re = re.compile(r"([0-9]+[.,][0-9]+)")
+
+
+def _remove_commas(m):
+    text = m.group(0)
+    if "," in text:
+        text = text.replace(",", "")
+    return text
+
+
+def _remove_dots(m):
+    text = m.group(0)
+    if "." in text:
+        text = text.replace(".", "")
+    return text
+
+
+def _expand_decimal_point(m, lang="en"):
+    amount = m.group(1).replace(",", ".")
+    return num2words(float(amount), lang=lang if lang != "cs" else "cz")
+
+
+def _expand_currency(m, lang="en", currency="USD"):
+    amount = float((re.sub(r"[^\d.]", "", m.group(0).replace(",", "."))))
+    full_amount = num2words(amount, to="currency", currency=currency, lang=lang if lang != "cs" else "cz")
+
+    and_equivalents = {
+        "en": ", ",
+        "es": " con ",
+        "fr": " et ",
+        "de": " und ",
+        "pt": " e ",
+        "it": " e ",
+        "pl": ", ",
+        "cs": ", ",
+        "ru": ", ",
+        "nl": ", ",
+        "ar": ", ",
+        "tr": ", ",
+        "hu": ", ",
+        "ko": ", ",
+    }
+
+    if amount.is_integer():
+        last_and = full_amount.rfind(and_equivalents[lang])
+        if last_and != -1:
+            full_amount = full_amount[:last_and]
+
+    return full_amount
+
+
+def _expand_ordinal(m, lang="en"):
+    return num2words(int(m.group(1)), ordinal=True, lang=lang if lang != "cs" else "cz")
+
+
+def _expand_number(m, lang="en"):
+    return num2words(int(m.group(0)), lang=lang if lang != "cs" else "cz")
+
+
+def expand_numbers_multilingual(text, lang="en"):
+    if lang == "zh":
+        text = zh_num2words()(text)
+    else:
+        if lang in ["en", "ru"]:
+            text = re.sub(_comma_number_re, _remove_commas, text)
+        else:
+            text = re.sub(_dot_number_re, _remove_dots, text)
+        try:
+            text = re.sub(_currency_re["GBP"], lambda m: _expand_currency(m, lang, "GBP"), text)
+            text = re.sub(_currency_re["USD"], lambda m: _expand_currency(m, lang, "USD"), text)
+            text = re.sub(_currency_re["EUR"], lambda m: _expand_currency(m, lang, "EUR"), text)
+        except:
+            pass
+        if lang != "tr":
+            text = re.sub(_decimal_number_re, lambda m: _expand_decimal_point(m, lang), text)
+        text = re.sub(_ordinal_re[lang], lambda m: _expand_ordinal(m, lang), text)
+        text = re.sub(_number_re, lambda m: _expand_number(m, lang), text)
+    return text
+
+
+def lowercase(text):
+    return text.lower()
+
+
+def collapse_whitespace(text):
+    return re.sub(_whitespace_re, " ", text)
+
+
+def multilingual_cleaners(text, lang):
+    text = text.replace('"', "")
+    if lang == "tr":
+        text = text.replace("İ", "i")
+        text = text.replace("Ö", "ö")
+        text = text.replace("Ü", "ü")
+    text = lowercase(text)
+    text = expand_numbers_multilingual(text, lang)
+    text = expand_abbreviations_multilingual(text, lang)
+    text = expand_symbols_multilingual(text, lang=lang)
+    text = collapse_whitespace(text)
+    return text
+
+
+def basic_cleaners(text):
+    """Basic pipeline that lowercases and collapses whitespace without transliteration."""
+    text = lowercase(text)
+    text = collapse_whitespace(text)
+    return text
+
+
+def chinese_transliterate(text):
+    return "".join(
+        [p[0] for p in pypinyin.pinyin(text, style=pypinyin.Style.TONE3, heteronym=False, neutral_tone_with_five=True)]
+    )
+
+
+def japanese_cleaners(text, katsu):
+    text = katsu.romaji(text)
+    text = lowercase(text)
+    return text
+
+
+def korean_transliterate(text):
+    r = Transliter(academic)
+    return r.translit(text)
+
+
+DEFAULT_VOCAB_FILE = os.path.join(os.path.dirname(os.path.realpath(__file__)), "../data/tokenizer.json")
+
+
+class VoiceBpeTokenizer:
+    def __init__(self, vocab_file=None):
+        self.tokenizer = None
+        if vocab_file is not None:
+            self.tokenizer = Tokenizer.from_file(vocab_file)
+        self.char_limits = {
+            "en": 250,
+            "de": 253,
+            "fr": 273,
+            "es": 239,
+            "it": 213,
+            "pt": 203,
+            "pl": 224,
+            "zh": 82,
+            "ar": 166,
+            "cs": 186,
+            "ru": 182,
+            "nl": 251,
+            "tr": 226,
+            "ja": 71,
+            "hu": 224,
+            "ko": 95,
+        }
+
+    @cached_property
+    def katsu(self):
+        import cutlet
+
+        return cutlet.Cutlet()
+
+    def check_input_length(self, txt, lang):
+        lang = lang.split("-")[0]  # remove the region
+        limit = self.char_limits.get(lang, 250)
+        if len(txt) > limit:
+            print(
+                f"[!] Warning: The text length exceeds the character limit of {limit} for language '{lang}', this might cause truncated audio."
+            )
+
+    def preprocess_text(self, txt, lang):
+        if lang in {"ar", "cs", "de", "en", "es", "fr", "hu", "it", "nl", "pl", "pt", "ru", "tr", "zh", "ko"}:
+            txt = multilingual_cleaners(txt, lang)
+            if lang == "zh":
+                txt = chinese_transliterate(txt)
+            if lang == "ko":
+                txt = korean_transliterate(txt)
+        elif lang == "ja":
+            txt = japanese_cleaners(txt, self.katsu)
+        elif lang == "hi":
+            # @manmay will implement this
+            txt = basic_cleaners(txt)
+        else:
+            raise NotImplementedError(f"Language '{lang}' is not supported.")
+        return txt
+
+    def encode(self, txt, lang):
+        lang = lang.split("-")[0]  # remove the region
+        self.check_input_length(txt, lang)
+        txt = self.preprocess_text(txt, lang)
+        lang = "zh-cn" if lang == "zh" else lang
+        txt = f"[{lang}]{txt}"
+        txt = txt.replace(" ", "[SPACE]")
+        return self.tokenizer.encode(txt).ids
+
+    def decode(self, seq):
+        if isinstance(seq, torch.Tensor):
+            seq = seq.cpu().numpy()
+        txt = self.tokenizer.decode(seq, skip_special_tokens=False).replace(" ", "")
+        txt = txt.replace("[SPACE]", " ")
+        txt = txt.replace("[STOP]", "")
+        txt = txt.replace("[UNK]", "")
+        return txt
+
+    def __len__(self):
+        return self.tokenizer.get_vocab_size()
+
+    def get_number_tokens(self):
+        return max(self.tokenizer.get_vocab().values()) + 1
+
+
+def test_expand_numbers_multilingual():
+    test_cases = [
+        # English
+        ("In 12.5 seconds.", "In twelve point five seconds.", "en"),
+        ("There were 50 soldiers.", "There were fifty soldiers.", "en"),
+        ("This is a 1st test", "This is a first test", "en"),
+        ("That will be $20 sir.", "That will be twenty dollars sir.", "en"),
+        ("That will be 20€ sir.", "That will be twenty euro sir.", "en"),
+        ("That will be 20.15€ sir.", "That will be twenty euro, fifteen cents sir.", "en"),
+        ("That's 100,000.5.", "That's one hundred thousand point five.", "en"),
+        # French
+        ("En 12,5 secondes.", "En douze virgule cinq secondes.", "fr"),
+        ("Il y avait 50 soldats.", "Il y avait cinquante soldats.", "fr"),
+        ("Ceci est un 1er test", "Ceci est un premier test", "fr"),
+        ("Cela vous fera $20 monsieur.", "Cela vous fera vingt dollars monsieur.", "fr"),
+        ("Cela vous fera 20€ monsieur.", "Cela vous fera vingt euros monsieur.", "fr"),
+        ("Cela vous fera 20,15€ monsieur.", "Cela vous fera vingt euros et quinze centimes monsieur.", "fr"),
+        ("Ce sera 100.000,5.", "Ce sera cent mille virgule cinq.", "fr"),
+        # German
+        ("In 12,5 Sekunden.", "In zwölf Komma fünf Sekunden.", "de"),
+        ("Es gab 50 Soldaten.", "Es gab fünfzig Soldaten.", "de"),
+        ("Dies ist ein 1. Test", "Dies ist ein erste Test", "de"),  # Issue with gender
+        ("Das macht $20 Herr.", "Das macht zwanzig Dollar Herr.", "de"),
+        ("Das macht 20€ Herr.", "Das macht zwanzig Euro Herr.", "de"),
+        ("Das macht 20,15€ Herr.", "Das macht zwanzig Euro und fünfzehn Cent Herr.", "de"),
+        # Spanish
+        ("En 12,5 segundos.", "En doce punto cinco segundos.", "es"),
+        ("Había 50 soldados.", "Había cincuenta soldados.", "es"),
+        ("Este es un 1er test", "Este es un primero test", "es"),
+        ("Eso le costará $20 señor.", "Eso le costará veinte dólares señor.", "es"),
+        ("Eso le costará 20€ señor.", "Eso le costará veinte euros señor.", "es"),
+        ("Eso le costará 20,15€ señor.", "Eso le costará veinte euros con quince céntimos señor.", "es"),
+        # Italian
+        ("In 12,5 secondi.", "In dodici virgola cinque secondi.", "it"),
+        ("C'erano 50 soldati.", "C'erano cinquanta soldati.", "it"),
+        ("Questo è un 1° test", "Questo è un primo test", "it"),
+        ("Ti costerà $20 signore.", "Ti costerà venti dollari signore.", "it"),
+        ("Ti costerà 20€ signore.", "Ti costerà venti euro signore.", "it"),
+        ("Ti costerà 20,15€ signore.", "Ti costerà venti euro e quindici centesimi signore.", "it"),
+        # Portuguese
+        ("Em 12,5 segundos.", "Em doze vírgula cinco segundos.", "pt"),
+        ("Havia 50 soldados.", "Havia cinquenta soldados.", "pt"),
+        ("Este é um 1º teste", "Este é um primeiro teste", "pt"),
+        ("Isso custará $20 senhor.", "Isso custará vinte dólares senhor.", "pt"),
+        ("Isso custará 20€ senhor.", "Isso custará vinte euros senhor.", "pt"),
+        (
+            "Isso custará 20,15€ senhor.",
+            "Isso custará vinte euros e quinze cêntimos senhor.",
+            "pt",
+        ),  # "cêntimos" should be "centavos" num2words issue
+        # Polish
+        ("W 12,5 sekundy.", "W dwanaście przecinek pięć sekundy.", "pl"),
+        ("Było 50 żołnierzy.", "Było pięćdziesiąt żołnierzy.", "pl"),
+        ("To będzie kosztować 20€ panie.", "To będzie kosztować dwadzieścia euro panie.", "pl"),
+        ("To będzie kosztować 20,15€ panie.", "To będzie kosztować dwadzieścia euro, piętnaście centów panie.", "pl"),
+        # Arabic
+        ("في الـ 12,5 ثانية.", "في الـ اثنا عشر  , خمسون ثانية.", "ar"),
+        ("كان هناك 50 جنديًا.", "كان هناك خمسون جنديًا.", "ar"),
+        # ("ستكون النتيجة $20 يا سيد.", 'ستكون النتيجة عشرون دولار يا سيد.', 'ar'), # $ and € are mising from num2words
+        # ("ستكون النتيجة 20€ يا سيد.", 'ستكون النتيجة عشرون يورو يا سيد.', 'ar'),
+        # Czech
+        ("Za 12,5 vteřiny.", "Za dvanáct celá pět vteřiny.", "cs"),
+        ("Bylo tam 50 vojáků.", "Bylo tam padesát vojáků.", "cs"),
+        ("To bude stát 20€ pane.", "To bude stát dvacet euro pane.", "cs"),
+        ("To bude 20.15€ pane.", "To bude dvacet euro, patnáct centů pane.", "cs"),
+        # Russian
+        ("Через 12.5 секунды.", "Через двенадцать запятая пять секунды.", "ru"),
+        ("Там было 50 солдат.", "Там было пятьдесят солдат.", "ru"),
+        ("Это будет 20.15€ сэр.", "Это будет двадцать евро, пятнадцать центов сэр.", "ru"),
+        ("Это будет стоить 20€ господин.", "Это будет стоить двадцать евро господин.", "ru"),
+        # Dutch
+        ("In 12,5 seconden.", "In twaalf komma vijf seconden.", "nl"),
+        ("Er waren 50 soldaten.", "Er waren vijftig soldaten.", "nl"),
+        ("Dat wordt dan $20 meneer.", "Dat wordt dan twintig dollar meneer.", "nl"),
+        ("Dat wordt dan 20€ meneer.", "Dat wordt dan twintig euro meneer.", "nl"),
+        # Chinese (Simplified)
+        ("在12.5秒内", "在十二点五秒内", "zh"),
+        ("有50名士兵", "有五十名士兵", "zh"),
+        # ("那将是$20先生", '那将是二十美元先生', 'zh'), currency doesn't work
+        # ("那将是20€先生", '那将是二十欧元先生', 'zh'),
+        # Turkish
+        # ("12,5 saniye içinde.", 'On iki virgül beş saniye içinde.', 'tr'), # decimal doesn't work for TR
+        ("50 asker vardı.", "elli asker vardı.", "tr"),
+        ("Bu 1. test", "Bu birinci test", "tr"),
+        # ("Bu 100.000,5.", 'Bu yüz bin virgül beş.', 'tr'),
+        # Hungarian
+        ("12,5 másodperc alatt.", "tizenkettő egész öt tized másodperc alatt.", "hu"),
+        ("50 katona volt.", "ötven katona volt.", "hu"),
+        ("Ez az 1. teszt", "Ez az első teszt", "hu"),
+        # Korean
+        ("12.5 초 안에.", "십이 점 다섯 초 안에.", "ko"),
+        ("50 명의 병사가 있었다.", "오십 명의 병사가 있었다.", "ko"),
+        ("이것은 1 번째 테스트입니다", "이것은 첫 번째 테스트입니다", "ko"),
+    ]
+    for a, b, lang in test_cases:
+        out = expand_numbers_multilingual(a, lang=lang)
+        assert out == b, f"'{out}' vs '{b}'"
+
+
+def test_abbreviations_multilingual():
+    test_cases = [
+        # English
+        ("Hello Mr. Smith.", "Hello mister Smith.", "en"),
+        ("Dr. Jones is here.", "doctor Jones is here.", "en"),
+        # Spanish
+        ("Hola Sr. Garcia.", "Hola señor Garcia.", "es"),
+        ("La Dra. Martinez es muy buena.", "La doctora Martinez es muy buena.", "es"),
+        # French
+        ("Bonjour Mr. Dupond.", "Bonjour monsieur Dupond.", "fr"),
+        ("Mme. Moreau est absente aujourd'hui.", "madame Moreau est absente aujourd'hui.", "fr"),
+        # German
+        ("Frau Dr. Müller ist sehr klug.", "Frau doktor Müller ist sehr klug.", "de"),
+        # Portuguese
+        ("Olá Sr. Silva.", "Olá senhor Silva.", "pt"),
+        ("Dra. Costa, você está disponível?", "doutora Costa, você está disponível?", "pt"),
+        # Italian
+        ("Buongiorno, Sig. Rossi.", "Buongiorno, signore Rossi.", "it"),
+        # ("Sig.ra Bianchi, posso aiutarti?", 'signora Bianchi, posso aiutarti?', 'it'), # Issue with matching that pattern
+        # Polish
+        ("Dzień dobry, P. Kowalski.", "Dzień dobry, pani Kowalski.", "pl"),
+        ("M. Nowak, czy mogę zadać pytanie?", "pan Nowak, czy mogę zadać pytanie?", "pl"),
+        # Czech
+        ("P. Novák", "pan Novák", "cs"),
+        ("Dr. Vojtěch", "doktor Vojtěch", "cs"),
+        # Dutch
+        ("Dhr. Jansen", "de heer Jansen", "nl"),
+        ("Mevr. de Vries", "mevrouw de Vries", "nl"),
+        # Russian
+        ("Здравствуйте Г-н Иванов.", "Здравствуйте господин Иванов.", "ru"),
+        ("Д-р Смирнов здесь, чтобы увидеть вас.", "доктор Смирнов здесь, чтобы увидеть вас.", "ru"),
+        # Turkish
+        ("Merhaba B. Yılmaz.", "Merhaba bay Yılmaz.", "tr"),
+        ("Dr. Ayşe burada.", "doktor Ayşe burada.", "tr"),
+        # Hungarian
+        ("Dr. Szabó itt van.", "doktor Szabó itt van.", "hu"),
+    ]
+
+    for a, b, lang in test_cases:
+        out = expand_abbreviations_multilingual(a, lang=lang)
+        assert out == b, f"'{out}' vs '{b}'"
+
+
+def test_symbols_multilingual():
+    test_cases = [
+        ("I have 14% battery", "I have 14 percent battery", "en"),
+        ("Te veo @ la fiesta", "Te veo arroba la fiesta", "es"),
+        ("J'ai 14° de fièvre", "J'ai 14 degrés de fièvre", "fr"),
+        ("Die Rechnung beträgt £ 20", "Die Rechnung beträgt pfund 20", "de"),
+        ("O meu email é ana&joao@gmail.com", "O meu email é ana e joao arroba gmail.com", "pt"),
+        ("linguaggio di programmazione C#", "linguaggio di programmazione C cancelletto", "it"),
+        ("Moja temperatura to 36.6°", "Moja temperatura to 36.6 stopnie", "pl"),
+        ("Mám 14% baterie", "Mám 14 procento baterie", "cs"),
+        ("Těším se na tebe @ party", "Těším se na tebe na party", "cs"),
+        ("У меня 14% заряда", "У меня 14 процентов заряда", "ru"),
+        ("Я буду @ дома", "Я буду собака дома", "ru"),
+        ("Ik heb 14% batterij", "Ik heb 14 procent batterij", "nl"),
+        ("Ik zie je @ het feest", "Ik zie je bij het feest", "nl"),
+        ("لدي 14% في البطارية", "لدي 14 في المئة في البطارية", "ar"),
+        ("我的电量为 14%", "我的电量为 14 百分之", "zh"),
+        ("Pilim %14 dolu.", "Pilim yüzde 14 dolu.", "tr"),
+        ("Az akkumulátorom töltöttsége 14%", "Az akkumulátorom töltöttsége 14 százalék", "hu"),
+        ("배터리 잔량이 14%입니다.", "배터리 잔량이 14 퍼센트입니다.", "ko"),
+    ]
+
+    for a, b, lang in test_cases:
+        out = expand_symbols_multilingual(a, lang=lang)
+        assert out == b, f"'{out}' vs '{b}'"
+
+
+if __name__ == "__main__":
+    test_expand_numbers_multilingual()
+    test_abbreviations_multilingual()
+    test_symbols_multilingual()

system/requirements/requirements_standalone.txt

@@ -0,0 +1,172 @@
+absl-py==2.1.0
+aiofiles==23.2.1
+aiohttp==3.9.3
+aiosignal==1.3.1
+altair==5.2.0
+annotated-types==0.6.0
+anyascii==0.3.2
+anyio==4.3.0
+attrs==23.2.0
+audioread==3.0.1
+av==11.0.0
+Babel==2.14.0
+bangla==0.0.2
+blinker==1.7.0
+blis==0.7.11
+bnnumerizer==0.0.2
+bnunicodenormalizer==0.1.6
+catalogue==2.0.10
+certifi==2024.2.2
+cffi==1.16.0
+charset-normalizer==3.3.2
+click==8.1.7
+cloudpathlib==0.16.0
+colorama==0.4.6
+coloredlogs==15.0.1
+confection==0.1.4
+contourpy==1.2.0
+coqpit==0.0.17
+ctranslate2==4.1.0
+cutlet==0.4.0
+cycler==0.12.1
+cymem==2.0.8
+Cython==3.0.9
+dateparser==1.1.8
+decorator==5.1.1
+docopt==0.6.2
+einops==0.7.0
+encodec==0.1.1
+fastapi==0.110.0
+faster-whisper==1.0.1
+ffmpy==0.3.2
+filelock==3.13.3
+Flask==3.0.2
+flatbuffers==24.3.25
+fonttools==4.50.0
+frozenlist==1.4.1
+fsspec==2024.3.1
+fugashi==1.3.1
+fuzzywuzzy>=0.18.0
+g2pkk==0.1.2
+gradio==3.50.2
+gradio_client==0.6.1
+grpcio==1.62.1
+gruut==2.2.3
+gruut-ipa==0.13.0
+gruut-lang-de==2.0.0
+gruut-lang-en==2.0.0
+gruut-lang-es==2.0.0
+gruut-lang-fr==2.0.2
+h11==0.14.0
+hangul-romanize==0.1.0
+httpcore==1.0.4
+httpx==0.27.0
+huggingface-hub==0.22.1
+humanfriendly==10.0
+idna==3.6
+importlib_metadata==7.1.0
+importlib_resources==6.4.0
+inflect==7.0.0
+itsdangerous==2.1.2
+jaconv==0.3.4
+jamo==0.4.1
+jieba==0.42.1
+Jinja2==3.1.3
+joblib==1.3.2
+jsonlines==1.2.0
+jsonschema==4.21.1
+jsonschema-specifications==2023.12.1
+kiwisolver==1.4.5
+langcodes==3.3.0
+lazy_loader==0.3
+librosa==0.10.1
+llvmlite==0.42.0
+Markdown==3.6
+MarkupSafe==2.1.5
+matplotlib==3.8.3
+mojimoji==0.0.13
+mpmath==1.3.0
+msgpack==1.0.8
+multidict==6.0.5
+murmurhash==1.0.10
+networkx==2.8.8
+nltk==3.8.1
+num2words==0.5.13
+numba==0.59.1
+numpy==1.26.4
+nvidia-cublas-cu11>=11.11.3.6
+nvidia-cudnn-cu11>=9.0.0.312
+onnxruntime==1.17.1
+orjson==3.9.15
+packaging==24.0
+pandas==1.5.3
+pillow==10.2.0
+platformdirs==4.2.0
+pooch==1.8.1
+preshed==3.0.9
+protobuf==5.26.0
+psutil==5.9.8
+pycparser==2.21
+pydantic==2.6.4
+pydantic_core==2.16.3
+pydub==0.25.1
+pynndescent==0.5.11
+pyparsing==3.1.2
+pypinyin==0.51.0
+pyreadline3==3.4.1
+pysbd==0.3.4
+python-crfsuite==0.9.10
+python-dateutil==2.9.0.post0
+python-Levenshtein>=0.25.0
+python-multipart==0.0.9
+pytz==2024.1
+PyYAML==6.0.1
+referencing==0.34.0
+regex==2023.12.25
+requests==2.31.0
+rpds-py==0.18.0
+safetensors==0.4.2
+scikit-learn==1.4.1.post1
+scipy==1.12.0
+semantic-version==2.10.0
+six==1.16.0
+smart-open==6.4.0
+sniffio==1.3.1
+sounddevice==0.4.6
+soundfile==0.12.1
+soxr==0.3.7
+spacy==3.7.4
+spacy-legacy==3.0.12
+spacy-loggers==1.0.5
+srsly==2.4.8
+starlette==0.36.3
+SudachiDict-core==20240109
+SudachiPy==0.6.8
+sympy==1.12
+tensorboard==2.16.2
+tensorboard-data-server==0.7.2
+thinc==8.2.3
+threadpoolctl==3.4.0
+tokenizers==0.15.2
+toolz==0.12.1
+torch>=2.2.0
+torchaudio>=2.2.0
+tqdm==4.66.2
+trainer==0.0.36
+transformers==4.39.1
+TTS==0.22.0
+typer==0.9.4
+typing_extensions==4.10.0
+tzdata==2024.1
+tzlocal==5.2
+umap-learn==0.5.5
+Unidecode==1.3.8
+unidic-lite==1.0.8
+urllib3==2.2.1
+uvicorn==0.29.0
+wasabi==1.1.2
+weasel==0.3.4
+websockets==11.0.3
+Werkzeug==3.0.1
+yarl==1.9.4
+zipp==3.18.1

system/requirements/requirements_textgen.txt

@@ -0,0 +1,24 @@
+numpy>=1.22.0
+soundfile>=0.12.1
+uvicorn>=0.24.0.post1
+transformers>=4.37.1
+TTS>=0.22.0
+torch>=2.1.0+cu118
+torchaudio>=2.1.0+cu118
+fastapi>=0.104.1
+Jinja2>=3.1.2
+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
+cutlet>=0.3.0
+unidic-lite>=1.0.8
+faster-whisper>=0.10.0
+pandas>=1.5.0
+nvidia-cublas-cu11>=11.11.3.6
+nvidia-cudnn-cu11>=9.0.0.312
+fuzzywuzzy>=0.18.0
+python-Levenshtein>=0.25.0

system/st_files/alltalk.js

@@ -0,0 +1,833 @@
+import { doExtrasFetch, getApiUrl, modules } from '../../extensions.js';
+import { saveTtsProviderSettings } from './index.js';
+
+export { AllTalkTtsProvider };
+
+class AllTalkTtsProvider {
+    //########//
+    // Config //
+    //########//
+
+    settings = {};
+    constructor() {
+        // Initialize with default settings if they are not already set
+        this.settings = {
+            provider_endpoint: this.settings.provider_endpoint || 'http://localhost:7851',
+            language: this.settings.language || 'en',
+            voiceMap: this.settings.voiceMap || {},
+            at_generation_method: this.settings.at_generation_method || 'standard_generation',
+            narrator_enabled: this.settings.narrator_enabled || 'false',
+            at_narrator_text_not_inside: this.settings.at_narrator_text_not_inside || 'narrator',
+            narrator_voice_gen: this.settings.narrator_voice_gen || 'female_01.wav',
+            finetuned_model: this.settings.finetuned_model || 'false'
+        };
+        // Separate property for dynamically updated settings from the server
+        this.dynamicSettings = {
+            modelsAvailable: [],
+            currentModel: '',
+            deepspeed_available: false,
+            deepSpeedEnabled: false,
+            lowVramEnabled: false,
+        };
+    }
+    ready = false;
+    voices = [];
+    separator = '. ';
+    audioElement = document.createElement('audio');
+
+    languageLabels = {
+        'Arabic': 'ar',
+        'Brazilian Portuguese': 'pt',
+        'Chinese': 'zh-cn',
+        'Czech': 'cs',
+        'Dutch': 'nl',
+        'English': 'en',
+        'French': 'fr',
+        'German': 'de',
+        'Italian': 'it',
+        'Polish': 'pl',
+        'Russian': 'ru',
+        'Spanish': 'es',
+        'Turkish': 'tr',
+        'Japanese': 'ja',
+        'Korean': 'ko',
+        'Hungarian': 'hu',
+        'Hindi': 'hi',
+    };
+
+    get settingsHtml() {
+        let html = `<div class="at-settings-separator">AllTalk Settings</div>`;
+
+        html += `<div class="at-settings-row">
+
+        <div class="at-settings-option">
+            <label for="at_generation_method">AllTalk TTS Generation Method</label>
+                <select id="at_generation_method">
+                <option value="standard_generation">Standard Audio Generation (AT Narrator - Optional)</option>
+                <option value="streaming_enabled">Streaming Audio Generation (AT Narrator - Disabled)</option>
+        </select>
+        </div>
+        </div>`;
+
+        html += `<div class="at-settings-row">
+
+        <div class="at-settings-option">
+            <label for="at_narrator_enabled">AT Narrator</label>
+                <select id="at_narrator_enabled">
+                <option value="true">Enabled</option>
+                <option value="false">Disabled</option>
+        </select>
+        </div>
+
+        <div class="at-settings-option">
+            <label for="at_narrator_text_not_inside">Text Not Inside * or " is</label>
+                <select id="at_narrator_text_not_inside">
+                <option value="narrator">Narrator</option>
+                <option value="character">Character</option>
+        </select>
+        </div>
+
+    </div>`;
+
+        html += `<div class="at-settings-row">
+        <div class="at-settings-option">
+            <label for="narrator_voice">Narrator Voice</label>
+            <select id="narrator_voice">`;
+        if (this.voices) {
+            for (let voice of this.voices) {
+                html += `<option value="${voice.voice_id}">${voice.name}</option>`;
+            }
+        }
+        html += `</select>
+        </div>
+        <div class="at-settings-option">
+            <label for="language_options">Language</label>
+            <select id="language_options">`;
+        for (let language in this.languageLabels) {
+            html += `<option value="${this.languageLabels[language]}" ${this.languageLabels[language] === this.settings?.language ? 'selected="selected"' : ''}>${language}</option>`;
+        }
+        html += `</select>
+        </div>
+    </div>`;
+
+
+        html += `<div class="at-model-endpoint-row">
+    <div class="at-model-option">
+            <label for="switch_model">Switch Model</label>
+            <select id="switch_model">
+            <option value="api_tts">API TTS</option>
+            <option value="api_local">API Local</option>
+            <option value="xttsv2_local">XTTSv2 Local</option>
+        </select>
+        </div>
+
+        <div class="at-endpoint-option">
+            <label for="at_server">AllTalk Endpoint:</label>
+            <input id="at_server" type="text" class="text_pole" maxlength="80" value="${this.settings.provider_endpoint}"/>
+        </div>
+   </div>`;
+
+
+        html += `<div class="at-model-endpoint-row">
+    <div class="at-settings-option">
+        <label for="low_vram">Low VRAM</label>
+        <input id="low_vram" type="checkbox"/>
+    </div>
+    <div class="at-settings-option">
+        <label for="deepspeed">DeepSpeed</label>
+        <input id="deepspeed" type="checkbox"/>
+    </div>
+    <div class="at-settings-option status-option">
+        <span>Status: <span id="status_info">Ready</span></span>
+    </div>
+    <div class="at-settings-option empty-option">
+        <!-- This div remains empty for spacing -->
+    </div>
+</div>`;
+
+
+        html += `<div class="at-website-row">
+        <div class="at-website-option">
+        <span>AllTalk <a target="_blank" href="${this.settings.provider_endpoint}">Config & Docs</a>.</span>
+    </div>
+
+    <div class="at-website-option">
+        <span>AllTalk <a target="_blank" href="https://github.com/erew123/alltalk_tts/">Website</a>.</span>
+    </div>
+</div>`;
+
+        html += `<div class="at-website-row">
+<div class="at-website-option">
+<span><strong>Text-generation-webui</strong> users - Uncheck <strong>Enable TTS</strong> in Text-generation-webui.</span>
+</div>
+</div>`;
+
+        return html;
+    }
+
+
+    //#################//
+    // Startup ST & AT //
+    //#################//
+
+    async loadSettings(settings) {
+        updateStatus('Offline');
+
+        if (Object.keys(settings).length === 0) {
+            console.info('Using default AllTalk TTS Provider settings');
+        } else {
+            // Populate settings with provided values, ignoring server-provided settings
+            for (const key in settings) {
+                if (key in this.settings) {
+                    this.settings[key] = settings[key];
+                } else {
+                    console.debug(`Ignoring non-user-configurable setting: ${key}`);
+                }
+            }
+        }
+
+        // Update UI elements to reflect the loaded settings
+        $('#at_server').val(this.settings.provider_endpoint);
+        $('#language_options').val(this.settings.language);
+        //$('#voicemap').val(this.settings.voiceMap);
+        $('#at_generation_method').val(this.settings.at_generation_method);
+        $('#at_narrator_enabled').val(this.settings.narrator_enabled);
+        $('#at_narrator_text_not_inside').val(this.settings.at_narrator_text_not_inside);
+        $('#narrator_voice').val(this.settings.narrator_voice_gen);
+
+        console.debug('AllTalkTTS: Settings loaded');
+        try {
+            // Check if TTS provider is ready
+            await this.checkReady();
+            await this.updateSettingsFromServer(); // Fetch dynamic settings from the TTS server
+            await this.fetchTtsVoiceObjects(); // Fetch voices only if service is ready
+            this.updateNarratorVoicesDropdown();
+            this.updateLanguageDropdown();
+            this.setupEventListeners();
+            this.applySettingsToHTML();
+            updateStatus('Ready');
+        } catch (error) {
+            console.error("Error loading settings:", error);
+            updateStatus('Offline');
+        }
+    }
+
+    applySettingsToHTML() {
+        // Apply loaded settings or use defaults
+        const narratorVoiceSelect = document.getElementById('narrator_voice');
+        const atNarratorSelect = document.getElementById('at_narrator_enabled');
+        const textNotInsideSelect = document.getElementById('at_narrator_text_not_inside');
+        const generationMethodSelect = document.getElementById('at_generation_method');
+        this.settings.narrator_voice = this.settings.narrator_voice_gen;
+        // Apply settings to Narrator Voice dropdown
+        if (narratorVoiceSelect && this.settings.narrator_voice) {
+            narratorVoiceSelect.value = this.settings.narrator_voice.replace('.wav', '');
+        }
+        // Apply settings to AT Narrator Enabled dropdown
+        if (atNarratorSelect) {
+            // Sync the state with the checkbox in index.js
+            const ttsPassAsterisksCheckbox = document.getElementById('tts_pass_asterisks'); // Access the checkbox from index.js
+            const ttsNarrateQuotedCheckbox = document.getElementById('tts_narrate_quoted'); // Access the checkbox from index.js
+            const ttsNarrateDialoguesCheckbox = document.getElementById('tts_narrate_dialogues'); // Access the checkbox from index.js
+            // Sync the state with the checkbox in index.js
+            if (this.settings.narrator_enabled) {
+                ttsPassAsterisksCheckbox.checked = false;
+                $('#tts_pass_asterisks').click(); // Simulate a click event
+                $('#tts_pass_asterisks').trigger('change');
+            }
+            if (!this.settings.narrator_enabled) {
+                ttsPassAsterisksCheckbox.checked = true;
+                $('#tts_pass_asterisks').click(); // Simulate a click event
+                $('#tts_pass_asterisks').trigger('change');
+            }
+            // Uncheck and set tts_narrate_quoted to false if narrator is enabled
+            if (this.settings.narrator_enabledd) {
+                ttsNarrateQuotedCheckbox.checked = true;
+                ttsNarrateDialoguesCheckbox.checked = true;
+                // Trigger click events instead of change events
+                $('#tts_narrate_quoted').click();
+                $('#tts_narrate_quoted').trigger('change');
+                $('#tts_narrate_dialogues').click();
+                $('#tts_narrate_dialogues').trigger('change');
+            }
+            atNarratorSelect.value = this.settings.narrator_enabled.toString();
+            this.settings.narrator_enabled = this.settings.narrator_enabled.toString();
+        }
+        // Apply settings to the Language dropdown
+        const languageSelect = document.getElementById('language_options');
+        if (languageSelect && this.settings.language) {
+            languageSelect.value = this.settings.language;
+        }
+        // Apply settings to Text Not Inside dropdown
+        if (textNotInsideSelect && this.settings.text_not_inside) {
+            textNotInsideSelect.value = this.settings.text_not_inside;
+            this.settings.at_narrator_text_not_inside = this.settings.text_not_inside;
+        }
+        // Apply settings to Generation Method dropdown
+        if (generationMethodSelect && this.settings.at_generation_method) {
+            generationMethodSelect.value = this.settings.at_generation_method;
+        }
+        // Additional logic to disable/enable dropdowns based on the selected generation method
+        const isStreamingEnabled = this.settings.at_generation_method === 'streaming_enabled';
+        if (isStreamingEnabled) {
+            // Disable certain dropdowns when streaming is enabled
+            if (atNarratorSelect) atNarratorSelect.disabled = true;
+            if (textNotInsideSelect) textNotInsideSelect.disabled = true;
+            if (narratorVoiceSelect) narratorVoiceSelect.disabled = true;
+        } else {
+            // Enable dropdowns for standard generation
+            if (atNarratorSelect) atNarratorSelect.disabled = false;
+            if (textNotInsideSelect) textNotInsideSelect.disabled = !this.settings.narrator_enabled;
+            if (narratorVoiceSelect) narratorVoiceSelect.disabled = !this.settings.narrator_enabled;
+        }
+        const modelSelect = document.getElementById('switch_model');
+        if (this.settings.finetuned_model === 'true') {
+            const ftOption = document.createElement('option');
+            ftOption.value = 'XTTSv2 FT';
+            ftOption.textContent = 'XTTSv2 FT';
+            modelSelect.appendChild(ftOption);
+        }
+    }
+
+    //##############################//
+    // Check AT Server is Available //
+    //##############################//
+
+    async checkReady() {
+        try {
+            const response = await fetch(`${this.settings.provider_endpoint}/api/ready`);
+            // Check if the HTTP request was successful
+            if (!response.ok) {
+                throw new Error(`HTTP Error Response: ${response.status} ${response.statusText}`);
+            }
+            const statusText = await response.text();
+            // Check if the response is 'Ready'
+            if (statusText === 'Ready') {
+                this.ready = true; // Set the ready flag to true
+                console.log('TTS service is ready.');
+            } else {
+                this.ready = false;
+                console.log('TTS service is not ready.');
+            }
+        } catch (error) {
+            console.error('Error checking TTS service readiness:', error);
+            this.ready = false; // Ensure ready flag is set to false in case of error
+        }
+    }
+
+    //######################//
+    // Get Available Voices //
+    //######################//
+
+    async fetchTtsVoiceObjects() {
+        const response = await fetch(`${this.settings.provider_endpoint}/api/voices`);
+        if (!response.ok) {
+            const errorText = await response.text();
+            throw new Error(`HTTP ${response.status}: ${errorText}`);
+        }
+        const data = await response.json();
+        const voices = data.voices.map(filename => {
+            const voiceName = filename.replace('.wav', '');
+            return {
+                name: voiceName,
+                voice_id: voiceName,
+                preview_url: null, // Preview URL will be dynamically generated
+                lang: 'en' // Default language
+            };
+        });
+        this.voices = voices; // Assign to the class property
+        return voices; // Also return this list
+    }
+
+    //##########################################//
+    // Get Current AT Server Config & Update ST //
+    //##########################################//
+
+    async updateSettingsFromServer() {
+        try {
+            // Fetch current settings
+            const response = await fetch(`${this.settings.provider_endpoint}/api/currentsettings`);
+            if (!response.ok) {
+                throw new Error(`Failed to fetch current settings: ${response.statusText}`);
+            }
+            const currentSettings = await response.json();
+            // Update internal settings
+            this.settings.modelsAvailable = currentSettings.models_available;
+            this.settings.currentModel = currentSettings.current_model_loaded;
+            this.settings.deepspeed_available = currentSettings.deepspeed_available;
+            this.settings.deepSpeedEnabled = currentSettings.deepspeed_status;
+            this.settings.lowVramEnabled = currentSettings.low_vram_status;
+            this.settings.finetuned_model = currentSettings.finetuned_model
+            // Update HTML elements
+            this.updateModelDropdown();
+            this.updateCheckboxes();
+        } catch (error) {
+            console.error(`Error updating settings from server: ${error}`);
+        }
+    }
+
+    //###################################################//
+    // Get Current AT Server Config & Update ST (Models) //
+    //###################################################//
+
+    updateModelDropdown() {
+        const modelSelect = document.getElementById('switch_model');
+        if (modelSelect) {
+            modelSelect.innerHTML = ''; // Clear existing options
+            this.settings.modelsAvailable.forEach(model => {
+                const option = document.createElement('option');
+                option.value = model.model_name;
+                option.textContent = model.model_name; // Use model_name instead of name
+                option.selected = model.model_name === this.settings.currentModel;
+                modelSelect.appendChild(option);
+            });
+        }
+    }
+
+    //#######################################################//
+    // Get Current AT Server Config & Update ST (DS and LVR) //
+    //#######################################################//
+
+    updateCheckboxes() {
+        const deepspeedCheckbox = document.getElementById('deepspeed');
+        const lowVramCheckbox = document.getElementById('low_vram');
+        if (lowVramCheckbox) lowVramCheckbox.checked = this.settings.lowVramEnabled;
+        if (deepspeedCheckbox) {
+            deepspeedCheckbox.checked = this.settings.deepSpeedEnabled;
+            deepspeedCheckbox.disabled = !this.settings.deepspeed_available; // Disable checkbox if deepspeed is not available
+        }
+    }
+
+    //###############################################################//
+    // Get Current AT Server Config & Update ST (AT Narrator Voices) //
+    //###############################################################//
+
+    updateNarratorVoicesDropdown() {
+        const narratorVoiceSelect = document.getElementById('narrator_voice');
+        if (narratorVoiceSelect && this.voices) {
+            // Clear existing options
+            narratorVoiceSelect.innerHTML = '';
+            // Add new options
+            for (let voice of this.voices) {
+                const option = document.createElement('option');
+                option.value = voice.voice_id;
+                option.textContent = voice.name;
+                narratorVoiceSelect.appendChild(option);
+            }
+        }
+    }
+
+    //######################################################//
+    // Get Current AT Server Config & Update ST (Languages) //
+    //######################################################//
+
+    updateLanguageDropdown() {
+        const languageSelect = document.getElementById('language_options');
+        if (languageSelect) {
+            // Ensure default language is set
+            this.settings.language = this.settings.language;
+
+            languageSelect.innerHTML = '';
+            for (let language in this.languageLabels) {
+                const option = document.createElement('option');
+                option.value = this.languageLabels[language];
+                option.textContent = language;
+                if (this.languageLabels[language] === this.settings.language) {
+                    option.selected = true;
+                }
+                languageSelect.appendChild(option);
+            }
+        }
+    }
+
+    //########################################//
+    // Start AT TTS extenstion page listeners //
+    //########################################//
+
+    setupEventListeners() {
+
+        let debounceTimeout;
+        const debounceDelay = 500; // Milliseconds
+
+        // Define the event handler function
+        const onModelSelectChange = async (event) => {
+            console.log("Model select change event triggered"); // Debugging statement
+            const selectedModel = event.target.value;
+            console.log(`Selected model: ${selectedModel}`); // Debugging statement 
+            // Set status to Processing
+            updateStatus('Processing');
+            try {
+                const response = await fetch(`${this.settings.provider_endpoint}/api/reload?tts_method=${encodeURIComponent(selectedModel)}`, {
+                    method: 'POST'
+                });
+                if (!response.ok) {
+                    throw new Error(`HTTP Error: ${response.status}`);
+                }
+                const data = await response.json();
+                console.log("POST response data:", data); // Debugging statement 
+                // Set status to Ready if successful
+                updateStatus('Ready');
+            } catch (error) {
+                console.error("POST request error:", error); // Debugging statement
+                // Set status to Error in case of failure
+                updateStatus('Error');
+            }
+
+            // Handle response or error
+        };
+
+        const debouncedModelSelectChange = (event) => {
+            clearTimeout(debounceTimeout);
+            debounceTimeout = setTimeout(() => {
+                onModelSelectChange(event);
+            }, debounceDelay);
+        };
+
+        // Switch Model Listener
+        const modelSelect = document.getElementById('switch_model');
+        if (modelSelect) {
+            // Remove the event listener if it was previously added
+            modelSelect.removeEventListener('change', debouncedModelSelectChange);
+            // Add the debounced event listener
+            modelSelect.addEventListener('change', debouncedModelSelectChange);
+        }
+
+        // DeepSpeed Listener
+        const deepspeedCheckbox = document.getElementById('deepspeed');
+        if (deepspeedCheckbox) {
+            deepspeedCheckbox.addEventListener('change', async (event) => {
+                const deepSpeedValue = event.target.checked ? 'True' : 'False';
+                // Set status to Processing
+                updateStatus('Processing');
+                try {
+                    const response = await fetch(`${this.settings.provider_endpoint}/api/deepspeed?new_deepspeed_value=${deepSpeedValue}`, {
+                        method: 'POST'
+                    });
+                    if (!response.ok) {
+                        throw new Error(`HTTP Error: ${response.status}`);
+                    }
+                    const data = await response.json();
+                    console.log("POST response data:", data); // Debugging statement
+                    // Set status to Ready if successful
+                    updateStatus('Ready');
+                } catch (error) {
+                    console.error("POST request error:", error); // Debugging statement
+                    // Set status to Error in case of failure
+                    updateStatus('Error');
+                }
+            });
+        }
+
+        // Low VRAM Listener
+        const lowVramCheckbox = document.getElementById('low_vram');
+        if (lowVramCheckbox) {
+            lowVramCheckbox.addEventListener('change', async (event) => {
+                const lowVramValue = event.target.checked ? 'True' : 'False';
+                // Set status to Processing
+                updateStatus('Processing');
+                try {
+                    const response = await fetch(`${this.settings.provider_endpoint}/api/lowvramsetting?new_low_vram_value=${lowVramValue}`, {
+                        method: 'POST'
+                    });
+                    if (!response.ok) {
+                        throw new Error(`HTTP Error: ${response.status}`);
+                    }
+                    const data = await response.json();
+                    console.log("POST response data:", data); // Debugging statement
+                    // Set status to Ready if successful
+                    updateStatus('Ready');
+                } catch (error) {
+                    console.error("POST request error:", error); // Debugging statement
+                    // Set status to Error in case of failure
+                    updateStatus('Error');
+                }
+            });
+        }
+
+        // Narrator Voice Dropdown Listener
+        const narratorVoiceSelect = document.getElementById('narrator_voice');
+        if (narratorVoiceSelect) {
+            narratorVoiceSelect.addEventListener('change', (event) => {
+                this.settings.narrator_voice_gen = `${event.target.value}.wav`;
+                this.onSettingsChange(); // Save the settings after change
+            });
+        }
+
+        const textNotInsideSelect = document.getElementById('at_narrator_text_not_inside');
+        if (textNotInsideSelect) {
+            textNotInsideSelect.addEventListener('change', (event) => {
+                this.settings.text_not_inside = event.target.value;
+                this.onSettingsChange(); // Save the settings after change
+            });
+        }
+
+        // AT Narrator Dropdown Listener
+        const atNarratorSelect = document.getElementById('at_narrator_enabled');
+        const ttsPassAsterisksCheckbox = document.getElementById('tts_pass_asterisks'); // Access the checkbox from index.js
+        const ttsNarrateQuotedCheckbox = document.getElementById('tts_narrate_quoted'); // Access the checkbox from index.js
+        const ttsNarrateDialoguesCheckbox = document.getElementById('tts_narrate_dialogues'); // Access the checkbox from index.js
+
+        if (atNarratorSelect && textNotInsideSelect && narratorVoiceSelect) {
+            atNarratorSelect.addEventListener('change', (event) => {
+                const isNarratorEnabled = event.target.value === 'true';
+                this.settings.narrator_enabled = isNarratorEnabled; // Update the setting here
+                textNotInsideSelect.disabled = !isNarratorEnabled;
+                narratorVoiceSelect.disabled = !isNarratorEnabled;
+
+                // Sync the state with the checkbox in index.js
+                if (isNarratorEnabled) {
+                    ttsPassAsterisksCheckbox.checked = false;
+                    $('#tts_pass_asterisks').click(); // Simulate a click event
+                    $('#tts_pass_asterisks').trigger('change');
+                }
+                if (!isNarratorEnabled) {
+                    ttsPassAsterisksCheckbox.checked = true;
+                    $('#tts_pass_asterisks').click(); // Simulate a click event
+                    $('#tts_pass_asterisks').trigger('change');
+                }
+                // Uncheck and set tts_narrate_quoted to false if narrator is enabled
+                if (isNarratorEnabled) {
+                    ttsNarrateQuotedCheckbox.checked = true;
+                    ttsNarrateDialoguesCheckbox.checked = true;
+                    // Trigger click events instead of change events
+                    $('#tts_narrate_quoted').click();
+                    $('#tts_narrate_quoted').trigger('change');
+                    $('#tts_narrate_dialogues').click();
+                    $('#tts_narrate_dialogues').trigger('change');
+                }
+                this.onSettingsChange(); // Save the settings after change
+            });
+        }
+
+
+        // Event Listener for AT Generation Method Dropdown
+        const atGenerationMethodSelect = document.getElementById('at_generation_method');
+        const atNarratorEnabledSelect = document.getElementById('at_narrator_enabled');
+        if (atGenerationMethodSelect) {
+            atGenerationMethodSelect.addEventListener('change', (event) => {
+                const selectedMethod = event.target.value;
+
+                if (selectedMethod === 'streaming_enabled') {
+                    // Disable and unselect AT Narrator
+                    atNarratorEnabledSelect.disabled = true;
+                    atNarratorEnabledSelect.value = 'false';
+                    textNotInsideSelect.disabled = true;
+                    narratorVoiceSelect.disabled = true;
+                } else if (selectedMethod === 'standard_generation') {
+                    // Enable AT Narrator
+                    atNarratorEnabledSelect.disabled = false;
+                }
+                this.settings.at_generation_method = selectedMethod; // Update the setting here
+                this.onSettingsChange(); // Save the settings after change
+            });
+        }
+
+        // Listener for Language Dropdown
+        const languageSelect = document.getElementById('language_options');
+        if (languageSelect) {
+            languageSelect.addEventListener('change', (event) => {
+                this.settings.language = event.target.value;
+                this.onSettingsChange(); // Save the settings after change
+            });
+        }
+
+        // Listener for AllTalk Endpoint Input
+        const atServerInput = document.getElementById('at_server');
+        if (atServerInput) {
+            atServerInput.addEventListener('input', (event) => {
+                this.settings.provider_endpoint = event.target.value;
+                this.onSettingsChange(); // Save the settings after change
+            });
+        }
+
+    }
+
+    //#############################//
+    // Store ST interface settings //
+    //#############################//
+
+    onSettingsChange() {
+        // Update settings based on the UI elements
+        //this.settings.provider_endpoint = $('#at_server').val();
+        this.settings.language = $('#language_options').val();
+        //this.settings.voiceMap = $('#voicemap').val();
+        this.settings.at_generation_method = $('#at_generation_method').val();
+        this.settings.narrator_enabled = $('#at_narrator_enabled').val();
+        this.settings.at_narrator_text_not_inside = $('#at_narrator_text_not_inside').val();
+        this.settings.narrator_voice_gen = $('#narrator_voice').val();
+        // Save the updated settings
+        saveTtsProviderSettings();
+    }
+
+    //#########################//
+    // ST Handle Reload button //
+    //#########################//
+
+    async onRefreshClick() {
+        await this.checkReady(); // Check if the TTS provider is ready
+        await this.loadSettings(this.settings); // Reload the settings
+        // Additional actions as needed
+    }
+
+    //##################//
+    // Preview AT Voice //
+    //##################//
+
+    async previewTtsVoice(voiceName) {
+        try {
+            // Prepare data for POST request
+            const postData = new URLSearchParams();
+            postData.append("voice", `${voiceName}.wav`);
+            // Making the POST request
+            const response = await fetch(`${this.settings.provider_endpoint}/api/previewvoice/`, {
+                method: "POST",
+                headers: {
+                    'Content-Type': 'application/x-www-form-urlencoded'
+                },
+                body: postData,
+            });
+            if (!response.ok) {
+                const errorText = await response.text();
+                console.error(`[previewTtsVoice] Error Response Text:`, errorText);
+                throw new Error(`HTTP ${response.status}: ${errorText}`);
+            }
+            // Assuming the server returns a URL to the .wav file
+            const data = await response.json();
+            if (data.output_file_url) {
+                // Use an audio element to play the .wav file
+                const audioElement = new Audio(data.output_file_url);
+                audioElement.play().catch(e => console.error("Error playing audio:", e));
+            } else {
+                console.warn("[previewTtsVoice] No output file URL received in the response");
+                throw new Error("No output file URL received in the response");
+            }
+
+        } catch (error) {
+            console.error("[previewTtsVoice] Exception caught during preview generation:", error);
+            throw error;
+        }
+    }
+
+    //#####################//
+    //  Populate ST voices //
+    //#####################//
+
+    async getVoice(voiceName, generatePreview = false) {
+        // Ensure this.voices is populated
+        if (this.voices.length === 0) {
+            // Fetch voice objects logic
+        }
+        // Find the object where the name matches voiceName
+        const match = this.voices.find(voice => voice.name === voiceName);
+        if (!match) {
+            // Error handling
+        }
+        // Generate preview URL only if requested
+        if (!match.preview_url && generatePreview) {
+            // Generate preview logic
+        }
+        return match; // Return the found voice object
+    }
+
+    //##########################################//
+    //  Generate TTS Streaming or call Standard //
+    //##########################################//
+
+    async generateTts(inputText, voiceId) {
+        try {
+            if (this.settings.at_generation_method === 'streaming_enabled') {
+                // Construct the streaming URL
+                const streamingUrl = `${this.settings.provider_endpoint}/api/tts-generate-streaming?text=${encodeURIComponent(inputText)}&voice=${encodeURIComponent(voiceId)}.wav&language=${encodeURIComponent(this.settings.language)}&output_file=stream_output.wav`;
+                console.log("Streaming URL:", streamingUrl);
+        
+                // Return the streaming URL directly
+                return streamingUrl; 
+            } else {
+                // For standard method
+                const outputUrl = await this.fetchTtsGeneration(inputText, voiceId);
+                const audioResponse = await fetch(outputUrl);
+                if (!audioResponse.ok) {
+                    throw new Error(`HTTP ${audioResponse.status}: Failed to fetch audio data`);
+                }
+                return audioResponse; // Return the fetch response directly
+            }
+        } catch (error) {
+            console.error("Error in generateTts:", error);
+            throw error;
+        }
+    }
+
+
+    //####################//
+    //  Generate Standard //
+    //####################//
+
+    async fetchTtsGeneration(inputText, voiceId) {
+        // Prepare the request payload
+        const requestBody = new URLSearchParams({
+            'text_input': inputText,
+            'text_filtering': "standard",
+            'character_voice_gen': voiceId + ".wav",
+            'narrator_enabled': this.settings.narrator_enabled,
+            'narrator_voice_gen': this.settings.narrator_voice_gen + ".wav",
+            'text_not_inside': this.settings.at_narrator_text_not_inside,
+            'language': this.settings.language,
+            'output_file_name': "st_output",
+            'output_file_timestamp': "true",
+            'autoplay': "false",
+            'autoplay_volume': "0.8"
+        }).toString();
+
+        try {
+            const response = await doExtrasFetch(
+                `${this.settings.provider_endpoint}/api/tts-generate`,
+                {
+                    method: 'POST',
+                    headers: {
+                        'Content-Type': 'application/x-www-form-urlencoded',
+                        'Cache-Control': 'no-cache',
+                    },
+                    body: requestBody
+                }
+            );
+
+            if (!response.ok) {
+                const errorText = await response.text();
+                console.error(`[fetchTtsGeneration] Error Response Text:`, errorText);
+                // toastr.error(response.statusText, 'TTS Generation Failed');
+                throw new Error(`HTTP ${response.status}: ${errorText}`);
+            }
+            const data = await response.json();
+            const outputUrl = data.output_file_url;
+            return outputUrl; // Return only the output_file_url
+        } catch (error) {
+            console.error("[fetchTtsGeneration] Exception caught:", error);
+            throw error; // Rethrow the error for further handling
+        }
+    }
+}
+
+//#########################//
+//  Update Status Messages //
+//#########################//
+
+function updateStatus(message) {
+    const statusElement = document.getElementById('status_info');
+    if (statusElement) {
+        statusElement.textContent = message;
+        switch (message) {
+            case 'Offline':
+                statusElement.style.color = 'red';
+                break;
+            case 'Ready':
+                statusElement.style.color = 'lightgreen';
+                break;
+            case 'Processing':
+                statusElement.style.color = 'blue';
+                break;
+            case 'Error':
+                statusElement.style.color = 'red';
+                break;
+        }
+    }
+}

system/st_files/style.css

@@ -0,0 +1,159 @@
+#tts_media_control {
+    /* order: 100; */
+    /*     width: 40px;
+    height: 40px;
+    margin: 0;
+    padding: 1px; */
+    outline: none;
+    border: none;
+    cursor: pointer;
+    /*     transition: 0.3s;
+    opacity: 0.7; */
+    display: flex;
+    align-items: center;
+    /* justify-content: center; */
+
+}
+
+#ttsExtensionMenuItem {
+    transition: 0.3s;
+    opacity: 0.7;
+}
+
+#ttsExtensionMenuItem:hover {
+    opacity: 1;
+    filter: brightness(1.2);
+}
+
+#tts_media_control:hover {
+    opacity: 1;
+    filter: brightness(1.2);
+}
+
+.voice_preview {
+    margin: 0.25rem 0.5rem;
+    display: flex;
+    justify-content: space-between;
+    align-items: center;
+    gap: 0.5rem;
+}
+
+.voice_preview .voice_name {
+    text-align: left;
+    flex: 1;
+}
+
+.voice_preview .voice_lang {
+    width: 4rem;
+    text-align: left;
+}
+
+.voice_preview .fa-play {
+    cursor: pointer;
+}
+
+.tts-button {
+    margin: 0;
+    outline: none;
+    border: none;
+    cursor: pointer;
+    transition: 0.3s;
+    opacity: 0.7;
+    align-items: center;
+    justify-content: center;
+
+}
+
+.tts-button:hover {
+    opacity: 1;
+}
+
+.tts_block {
+    display: flex;
+    align-items: baseline;
+    column-gap: 5px;
+    flex-wrap: wrap;
+}
+
+.tts_custom_voices {
+    display: flex;
+    align-items: baseline;
+    gap: 5px;
+}
+
+.novel_tts_hints {
+    font-size: calc(0.9 * var(--mainFontSize));
+    display: flex;
+    flex-direction: column;
+    gap: 5px;
+    margin-bottom: 5px;
+}
+
+.at-settings-row {
+    display: flex;
+    justify-content: space-between;
+    align-items: center;
+    width: 100%;
+}
+
+.at-settings-option {
+    flex: 1;
+    margin: 0 10px;
+}
+
+.at-endpoint-option {
+    flex: 1; 
+    margin: 0 10px;
+    margin-right: 25px;
+    width: 38%;
+}
+
+.at-website-row {
+    display: flex;
+    justify-content: start;
+    align-items: center;
+    margin-top: 10px; 
+    margin-bottom: 10px;
+}
+
+.at-website-option {
+    flex: 1; 
+    margin-right: 10px; 
+    margin-left: 10px; 
+}
+
+.at-settings-separator {
+    margin-top: 10px;
+    margin-bottom: 10px;
+    padding: 18x;
+    font-weight: bold;
+    border-top: 1px solid #e1e1e1; /* Grey line */
+    border-bottom: 1px solid #e1e1e1; /* Grey line */
+    text-align: center;
+}
+
+.at-status-message {
+    flex: 1;
+    margin: 0 10px;
+}
+
+.at-model-endpoint-row {
+    display: flex;
+    justify-content: space-between;
+    align-items: center;
+    width: 100%;
+}
+
+.at-model-option, .endpoint-option {
+    flex: 1;
+    margin: 0 10px;
+    margin-left: 10px; 
+}
+
+.at-endpoint-option {
+    width: 38%;
+}
+
+#at-status_info {
+    color: lightgreen; 
+}

system/tts_diff/tts_diff.py

@@ -0,0 +1,269 @@
+import json
+import argparse
+from pathlib import Path
+import os
+import glob
+import platform
+import site
+import subprocess
+import sys
+# version 0.8
+
+def find_files_in_path_with_wildcard(pattern):
+    # Get the site-packages directory of the current Python environment
+    site_packages_path = site.getsitepackages()
+    found_paths = []
+    # Adjust the sub-directory based on the operating system
+    sub_directory = "nvidia/cublas"
+    if platform.system() == "Linux":
+        sub_directory = os.path.join(sub_directory, "lib")
+    else:
+        sub_directory = os.path.join(sub_directory, "bin")
+    
+    # Iterate over each site-packages directory (there can be more than one)
+    for directory in site_packages_path:
+        # Construct the search directory path
+        search_directory = os.path.join(directory, sub_directory)
+        # Use glob to find all files matching the pattern in this directory
+        for file_path in glob.glob(os.path.join(search_directory, pattern)):
+            if os.path.isfile(file_path):  # Ensure it's a file
+                found_paths.append(file_path)
+    return found_paths
+
+def detect_cublas():
+    # Use different file patterns based on the operating system
+    file_name_pattern = 'cublas64_11.*' if platform.system() == "Windows" else 'libcublas.so.11*'
+    found_paths = find_files_in_path_with_wildcard(file_name_pattern)
+    if found_paths:
+        print("[AllTalk TTSDiff] \033[94mCublas:\033[0m \033[92mDetected\033[0m", found_paths)
+    else:
+        print("[AllTalk TTSDiff] \033[94mCublas:\033[0m \033[91mERROR Not Detected\033[0m")
+        print("[AllTalk TTSDiff] \033[94mPlease install Cublas from the Nvidia CUDA Toolkit \033[0mhttps://developer.nvidia.com/cuda-downloads")
+        exit(1)
+        
+
+parser = argparse.ArgumentParser(description="Compare TTS output with the original text using detailed comparison.")
+parser.add_argument("--threshold", type=int, default=98, help="Similarity threshold for considering a match (default: 98)")
+parser.add_argument("--ttslistpath", help="Path to the ttsList.json file")
+parser.add_argument("--wavfilespath", help="Path to the wav outputs folder")
+args = parser.parse_args()
+
+if not args.ttslistpath:
+    parser.error("[AllTalk TTSDiff] Please specify the path to the ttslist.json file using the --ttslistpath argument.")
+if not args.wavfilespath:
+    parser.error("[AllTalk TTSDiff] Please specify the path to the wavs output folder file using the --wavfilespath argument.")
+
+json_file_path = Path(args.ttslistpath).resolve()
+wav_file_path = Path(args.wavfilespath).resolve()
+accuracy_threshold = args.threshold
+
+def disclaimer_text():
+    print(f"\nDESCRIPTION: ")
+    print(f"  This script is designed to assist in identifying bad TTS generation ID's from the TTS Generator.\n")
+    print(f"  This will download the Whisper Large-v2 model (if not already downloaded), and use it to compare your text to")
+    print(f"  to the generated TTS. If it finds an issue, it will flag the ID number that has the issue. This does NOT 100%")
+    print(f"  ensure that all TTS generated is perfect, sounds good etc, but it should flag up glaring issues and help with")
+    print(f"  the process of identifying bad TTS generations.")
+    print(f"\nNOTES ON USE: ")
+    print(f"  - Ensure AllTalk is running in its own command prompt/terminal.")
+    print(f"  - This script should be running in its own command prompt/terminal window in the same Python Environment that")
+    print(f"    AllTalk is running in.")
+    print(f"  - After generating your text in the TTS Generator, you need to `Export List to JSON` and save the file in the")
+    print(f"    same folder/directory this script is running from.")
+    print(f"  - You can use `--threshold` with a numerical value from 1 to 100 to set accuracy detection. For example it may")
+    print(f"    detect/transcribe `their` as `there`, which of course, both words sound the same. If you want 100% accuracy")
+    print(f"    you will set 100 as the threshold. You will more than likely want a number in the high 90's. Default is set")
+    print(f"    at 98, which gives a little flexibility.")
+    print(f"  - The JSON file must be named \033[93mttsList.json\033[0m")
+    print(f"  - When you have your ID list, go back into the TTS Generator, correct any lines and regenerate them. If you")
+    print(f"    want to re-test everthing again after re-generating, you will need to export your list again and re-run this")
+    print(f"    script again, against your newly exported JSON list.")
+    print(f"  - This requires access to \033[93mcublas64_11\033[0m, the same as Finetuning.")
+    print(f"    https://github.com/erew123/alltalk_tts/tree/main?#-important-requirements-cuda-118\n")
+    return
+
+try:
+    from faster_whisper import WhisperModel
+    import re
+    import string
+    import spacy
+    import torch
+    from fuzzywuzzy import fuzz
+except ImportError as e:
+    print(f"[AllTalk TTSDiff] ERROR STARTING SCRIPT:")
+    print("[AllTalk TTSDiff] An error occurred importing one or more required libraries.")
+    print("[AllTalk TTSDiff] Please ensure you have \033[94mactivated your Python environment \033[0mand \033[94minstalled all requirements.\033[0m")
+    print("[AllTalk TTSDiff] \033[94mMissing library:\033[93m", str(e), "\033[0m")
+    exit(1)
+
+# Attempt to load the spaCy model
+try:
+    # Load a medium-sized spaCy model, adjust to "en_core_web_md" or "en_core_web_lg" as needed
+    nlp = spacy.load("en_core_web_md")
+except Exception as e:
+    print(f"[AllTalk TTSDiff] ERROR STARTING SCRIPT:")
+    print("[AllTalk TTSDiff] Failed to load the spaCy language model.")
+    
+    # Attempt to download the spaCy model automatically
+    try:
+        print("[AllTalk TTSDiff] Attempting to automatically download the spaCy language model...")
+        subprocess.run([sys.executable, "-m", "spacy", "download", "en_core_web_md"], check=True)
+        
+        # Try to load the model again after downloading
+        nlp = spacy.load("en_core_web_md")
+        print("[AllTalk TTSDiff] Model downloaded and loaded successfully.")
+    except Exception as download_exception:
+        print("[AllTalk TTSDiff] Automatic download failed.")
+        print("[AllTalk TTSDiff] Please manually install the spaCy language model by running:")
+        print("[AllTalk TTSDiff] \033[93mpython -m spacy download en_core_web_md\033[0m")
+        exit(1)
+
+def texts_are_similar(text1, text2, threshold=0.8):
+    # Preliminary check for short texts
+    if len(text1) < 10 or len(text2) < 10:
+        ratio = fuzz.ratio(text1, text2) / 100.0  # Use FuzzyWuzzy for short texts
+        return ratio > threshold
+
+    # Process the texts through the NLP model for longer texts
+    doc1 = nlp(text1)
+    doc2 = nlp(text2)
+    
+    # Compute semantic similarity
+    similarity = doc1.similarity(doc2)
+    
+    return similarity >= threshold
+
+def normalize_text(text):
+    # Normalize or remove CRLF and other non-standard whitespaces
+    text = text.replace("\r\n", " ").replace("\n", " ").replace("\r", " ")
+    
+    # Convert to lowercase
+    text = text.lower()
+    
+    # Standardize and then remove quotation marks
+    text = text.replace("“", '"').replace("”", '"').replace("‘", "'").replace("’", "'")
+    text = text.translate(str.maketrans('', '', '"\''))
+    
+    # Remove all other punctuation except hyphens to preserve compound words
+    text = text.translate(str.maketrans('', '', string.punctuation.replace("-", "")))
+    
+    # Collapse any sequence of whitespace (including spaces) into a single space
+    text = re.sub(r'\s+', ' ', text)
+    
+    return text.strip()
+
+spoken_punctuation_mapping = {
+    "dot": ".",
+    "comma": ",",
+    # Add more mappings as needed
+}
+
+def contains_spoken_punctuation(transcribed_text):
+    for spoken, punctuation in spoken_punctuation_mapping.items():
+        if spoken in transcribed_text:
+            return True
+    return False
+
+def detailed_comparison(original_text, transcribed_text, threshold=98):
+    original_clean = normalize_text(original_text)
+    transcribed_clean = normalize_text(transcribed_text)
+    ratio = fuzz.ratio(original_clean, transcribed_clean)
+    return ratio > threshold
+
+def access_local_file(url):
+    # Extract the file name from the URL
+    file_name = url.split('/')[-1]
+    # Construct the full path to the file on disk
+    file_path = wav_file_path / file_name
+    # Check if the file exists
+    if not file_path.exists():
+        print(f"[AllTalk TTSDiff] File does not exist: {file_path}")
+        return None
+    return file_path
+
+def transcribe_and_compare(file_url, original_text, model, item_id, flagged_ids):
+    audio_file_path = access_local_file(file_url)
+    if audio_file_path is None:
+        print(f"[AllTalk TTSDiff] Could not access local file for URL: {file_url}")
+        return  # Skip this file if it can't be accessed
+
+    try:
+        segments, info = model.transcribe(str(audio_file_path), beam_size=5)
+        transcribed_text = " ".join([segment.text for segment in segments])
+    except Exception as e:
+        print(f"[AllTalk TTSDiff] Error transcribing file {audio_file_path}: {e}")
+        return  # Skip this file if transcription fails
+    
+    segments, info = model.transcribe(str(audio_file_path), beam_size=5)
+    transcribed_text = " ".join([segment.text for segment in segments])
+    
+    # Normalize texts for comparison
+    original_text_normalized = normalize_text(original_text)
+    transcribed_text_normalized = normalize_text(transcribed_text)
+    
+    # Enhanced comparison using detailed fuzzy matching
+    is_detailed_match = detailed_comparison(original_text_normalized, transcribed_text_normalized, args.threshold)
+    has_spoken_punctuation = contains_spoken_punctuation(transcribed_text_normalized) and not contains_spoken_punctuation(original_text_normalized)
+    
+    # Adjust is_match based on detailed comparison and spoken punctuation check
+    is_match = is_detailed_match and not has_spoken_punctuation
+    
+    # Only log and flag IDs for review if there's a mismatch or detected issues
+    if not is_match:
+        #print(f"\033[93mMismatch Detected - ID:\033[0m {item_id}")
+        print(f"[AllTalk TTSDiff] \033[93mText:\033[0m {original_text}")
+        print(f"[AllTalk TTSDiff] \033[91mTTS :\033[0m{transcribed_text}")
+        if has_spoken_punctuation:
+            print(f"[AllTalk TTSDiff] Note: Potential incorrect spoken punctuation detected.")
+        flagged_ids.append(item_id)  # Track the ID for review
+
+def main():
+    print(f"[AllTalk TTSDiff]")
+    print(f"[AllTalk TTSDiff]")
+    print("[AllTalk TTSDiff] \033[92mStarting Compare of Text vs TTS:\033[0m")
+    print("[AllTalk TTSDiff]")
+    print("[AllTalk TTSDiff] \033[94mJSON file  :\033[92m", json_file_path, "\033[0m")
+    print("[AllTalk TTSDiff] \033[94mWAV files  :\033[92m", wav_file_path, "\033[0m")
+    print("[AllTalk TTSDiff] \033[94mAccuracy   :\033[92m", accuracy_threshold, "%", "\033[0m")
+    detect_cublas()
+    model_size = "large-v2"
+    device = "cuda" if torch.cuda.is_available() else "cpu"
+    model = WhisperModel(model_size, device=device, compute_type="float32")
+    
+    flagged_ids = []  # Initialize the list to track IDs needing review
+
+    try:
+        with open(json_file_path, "r", encoding="utf-8") as f:
+            tts_list = json.load(f)
+    except FileNotFoundError:
+        print(f"[AllTalk TTSDiff] ERROR STARTING SCRIPT:")
+        print("[AllTalk TTSDiff] Error: \033[93mttsList.json\033[0m file not found.")
+        print("[AllTalk TTSDiff] Please ensure you follow these steps:")
+        print("[AllTalk TTSDiff] After generating your text in the TTS Generator, you need to `Export List to JSON` and save the file in the")
+        print("[AllTalk TTSDiff] same folder/directory this script is running from.")
+        print("[AllTalk TTSDiff] The JSON file must be named \033[93mttsList.json\033[0m")
+        exit(1)
+
+    print(f"[AllTalk TTSDiff]")
+
+    for item in tts_list:
+        print(f"[AllTalk TTSDiff] Processing ID: {item['id']}")
+        transcribe_and_compare(item['fileUrl'], item['text'], model, item['id'], flagged_ids)
+    
+    print(f"[AllTalk TTSDiff]")
+    # Print summary information at the end
+    if flagged_ids:
+        print(f"[AllTalk TTSDiff] \033[94mIDs needing review:\033[0m", ', '.join(map(str, flagged_ids)))
+        print(f"[AllTalk TTSDiff]")
+        print(f"[AllTalk TTSDiff] Review ID's and correct any lines by editing & regenerating as necessary.")
+    else:
+        print("[AllTalk TTSDiff] \033[94mIDs needing review:\033[0m No issues detected.")
+    summary_data = {
+        "flagged_ids": flagged_ids
+    }
+    with open(wav_file_path / "analysis_summary.json", "w") as summary_file:
+        json.dump(summary_data, summary_file)
+    print("[AllTalk TTSDiff]")
+
+if __name__ == "__main__":
+    main()

system/tts_generator/crunker.d.ts

@@ -0,0 +1,179 @@
+export interface CrunkerConstructorOptions {
+    /**
+     * Sample rate for Crunker's internal audio context.
+     *
+     * @default 44100
+     */
+    sampleRate: number;
+}
+export type CrunkerInputTypes = string | File | Blob;
+/**
+ * An exported Crunker audio object.
+ */
+export interface ExportedCrunkerAudio {
+    blob: Blob;
+    url: string;
+    element: HTMLAudioElement;
+}
+/**
+ * Crunker is the simple way to merge, concatenate, play, export and download audio files using the Web Audio API.
+ */
+export default class Crunker {
+    private readonly _sampleRate;
+    private readonly _context;
+    /**
+     * Creates a new instance of Crunker with the provided options.
+     *
+     * If `sampleRate` is not defined, it will auto-select an appropriate sample rate
+     * for the device being used.
+     */
+    constructor({ sampleRate }?: Partial<CrunkerConstructorOptions>);
+    /**
+     * Creates Crunker's internal AudioContext.
+     *
+     * @internal
+     */
+    private _createContext;
+    /**
+     *
+     * The internal AudioContext used by Crunker.
+     */
+    get context(): AudioContext;
+    /**
+     * Asynchronously fetches multiple audio files and returns an array of AudioBuffers.
+     */
+    fetchAudio(...filepaths: CrunkerInputTypes[]): Promise<AudioBuffer[]>;
+    /**
+     * Merges (layers) multiple AudioBuffers into a single AudioBuffer.
+     *
+     * **Visual representation:**
+     *
+     * ![](https://user-images.githubusercontent.com/12958674/88806278-968f0680-d186-11ea-9cb5-8ef2606ffcc7.png)
+     */
+    mergeAudio(buffers: AudioBuffer[]): AudioBuffer;
+    /**
+     * Concatenates multiple AudioBuffers into a single AudioBuffer.
+     *
+     * **Visual representation:**
+     *
+     * ![](https://user-images.githubusercontent.com/12958674/88806297-9d1d7e00-d186-11ea-8cd2-c64cb0324845.png)
+     */
+    concatAudio(buffers: AudioBuffer[]): AudioBuffer;
+    /**
+     * Pads a specified AudioBuffer with silence from a specified start time,
+     * for a specified length of time.
+     *
+     * Accepts float values as well as whole integers.
+     *
+     * @param buffer AudioBuffer to pad
+     * @param padStart Time to start padding (in seconds)
+     * @param seconds Duration to pad for (in seconds)
+     */
+    padAudio(buffer: AudioBuffer, padStart?: number, seconds?: number): AudioBuffer;
+    /**
+     * Slices an AudioBuffer from the specified start time to the end time, with optional fade in and out.
+     *
+     * @param buffer AudioBuffer to slice
+     * @param start Start time (in seconds)
+     * @param end End time (in seconds)
+     * @param fadeIn Fade in duration (in seconds, default is 0)
+     * @param fadeOut Fade out duration (in seconds, default is 0)
+     */
+    sliceAudio(buffer: AudioBuffer, start: number, end: number, fadeIn?: number, fadeOut?: number): AudioBuffer;
+    /**
+     * Plays the provided AudioBuffer in an AudioBufferSourceNode.
+     */
+    play(buffer: AudioBuffer): AudioBufferSourceNode;
+    /**
+     * Exports the specified AudioBuffer to a Blob, Object URI and HTMLAudioElement.
+     *
+     * Note that changing the MIME type does not change the actual file format. The
+     * file format will **always** be a WAVE file due to how audio is stored in the
+     * browser.
+     *
+     * @param buffer Buffer to export
+     * @param type MIME type (default: `audio/wav`)
+     */
+    export(buffer: AudioBuffer, type?: string): ExportedCrunkerAudio;
+    /**
+     * Downloads the provided Blob.
+     *
+     * @param blob Blob to download
+     * @param filename An optional file name to use for the download (default: `crunker`)
+     */
+    download(blob: Blob, filename?: string): HTMLAnchorElement;
+    /**
+     * Executes a callback if the browser does not support the Web Audio API.
+     *
+     * Returns the result of the callback, or `undefined` if the Web Audio API is supported.
+     *
+     * @param callback callback to run if the browser does not support the Web Audio API
+     */
+    notSupported<T>(callback: () => T): T | undefined;
+    /**
+     * Closes Crunker's internal AudioContext.
+     */
+    close(): this;
+    /**
+     * Returns the largest duration of the longest AudioBuffer.
+     *
+     * @internal
+     */
+    private _maxDuration;
+    /**
+     * Returns the largest number of channels in an array of AudioBuffers.
+     *
+     * @internal
+     */
+    private _maxNumberOfChannels;
+    /**
+     * Returns the sum of the lengths of an array of AudioBuffers.
+     *
+     * @internal
+     */
+    private _totalLength;
+    /**
+     * Returns whether the browser supports the Web Audio API.
+     *
+     * @internal
+     */
+    private _isSupported;
+    /**
+     * Writes the WAV headers for the specified Float32Array.
+     *
+     * Returns a DataView containing the WAV headers and file content.
+     *
+     * @internal
+     */
+    private _writeHeaders;
+    /**
+     * Converts a Float32Array to 16-bit PCM.
+     *
+     * @internal
+     */
+    private _floatTo16BitPCM;
+    /**
+     * Writes a string to a DataView at the specified offset.
+     *
+     * @internal
+     */
+    private _writeString;
+    /**
+     * Converts an AudioBuffer to a Float32Array.
+     *
+     * @internal
+     */
+    private _interleave;
+    /**
+     * Creates an HTMLAudioElement whose source is the specified Blob.
+     *
+     * @internal
+     */
+    private _renderAudioElement;
+    /**
+     * Creates an Object URL for the specified Blob.
+     *
+     * @internal
+     */
+    private _renderURL;
+}

system/tts_generator/crunker.esm.js

@@ -0,0 +1,2 @@
+var e={d:(t,n)=>{for(var r in n)e.o(n,r)&&!e.o(t,r)&&Object.defineProperty(t,r,{enumerable:!0,get:n[r]})},o:(e,t)=>Object.prototype.hasOwnProperty.call(e,t)},t={};function n(e){return n="function"==typeof Symbol&&"symbol"==typeof Symbol.iterator?function(e){return typeof e}:function(e){return e&&"function"==typeof Symbol&&e.constructor===Symbol&&e!==Symbol.prototype?"symbol":typeof e},n(e)}function r(e){return function(e){if(Array.isArray(e))return a(e)}(e)||function(e){if("undefined"!=typeof Symbol&&null!=e[Symbol.iterator]||null!=e["@@iterator"])return Array.from(e)}(e)||function(e,t){if(!e)return;if("string"==typeof e)return a(e,t);var n=Object.prototype.toString.call(e).slice(8,-1);"Object"===n&&e.constructor&&(n=e.constructor.name);if("Map"===n||"Set"===n)return Array.from(e);if("Arguments"===n||/^(?:Ui|I)nt(?:8|16|32)(?:Clamped)?Array$/.test(n))return a(e,t)}(e)||function(){throw new TypeError("Invalid attempt to spread non-iterable instance.\nIn order to be iterable, non-array objects must have a [Symbol.iterator]() method.")}()}function a(e,t){(null==t||t>e.length)&&(t=e.length);for(var n=0,r=new Array(t);n<t;n++)r[n]=e[n];return r}function o(e,t){if(!(e instanceof t))throw new TypeError("Cannot call a class as a function")}function i(e,t){for(var r=0;r<t.length;r++){var a=t[r];a.enumerable=a.enumerable||!1,a.configurable=!0,"value"in a&&(a.writable=!0),Object.defineProperty(e,(o=a.key,i=void 0,i=function(e,t){if("object"!==n(e)||null===e)return e;var r=e[Symbol.toPrimitive];if(void 0!==r){var a=r.call(e,t||"default");if("object"!==n(a))return a;throw new TypeError("@@toPrimitive must return a primitive value.")}return("string"===t?String:Number)(e)}(o,"string"),"symbol"===n(i)?i:String(i)),a)}var o,i}e.d(t,{Z:()=>u});var u=function(){function e(){var t=arguments.length>0&&void 0!==arguments[0]?arguments[0]:{},n=t.sampleRate;o(this,e),this._context=this._createContext(n),n||(n=this._context.sampleRate),this._sampleRate=n}var t,n,a;return t=e,n=[{key:"_createContext",value:function(){var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:44100;return window.AudioContext=window.AudioContext||window.webkitAudioContext||window.mozAudioContext,new AudioContext({sampleRate:e})}},{key:"context",get:function(){return this._context}},{key:"fetchAudio",value:async function(){for(var e=this,t=arguments.length,n=new Array(t),r=0;r<t;r++)n[r]=arguments[r];return await Promise.all(n.map((async function(t){var n;return n=t instanceof File||t instanceof Blob?await t.arrayBuffer():await fetch(t).then((function(e){return e.headers.has("Content-Type")&&!e.headers.get("Content-Type").includes("audio/")&&console.warn("Crunker: Attempted to fetch an audio file, but its MIME type is `".concat(e.headers.get("Content-Type").split(";")[0],"`. We'll try and continue anyway. (file: \"").concat(t,'")')),e.arrayBuffer()})),await e._context.decodeAudioData(n)})))}},{key:"mergeAudio",value:function(e){var t=this._context.createBuffer(this._maxNumberOfChannels(e),this._sampleRate*this._maxDuration(e),this._sampleRate);return e.forEach((function(e){for(var n=0;n<e.numberOfChannels;n++){for(var r=t.getChannelData(n),a=e.getChannelData(n),o=e.getChannelData(n).length-1;o>=0;o--)r[o]+=a[o];t.getChannelData(n).set(r)}})),t}},{key:"concatAudio",value:function(e){var t=this._context.createBuffer(this._maxNumberOfChannels(e),this._totalLength(e),this._sampleRate),n=0;return e.forEach((function(e){for(var r=0;r<e.numberOfChannels;r++)t.getChannelData(r).set(e.getChannelData(r),n);n+=e.length})),t}},{key:"padAudio",value:function(e){var t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:0,n=arguments.length>2&&void 0!==arguments[2]?arguments[2]:0;if(0===n)return e;if(t<0)throw new Error('Crunker: Parameter "padStart" in padAudio must be positive');if(n<0)throw new Error('Crunker: Parameter "seconds" in padAudio must be positive');for(var r=this._context.createBuffer(e.numberOfChannels,Math.ceil(e.length+n*e.sampleRate),e.sampleRate),a=0;a<e.numberOfChannels;a++){var o=e.getChannelData(a);r.getChannelData(a).set(o.subarray(0,Math.ceil(t*e.sampleRate)+1),0),r.getChannelData(a).set(o.subarray(Math.ceil(t*e.sampleRate)+2,r.length+1),Math.ceil((t+n)*e.sampleRate))}return r}},{key:"sliceAudio",value:function(e,t,n){var r=arguments.length>3&&void 0!==arguments[3]?arguments[3]:0,a=arguments.length>4&&void 0!==arguments[4]?arguments[4]:0;if(t>=n)throw new Error('Crunker: "start" time should be less than "end" time in sliceAudio method');for(var o=Math.round((n-t)*this._sampleRate),i=Math.round(t*this._sampleRate),u=this._context.createBuffer(e.numberOfChannels,o,this._sampleRate),l=0;l<e.numberOfChannels;l++)for(var s=e.getChannelData(l),c=u.getChannelData(l),f=0;f<o;f++)c[f]=s[i+f],f<r*this._sampleRate&&(c[f]*=f/(r*this._sampleRate)),f>o-a*this._sampleRate&&(c[f]*=(o-f)/(a*this._sampleRate));return u}},{key:"play",value:function(e){var t=this._context.createBufferSource();return t.buffer=e,t.connect(this._context.destination),t.start(),Line truncated
+//# sourceMappingURL=crunker.esm.js.map

system/tts_generator/crunker.esm.js.map

@@ -0,0 +1 @@
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truncated

system/tts_generator/howler.min.js

@@ -0,0 +1,4 @@
+/*! howler.js v2.2.4 | (c) 2013-2020, James Simpson of GoldFire Studios | MIT License | howlerjs.com */
+!function(){"use strict";var e=function(){this.init()};e.prototype={init:function(){var e=this||n;return e._counter=1e3,e._html5AudioPool=[],e.html5PoolSize=10,e._codecs={},e._howls=[],e._muted=!1,e._volume=1,e._canPlayEvent="canplaythrough",e._navigator="undefined"!=typeof window&&window.navigator?window.navigator:null,e.masterGain=null,e.noAudio=!1,e.usingWebAudio=!0,e.autoSuspend=!0,e.ctx=null,e.autoUnlock=!0,e._setup(),e},volume:function(e){var o=this||n;if(e=parseFloat(e),o.ctx||_(),void 0!==e&&e>=0&&e<=1){if(o._volume=e,o._muted)return o;o.usingWebAudio&&o.masterGain.gain.setValueAtTime(e,n.ctx.currentTime);for(var t=0;t<o._howls.length;t++)if(!o._howls[t]._webAudio)for(var r=o._howls[t]._getSoundIds(),a=0;a<r.length;a++){var u=o._howls[t]._soundById(r[a]);u&&u._node&&(u._node.volume=u._volume*e)}return o}return o._volume},mute:function(e){var o=this||n;o.ctx||_(),o._muted=e,o.usingWebAudio&&o.masterGain.gain.setValueAtTime(e?0:o._volume,n.ctx.currentTime);for(var t=0;t<o._howls.length;t++)if(!o._howls[t]._webAudio)for(var r=o._howls[t]._getSoundIds(),a=0;a<r.length;a++){var u=o._howls[t]._soundById(r[a]);u&&u._node&&(u._node.muted=!!e||u._muted)}return o},stop:function(){for(var e=this||n,o=0;o<e._howls.length;o++)e._howls[o].stop();return e},unload:function(){for(var e=this||n,o=e._howls.length-1;o>=0;o--)e._howls[o].unload();return e.usingWebAudio&&e.ctx&&void 0!==e.ctx.close&&(e.ctx.close(),e.ctx=null,_()),e},codecs:function(e){return(this||n)._codecs[e.replace(/^x-/,"")]},_setup:function(){var e=this||n;if(e.state=e.ctx?e.ctx.state||"suspended":"suspended",e._autoSuspend(),!e.usingWebAudio)if("undefined"!=typeof Audio)try{var o=new Audio;void 0===o.oncanplaythrough&&(e._canPlayEvent="canplay")}catch(n){e.noAudio=!0}else e.noAudio=!0;try{var o=new Audio;o.muted&&(e.noAudio=!0)}catch(e){}return e.noAudio||e._setupCodecs(),e},_setupCodecs:function(){var e=this||n,o=null;try{o="undefined"!=typeof Audio?new Audio:null}catch(n){return e}if(!o||"function"!=typeof o.canPlayType)return e;var t=o.canPlayType("audio/mpeg;").replace(/^no$/,""),r=e._navigator?e._navigator.userAgent:"",a=r.match(/OPR\/(\d+)/g),u=a&&parseInt(a[0].split("/")[1],10)<33,d=-1!==r.indexOf("Safari")&&-1===r.indexOf("Chrome"),i=r.match(/Version\/(.*?) /),_=d&&i&&parseInt(i[1],10)<15;return e._codecs={mp3:!(u||!t&&!o.canPlayType("audio/mp3;").replace(/^no$/,"")),mpeg:!!t,opus:!!o.canPlayType('audio/ogg; codecs="opus"').replace(/^no$/,""),ogg:!!o.canPlayType('audio/ogg; codecs="vorbis"').replace(/^no$/,""),oga:!!o.canPlayType('audio/ogg; codecs="vorbis"').replace(/^no$/,""),wav:!!(o.canPlayType('audio/wav; codecs="1"')||o.canPlayType("audio/wav")).replace(/^no$/,""),aac:!!o.canPlayType("audio/aac;").replace(/^no$/,""),caf:!!o.canPlayType("audio/x-caf;").replace(/^no$/,""),m4a:!!(o.canPlayType("audio/x-m4a;")||o.canPlayType("audio/m4a;")||o.canPlayType("audio/aac;")).replace(/^no$/,""),m4b:!!(o.canPlayType("audio/x-m4b;")||o.canPlayType("audio/m4b;")||o.canPlayType("audio/aac;")).replace(/^no$/,""),mp4:!!(o.canPlayType("audio/x-mp4;")||o.canPlayType("audio/mp4;")||o.canPlayType("audio/aac;")).replace(/^no$/,""),weba:!(_||!o.canPlayType('audio/webm; codecs="vorbis"').replace(/^no$/,"")),webm:!(_||!o.canPlayType('audio/webm; codecs="vorbis"').replace(/^no$/,"")),dolby:!!o.canPlayType('audio/mp4; codecs="ec-3"').replace(/^no$/,""),flac:!!(o.canPlayType("audio/x-flac;")||o.canPlayType("audio/flac;")).replace(/^no$/,"")},e},_unlockAudio:function(){var e=this||n;if(!e._audioUnlocked&&e.ctx){e._audioUnlocked=!1,e.autoUnlock=!1,e._mobileUnloaded||44100===e.ctx.sampleRate||(e._mobileUnloaded=!0,e.unload()),e._scratchBuffer=e.ctx.createBuffer(1,1,22050);var o=function(n){for(;e._html5AudioPool.length<e.html5PoolSize;)try{var t=new Audio;t._unlocked=!0,e._releaseHtml5Audio(t)}catch(n){e.noAudio=!0;break}for(var r=0;r<e._howls.length;r++)if(!e._howls[r]._webAudio)for(var a=e._howls[r]._getSoundIds(),u=0;u<a.length;u++){var d=e._howls[r]._soundById(a[u]);d&&d._node&&!d._node._unlocked&&(d._node._unlocked=!0,d._node.load())}e._autoResume();var i=e.ctx.createBufferSource();i.buffer=e._scratchBuffer,i.connect(e.ctx.destination),void 0===i.start?i.noteOn(0):i.start(0),"function"==typeof e.ctx.resume&&e.ctx.resume(),i.onended=function(){i.disconnect(0),e._audioUnlocked=!0,document.removeEventListener("touchstart",o,!0),document.removeEventListener("touchend",o,!0),document.removeEventListener("click",o,!0),document.removeEventListener("keydown",o,!0);for(var n=0;n<e._howls.length;n++)e._howls[n]._emit("unlock")}};return document.addEventListener("touchstart",o,!0),document.addEventListener("touchend",o,!0),document.addEventListener("click",o,!0),document.addEventListener("keydown",o,!0),e}},_obtainHtml5Audio:function(){var e=this||n;if(e._html5AudioPool.length)return e._html5AudioPool.pop();var o=(new Audio).play();return o&&"undefined"!=typeof Promise&&(o instanceof Promise||"function"==typeof o.then)&&o.catch(function(){console.warn("HTML5 Audio pool eLine truncated
+/*! Spatial Plugin */
+!function(){"use strict";HowlerGlobal.prototype._pos=[0,0,0],HowlerGlobal.prototype._orientation=[0,0,-1,0,1,0],HowlerGlobal.prototype.stereo=function(e){var n=this;if(!n.ctx||!n.ctx.listener)return n;for(var t=n._howls.length-1;t>=0;t--)n._howls[t].stereo(e);return n},HowlerGlobal.prototype.pos=function(e,n,t){var r=this;return r.ctx&&r.ctx.listener?(n="number"!=typeof n?r._pos[1]:n,t="number"!=typeof t?r._pos[2]:t,"number"!=typeof e?r._pos:(r._pos=[e,n,t],void 0!==r.ctx.listener.positionX?(r.ctx.listener.positionX.setTargetAtTime(r._pos[0],Howler.ctx.currentTime,.1),r.ctx.listener.positionY.setTargetAtTime(r._pos[1],Howler.ctx.currentTime,.1),r.ctx.listener.positionZ.setTargetAtTime(r._pos[2],Howler.ctx.currentTime,.1)):r.ctx.listener.setPosition(r._pos[0],r._pos[1],r._pos[2]),r)):r},HowlerGlobal.prototype.orientation=function(e,n,t,r,o,i){var a=this;if(!a.ctx||!a.ctx.listener)return a;var p=a._orientation;return n="number"!=typeof n?p[1]:n,t="number"!=typeof t?p[2]:t,r="number"!=typeof r?p[3]:r,o="number"!=typeof o?p[4]:o,i="number"!=typeof i?p[5]:i,"number"!=typeof e?p:(a._orientation=[e,n,t,r,o,i],void 0!==a.ctx.listener.forwardX?(a.ctx.listener.forwardX.setTargetAtTime(e,Howler.ctx.currentTime,.1),a.ctx.listener.forwardY.setTargetAtTime(n,Howler.ctx.currentTime,.1),a.ctx.listener.forwardZ.setTargetAtTime(t,Howler.ctx.currentTime,.1),a.ctx.listener.upX.setTargetAtTime(r,Howler.ctx.currentTime,.1),a.ctx.listener.upY.setTargetAtTime(o,Howler.ctx.currentTime,.1),a.ctx.listener.upZ.setTargetAtTime(i,Howler.ctx.currentTime,.1)):a.ctx.listener.setOrientation(e,n,t,r,o,i),a)},Howl.prototype.init=function(e){return function(n){var t=this;return t._orientation=n.orientation||[1,0,0],t._stereo=n.stereo||null,t._pos=n.pos||null,t._pannerAttr={coneInnerAngle:void 0!==n.coneInnerAngle?n.coneInnerAngle:360,coneOuterAngle:void 0!==n.coneOuterAngle?n.coneOuterAngle:360,coneOuterGain:void 0!==n.coneOuterGain?n.coneOuterGain:0,distanceModel:void 0!==n.distanceModel?n.distanceModel:"inverse",maxDistance:void 0!==n.maxDistance?n.maxDistance:1e4,panningModel:void 0!==n.panningModel?n.panningModel:"HRTF",refDistance:void 0!==n.refDistance?n.refDistance:1,rolloffFactor:void 0!==n.rolloffFactor?n.rolloffFactor:1},t._onstereo=n.onstereo?[{fn:n.onstereo}]:[],t._onpos=n.onpos?[{fn:n.onpos}]:[],t._onorientation=n.onorientation?[{fn:n.onorientation}]:[],e.call(this,n)}}(Howl.prototype.init),Howl.prototype.stereo=function(n,t){var r=this;if(!r._webAudio)return r;if("loaded"!==r._state)return r._queue.push({event:"stereo",action:function(){r.stereo(n,t)}}),r;var o=void 0===Howler.ctx.createStereoPanner?"spatial":"stereo";if(void 0===t){if("number"!=typeof n)return r._stereo;r._stereo=n,r._pos=[n,0,0]}for(var i=r._getSoundIds(t),a=0;a<i.length;a++){var p=r._soundById(i[a]);if(p){if("number"!=typeof n)return p._stereo;p._stereo=n,p._pos=[n,0,0],p._node&&(p._pannerAttr.panningModel="equalpower",p._panner&&p._panner.pan||e(p,o),"spatial"===o?void 0!==p._panner.positionX?(p._panner.positionX.setValueAtTime(n,Howler.ctx.currentTime),p._panner.positionY.setValueAtTime(0,Howler.ctx.currentTime),p._panner.positionZ.setValueAtTime(0,Howler.ctx.currentTime)):p._panner.setPosition(n,0,0):p._panner.pan.setValueAtTime(n,Howler.ctx.currentTime)),r._emit("stereo",p._id)}}return r},Howl.prototype.pos=function(n,t,r,o){var i=this;if(!i._webAudio)return i;if("loaded"!==i._state)return i._queue.push({event:"pos",action:function(){i.pos(n,t,r,o)}}),i;if(t="number"!=typeof t?0:t,r="number"!=typeof r?-.5:r,void 0===o){if("number"!=typeof n)return i._pos;i._pos=[n,t,r]}for(var a=i._getSoundIds(o),p=0;p<a.length;p++){var s=i._soundById(a[p]);if(s){if("number"!=typeof n)return s._pos;s._pos=[n,t,r],s._node&&(s._panner&&!s._panner.pan||e(s,"spatial"),void 0!==s._panner.positionX?(s._panner.positionX.setValueAtTime(n,Howler.ctx.currentTime),s._panner.positionY.setValueAtTime(t,Howler.ctx.currentTime),s._panner.positionZ.setValueAtTime(r,Howler.ctx.currentTime)):s._panner.setPosition(n,t,r)),i._emit("pos",s._id)}}return i},Howl.prototype.orientation=function(n,t,r,o){var i=this;if(!i._webAudio)return i;if("loaded"!==i._state)return i._queue.push({event:"orientation",action:function(){i.orientation(n,t,r,o)}}),i;if(t="number"!=typeof t?i._orientation[1]:t,r="number"!=typeof r?i._orientation[2]:r,void 0===o){if("number"!=typeof n)return i._orientation;i._orientation=[n,t,r]}for(var a=i._getSoundIds(o),p=0;p<a.length;p++){var s=i._soundById(a[p]);if(s){if("number"!=typeof n)return s._orientation;s._orientation=[n,t,r],s._node&&(s._panner||(s._pos||(s._pos=i._pos||[0,0,-.5]),e(s,"spatial")),void 0!==s._panner.orientationX?(s._panner.orientationX.setValueAtTime(n,Howler.ctx.currentTime),s._panner.orientationY.setValueAtTime(t,Howler.ctx.currentTime),s._panner.orientationZ.setValueAtTime(r,Howler.ctx.currentTime)):s._panner.setOrientation(n,t,r)),i._emit("orientation",s._id)}}return i},Howl.prototype.pannerAttr=function(){var n,t,r,o=this,i=arguments;if(!o._webAudioLine truncated

system/tts_srt/tts_srt.py

@@ -0,0 +1,77 @@
+import json
+import argparse
+import soundfile as sf
+from pathlib import Path
+
+parser = argparse.ArgumentParser(description="Compare TTS output with the original text using detailed comparison.")
+parser.add_argument("--ttslistpath", help="Path to the ttsList.json file")
+parser.add_argument("--wavfilespath", help="Path to the wav outputs folder")
+args = parser.parse_args()
+
+if not args.ttslistpath:
+    parser.error("[AllTalk TTSSRT] Please specify the path to the ttslist.json file using the --ttslistpath argument.")
+if not args.wavfilespath:
+    parser.error("[AllTalk TTSSRT] Please specify the path to the wavs output folder file using the --wavfilespath argument.")
+
+json_file_path = Path(args.ttslistpath).resolve()
+audio_files_base_path = Path(args.wavfilespath).resolve()
+
+print(f"[AllTalk TTSSRT]")
+print("[AllTalk TTSSRT] \033[92mStarting SRT Subtitle generation:\033[0m")
+print("[AllTalk TTSSRT]")
+print("[AllTalk TTSSRT] \033[94mJSON file  :\033[92m", json_file_path, "\033[0m")
+print("[AllTalk TTSSRT] \033[94mWAV files  :\033[92m", audio_files_base_path, "\033[0m")
+print("[AllTalk TTSSRT]")
+
+# Function to convert time in seconds to SRT time format
+def format_srt_time(seconds):
+    hours = int(seconds // 3600)
+    minutes = int((seconds % 3600) // 60)
+    seconds = seconds % 60
+    milliseconds = int((seconds - int(seconds)) * 1000)
+    return f"{hours:02}:{minutes:02}:{int(seconds):02},{milliseconds:03}"
+
+# Load the JSON data
+with open(json_file_path, 'r') as json_file:
+    data = json.load(json_file)
+
+# Initialize start time and SRT lines
+start_time = 0.0
+srt_lines = []
+
+# Loop through the JSON data to build SRT entries
+for entry in data:
+    file_name = Path(entry['fileUrl']).name  # Get the file name from the URL
+    file_path = audio_files_base_path / file_name
+    print(f"[AllTalk TTSSRT] Processing file: {file_name}")
+
+    if not file_path.exists():
+        print(f"[AllTalk TTSSRT] Audio file does not exist: {file_path}")
+        continue
+
+    try:
+        # Use soundfile to read the duration of the WAV file
+        with sf.SoundFile(str(file_path), 'r') as f:
+            duration = len(f) / f.samplerate
+            end_time = start_time + duration
+            
+            # Format the SRT entry
+            start_timestamp = format_srt_time(start_time)
+            end_timestamp = format_srt_time(end_time)
+            srt_lines.append(f"{len(srt_lines)+1}\n{start_timestamp} --> {end_timestamp}\n{entry['text']}\n")
+            
+            # Update the start time for the next entry
+            start_time = end_time
+    except RuntimeError as e:
+        print(f"[AllTalk TTSSRT] Error reading {file_path}: {e}")
+
+# Join all SRT lines into the final SRT content
+srt_content = "\n".join(srt_lines)
+
+# Save the SRT content to a file
+srt_file_path = audio_files_base_path / "subtitles.srt"
+with open(srt_file_path, "w") as srt_file:
+    srt_file.write(srt_content)
+
+print("[AllTalk TTSSRT]")
+print(f"[AllTalk TTSSRT] \033[94mSRT file created at \033[0m{srt_file_path}")

system/word_addin/1995fcd6d39cade7d871.js

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+/*! For license information please see 1995fcd6d39cade7d871.js.LICENSE.txt */
+function _typeof(t){return _typeof="function"==typeof Symbol&&"symbol"==typeof Symbol.iterator?function(t){return typeof t}:function(t){return t&&"function"==typeof Symbol&&t.constructor===Symbol&&t!==Symbol.prototype?"symbol":typeof t},_typeof(t)}function _regeneratorRuntime(){"use strict";_regeneratorRuntime=function(){return e};var t,e={},r=Object.prototype,n=r.hasOwnProperty,o=Object.defineProperty||function(t,e,r){t[e]=r.value},i="function"==typeof Symbol?Symbol:{},a=i.iterator||"@@iterator",c=i.asyncIterator||"@@asyncIterator",u=i.toStringTag||"@@toStringTag";function l(t,e,r){return Object.defineProperty(t,e,{value:r,enumerable:!0,configurable:!0,writable:!0}),t[e]}try{l({},"")}catch(t){l=function(t,e,r){return t[e]=r}}function f(t,e,r,n){var i=e&&e.prototype instanceof m?e:m,a=Object.create(i.prototype),c=new G(n||[]);return o(a,"_invoke",{value:S(t,r,c)}),a}function s(t,e,r){try{return{type:"normal",arg:t.call(e,r)}}catch(t){return{type:"throw",arg:t}}}e.wrap=f;var 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system/word_addin/1995fcd6d39cade7d871.js.LICENSE.txt

@@ -0,0 +1 @@
+/*! regenerator-runtime -- Copyright (c) 2014-present, Facebook, Inc. -- license (MIT): https://github.com/facebook/regenerator/blob/main/LICENSE */

system/word_addin/1fda685b81e1123773f6.css

@@ -0,0 +1,80 @@
+/* 
+ * Copyright (c) Microsoft Corporation. All rights reserved. Licensed under the MIT license.
+ * See LICENSE in the project root for license information.
+ */
+
+ html,
+ body {
+     width: 100%;
+     height: 100%;
+     margin: 0;
+     padding: 0;
+ }
+ 
+ ul {
+     margin: 0;
+     padding: 0;
+ }
+ 
+ .ms-welcome__header {
+    padding: 20px;
+    padding-bottom: 30px;
+    padding-top: 100px;
+    display: -webkit-flex;
+    display: flex;
+    -webkit-flex-direction: column;
+    flex-direction: column;
+    align-items: center;
+ }
+
+ .ms-welcome__main {
+    display: -webkit-flex;
+    display: flex;
+    -webkit-flex-direction: column;
+    flex-direction: column;
+    -webkit-flex-wrap: nowrap;
+    flex-wrap: nowrap;
+    -webkit-align-items: center;
+    align-items: center;
+    -webkit-flex: 1 0 0;
+    flex: 1 0 0;
+    padding: 10px 20px;
+ }
+ 
+ .ms-welcome__main > h2 {
+     width: 100%;
+     text-align: center;
+ }
+ 
+ .ms-welcome__features {
+     list-style-type: none;
+     margin-top: 20px;
+ }
+ 
+ .ms-welcome__features.ms-List .ms-ListItem {
+     padding-bottom: 20px;
+     display: -webkit-flex;
+     display: flex;
+ }
+ 
+ .ms-welcome__features.ms-List .ms-ListItem > .ms-Icon {
+     margin-right: 10px;
+ }
+ 
+ .ms-welcome__action.ms-Button--hero {
+     margin-top: 30px;
+ }
+ 
+.ms-Button.ms-Button--hero .ms-Button-label {
+  color: #0078d7;
+}
+
+.ms-Button.ms-Button--hero:hover .ms-Button-label,
+.ms-Button.ms-Button--hero:focus .ms-Button-label{
+  color: #005a9e;
+  cursor: pointer;
+}
+
+b {
+    font-weight: bold;
+}

system/word_addin/commands.html

@@ -0,0 +1 @@
+<!doctype html><html><head><meta charset="UTF-8"/><meta http-equiv="X-UA-Compatible" content="IE=Edge"/><script src="https://appsforoffice.microsoft.com/lib/1.1/hosted/office.js"></script><script defer="defer" src="polyfill.js"></script><script defer="defer" src="commands.js"></script></head><body></body></html>

system/word_addin/commands.js

@@ -0,0 +1,2 @@
+!function(){var e={};e.g=function(){if("object"==typeof globalThis)return globalThis;try{return this||new Function("return this")()}catch(e){if("object"==typeof window)return window}}(),Office.onReady((function(){})),("undefined"!=typeof self?self:"undefined"!=typeof window?window:void 0!==e.g?e.g:void 0).action=function(e){var n={type:Office.MailboxEnums.ItemNotificationMessageType.InformationalMessage,message:"Performed action.",icon:"Icon.80x80",persistent:!0};Office.context.mailbox.item.notificationMessages.replaceAsync("action",n),e.completed()}}();
+//# sourceMappingURL=commands.js.map

system/word_addin/commands.js.map

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+{"version":3,"file":"commands.js","mappings":"YACA,IAAIA,EAAsB,CAAC,ECD3BA,EAAoBC,EAAI,WACvB,GAA0B,iBAAfC,WAAyB,OAAOA,WAC3C,IACC,OAAOC,MAAQ,IAAIC,SAAS,cAAb,EAChB,CAAE,MAAOC,GACR,GAAsB,iBAAXC,OAAqB,OAAOA,MACxC,CACA,CAPuB,GCOxBC,OAAOC,SAAQ,WACb,KAuBuB,oBAATC,KACVA,KACkB,oBAAXH,OACPA,YACkB,IAAXI,EAAAA,EACPA,EAAAA,OACAC,GAMJC,OA5BF,SAAgBC,GACd,IAAMC,EAAU,CACdC,KAAMR,OAAOS,aAAaC,4BAA4BC,qBACtDJ,QAAS,oBACTK,KAAM,aACNC,YAAY,GAIdb,OAAOc,QAAQC,QAAQC,KAAKC,qBAAqBC,aAAa,SAAUX,GAGxED,EAAMa,WACR,C","sources":["webpack://office-addin-taskpane-js/webpack/bootstrap","webpack://office-addin-taskpane-js/webpack/runtime/global","webpack://office-addin-taskpane-js/./src/commands/commands.js"],"sourcesContent":["// The require scope\nvar __webpack_require__ = {};\n\n","__webpack_require__.g = (function() {\n\tif (typeof globalThis === 'object') return globalThis;\n\ttry {\n\t\treturn this || new Function('return this')();\n\t} catch (e) {\n\t\tif (typeof window === 'object') return window;\n\t}\n})();","/*\n * Copyright (c) Microsoft Corporation. All rights reserved. Licensed under the MIT license.\n * See LICENSE in the project root for license information.\n */\n\n/* global global, Office, self, window */\n\nOffice.onReady(() => {\n  // If needed, Office.js is ready to be called\n});\n\n/**\n * Shows a notification when the add-in command is executed.\n * @param event {Office.AddinCommands.Event}\n */\nfunction action(event) {\n  const message = {\n    type: Office.MailboxEnums.ItemNotificationMessageType.InformationalMessage,\n    message: \"Performed action.\",\n    icon: \"Icon.80x80\",\n    persistent: true,\n  };\n\n  // Show a notification message\n  Office.context.mailbox.item.notificationMessages.replaceAsync(\"action\", message);\n\n  // Be sure to indicate when the add-in command function is complete\n  event.completed();\n}\n\nfunction getGlobal() {\n  return typeof self !== \"undefined\"\n    ? self\n    : typeof window !== \"undefined\"\n    ? window\n    : typeof global !== \"undefined\"\n    ? global\n    : undefined;\n}\n\nconst g = getGlobal();\n\n// The add-in command functions need to be available in global scope\ng.action = action;\n"],"names":["__webpack_require__","g","globalThis","this","Function","e","window","Office","onReady","self","global","undefined","action","event","message","type","MailboxEnums","ItemNotificationMessageType","InformationalMessage","icon","persistent","context","mailbox","item","notificationMessages","replaceAsync","completed"],"sourceRoot":""}

system/word_addin/manifest.xml

@@ -0,0 +1,79 @@
+<?xml version="1.0" encoding="UTF-8" standalone="yes"?>
+<OfficeApp xmlns="http://schemas.microsoft.com/office/appforoffice/1.1" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:bt="http://schemas.microsoft.com/office/officeappbasictypes/1.0" xmlns:ov="http://schemas.microsoft.com/office/taskpaneappversionoverrides" xsi:type="TaskPaneApp">
+  <Id>68b6ad53-4f72-42a8-a971-a9643c2f409a</Id>
+  <Version>1.0.0.0</Version>
+  <ProviderName>AllTalk</ProviderName>
+  <DefaultLocale>en-US</DefaultLocale>
+  <DisplayName DefaultValue="AllTalk TTS"/>
+  <Description DefaultValue="Enhance your document creation with AllTalk TTS's advanced text-to-voice functionality. Requires connection to AllTalk server."/>
+  <IconUrl DefaultValue="http://127.0.0.1:7851/api/word_addin/assets/icon-32.png"/>
+  <HighResolutionIconUrl DefaultValue="http://127.0.0.1:7851/api/word_addin/assets/icon-64.png"/>
+  <SupportUrl DefaultValue="https://github.com/erew123/alltalk_tts/issues"/>
+  <AppDomains>
+    <AppDomain>https://www.contoso.com</AppDomain>
+  </AppDomains>
+  <Hosts>
+    <Host Name="Document"/>
+  </Hosts>
+  <DefaultSettings>
+    <SourceLocation DefaultValue="http://127.0.0.1:7851/api/word_addin/taskpane.html"/>
+  </DefaultSettings>
+  <Permissions>ReadWriteDocument</Permissions>
+  <VersionOverrides xmlns="http://schemas.microsoft.com/office/taskpaneappversionoverrides" xsi:type="VersionOverridesV1_0">
+    <Hosts>
+      <Host xsi:type="Document">
+        <DesktopFormFactor>
+          <!-- You can add GetStarted information here if needed -->
+          <FunctionFile resid="Commands.Url"/>
+          <ExtensionPoint xsi:type="PrimaryCommandSurface">
+            <OfficeTab id="TabHome">
+              <Group id="AllTalkGroup">
+                <Label resid="AllTalkGroup.Label"/>
+                <Icon>
+                  <bt:Image size="16" resid="Icon.16x16"/>
+                  <bt:Image size="32" resid="Icon.32x32"/>
+                  <bt:Image size="80" resid="Icon.80x80"/>
+                </Icon>
+                <Control xsi:type="Button" id="AllTalkTaskpaneButton">
+                  <Label resid="AllTalkTaskpaneButton.Label"/>
+                  <Supertip>
+                    <Title resid="AllTalkTaskpaneButton.Label"/>
+                    <Description resid="AllTalkTaskpaneButton.Tooltip"/>
+                  </Supertip>
+                  <Icon>
+                    <bt:Image size="16" resid="Icon.16x16"/>
+                    <bt:Image size="32" resid="Icon.32x32"/>
+                    <bt:Image size="80" resid="Icon.80x80"/>
+                  </Icon>
+                  <Action xsi:type="ShowTaskpane">
+                    <TaskpaneId>ButtonId1</TaskpaneId>
+                    <SourceLocation resid="Taskpane.Url"/>
+                  </Action>
+                </Control>
+              </Group>
+            </OfficeTab>
+          </ExtensionPoint>
+        </DesktopFormFactor>
+      </Host>
+    </Hosts>
+    <Resources>
+      <bt:Images>
+        <bt:Image id="Icon.16x16" DefaultValue="http://127.0.0.1:7851/api/word_addin/assets/icon-16.png"/>
+        <bt:Image id="Icon.32x32" DefaultValue="http://127.0.0.1:7851/api/word_addin/assets/icon-32.png"/>
+        <bt:Image id="Icon.80x80" DefaultValue="http://127.0.0.1:7851/api/word_addin/assets/icon-80.png"/>
+      </bt:Images>
+      <bt:Urls>
+        <!-- Ensure that these URLs are pointing to valid locations -->
+        <bt:Url id="Commands.Url" DefaultValue="http://127.0.0.1:7851/api/word_addin/commands.html"/>
+        <bt:Url id="Taskpane.Url" DefaultValue="http://127.0.0.1:7851/api/word_addin/taskpane.html"/>
+      </bt:Urls>
+      <bt:ShortStrings>
+        <bt:String id="AllTalkGroup.Label" DefaultValue="AllTalk Controls"/>
+        <bt:String id="AllTalkTaskpaneButton.Label" DefaultValue="Open AllTalk"/>
+      </bt:ShortStrings>
+      <bt:LongStrings>
+        <bt:String id="AllTalkTaskpaneButton.Tooltip" DefaultValue="Open the AllTalk task pane to start using the add-in."/>
+      </bt:LongStrings>
+    </Resources>
+  </VersionOverrides>
+</OfficeApp>

system/word_addin/polyfill.js

@@ -0,0 +1,2 @@
+!function(){var t={35666:function(t){var r=function(t){"use strict";var r,e=Object.prototype,n=e.hasOwnProperty,i=Object.defineProperty||function(t,r,e){t[r]=e.value},o="function"==typeof Symbol?Symbol:{},u=o.iterator||"@@iterator",a=o.asyncIterator||"@@asyncIterator",c=o.toStringTag||"@@toStringTag";function s(t,r,e){return Object.defineProperty(t,r,{value:e,enumerable:!0,configurable:!0,writable:!0}),t[r]}try{s({},"")}catch(t){s=function(t,r,e){return t[r]=e}}function f(t,r,e,n){var o=r&&r.prototype instanceof y?r:y,u=Object.create(o.prototype),a=new j(n||[]);return i(u,"_invoke",{value:R(t,e,a)}),u}function l(t,r,e){try{return{type:"normal",arg:t.call(r,e)}}catch(t){return{type:"throw",arg:t}}}t.wrap=f;var h="suspendedStart",p="suspendedYield",v="executing",g="completed",d={};function y(){}function m(){}function b(){}var x={};s(x,u,(function(){return this}));var w=Object.getPrototypeOf,E=w&&w(w(P([])));E&&E!==e&&n.call(E,u)&&(x=E);var 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system/word_addin/taskpane.html

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+<!doctype html>
+<html>
+
+<head>
+    <meta charset="UTF-8" />
+    <meta http-equiv="X-UA-Compatible" content="IE=Edge" />
+    <meta name="viewport" content="width=device-width,initial-scale=1">
+    <title>AllTalk TTS Add-in</title>
+    <script src="https://appsforoffice.microsoft.com/lib/1.1/hosted/office.js"></script>
+    <link rel="stylesheet"
+        href="https://static2.sharepointonline.com/files/fabric/office-ui-fabric-core/11.0.0/css/fabric.min.css" />
+    <link href="1fda685b81e1123773f6.css" rel="stylesheet" />
+    <style>
+        label {
+            font-weight: 700;
+            display: block;
+            margin-top: 10px
+        }
+
+        select {
+            width: 100%;
+            padding: 5px
+        }
+
+        .nice-button {
+            background-color: #0078d4;
+            color: #fff;
+            padding: 10px 20px;
+            border: none;
+            border-radius: 5px;
+            cursor: pointer;
+            font-size: 16px;
+            transition: background-color .3s ease
+        }
+
+        .nice-button:hover {
+            background-color: #005a9e
+        }
+
+        #audioSource {
+            width: 300px;
+            height: 50px
+        }
+
+        .input-container {
+            display: flex;
+            flex-direction: column;
+            margin-right: 10px
+        }
+
+        .input-group {
+            display: flex;
+            justify-content: start;
+            align-items: flex-end
+        }
+
+        .input-group>.input-container {
+            flex: 1
+        }
+
+        input {
+            width: 100%
+        }
+    </style>
+    <script defer="defer" src="polyfill.js"></script>
+    <script defer="defer" src="taskpane.js"></script>
+</head>
+
+<body class="ms-font-m ms-welcome ms-Fabric">
+    <header class="ms-welcome__header ms-bgColor-neutralLighter"><img width="90" height="90"
+            src="http://127.0.0.1:7851/api/word_addin/assets/logo-filled.png" alt="AllTalk TTS" title="AllTalk TTS" />
+        <h1 class="ms-font-su">AllTalk TTS</h1>
+    </header>
+    <main class="ms-welcome__main"><textarea id="text" rows="4" placeholder="Enter text here"
+            style="display:none"></textarea> <label for="voice">Voice:</label> <select id="voice" name="voice"
+            required></select> <label for="language">Language:</label> <select id="language" name="language"
+            value="English" required>
+            <option value="en" selected="selected">English</option>
+            <option value="ar">Arabic</option>
+            <option value="zh-cn">Chinese</option>
+            <option value="cs">Czech</option>
+            <option value="nl">Dutch</option>
+            <option value="fr">French</option>
+            <option value="de">German</option>
+            <option value="hu">Hungarian</option>
+            <option value="it">Italian</option>
+            <option value="ja">Japanese</option>
+            <option value="ko">Korean</option>
+            <option value="pl">Polish</option>
+            <option value="pt">Portuguese</option>
+            <option value="ru">Russian</option>
+            <option value="es">Spanish</option>
+            <option value="tr">Turkish</option>
+        </select><br><audio id="audioSource" controls autoplay></audio><br><button id="sendTextButton"
+            class="nice-button">Send Text to TTS</button><br><br><br><br>
+        <div class="input-group">
+            <div class="input-container"><label for="serverIP">Server IP:</label> <input id="serverIP" name="serverIP"
+                    value="127.0.0.1" required></div>
+            <div class="input-container"><label for="portNumber">Port Number:</label> <input type="number"
+                    id="portNumber" name="portNumber" value="7851" required></div>
+        </div>
+    </main>
+    <script src="1995fcd6d39cade7d871.js"></script>
+</body>
+
+</html>

system/word_addin/taskpane.js

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system/word_addin/taskpane.js.LICENSE.txt

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voices/Clint_Eastwood CC3.txt

@@ -9,4 +9,6 @@ Author	BBC
 This file is licensed under the Creative Commons Attribution 3.0 Unported license.
 https://creativecommons.org/licenses/by/3.0/deed.en
 
-Downsampled to 22050hz, mono and cut shorter
+Downsampled to 22050hz, mono and cut shorter.
+
+This license applies to both the original file ( «Clint_Eastwood CC3.wav» ) and it's derivative, the enhanced file ( «Clint_Eastwood (enhanced)CC3.wav» ).