Updated to deal with Gradio 4.xx versions

Set API Local to use float as Transformers demands it

.github/FUNDING.yml

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

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

@@ -1,13 +1,14 @@
 ---
-name: Bug report/Support request
-about: Create a report to help us improve
+name: Support Request/Issue
+about: Use this to create a support request or report a bug/issue
 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 generate a diagnostics report and upload the "diagnostics.log".
+🔴 Please generate a diagnostics report and upload the "diagnostics.log" as this helps me understand your configuration.
 
 https://github.com/erew123/alltalk_tts/tree/main?#-how-to-make-a-diagnostics-report-file
 

.github/ISSUE_TEMPLATE/feature_request.md

@@ -1,6 +1,6 @@
 ---
 name: Feature request
-about: Suggest an idea for this project
+about: Use this to create a Feature request
 title: ''
 labels: ''
 assignees: ''

.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 }}

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 +1,19 @@
+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 libaio-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 --no-deps -r system/requirements/requirements_docker.txt && \
+    pip install --no-cache-dir deepspeed
+
+EXPOSE 7851 7852
+RUN chmod +x launch.sh
+ENTRYPOINT ["sh", "-c", "./launch.sh"]

atsetup.bat

@@ -0,0 +1,659 @@
+@echo off
+cd /D "%~dp0"
+setlocal enabledelayedexpansion
+@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"
+
+echo "%CD%"| findstr /C:" " >nul &&  echo. && echo    %L_BLUE%ALLTALK WINDOWS SETUP UTILITY%RESET% && echo. &&  echo. &&  echo    You are trying to install AllTalk in a folder that has a space in the folder path e.g. && echo. && echo       C:\%L_RED%program files%RESET%\alltalk_tts && echo.	&& echo    This causes errors with Conda and Python scripts. Please follow this link for reference: &&  echo. && echo      %L_CYAN%https://docs.anaconda.com/free/working-with-conda/reference/faq/#installing-anaconda%RESET% && echo. && echo    Please use a folder path that has no spaces in it e.g. && echo. && echo       C:\myfiles\alltalk_tts\ && echo. && echo. && pause && goto :end
+
+@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 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 EndStandalone
+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    Have you started your Text-gen-webui Python environment
+    echo    with cmd_{yourOS} before running atsetup.bat?
+    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==2.2.2+cu121 torchaudio>=2.2.2+cu121 --upgrade --force-reinstall --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-14.0/deepspeed-0.14.0+ce78a63-cp311-cp311-win_amd64.whl
+echo Installing DeepSpeed...
+pip install deepspeed-0.14.0+ce78a63-cp311-cp311-win_amd64.whl
+del deepspeed-0.14.0+ce78a63-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==2.2.2+cu121 torchaudio>=2.2.2+cu121 --upgrade --force-reinstall --extra-index-url https://download.pytorch.org/whl/cu121
+echo Installing other requirements.
+echo.
+pip install -r system\requirements\requirements_standalone.txt
+C:/Windows/system32/curl.exe -LO https://github.com/erew123/alltalk_tts/releases/download/DeepSpeed-14.0/deepspeed-0.14.0+ce78a63-cp311-cp311-win_amd64.whl
+echo Installing DeepSpeed...
+pip install deepspeed-0.14.0+ce78a63-cp311-cp311-win_amd64.whl
+del deepspeed-0.14.0+ce78a63-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
+
+:EndStandalone
+echo Exiting AllTalk Setup Utility...
+echo.
+Echo    Remember, after installation you can....
+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.
+exit /b
+
+:End
+echo Exiting AllTalk Setup Utility...
+exit /b

atsetup.sh

@@ -0,0 +1,520 @@
+#!/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 "$0")"
+
+# Function to check if curl is installed
+check_curl() {
+    if ! command -v curl &> /dev/null; then
+        echo "curl is not available on this system. Please install curl then re-run the script https://curl.se/"
+        echo "or perform a manual installation of a Conda Python environment."
+        exit 1
+    fi
+}
+
+# Check if the current directory path contains a space
+containsSpace=false
+currentPath=$(pwd)
+if echo "$currentPath" | grep -q ' '; then
+    containsSpace=true
+fi
+
+if [ "$containsSpace" = true ]; then
+    echo
+    echo -e "    ${L_BLUE}ALLTALK LINUX SETUP UTILITY${NC}"
+    echo
+    echo
+    echo -e "    You are trying to install AllTalk in a folder that has a space in the"
+    echo -e "    folder path e.g."
+    echo 
+    echo -e "       /home/${L_RED}program files${NC}/alltalk_tts"
+    echo 
+    echo -e "    This causes errors with Conda and Python scripts. Please follow this"
+    echo -e "    link for reference:"
+    echo 
+    echo -e "      ${L_CYAN}https://docs.anaconda.com/free/working-with-conda/reference/faq/#installing-anaconda${NC}"
+    echo 
+    echo -e "    Please use a folder path that has no spaces in it e.g." 
+    echo 
+    echo -e "       /home/myfiles/alltalk_tts/"
+    echo 
+    echo
+    read -p "Press Enter to continue..." 
+    exit 1
+else
+    # Continue with the main menu
+    echo "Continue with the main menu."
+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 "${INSTALL_ENV_DIR}"
+    echo
+    echo "    Downloading and installing PyTorch. This step can take a long time"
+    echo "    depending on your internet connection and hard drive speed. Please"
+    echo "    be patient."
+    pip install torch>=2.2.1+cu121 torchaudio>=2.2.1+cu121 --upgrade --force-reinstall --extra-index-url https://download.pytorch.org/whl/cu121
+    echo
+    echo "    Installing additional requirements."
+    echo
+    pip install -r system/requirements/requirements_standalone.txt
+    # Create start_environment.sh to run AllTalk
+    cat << EOF > start_environment.sh
+#!/bin/bash
+cd "$(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 --upgrade --force-reinstall --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

@@ -8,12 +8,15 @@ try:
     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")
@@ -21,6 +24,8 @@ except ImportError as e:
     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:
@@ -29,24 +34,30 @@ except ImportError:
     import psutil
 
 def get_requirements_file():
-    requirements_files = glob.glob("requirements*.txt")
+    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 in enumerate(requirements_files, start=1):
-        print(f"{i}. {file}")
+    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 requirements_files[choice]
+        return str(requirements_files[choice])  # Return the full path as a string
     except (ValueError, IndexError):
-        return "requirements.txt"
+        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)
+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():
@@ -56,6 +67,22 @@ def get_gpu_info():
     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):
     for conn in psutil.net_connections():
@@ -73,6 +100,38 @@ def satisfies_wildcard(installed_version, required_version):
         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
@@ -88,6 +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:
@@ -123,6 +185,10 @@ def log_system_info():
     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:
@@ -146,52 +212,72 @@ def log_system_info():
             logging.info(f"NOTE {requirements_file} not found. Skipping version checks.")
 
     # Log and print information
-    logging.info(f"OS Version: {os_version}")
-    logging.info(f"Note: Windows 11 will list as build is 10.x.22xxx")
-    logging.info(f"Torch Version: {torch_version}")
-    logging.info(f"System RAM: {system_ram}")
-    logging.info(f"CUDA_HOME: {cuda_home}")
-    logging.info(f"Port Status: {port_status}")
-    logging.info(f"Python Version: {platform.python_version()}")
-    logging.info(f"Python Version Info: {python_version_info}")
-    logging.info(f"Python Executable: {python_executable}")
-    logging.info(f"Python Virtual Environment: {python_virtual_env} (Should be N/A when in Text-generation-webui Conda Python environment)")
-    logging.info(f"Conda Environment: {conda_env}")
+    logging.info(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 PATH Environment Variable:")
+    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:")
+        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(f"GPU Information:\n{gpu_info}")
-    logging.info("Package Versions:")
+            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"\n\033[94mOS Version:\033[0m \033[92m{os_version}\033[0m")
     print(f"\033[94mOS Ver note:\033[0m \033[92m(Windows 11 will say build is 10.x.22xxx)\033[0m")
-    print(f"\033[94mCUDA_HOME:\033[0m \033[92m{cuda_home}\033[0m")
     print(f"\033[94mSystem RAM:\033[0m \033[92m{system_ram}\033[0m")
-    print(f"\033[94mPort Status:\033[0m \033[92m{port_status}\033[0m")
-    print(f"\033[94mTorch Version:\033[0m \033[92m{torch_version}\033[0m")
+    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")
+    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 Version Info:\033[0m \033[92m{python_version_info}\033[0m")
     print(f"\033[94mPython Executable:\033[0m \033[92m{python_executable}\033[0m")
-    print(f"\033[94mPython Virtual Environment:\033[0m \033[92m{python_virtual_env}\033[0m (Should be N/A when in Text-generation-webui Conda Python environment)")
     print(f"\033[94mConda Environment:\033[0m \033[92m{conda_env}\033[0m")
     print(f"\n\033[94mPython Search Path:\033[0m")
     for path in search_path:
         print(f"  {path}")
-    print(f"\n\033[94mOS Search PATH Environment Variable:\033[0m")
-    for path in path_env.split(';'):
-        print(f"  {path}")
     if required_packages:  # Check if the dictionary is not empty
         print("\033[94m\nRequirements file package comparison:\033[0m")
         max_package_length = max(len(package) for package in required_packages.keys())
@@ -214,7 +300,14 @@ def log_system_info():
             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(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               
@@ -224,9 +317,9 @@ def log_system_info():
         """)
         print(explanation.strip())
     print("")
-    print(f"GPU Information:{gpu_info}")
-    print(f"\033[94mDiagnostic log created:\033[0m \033[92mdiagnostics.log\033[0m")
-    print(f"\033[94mPlease upload the log file with any support ticket.\033[0m")
+    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 +1,21 @@
+version: '3.8'
+services:
+  alltalk-tts:
+    image: alltalk:v1-9c
+    restart: unless-stopped
+    ports:
+      - "7851:7851"
+      - "7852:7852"
+    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 ]

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"
+}

finetune/compact.py

@@ -1,26 +0,0 @@
-import torch
-import os
-MODEL_PATH = "best_model.pth"
-# Check if best_model.pth exists
-if not os.path.exists(MODEL_PATH):
-    print(f"\nCannot find \033[94m{MODEL_PATH}\033[0m in the current folder.")
-    
-    # Check if model.pth exists as an alternative
-    ALTERNATIVE_PATH = "model.pth"
-    if os.path.exists(ALTERNATIVE_PATH):
-        print(f"\nIf your model is currently called \033[93m{ALTERNATIVE_PATH}\033[0m please rename it to \033[94mbest_model.pth\033[0m.")
-    else:
-        print(f"Please put \033[91mbest_model.pth\033[0m in the current folder or rename your model file to \033[94mbest_model.pth\033[0m.")
-    exit(1)
-# Attempt to load the model
-try:
-    checkpoint = torch.load(MODEL_PATH, map_location=torch.device("cpu"))
-except Exception as e:
-    print("Error loading checkpoint:", e)
-    raise
-del checkpoint["optimizer"]
-for key in list(checkpoint["model"].keys()):
-    if "dvae" in key:
-        del checkpoint["model"][key]
-torch.save(checkpoint, "model.pth")
-print(f"\nYour compacted model is created \033[93mmodel.pth\033[0m.")

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.py

@@ -1,10 +1,13 @@
 import os
+import sys
 from pathlib import Path
 import requests
+from requests.exceptions import ConnectionError
 from tqdm import tqdm
 import importlib.metadata as metadata
 import json
 from packaging import version
+from datetime import datetime
 
 #################################################################
 #### LOAD PARAMS FROM confignew.json - REQUIRED FOR BRANDING ####
@@ -12,14 +15,12 @@ from packaging import version
 # STARTUP VARIABLE - Create "this_dir" variable as the current script directory
 this_dir = Path(__file__).parent.resolve()
 
-
 # load standard 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"
 params = load_config(config_file_path)
 
@@ -37,34 +38,26 @@ if modeldownload_config_file_path.exists():
     files_to_download = settings.get("files_to_download", {})
 else:
     # Default settings if the JSON file doesn't exist or is empty
-    print(
-        f"[{params['branding']}Startup] \033[91mWarning\033[0m modeldownload.json is missing so please re-download it and save it in the coquii_tts main folder."
-    )
-    print(
-        f"[{params['branding']}Startup] \033[91mWarning\033[0m API Local and XTTSv2 Local will error unless this is corrected."
-    )
+    print(f"[{params['branding']}Startup] \033[91mWarning\033[0m modeldownload.json is missing so please re-download it and save it in the coquii_tts main folder.")
+    print(f"[{params['branding']}Startup] \033[91mWarning\033[0m API Local and XTTSv2 Local will error unless this is corrected.")
 
 # 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"
-    )
-
+    raise ValueError(f"[{params['branding']}Startup] \033[91mWarning\033[0m Could not find TTS version specifier in requirements file")
 
 def create_directory_if_not_exists(directory):
     if not directory.exists():
         directory.mkdir(parents=True)
 
-
 def download_file(url, destination):
     response = requests.get(url, stream=True)
     total_size_in_bytes = int(response.headers.get("content-length", 0))
@@ -83,63 +76,118 @@ def download_file(url, destination):
 def check_tts_version():
     try:
         tts_version = metadata.version("tts")
-        print(
-            f"[{params['branding']}Startup] TTS version installed: \033[93m"
-            + tts_version
-            + "\033[0m"
-        )
+        print(f"[{params['branding']}Startup] \033[92mCurrent TTS Version    : \033[93m"+tts_version+"\033[0m")
 
         if version.parse(tts_version) < version.parse(tts_version_required):
-            print(
-                f"[{params['branding']}Startup] \033[91mWarning\033[0m TTS version is too old. Please upgrade to version \033[93m"
-                + tts_version_required
-                + "\033[0m or later.\033[0m"
-            )
-            print(
-                f"[{params['branding']}Startup] \033[91mWarning\033[0m At your terminal/command prompt \033[94mpip install --upgrade tts\033[0m"
-            )
+            print(f"[{params['branding']}Startup] \033[91mWarning\033[0m TTS version is too old. Please upgrade to version \033[93m"+tts_version_required+"\033[0m or later.\033[0m")
+            print(f"[{params['branding']}Startup] \033[91mWarning\033[0m At your terminal/command prompt \033[94mpip install --upgrade tts\033[0m")
         else:
-            print(f"[{params['branding']}Startup] TTS version is up to date.")
+            print(f"[{params['branding']}Startup] \033[92mCurrent TTS Version is :\033[93m Up to date\033[0m")
     except metadata.PackageNotFoundError:
-        print(
-            f"[{params['branding']}Startup] \033[91mWarning\033[0m TTS is not installed."
-        )
+        print(f"[{params['branding']}Startup] \033[91mWarning\033[0m TTS is not installed")
 
+def check_torch_version():
+    import torch
+    pytorch_version = torch.__version__
+    cuda_version = torch.version.cuda
+    major, minor, micro = sys.version_info[:3]
+    python_version = f"{major}.{minor}.{micro}"
+    print(f"[{params['branding']}Startup] \033[92mCurrent Python Version :\033[93m {python_version}\033[0m")
+    print(f"[{params['branding']}Startup] \033[92mCurrent PyTorch Version:\033[93m {pytorch_version}\033[0m")
+    if cuda_version is None:
+        print(f"[{params['branding']}Startup] \033[92mCurrent CUDA Version   :\033[91m CUDA is not available\033[0m")
+    else:
+        print(f"[{params['branding']}Startup] \033[92mCurrent CUDA Version   :\033[93m {cuda_version}\033[0m")
+
+def ordinal(n):
+    return "%d%s" % (n, "th" if 4 <= n % 100 <= 20 else {1: "st", 2: "nd", 3: "rd"}.get(n % 10, "th"))
+
+def format_datetime(iso_str):
+    # Parse the ISO 8601 string to datetime
+    dt = datetime.strptime(iso_str, "%Y-%m-%dT%H:%M:%SZ")
+    # Format the datetime into a more readable string
+    return dt.strftime(f"{ordinal(dt.day)} %B %Y at %H:%M")
+
+def fetch_latest_commit_sha_and_date(owner, repo):
+    url = f"https://api.github.com/repos/{owner}/{repo}/commits"
+    try:
+        response = requests.get(url)
+        if response.status_code == 200:
+            latest_commit = response.json()[0]
+            latest_commit_sha = latest_commit['sha']
+            latest_commit_date = latest_commit['commit']['committer']['date']
+            return latest_commit_sha, latest_commit_date
+        else:
+            print(f"[{params['branding']}Startup] \033[92m{params['branding']}Github updated :\033[91m Failed to fetch the latest commits due to an unexpected response from GitHub")
+            return None, None
+    except ConnectionError:
+        # This block is executed when a connection error occurs
+        print(f"[{params['branding']}Startup] \033[92m{params['branding']}Github updated :\033[91m Could not reach GitHub to check for updates\033[0m")
+        return None, None
+
+def read_or_initialize_sha(file_path):
+    if os.path.exists(file_path):
+        with open(file_path, 'r') as file:
+            data = json.load(file)
+            return data.get("last_known_commit_sha")
+    else:
+        # File doesn't exist, fetch the latest SHA and create the file
+        latest_commit_sha = fetch_latest_commit_sha_and_date(github_site, github_repository)
+        if latest_commit_sha:
+            with open(file_path, 'w') as file:
+                json.dump({"last_known_commit_sha": latest_commit_sha}, file)
+            return latest_commit_sha
+        else:
+            # Handle the case where GitHub couldn't be reached
+            return None
+
+def update_sha_file(file_path, new_sha):
+    with open(file_path, 'w') as file:
+        json.dump({"last_known_commit_sha": new_sha}, file)
 
 # Check and create directories
 if str(base_path) == "models":
     create_directory_if_not_exists(this_dir / base_path / model_path)
 else:
     create_directory_if_not_exists(base_path / model_path)
-    print(
-        f"[{params['branding']}Startup] \033[94mInfo\033[0m Custom path set in \033[93mmodeldownload.json\033[0m. Using the following settings:"
-    )
-    print(
-        f"[{params['branding']}Startup] \033[94mInfo\033[0m Base folder Path:\033[93m",
-        base_path,
-        "\033[0m",
-    )
-    print(
-        f"[{params['branding']}Startup] \033[94mInfo\033[0m Model folder Path:\033[93m",
-        model_path,
-        "\033[0m",
-    )
-    print(
-        f"[{params['branding']}Startup] \033[94mInfo\033[0m Full Path:\033[93m",
-        base_path / model_path,
-        "\033[0m",
-    )
+    print(f"[{params['branding']}Startup] \033[94mInfo\033[0m Custom path set in \033[93mmodeldownload.json\033[0m. Using the following settings:")
+    print(f"[{params['branding']}Startup] \033[94mInfo\033[0m Base folder Path:\033[93m",base_path,"\033[0m",)
+    print(f"[{params['branding']}Startup] \033[94mInfo\033[0m Model folder Path:\033[93m",model_path,"\033[0m",)
+    print(f"[{params['branding']}Startup] \033[94mInfo\033[0m Full Path:\033[93m",base_path / model_path,"\033[0m",)
 
 # Download files if they don't exist
-print("[" + params["branding"] + "Startup] Checking Model is Downloaded.")
+print(f"[{params['branding']}Startup] \033[92mModel is available     :\033[93m Checking\033[0m")
 for filename, url in files_to_download.items():
     if str(base_path) == "models":
         destination = this_dir / base_path / model_path / filename
     else:
         destination = Path(base_path) / model_path / filename
-
     if not destination.exists():
-        print(f"[{params['branding']}Startup] Downloading " + filename + "...")
+        print(f"[{params['branding']}Startup] \033[92mModel Downloading file : \033[93m" + filename + "\033[0m")
         download_file(url, destination)
+print(f"[{params['branding']}Startup] \033[92mModel is available     :\033[93m Checked\033[0m")
 
+github_site = "erew123"
+github_repository = "alltalk_tts"
+
+check_torch_version()
 check_tts_version()
+# Define the file path based on your directory structure
+sha_file_path = this_dir / "system" / "config" / "at_github_sha.json"
+
+# Read or initialize the SHA (adjusted for handling both SHA and date)
+last_known_commit_sha = read_or_initialize_sha(sha_file_path)  # Assuming adjustment for date
+
+# Assuming you have fetched the latest commit SHA and date
+latest_commit_sha, latest_commit_date = fetch_latest_commit_sha_and_date(github_site, github_repository)
+
+formatted_date = format_datetime(latest_commit_date) if latest_commit_date else "an unknown date"
+
+if latest_commit_sha and latest_commit_sha != last_known_commit_sha:
+    #print(f"There's an update available for alltalk_tts.")
+    print(f"[{params['branding']}Startup] \033[92m{params['branding']}Github updated :\033[93m {formatted_date}\033[0m")
+    # Update the file with the new SHA
+    update_sha_file(sha_file_path, latest_commit_sha)
+elif latest_commit_sha == last_known_commit_sha:
+    #print(f"Your alltalk_tts software is up to date.")
+    print(f"[{params['branding']}Startup] \033[92m{params['branding']}Github updated :\033[93m {formatted_date}\033[0m")

nvidia.Dockerfile

@@ -0,0 +1,22 @@
+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
+
+RUN mkdir /app/pip_cache
+ENV PIP_CACHE_DIR=/app/pip_cache
+
+WORKDIR /app
+COPY . .
+ENV CUDA_DOCKER_ARCH=all
+RUN pip install --no-cache-dir --no-deps -r system/requirements/requirements_standalone.txt --cache-dir=/app/pip_cache && \
+    pip install --no-cache-dir deepspeed --cache-dir=/app/pip_cache
+
+EXPOSE 7851
+RUN chmod +x launch.sh
+ENTRYPOINT ["sh", "-c", "./launch.sh"]

requirements_finetune.txt

@@ -1,7 +0,0 @@
-gradio>=3.50.2
-torch>=2.1.0+cu118
-torchaudio>=2.1.0+cu118
-TTS==0.21.3
-faster-whisper>=0.10.0
-tqdm>=4.66.0
-pandas>=1.5.0

requirements_other.txt

@@ -1,15 +0,0 @@
-numpy>=1.22.0
-soundfile>=0.12.1
-uvicorn>=0.24.0.post1
-TTS>=0.21.3
-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
-pydantic>=1.10.13
-sounddevice>=0.4.6
-python-multipart>=0.0.6

script.py

@@ -9,12 +9,24 @@ import threading
 import signal
 import sys
 import atexit
+import shutil
 from pathlib import Path
 from datetime import datetime, timedelta
 import re
 import numpy as np
 import soundfile as sf
 import uuid
+import logging
+# Store the current disable level
+current_disable_level = logging.getLogger().manager.disable
+
+######################################
+#### 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 ####
@@ -32,40 +44,111 @@ config_file_path = this_dir / "confignew.json"
 # Load the params dictionary from the confignew.json file
 params = load_config(config_file_path)
 
+print(f"[{params['branding']}Startup]\033[94m     _    _ _ \033[1;35m_____     _ _     \033[0m  _____ _____ ____  ")
+print(f"[{params['branding']}Startup]\033[94m    / \  | | |\033[1;35m_   _|_ _| | | __ \033[0m |_   _|_   _/ ___| ")
+print(f"[{params['branding']}Startup]\033[94m   / _ \ | | |\033[1;35m | |/ _` | | |/ / \033[0m   | |   | | \___ \ ")
+print(f"[{params['branding']}Startup]\033[94m  / ___ \| | |\033[1;35m | | (_| | |   <  \033[0m   | |   | |  ___) |")
+print(f"[{params['branding']}Startup]\033[94m /_/   \_\_|_|\033[1;35m |_|\__,_|_|_|\_\ \033[0m   |_|   |_| |____/ ")
+print(f"[{params['branding']}Startup]")
+
+##############################################
+#### Update any changes to confignew.json ####
+##############################################
+
+update_config_path = this_dir / "system" / "config" / "at_configupdate.json"
+downgrade_config_path = this_dir / "system" / "config" / "at_configdowngrade.json"
+
+def changes_needed(main_config, update_config, downgrade_config):
+    """Check if there are any changes to be made to the main configuration."""
+    for key in downgrade_config.keys():
+        if key in main_config:
+            return True
+    for key, value in update_config.items():
+        if key not in main_config:
+            return True
+    return False
+
+def update_config(config_file_path, update_config_path, downgrade_config_path):
+    try:
+        with open(config_file_path, 'r') as file:
+            main_config = json.load(file)
+        with open(update_config_path, 'r') as file:
+            update_config = json.load(file)
+        with open(downgrade_config_path, 'r') as file:
+            downgrade_config = json.load(file)
+
+        # Determine if changes are needed
+        if changes_needed(main_config, update_config, downgrade_config):
+            # Backup with timestamp to avoid overwriting
+            timestamp = datetime.now().strftime("%Y%m%d%H%M%S")
+            backup_path = config_file_path.with_suffix(f".{timestamp}.bak")
+            logging.info(f"Creating backup of the main config to {backup_path}")
+            shutil.copy(config_file_path, backup_path)
+
+            # Proceed with updates and downgrades
+            for key, value in update_config.items():
+                if key not in main_config:
+                    main_config[key] = value
+            for key in downgrade_config.keys():
+                if key in main_config:
+                    del main_config[key]
+
+            # Save the updated configuration
+            with open(config_file_path, 'w') as file:
+                json.dump(main_config, file, indent=4)
+
+            print(f"[{params['branding']}Startup] \033[92mConfig file check      : \033[91mUpdates applied\033[0m")
+        else:
+            print(f"[{params['branding']}Startup] \033[92mConfig file check      : \033[93mNo Updates required\033[0m")
+
+    except Exception as e:
+        print(f"[{params['branding']}Startup] \033[92mConfig file check      : \033[91mError updating\033[0m")
+
+# Update the configuration
+update_config(config_file_path, update_config_path, downgrade_config_path)
+# Re-Load the params dictionary from the confignew.json file
+params = load_config(config_file_path)
+
+#########################################
+#### Continue on with Startup Checks ####
+#########################################
+            
 # Required for sentence splitting
 try:
     from TTS.api import TTS
     from TTS.utils.synthesizer import Synthesizer
 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 /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."
-    )
+    # Inform the user about the missing module and suggest next steps
+    print(f"[{params['branding']}]\033[91mWarning\033[0m Could not find the TTS module. Make sure to install the requirements for the {params['branding']} extension.")
+    print(f"[{params['branding']}]\033[91mWarning\033[0m Please use the ATSetup utility or check the Github installation instructions.")
+    # Re-raise the ModuleNotFoundError to stop the program and print the traceback
     raise 
 
-# IMPORT - Attempt Importing DeepSpeed (required for displaying Deepspeed checkbox in gradio)
+# Suppress logging
+logging.disable(logging.ERROR)
 try:
     import deepspeed
     deepspeed_installed = True
 except ImportError:
     deepspeed_installed = False
+# Restore previous logging level
+logging.disable(current_disable_level)
 
 # Import gradio if being used within text generation webUI
 try:
     import gradio as gr
-
     from modules import chat, shared, ui_chat
     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"]
+    print(f"[{params['branding']}Startup] \033[92m{params['branding']}startup Mode   : \033[93mText-Gen-webui mode\033[0m")
 except ModuleNotFoundError:
     output_folder_wav = params["output_folder_wav_standalone"]
-    print(f"[{params['branding']}Startup] Running script.py in standalone mode")
+    print(f"[{params['branding']}Startup] \033[92m{params['branding']}startup Mode   : \033[93mStandalone mode\033[0m")
     # 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
 
@@ -73,34 +156,25 @@ 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 ####
-#########################
-# STARTUP Display Licence Information
-print(f"[{params['branding']}Startup] \033[94mCoqui Public Model License\033[0m")
-print(f"[{params['branding']}Startup] \033[94mhttps://coqui.ai/cpml.txt\033[0m")
-
 
 ############################################
 #### DELETE OLD OUTPUT WAV FILES IF SET ####
 ############################################
 def delete_old_files(folder_path, days_to_keep):
     current_time = datetime.now()
-    print(
-        f"[{params['branding']}Startup] Deletion of old output folder WAV files is currently enabled and set at",
-        delete_output_wavs_setting,
-    )
+    print(f"[{params['branding']}Startup] \033[92mWAV file deletion      :\033[93m", delete_output_wavs_setting,"\033[0m")
     for file_name in os.listdir(folder_path):
         file_path = os.path.join(folder_path, file_name)
         if os.path.isfile(file_path):
@@ -116,20 +190,18 @@ output_folder_wav = os.path.normpath(output_folder_wav)
 
 # Check and perform file deletion
 if delete_output_wavs_setting.lower() == "disabled":
-    print(
-        "["
-        + params["branding"]
-        + "Startup] Old output wav file deletion is set to disabled."
-    )
+    print("["+ params["branding"]+"Startup] \033[92mWAV file deletion      :\033[93m Disabled\033[0m")
 else:
     try:
         days_to_keep = int(delete_output_wavs_setting.split()[0])
         delete_old_files(output_folder_wav, days_to_keep)
     except ValueError:
-        print(
-            f"[{params['branding']}Startup] Invalid setting for deleting old wav files. Please use 'Disabled' or 'X Days' format."
-        )
+        print(f"[{params['branding']}Startup] \033[92mWAV file deletion      :\033[93m Invalid setting for deleting old wav files. Please use 'Disabled' or 'X Days' format\033[0m")
 
+if deepspeed_installed:
+    print(f"[{params['branding']}Startup] \033[92mDeepSpeed version      :\033[93m",deepspeed.__version__,"\033[0m")
+else:
+    print(f"[{params['branding']}Startup] \033[92mDeepSpeed version      :\033[91m Not Detected\033[0m")
 
 ########################
 #### STARTUP CHECKS ####
@@ -139,7 +211,6 @@ def check_required_files():
     this_dir = Path(__file__).parent.resolve()
     download_script_path = this_dir / "modeldownload.py"
     subprocess.run(["python", str(download_script_path)])
-    print(f"[{params['branding']}Startup] All required files are present.")
 
 # STARTUP Call Check routine
 check_required_files()
@@ -155,9 +226,11 @@ finetuned_model = trained_model_directory.exists()
 # 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)
+    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")
+    print(f"[{params['branding']}Startup] \033[92mFinetuned model        :\033[93m Detected\033[0m")
 
 ####################################################
 #### SET GRADIO BUTTONS BASED ON confignew.json ####
@@ -219,9 +292,7 @@ script_path = this_dir / "tts_server.py"
 
 
 def signal_handler(sig, frame):
-    print(
-        f"[{params['branding']}Shutdown] \033[94mReceived Ctrl+C, terminating subprocess\033[92m"
-    )
+    print(f"[{params['branding']}Shutdown] \033[94mReceived Ctrl+C, terminating subprocess\033[92m")
     if process.poll() is None:
         process.terminate()
         process.wait()  # Wait for the subprocess to finish
@@ -230,60 +301,53 @@ 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:
+    # 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] \033[92mTTS Subprocess         :\033[93m Starting up\033[0m")
+        print(f"[{params['branding']}Startup]")
         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."
+            f"[{params['branding']}Startup] \033[94m{params['branding']}Settings & Documentation:\033[00m",
+            f"\033[92mhttp://{params['ip_address']}:{params['port_number']}\033[00m",
         )
+        print(f"[{params['branding']}Startup]")
+    else:
+        print(f"[{params['branding']}Startup] \033[91mWarning\033[0m TTS Subprocess Webserver failing to start process")
+        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 = 120  # Adjust the timeout as needed
+    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:
+    # 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 120 seconds maximum. Please wait."
-        )
-    time.sleep(4)
-else:
-    print(
-        f"[{params['branding']}Startup] Startup timed out. Check the server logs for more information."
-    )
+            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)
 
@@ -311,35 +375,34 @@ 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 / "templates" / "xttsfinetuned.wav"
+                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
-        print(
-            f"[{params['branding']}Server] \033[91mWarning\033[0m Error during request to webserver process: {e}"
-        )
+        print(f"[{params['branding']}Server] \033[91mWarning\033[0m Error during request to webserver process: {e}")
         return {"status": "error", "message": str(e)}
 
+
 ##################
 #### LOW VRAM ####
 ##################
@@ -348,9 +411,9 @@ 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)
@@ -363,9 +426,7 @@ def send_lowvram_request(low_vram):
         return f'<audio src="file/{audio_path}" controls autoplay></audio>'
     except requests.exceptions.RequestException as e:
         # Handle the HTTP request error
-        print(
-            f"[{params['branding']}Server] \033[91mWarning\033[0m Error during request to webserver process: {e}"
-        )
+        print(f"[{params['branding']}Server] \033[91mWarning\033[0m Error during request to webserver process: {e}")
         return {"status": "error", "message": str(e)}
 
 
@@ -377,10 +438,9 @@ 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)
@@ -393,9 +453,7 @@ def send_deepspeed_request(deepspeed_param):
         return f'<audio src="file/{audio_path}" controls autoplay></audio>'
     except requests.exceptions.RequestException as e:
         # Handle the HTTP request error
-        print(
-            f"[{params['branding']}Server] \033[91mWarning\033[0m Error during request to webserver process: {e}"
-        )
+        print(f"[{params['branding']}Server] \033[91mWarning\033[0m Error during request to webserver process: {e}")
         return {"status": "error", "message": str(e)}
 
 
@@ -428,9 +486,7 @@ Synthesizer.split_into_sentences = new_split_into_sentences
 def before_audio_generation(string, params):
     # Check Model is loaded into cuda or cpu and error if not
     if not params["tts_model_loaded"]:
-        print(
-            f"[{params['branding']}Model] \033[91mWarning\033[0m Model is still loading, please wait before trying to generate TTS"
-        )
+        print(f"[{params['branding']}Model] \033[91mWarning\033[0m Model is still loading, please wait before trying to generate TTS")
         return
     string = html.unescape(string) or random_sentence()
     if string == "":
@@ -456,7 +512,7 @@ def combine(audio_files, output_folder, state):
     if "character_menu" in state:
         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:
@@ -470,7 +526,7 @@ 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))
 
 
@@ -487,18 +543,23 @@ 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():
-        print(
-            f"[{params['branding']}Model] \033[91mWarning\033[0m Audio generation is already in progress. Please wait."
-        )
+        print(f"[{params['branding']}Model] \033[91mWarning\033[0m Audio generation is already in progress. Please wait.")
         return
     if generate_response.get("status") == "generate-success":
         # Handle Gradio and playback
@@ -509,12 +570,16 @@ 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)
+    text = re.sub(r"\.{3,}", ".", text)
 
     # Pattern to identify combined narrator and character speech
     combined_pattern = r'(\*[^*"]+\*|"[^"*]+")'
@@ -529,22 +594,22 @@ def process_text(text):
     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()
+            ambiguous_text = text[start : match.start()].strip()
             if ambiguous_text:
-                ordered_parts.append(('ambiguous', 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()))
+        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()))
+            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('"')))
+            if "*" in matched_text:
+                ordered_parts.append(("narrator", matched_text.strip("*").strip('"')))
             else:
-                ordered_parts.append(('character', matched_text.strip('"').strip('*')))
+                ordered_parts.append(("character", matched_text.strip('"').strip("*")))
 
         # Update the start of the next segment
         start = match.end()
@@ -553,10 +618,35 @@ def process_text(text):
     if start < len(text):
         ambiguous_text = text[start:].strip()
         if ambiguous_text:
-            ordered_parts.append(('ambiguous', 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 ####
 #################################
@@ -564,19 +654,21 @@ def process_text(text):
 def output_modifier(string, state):
     if not params["activate"]:
         return string
-    original_string = string
-    #print("ORIGINAL STRING IS:", original_string)
-    cleaned_string = before_audio_generation(string, params)
+    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"]:
-                processed_parts = process_text(original_string)
+                processed_parts = process_text(cleaned_string)
 
                 audio_files_all_paragraphs = []
                 for part_type, part in processed_parts:
@@ -585,29 +677,44 @@ def output_modifier(string, state):
                         continue
 
                     # Determine the voice to use based on the part type
-                    if part_type == 'narrator':
+                    if part_type == "narrator":
                         voice_to_use = params["narrator_voice"]
                         print(f"[{params['branding']}TTSGen] \033[92mNarrator\033[0m")  # Green
-                    elif part_type == 'character':
+                    elif part_type == "character":
                         voice_to_use = params["voice"]
                         print(f"[{params['branding']}TTSGen] \033[36mCharacter\033[0m")  # Yellow
                     else:
                         # 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"
+                        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)
+                    cleaned_part = re.sub(r"([!?.\u3002\uFF1F\uFF01\uFF0C])\1+", r"\1", part)
+                    # Replace "Chinese ellipsis" with a single dot
+                    cleaned_part = re.sub(r"\u2026{1,2}", ". ", cleaned_part)
                     # Further clean to remove any other unwanted characters
-                    cleaned_part = re.sub(r'[^a-zA-Z0-9\s\.,;:!?\-\'"\u0400-\u04FFÀ-ÿ\u0150\u0151\u0170\u0171\$]', '', cleaned_part)
+                    cleaned_part = re.sub(r'[^a-zA-Z0-9\s.,;:!?\-\'"$\u0400-\u04FF\u00C0-\u00FF\u0150\u0151\u0170\u0171\u0900-\u097F\u2018\u2019\u201C\u201D\u3001\u3002\u3040-\u309F\u30A0-\u30FF\u4E00-\u9FFF\u3400-\u4DBF\uF900-\uFAFF\u0600-\u06FF\u0750-\u077F\uFB50-\uFDFF\uFE70-\uFEFF\uAC00-\uD7A3\u1100-\u11FF\u3130-\u318F\uFF01\uFF0c\uFF1A\uFF1B\uFF1F]', '', cleaned_part)
                     # Remove all newline characters (single or multiple)
-                    cleaned_part = re.sub(r'\n+', ' ', cleaned_part)
+                    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_filename
+                        cleaned_part,
+                        voice_to_use,
+                        language_code,
+                        temperature,
+                        repetition_penalty,
+                        output_filename,
                     )
                     audio_path = generate_response.get("data", {}).get("audio_path")
                     audio_files_all_paragraphs.append(audio_path)
@@ -618,22 +725,33 @@ def output_modifier(string, state):
                 )
             else:
                 # Decode HTML entities first
-                cleaned_part = html.unescape(original_string)
+                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)
+                cleaned_part = re.sub(r"([!?.\u3002\uFF1F\uFF01\uFF0C])\1+", r"\1", cleaned_part)
+                # Replace "Chinese ellipsis" with a single dot
+                cleaned_part = re.sub(r"\u2026{1,2}", ". ", cleaned_part)
                 # Further clean to remove any other unwanted characters
-                cleaned_part = re.sub(r'[^a-zA-Z0-9\s\.,;:!?\-\'"\u0400-\u04FFÀ-ÿ\u0150\u0151\u0170\u0171\$]', '', cleaned_part)
+                cleaned_part = re.sub(r'[^a-zA-Z0-9\s.,;:!?\-\'"$\u0400-\u04FF\u00C0-\u00FF\u0150\u0151\u0170\u0171\u0900-\u097F\u2018\u2019\u201C\u201D\u3001\u3002\u3040-\u309F\u30A0-\u30FF\u4E00-\u9FFF\u3400-\u4DBF\uF900-\uFAFF\u0600-\u06FF\u0750-\u077F\uFB50-\uFDFF\uFE70-\uFEFF\uAC00-\uD7A3\u1100-\u11FF\u3130-\u318F\uFF01\uFF0c\uFF1A\uFF1B\uFF1F]', '', cleaned_part)
                 # Remove all newline characters (single or multiple)
-                cleaned_part = re.sub(r'\n+', ' ', cleaned_part)
+                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
@@ -652,42 +770,40 @@ 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):
     if "character_menu" in state:
-        return Path(f'{params["output_folder_wav"]}/{state["character_menu"]}_{str(uuid.uuid4())[:8]}.wav').as_posix()
+        return Path(
+            f'{params["output_folder_wav"]}/{state["character_menu"]}_{str(uuid.uuid4())[:8]}.wav'
+        ).as_posix()
     else:
-        return Path(f'{params["output_folder_wav"]}/TTSOUT_{str(uuid.uuid4())[:8]}.wav').as_posix()
+        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"}
@@ -712,12 +828,14 @@ 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":
@@ -725,6 +843,7 @@ 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
@@ -735,35 +854,53 @@ def input_modifier(string, state):
 
 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,
                 )
@@ -777,14 +914,11 @@ 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(),
@@ -801,43 +935,42 @@ 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",
                 )
-
-        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():
-            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="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>⚙️ <a href='http://{params['ip_address']}:{params['port_number']}'>Click here for the Settings page, help & instructions</a><a href='http://{params['ip_address']}:{params['port_number']}'></a>⚙️<br>NOTE: Switching Model Type, Low VRAM & DeepSpeed, each takes 15 seconds. Each TTS generation method has a slightly different sound. DeepSpeed checkbox is only visible if DeepSpeed is installed on your system."
+                    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>"
                 )
 
+        # Preview speech
         with gr.Row():
             preview_text = gr.Text(
                 show_label=False,
@@ -907,18 +1040,34 @@ 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)

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>
@@ -124,6 +124,7 @@
             <option value="English" {% if data.language=='English' %}selected{% endif %}>English</option>
             <option value="French" {% if data.language=='French' %}selected{% endif %}>French</option>
             <option value="German" {% if data.language=='German' %}selected{% endif %}>German</option>
+            <option value="Hindi" {% if data.language=='Hindi' %}selected{% endif %}>Hindi</option>
             <option value="Hungarian" {% if data.language=='Hungarian' %}selected{% endif %}>Hungarian</option>
             <option value="Italian" {% if data.language=='Italian' %}selected{% endif %}>Italian</option>
             <option value="Japanese" {% if data.language=='Japanese' %}selected{% endif %}>Japanese</option>
@@ -135,20 +136,20 @@
             <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/config/at_configdowngrade.json

@@ -0,0 +1,2 @@
+{
+}

system/config/at_configupdate.json

@@ -0,0 +1,2 @@
+{
+}

system/config/languages.json

@@ -6,6 +6,7 @@
   "English": "en",
   "French": "fr",
   "German": "de",
+  "Hindi": "hi",
   "Hungarian": "hu",
   "Italian": "it",
   "Japanese": "ja",

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_docker.txt

@@ -0,0 +1,173 @@
+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
+exceptiongroup
+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_googlecolab.txt

@@ -0,0 +1,171 @@
+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>=1.17.0,<1.29.0
+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
+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_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

@@ -1,7 +1,8 @@
 numpy>=1.22.0
 soundfile>=0.12.1
 uvicorn>=0.24.0.post1
-TTS>=0.21.3
+transformers>=4.37.1
+TTS>=0.22.0
 torch>=2.1.0+cu118
 torchaudio>=2.1.0+cu118
 fastapi>=0.104.1
@@ -13,3 +14,12 @@ 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
+spacy>=3.7.2

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.esm.js

@@ -1,2 +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
+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 @@
+{"version":3,"file":"crunker.esm.js","mappings":"AACA,IAAIA,EAAsB,CCA1BA,EAAwB,CAACC,EAASC,KACjC,IAAI,IAAIC,KAAOD,EACXF,EAAoBI,EAAEF,EAAYC,KAASH,EAAoBI,EAAEH,EAASE,IAC5EE,OAAOC,eAAeL,EAASE,EAAK,CAAEI,YAAY,EAAMC,IAAKN,EAAWC,IAE1E,ECNDH,EAAwB,CAACS,EAAKC,IAAUL,OAAOM,UAAUC,eAAeC,KAAKJ,EAAKC,I,8jDCoBlF,IAGqBI,EAAO,WAU1B,aAAqE,6DAAJ,CAAC,EAApDC,EAAU,EAAVA,WAAU,UACtBC,KAAKC,SAAWD,KAAKE,eAAeH,GAEpCA,IAAAA,EAAeC,KAAKC,SAASF,YAE7BC,KAAKG,YAAcJ,CACrB,C,UAoZC,O,EAlZD,E,EAAA,6BAKA,WAAkE,IAA3CA,EAAqB,UAAH,6CAAG,MAE1C,OADAK,OAAOC,aAAeD,OAAOC,cAAiBD,OAAeE,oBAAuBF,OAAeG,gBAC5F,IAAIF,aAAa,CAAEN,WAAAA,GAC5B,GAEA,mBAIA,WACE,OAAOC,KAAKC,QACd,GAEA,wBAGAO,iBAA4E,kCAAxDC,EAAS,yBAATA,EAAS,gBAC3B,aAAaC,QAAQC,IACnBF,EAAUG,KAAIJ,eAAOK,GACnB,IAAIC,EAkBJ,OAfEA,EADED,aAAoBE,MAAQF,aAAoBG,WACnCH,EAASI,oBAETC,MAAML,GAAUM,MAAK,SAACC,GASnC,OARIA,EAASC,QAAQC,IAAI,kBAAoBF,EAASC,QAAQ7B,IAAI,gBAAiB+B,SAAS,WAC1FC,QAAQC,KAAK,oEAAD,OAERL,EAASC,QAAQ7B,IAAI,gBAAiBkC,MAAM,KAAK,GAAE,sDACPb,EAAQ,OAInDO,EAASH,aAClB,UAGW,EAAKhB,SAAS0B,gBAAgBb,EAC7C,IAEJ,GAEA,wBAOA,SAAWc,GACT,IAAMC,EAAS7B,KAAKC,SAAS6B,aAC3B9B,KAAK+B,qBAAqBH,GAC1B5B,KAAKG,YAAcH,KAAKgC,aAAaJ,GACrC5B,KAAKG,aAgBP,OAbAyB,EAAQK,SAAQ,SAACnB,GACf,IAAK,IAAIoB,EAAgB,EAAGA,EAAgBpB,EAAOqB,iBAAkBD,IAAiB,CAIpF,IAHA,IAAME,EAAaP,EAAOQ,eAAeH,GACnCI,EAAaxB,EAAOuB,eAAeH,GAEhCK,EAAIzB,EAAOuB,eAAeH,GAAeM,OAAS,EAAGD,GAAK,EAAGA,IACpEH,EAAWG,IAAMD,EAAWC,GAG9BV,EAAOQ,eAAeH,GAAeO,IAAIL,EAC3C,CACF,IAEOP,CACT,GAEA,yBAOA,SAAYD,GACV,IAAMC,EAAS7B,KAAKC,SAAS6B,aAC3B9B,KAAK+B,qBAAqBH,GAC1B5B,KAAK0C,aAAad,GAClB5B,KAAKG,aAEHwC,EAAS,EAUb,OARAf,EAAQK,SAAQ,SAACnB,GACf,IAAK,IAAIoB,EAAgB,EAAGA,EAAgBpB,EAAOqB,iBAAkBD,IACnEL,EAAOQ,eAAeH,GAAeO,IAAI3B,EAAOuB,eAAeH,GAAgBS,GAGjFA,GAAU7B,EAAO0B,MACnB,IAEOX,CACT,GAEA,sBAUA,SAASf,GAA6E,IAAxD8B,EAAmB,UAAH,6CAAG,EAAGC,EAAkB,UAAH,6CAAG,EACpE,GAAgB,IAAZA,EAAe,OAAO/B,EAE1B,GAAI8B,EAAW,EAAG,MAAM,IAAIE,MAAM,8DAClC,GAAID,EAAU,EAAG,MAAM,IAAIC,MAAM,6DAQjC,IANA,IAAMC,EAAgB/C,KAAKC,SAAS6B,aAClChB,EAAOqB,iBACPa,KAAKC,KAAKnC,EAAO0B,OAASK,EAAU/B,EAAOf,YAC3Ce,EAAOf,YAGAmC,EAAgB,EAAGA,EAAgBpB,EAAOqB,iBAAkBD,IAAiB,CACpF,IAAMgB,EAAcpC,EAAOuB,eAAeH,GAC1Ca,EACGV,eAAeH,GACfO,IAAIS,EAAYC,SAAS,EAAGH,KAAKC,KAAKL,EAAW9B,EAAOf,YAAc,GAAI,GAE7EgD,EACGV,eAAeH,GACfO,IACCS,EAAYC,SAASH,KAAKC,KAAKL,EAAW9B,EAAOf,YAAc,EAAGgD,EAAcP,OAAS,GACzFQ,KAAKC,MAAML,EAAWC,GAAW/B,EAAOf,YAE9C,CAEA,OAAOgD,CACT,GAEA,wBASA,SAAWjC,EAAqBsC,EAAeC,GAAmE,IAAtDC,EAAiB,UAAH,6CAAG,EAAGC,EAAkB,UAAH,6CAAG,EAChG,GAAIH,GAASC,EAAK,MAAM,IAAIP,MAAM,6EAMlC,IAJA,IAAMN,EAASQ,KAAKQ,OAAOH,EAAMD,GAASpD,KAAKG,aACzCwC,EAASK,KAAKQ,MAAMJ,EAAQpD,KAAKG,aACjCsD,EAAYzD,KAAKC,SAAS6B,aAAahB,EAAOqB,iBAAkBK,EAAQxC,KAAKG,aAE1EuD,EAAU,EAAGA,EAAU5C,EAAOqB,iBAAkBuB,IAIvD,IAHA,IAAMC,EAAY7C,EAAOuB,eAAeqB,GAClCtB,EAAaqB,EAAUpB,eAAeqB,GAEnCnB,EAAI,EAAGA,EAAIC,EAAQD,IAC1BH,EAAWG,GAAKoB,EAAUhB,EAASJ,GAG/BA,EAAIe,EAAStD,KAAKG,cACpBiC,EAAWG,IAAMA,GAAKe,EAAStD,KAAKG,cAIlCoC,EAAIC,EAASe,EAAUvD,KAAKG,cAC9BiC,EAAWG,KAAOC,EAASD,IAAMgB,EAAUvD,KAAKG,cAKtD,OAAOsD,CACT,GAEA,kBAGA,SAAK3C,GACH,IAAM8C,EAAS5D,KAAKC,SAAS4D,qBAM7B,OAJAD,EAAO9C,OAASA,EAChB8C,EAAOE,QAAQ9D,KAAKC,SAAS8D,aAC7BH,EAAOR,QAEAQ,CACT,GAEA,oBAUA,SAAO9C,GAAuE,IAAlDkD,EAAe,UAAH,6CAAG,YACnCC,EAAWjE,KAAKkE,YAAYpD,GAC5BqD,EAAWnE,KAAKoE,cAAcH,EAAUnD,EAAOqB,iBAAkBrB,EAAOf,YACxEsE,EAAY,IAAIrD,KAAK,CAACmD,GAAW,CAAEH,KAAAA,IAEzC,MAAO,CACLM,KAAMD,EACNE,IAAKvE,KAAKwE,WAAWH,GACrBI,QAASzE,KAAK0E,oBAAoBL,GAEtC,GAEA,sBAMA,SAASC,GAA6D,IAAjDK,EAAmB,UAAH,6CAAG,UAChCC,EAAIC,SAASC,cAAc,KAOjC,OALAF,EAAEG,MAAMC,QAAU,OAClBJ,EAAEK,KAAOjF,KAAKwE,WAAWF,GACzBM,EAAEM,SAAW,GAAH,OAAMP,EAAQ,YAAIL,EAAKN,KAAKtC,MAAM,KAAK,IACjDkD,EAAEO,QAEKP,CACT,GAEA,0BAOA,SAAgBQ,GACd,OAAOpF,KAAKqF,oBAAiBC,EAAYF,GAC3C,GAEA,mBAGA,WAEE,OADApF,KAAKC,SAASsF,QACPvF,IACT,GAEA,0BAKA,SAAqB4B,GACnB,OAAOoB,KAAKwC,IAAG,MAARxC,KAAI,EAAQpB,EAAQhB,KAAI,SAACE,GAAM,OAAKA,EAAO2E,QAAQ,KAC5D,GAEA,kCAKA,SAA6B7D,GAC3B,OAAOoB,KAAKwC,IAAG,MAARxC,KAAI,EAAQpB,EAAQhB,KAAI,SAACE,GAAM,OAAKA,EAAOqB,gBAAgB,KACpE,GAEA,0BAKA,SAAqBP,GACnB,OAAOA,EAAQhB,KAAI,SAACE,GAAM,OAAKA,EAAO0B,MAAM,IAAEkD,QAAO,SAACd,EAAGe,GAAC,OAAKf,EAAIe,CAAC,GAAE,EACxE,GAEA,0BAKA,WACE,MAAO,iBAAkBvF,QAAU,uBAAwBA,QAAU,oBAAqBA,MAC5F,GAEA,2BAOA,SAAsBU,EAAsB8E,EAAuB7F,GACjE,IAEM8F,EADiBC,EACJF,EAIbG,EALiBD,EAKDhF,EAAO0B,OACvBwD,EAFkB,GAEiBD,EAEnC9E,EAAc,IAAIgF,YALD,EAK8BD,GAC/CE,EAAO,IAAIC,SAASlF,GAgB1B,OAdAjB,KAAKoG,aAAaF,EAAM,EAAG,QAC3BA,EAAKG,UAAU,EAAGL,GAAgB,GAClChG,KAAKoG,aAAaF,EAAM,EAAG,QAC3BlG,KAAKoG,aAAaF,EAAM,GAAI,QAC5BA,EAAKG,UAAU,GAAI,IAAI,GACvBH,EAAKI,UAAU,GAAI,GAAG,GACtBJ,EAAKI,UAAU,GAAIV,GAAe,GAClCM,EAAKG,UAAU,GAAItG,GAAY,GAC/BmG,EAAKG,UAAU,GAAItG,EAAa8F,GAAY,GAC5CK,EAAKI,UAAU,GAAIT,GAAY,GAC/BK,EAAKI,UAAU,GAtBE,IAsBY,GAC7BtG,KAAKoG,aAAaF,EAAM,GAAI,QAC5BA,EAAKG,UAAU,GAAIN,GAAe,GAE3B/F,KAAKuG,iBAAiBL,EAAMpF,EAAQ0F,GAC7C,GAEA,8BAKA,SAAyBrC,EAAoBrD,EAAsB6B,GACjE,IAAK,IAAIJ,EAAI,EAAGA,EAAIzB,EAAO0B,OAAQD,IAAKI,GAAU,EAAG,CACnD,IAAM8D,EAAMzD,KAAKwC,KAAK,EAAGxC,KAAK0D,IAAI,EAAG5F,EAAOyB,KAC5C4B,EAASwC,SAAShE,EAAQ8D,EAAM,EAAU,MAANA,EAAqB,MAANA,GAAc,EACnE,CAEA,OAAOtC,CACT,GAEA,0BAKA,SAAqBA,EAAoBxB,EAAgBiE,GACvD,IAAK,IAAIrE,EAAI,EAAGA,EAALine 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}")

templates/tts_chunk_player/crunker.esm.js.map

@@ -1 +0,0 @@
-{"version":3,"file":"crunker.esm.js","mappings":"AACA,IAAIA,EAAsB,CCA1BA,EAAwB,CAACC,EAASC,KACjC,IAAI,IAAIC,KAAOD,EACXF,EAAoBI,EAAEF,EAAYC,KAASH,EAAoBI,EAAEH,EAASE,IAC5EE,OAAOC,eAAeL,EAASE,EAAK,CAAEI,YAAY,EAAMC,IAAKN,EAAWC,IAE1E,ECNDH,EAAwB,CAACS,EAAKC,IAAUL,OAAOM,UAAUC,eAAeC,KAAKJ,EAAKC,I,8jDCoBlF,IAGqBI,EAAO,WAU1B,aAAqE,6DAAJ,CAAC,EAApDC,EAAU,EAAVA,WAAU,UACtBC,KAAKC,SAAWD,KAAKE,eAAeH,GAEpCA,IAAAA,EAAeC,KAAKC,SAASF,YAE7BC,KAAKG,YAAcJ,CACrB,C,UA6YC,O,EA3YD,E,EAAA,6BAKA,WAAkE,IAA3CA,EAAqB,UAAH,6CAAG,MAE1C,OADAK,OAAOC,aAAeD,OAAOC,cAAiBD,OAAeE,oBAAuBF,OAAeG,gBAC5F,IAAIF,aAAa,CAAEN,WAAAA,GAC5B,GAEA,mBAIA,WACE,OAAOC,KAAKC,QACd,GAEA,wBAGAO,iBAA4E,kCAAxDC,EAAS,yBAATA,EAAS,gBAC3B,aAAaC,QAAQC,IACnBF,EAAUG,KAAIJ,eAAOK,GACnB,IAAIC,EAkBJ,OAfEA,EADED,aAAoBE,MAAQF,aAAoBG,WACnCH,EAASI,oBAETC,MAAML,GAAUM,MAAK,SAACC,GASnC,OARIA,EAASC,QAAQC,IAAI,kBAAoBF,EAASC,QAAQ7B,IAAI,gBAAiB+B,SAAS,WAC1FC,QAAQC,KAAK,oEAAD,OAERL,EAASC,QAAQ7B,IAAI,gBAAiBkC,MAAM,KAAK,GAAE,sDACPb,EAAQ,OAInDO,EAASH,aAClB,UAGW,EAAKhB,SAAS0B,gBAAgBb,EAC7C,IAEJ,GAEA,wBAOA,SAAWc,GACT,IAAMC,EAAS7B,KAAKC,SAAS6B,aAC3B9B,KAAK+B,qBAAqBH,GAC1B5B,KAAKG,YAAcH,KAAKgC,aAAaJ,GACrC5B,KAAKG,aAgBP,OAbAyB,EAAQK,SAAQ,SAACnB,GACf,IAAK,IAAIoB,EAAgB,EAAGA,EAAgBpB,EAAOqB,iBAAkBD,IAAiB,CAIpF,IAHA,IAAME,EAAaP,EAAOQ,eAAeH,GACnCI,EAAaxB,EAAOuB,eAAeH,GAEhCK,EAAIzB,EAAOuB,eAAeH,GAAeM,OAAS,EAAGD,GAAK,EAAGA,IACpEH,EAAWG,IAAMD,EAAWC,GAG9BV,EAAOQ,eAAeH,GAAeO,IAAIL,EAC3C,CACF,IAEOP,CACT,GAEA,yBAOA,SAAYD,GACV,IAAMC,EAAS7B,KAAKC,SAAS6B,aAC3B9B,KAAK+B,qBAAqBH,GAC1B5B,KAAK0C,aAAad,GAClB5B,KAAKG,aAEHwC,EAAS,EAUb,OARAf,EAAQK,SAAQ,SAACnB,GACf,IAAK,IAAIoB,EAAgB,EAAGA,EAAgBpB,EAAOqB,iBAAkBD,IACnEL,EAAOQ,eAAeH,GAAeO,IAAI3B,EAAOuB,eAAeH,GAAgBS,GAGjFA,GAAU7B,EAAO0B,MACnB,IAEOX,CACT,GAEA,sBAUA,SAASf,GAA6E,IAAxD8B,EAAmB,UAAH,6CAAG,EAAGC,EAAkB,UAAH,6CAAG,EACpE,GAAgB,IAAZA,EAAe,OAAO/B,EAE1B,GAAI8B,EAAW,EAAG,MAAM,IAAIE,MAAM,8DAClC,GAAID,EAAU,EAAG,MAAM,IAAIC,MAAM,6DAQjC,IANA,IAAMC,EAAgB/C,KAAKC,SAAS6B,aAClChB,EAAOqB,iBACPa,KAAKC,KAAKnC,EAAO0B,OAASK,EAAU/B,EAAOf,YAC3Ce,EAAOf,YAGAmC,EAAgB,EAAGA,EAAgBpB,EAAOqB,iBAAkBD,IAAiB,CACpF,IAAMgB,EAAcpC,EAAOuB,eAAeH,GAC1Ca,EACGV,eAAeH,GACfO,IAAIS,EAAYC,SAAS,EAAGH,KAAKC,KAAKL,EAAW9B,EAAOf,YAAc,GAAI,GAE7EgD,EACGV,eAAeH,GACfO,IACCS,EAAYC,SAASH,KAAKC,KAAKL,EAAW9B,EAAOf,YAAc,EAAGgD,EAAcP,OAAS,GACzFQ,KAAKC,MAAML,EAAWC,GAAW/B,EAAOf,YAE9C,CAEA,OAAOgD,CACT,GAEA,wBASA,SAAWjC,EAAqBsC,EAAeC,GAAmE,IAAtDC,EAAiB,UAAH,6CAAG,EAAGC,EAAkB,UAAH,6CAAG,EAChG,GAAIH,GAASC,EAAK,MAAM,IAAIP,MAAM,6EAMlC,IAJA,IAAMN,EAASQ,KAAKQ,OAAOH,EAAMD,GAASpD,KAAKG,aACzCwC,EAASK,KAAKQ,MAAMJ,EAAQpD,KAAKG,aACjCsD,EAAYzD,KAAKC,SAAS6B,aAAahB,EAAOqB,iBAAkBK,EAAQxC,KAAKG,aAE1EuD,EAAU,EAAGA,EAAU5C,EAAOqB,iBAAkBuB,IAIvD,IAHA,IAAMC,EAAY7C,EAAOuB,eAAeqB,GAClCtB,EAAaqB,EAAUpB,eAAeqB,GAEnCnB,EAAI,EAAGA,EAAIC,EAAQD,IAC1BH,EAAWG,GAAKoB,EAAUhB,EAASJ,GAG/BA,EAAIe,EAAStD,KAAKG,cACpBiC,EAAWG,IAAMA,GAAKe,EAAStD,KAAKG,cAIlCoC,EAAIC,EAASe,EAAUvD,KAAKG,cAC9BiC,EAAWG,KAAOC,EAASD,IAAMgB,EAAUvD,KAAKG,cAKtD,OAAOsD,CACT,GAEA,kBAGA,SAAK3C,GACH,IAAM8C,EAAS5D,KAAKC,SAAS4D,qBAM7B,OAJAD,EAAO9C,OAASA,EAChB8C,EAAOE,QAAQ9D,KAAKC,SAAS8D,aAC7BH,EAAOR,QAEAQ,CACT,GAEA,oBAUA,SAAO9C,GAAuE,IAAlDkD,EAAe,UAAH,6CAAG,YACnCC,EAAWjE,KAAKkE,YAAYpD,GAC5BqD,EAAWnE,KAAKoE,cAAcH,EAAUnD,EAAOqB,iBAAkBrB,EAAOf,YACxEsE,EAAY,IAAIrD,KAAK,CAACmD,GAAW,CAAEH,KAAAA,IAEzC,MAAO,CACLM,KAAMD,EACNE,IAAKvE,KAAKwE,WAAWH,GACrBI,QAASzE,KAAK0E,oBAAoBL,GAEtC,GAEA,sBAMA,SAASC,GAA6D,IAAjDK,EAAmB,UAAH,6CAAG,UAChCC,EAAIC,SAASC,cAAc,KAOjC,OALAF,EAAEG,MAAMC,QAAU,OAClBJ,EAAEK,KAAOjF,KAAKwE,WAAWF,GACzBM,EAAEM,SAAW,GAAH,OAAMP,EAAQ,YAAIL,EAAKN,KAAKtC,MAAM,KAAK,IACjDkD,EAAEO,QAEKP,CACT,GAEA,0BAOA,SAAgBQ,GACd,OAAOpF,KAAKqF,oBAAiBC,EAAYF,GAC3C,GAEA,mBAGA,WAEE,OADApF,KAAKC,SAASsF,QACPvF,IACT,GAEA,0BAKA,SAAqB4B,GACnB,OAAOoB,KAAKwC,IAAG,MAARxC,KAAI,EAAQpB,EAAQhB,KAAI,SAACE,GAAM,OAAKA,EAAO2E,QAAQ,KAC5D,GAEA,kCAKA,SAA6B7D,GAC3B,OAAOoB,KAAKwC,IAAG,MAARxC,KAAI,EAAQpB,EAAQhB,KAAI,SAACE,GAAM,OAAKA,EAAOqB,gBAAgB,KACpE,GAEA,0BAKA,SAAqBP,GACnB,OAAOA,EAAQhB,KAAI,SAACE,GAAM,OAAKA,EAAO0B,MAAM,IAAEkD,QAAO,SAACd,EAAGe,GAAC,OAAKf,EAAIe,CAAC,GAAE,EACxE,GAEA,0BAKA,WACE,MAAO,iBAAkBvF,QAAU,uBAAwBA,QAAU,oBAAqBA,MAC5F,GAEA,2BAOA,SAAsBU,EAAsB8E,EAAuB7F,GACjE,IAEM8F,EADiBC,EACJF,EAIbG,EALiBD,EAKDhF,EAAO0B,OACvBwD,EAFkB,GAEiBD,EAEnC9E,EAAc,IAAIgF,YALD,EAK8BD,GAC/CE,EAAO,IAAIC,SAASlF,GAgB1B,OAdAjB,KAAKoG,aAAaF,EAAM,EAAG,QAC3BA,EAAKG,UAAU,EAAGL,GAAgB,GAClChG,KAAKoG,aAAaF,EAAM,EAAG,QAC3BlG,KAAKoG,aAAaF,EAAM,GAAI,QAC5BA,EAAKG,UAAU,GAAI,IAAI,GACvBH,EAAKI,UAAU,GAAI,GAAG,GACtBJ,EAAKI,UAAU,GAAIV,GAAe,GAClCM,EAAKG,UAAU,GAAItG,GAAY,GAC/BmG,EAAKG,UAAU,GAAItG,EAAa8F,GAAY,GAC5CK,EAAKI,UAAU,GAAIT,GAAY,GAC/BK,EAAKI,UAAU,GAtBE,IAsBY,GAC7BtG,KAAKoG,aAAaF,EAAM,GAAI,QAC5BA,EAAKG,UAAU,GAAIN,GAAe,GAE3B/F,KAAKuG,iBAAiBL,EAAMpF,EAAQ0F,GAC7C,GAEA,8BAKA,SAAyBrC,EAAoBrD,EAAsB6B,GACjE,IAAK,IAAIJ,EAAI,EAAGA,EAAIzB,EAAO0B,OAAQD,IAAKI,GAAU,EAAG,CACnD,IAAM8D,EAAMzD,KAAKwC,KAAK,EAAGxC,KAAK0D,IAAI,EAAG5F,EAAOyB,KAC5C4B,EAASwC,SAAShE,EAAQ8D,EAAM,EAAU,MAANA,EAAqB,MAANA,GAAc,EACnE,CAEA,OAAOtC,CACT,GAEA,0BAKA,SAAqBA,EAAoBxB,EAAgBiE,GACvD,IAAK,IAAIrE,EAAI,EAAGA,EAALine truncated

tts_server.py

@@ -8,7 +8,8 @@ from TTS.tts.configs.xtts_config import XttsConfig
 from TTS.tts.models.xtts import Xtts
 import io
 import wave
-
+import logging
+logging.disable(logging.WARNING)
 ##########################
 #### Webserver Imports####
 ##########################
@@ -19,6 +20,7 @@ from fastapi import (
     Response,
     Depends,
     HTTPException,
+    Query,
 )
 from fastapi.responses import JSONResponse, HTMLResponse, RedirectResponse, FileResponse, StreamingResponse
 from fastapi.middleware.cors import CORSMiddleware
@@ -34,7 +36,7 @@ this_dir = Path(__file__).parent.resolve()
 # STARTUP VARIABLE - Set "device" to cuda if exists, otherwise cpu
 device = "cuda" if torch.cuda.is_available() else "cpu"
 # STARTUP VARIABLE - Import languges file for Gradio to be able to display them in the interface
-with open(this_dir / "languages.json", encoding="utf8") as f:
+with open(this_dir / "system" / "config" / "languages.json", encoding="utf8") as f:
     languages = json.load(f)
 # Base setting for a possible FineTuned model existing and the loader being available
 tts_method_xtts_ft = False
@@ -57,6 +59,10 @@ params = load_config(configfile_path)
 # check someone hasnt enabled lowvram on a system thats not cuda enabled
 params["low_vram"] = "false" if not torch.cuda.is_available() else params["low_vram"]
 
+# Load values for temperature and repetition_penalty
+temperature = params["local_temperature"]
+repetition_penalty = params["local_repetition_penalty"]
+
 # Define the path to the JSON file
 config_file_path = this_dir / "modeldownload.json"
 
@@ -81,6 +87,17 @@ else:
         f"[{params['branding']}Startup] \033[91mWarning\033[0m modeldownload.config is missing so please re-download it and save it in the alltalk_tts main folder."
     )
 
+##################################################
+#### 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 finetuned_model:
+    required_files = ["model.pth", "config.json", "vocab.json"]
+    finetuned_model = all((trained_model_directory / file).exists() for file in required_files)
 
 ########################
 #### STARTUP CHECKS ####
@@ -98,20 +115,12 @@ except ModuleNotFoundError:
     raise
 
 # DEEPSPEED Import - Check for DeepSpeed and import it if it exists
+deepspeed_available = False
 try:
     import deepspeed
-
-    deepspeed_installed = True
-    print(f"[{params['branding']}Startup] DeepSpeed \033[93mDetected\033[0m")
-    print(
-        f"[{params['branding']}Startup] Activate DeepSpeed in {params['branding']} settings"
-    )
+    deepspeed_available = True
 except ImportError:
-    deepspeed_installed = False
-    print(
-        f"[{params['branding']}Startup] DeepSpeed \033[93mNot Detected\033[0m. See https://github.com/microsoft/DeepSpeed"
-    )
-
+    pass
 
 @asynccontextmanager
 async def startup_shutdown(no_actual_value_it_demanded_something_be_here):
@@ -173,9 +182,8 @@ async def setup():
     # Calculate start time minus end time
     generate_elapsed_time = generate_end_time - generate_start_time
     # Print out the result of the load time
-    print(
-        f"[{params['branding']}Model] \033[94mModel Loaded in \033[93m{generate_elapsed_time:.2f} seconds.\033[0m"
-    )
+    print(f"[{params['branding']}Model] \033[94mModel Loaded in \033[93m{generate_elapsed_time:.2f} seconds.\033[0m")
+    print(f"[{params['branding']}Model] Ready")
     # Set "tts_model_loaded" to true
     params["tts_model_loaded"] = True
     # Set the output path for wav files
@@ -209,6 +217,8 @@ async def api_manual_load_model():
             model_path=modeldownload_base_path / modeldownload_model_path,
             config_path=modeldownload_base_path / modeldownload_model_path / "config.json",
         ).to(device)
+        print(f"[{params['branding']}Model] \033[94mCoqui Public Model License\033[0m")
+        print(f"[{params['branding']}Model] \033[94mhttps://coqui.ai/cpml.txt\033[0m")
     return model
 
 
@@ -238,6 +248,8 @@ async def xtts_manual_load_model():
         use_deepspeed=params["deepspeed_activate"],
     )
     model.to(device)
+    print(f"[{params['branding']}Model] \033[94mCoqui Public Model License\033[0m")
+    print(f"[{params['branding']}Model] \033[94mhttps://coqui.ai/cpml.txt\033[0m")
     return model
 
 # MODEL LOADER For "XTTSv2 FT"
@@ -256,6 +268,8 @@ async def xtts_ft_manual_load_model():
         use_deepspeed=params["deepspeed_activate"],
     )
     model.to(device)
+    print(f"[{params['branding']}Model] \033[94mCoqui Public Model License\033[0m")
+    print(f"[{params['branding']}Model] \033[94mhttps://coqui.ai/cpml.txt\033[0m")
     return model
 
 # MODEL UNLOADER
@@ -462,19 +476,26 @@ async def deepspeed(request: Request, new_deepspeed_value: bool):
 ########################
 #### TTS GENERATION ####
 ########################
+debug_generate_audio = False
+tts_stop_generation = False # Called to stop generation of the current text at whatever stage its at. currently only set for streaming.
+tts_generation_lock = False # Tracks locking of the generaetion process.
+tts_narrator_generatingtts = False # Tracks if the current tts processes are narrator based, to avoid moving model on each chunk of text generated.
+# Not in use tts_queue_behaviour = False # True is to queue the current generation request. False is to cancel the current generation and start a new one.
 
 # TTS VOICE GENERATION METHODS (called from voice_preview and output_modifer)
-async def generate_audio(text, voice, language, output_file, streaming=False):
+async def generate_audio(text, voice, language, temperature, repetition_penalty, output_file, streaming=False):
     # Get the async generator from the internal function
-    response = generate_audio_internal(text, voice, language, output_file, streaming)
+    response = generate_audio_internal(text, voice, language, temperature, repetition_penalty, output_file, streaming)
     # If streaming, then return the generator as-is, otherwise just exhaust it and return
     if streaming:
         return response
     async for _ in response:
         pass
 
-async def generate_audio_internal(text, voice, language, output_file, streaming):
-    global model
+
+async def generate_audio_internal(text, voice, language, temperature, repetition_penalty, output_file, streaming):
+    global model, tts_stop_generation, tts_generation_lock
+    tts_generation_lock = True
     if params["low_vram"] and device == "cpu":
         await switch_device()
     generate_start_time = time.time()  # Record the start time of generating TTS
@@ -495,9 +516,9 @@ async def generate_audio_internal(text, voice, language, output_file, streaming)
             "language": language,
             "gpt_cond_latent": gpt_cond_latent,
             "speaker_embedding": speaker_embedding,
-            "temperature": float(params["local_temperature"]),
+            "temperature": float(temperature),
             "length_penalty": float(model.config.length_penalty),
-            "repetition_penalty": float(params["local_repetition_penalty"]),
+            "repetition_penalty": float(repetition_penalty),
             "top_k": int(model.config.top_k),
             "top_p": float(model.config.top_p),
             "enable_text_splitting": True
@@ -525,6 +546,12 @@ async def generate_audio_internal(text, voice, language, output_file, streaming)
             yield wav_buf.read()
 
             for i, chunk in enumerate(output):
+                if tts_stop_generation:
+                    print(f"[{params['branding']}TTSGen] Stopping audio generation.")
+                    file_chunks.clear()  # Clear the file_chunks list
+                    tts_stop_generation = False
+                    tts_generation_lock = False
+                    break
                 file_chunks.append(chunk)
                 if isinstance(chunk, list):
                     chunk = torch.cat(chunk, dim=0)
@@ -533,6 +560,7 @@ async def generate_audio_internal(text, voice, language, output_file, streaming)
                 chunk = np.clip(chunk, -1, 1)
                 chunk = (chunk * 32767).astype(np.int16)
                 yield chunk.tobytes()
+                print(f"[{params['branding']}Debug] Stream audio generation: Yielded audio chunk {i}.") if debug_generate_audio else None   
         else:
             # Non-streaming-specific operation
             torchaudio.save(output_file, torch.tensor(output["wav"]).unsqueeze(0), 24000)
@@ -551,9 +579,9 @@ async def generate_audio_internal(text, voice, language, output_file, streaming)
             file_path=output_file,
             speaker_wav=[f"{this_dir}/voices/{voice}"],
             language=language,
-            temperature=float(params["local_temperature"]),
-            length_penalty=model.config.length_penalty,
-            repetition_penalty=float(params["local_repetition_penalty"]),
+            temperature=float(temperature),
+            length_penalty=float(model.config.length_penalty),
+            repetition_penalty=float(repetition_penalty),
             top_k=model.config.top_k,
             top_p=model.config.top_p,
         )
@@ -575,12 +603,11 @@ async def generate_audio_internal(text, voice, language, output_file, streaming)
     # Print Generation time and settings
     generate_end_time = time.time()  # Record the end time to generate TTS
     generate_elapsed_time = generate_end_time - generate_start_time
-    print(
-        f"[{params['branding']}TTSGen] \033[93m{generate_elapsed_time:.2f} seconds. \033[94mLowVRAM: \033[33m{params['low_vram']} \033[94mDeepSpeed: \033[33m{params['deepspeed_activate']}\033[0m"
-    )
+    print(f"[{params['branding']}TTSGen] \033[93m{generate_elapsed_time:.2f} seconds. \033[94mLowVRAM: \033[33m{params['low_vram']} \033[94mDeepSpeed: \033[33m{params['deepspeed_activate']}\033[0m")
     # Move model back to cpu system ram if needed.
-    if params["low_vram"] and device == "cuda":
+    if params["low_vram"] and device == "cuda" and tts_narrator_generatingtts == False:
         await switch_device()
+    tts_generation_lock = False
     return
 
 
@@ -593,10 +620,12 @@ async def generate(request: Request):
         text = data["text"]
         voice = data["voice"]
         language = data["language"]
+        temperature = data["temperature"]
+        repetition_penalty = data["repetition_penalty"]
         output_file = data["output_file"]
         streaming = False
         # Generation logic
-        response = await generate_audio(text, voice, language, output_file, streaming)
+        response = await generate_audio(text, voice, language, temperature, repetition_penalty, output_file, streaming)
         if streaming:
             return StreamingResponse(response, media_type="audio/wav")
         return JSONResponse(
@@ -623,7 +652,7 @@ def list_files(directory):
 #############################
 
 # Create an instance of Jinja2Templates for rendering HTML templates
-templates = Jinja2Templates(directory=this_dir / "templates")
+templates = Jinja2Templates(directory=this_dir / "system")
 
 # Create a dependency to get the current JSON data
 def get_json_data():
@@ -638,7 +667,7 @@ async def get_settings(request: Request):
     wav_files = list_files(this_dir / "voices")
     # Render the template with the current JSON data and list of WAV files
     return templates.TemplateResponse(
-        "generate_form.html",
+        "/at_admin/at_settings.html",
         {
             "request": request,
             "data": get_json_data(),
@@ -648,7 +677,7 @@ async def get_settings(request: Request):
     )
 
 # Define an endpoint to serve static files
-app.mount("/static", StaticFiles(directory=str(this_dir / "templates")), name="static")
+app.mount("/static", StaticFiles(directory=str(this_dir / "system")), name="static")
 
 @app.post("/update-settings")
 async def update_settings(
@@ -713,7 +742,7 @@ async def update_settings(
 async def tts_demo_request_streaming(text: str, voice: str, language: str, output_file: str):
     try:
         output_file_path = this_dir / "outputs" / output_file
-        stream = await generate_audio(text, voice, language, output_file_path, streaming=True)
+        stream = await generate_audio(text, voice, language, temperature, repetition_penalty, output_file_path, streaming=True)
         return StreamingResponse(stream, media_type="audio/wav")
     except Exception as e:
         print(f"An error occurred: {e}")
@@ -723,12 +752,17 @@ async def tts_demo_request_streaming(text: str, voice: str, language: str, outpu
 async def tts_demo_request(request: Request, text: str = Form(...), voice: str = Form(...), language: str = Form(...), output_file: str = Form(...)):
     try:
         output_file_path = this_dir / "outputs" / output_file
-        await generate_audio(text, voice, language, output_file_path, streaming=False)
+        await generate_audio(text, voice, language, temperature, repetition_penalty, output_file_path, streaming=False)
         return JSONResponse(content={"output_file_path": str(output_file)}, status_code=200)
     except Exception as e:
         print(f"An error occurred: {e}")
         return JSONResponse(content={"error": "An error occurred"}, status_code=500)
 
+
+#####################
+#### Audio feeds ####
+#####################
+
 # Gives web access to the output files
 @app.get("/audio/{filename}")
 async def get_audio(filename: str):
@@ -780,7 +814,7 @@ async def preview_voice(request: Request, voice: str = Form(...)):
 
         # Generate the audio
         output_file_path = this_dir / "outputs" / f"{output_file_name}.wav"
-        await generate_audio(text, voice, language, output_file_path, streaming=False)
+        await generate_audio(text, voice, language, temperature, repetition_penalty, output_file_path, streaming=False)
 
         # Generate the URL
         output_file_url = f'http://{params["ip_address"]}:{params["port_number"]}/audio/{output_file_name}.wav'
@@ -807,6 +841,42 @@ import uuid
 import numpy as np
 import soundfile as sf
 import sys
+import hashlib
+
+##############################
+#### Streaming Generation ####
+##############################
+
+@app.get("/api/tts-generate-streaming", response_class=StreamingResponse)
+async def tts_generate_streaming(text: str, voice: str, language: str, output_file: str):
+    try:
+        output_file_path = this_dir / "outputs" / output_file
+        stream = await generate_audio(text, voice, language, temperature, repetition_penalty, output_file_path, streaming=True)
+        return StreamingResponse(stream, media_type="audio/wav")
+    except Exception as e:
+        print(f"An error occurred: {e}")
+        return JSONResponse(content={"error": "An error occurred"}, status_code=500)
+
+@app.post("/api/tts-generate-streaming", response_class=JSONResponse)
+async def tts_generate_streaming(request: Request, text: str = Form(...), voice: str = Form(...), language: str = Form(...), output_file: str = Form(...)):
+    try:
+        output_file_path = this_dir / "outputs" / output_file
+        await generate_audio(text, voice, language, temperature, repetition_penalty, output_file_path, streaming=False)
+        return JSONResponse(content={"output_file_path": str(output_file)}, status_code=200)
+    except Exception as e:
+        print(f"An error occurred: {e}")
+        return JSONResponse(content={"error": "An error occurred"}, status_code=500)
+
+@app.put("/api/stop-generation")
+async def stop_generation_endpoint():
+    global tts_stop_generation, tts_generation_lock
+    if tts_generation_lock and not tts_stop_generation:
+        tts_stop_generation = True
+    return {"message": "Generation stopped"}
+
+##############################
+#### Standard Generation ####
+##############################
 
 # Check for PortAudio library on Linux
 try:
@@ -821,7 +891,7 @@ except OSError:
         print(f"[{params['branding']}Startup] \033[91mInfo\033[0m On Linux, you can use the following command to install PortAudio:")
         print(f"[{params['branding']}Startup] \033[91mInfo\033[0m sudo apt-get install portaudio19-dev")
 
-from typing import Union, Dict
+from typing import Union, Dict, List
 from pydantic import BaseModel, ValidationError, Field
 
 def play_audio(file_path, volume):
@@ -834,13 +904,13 @@ class Request(BaseModel):
     pass
 
 class JSONInput(BaseModel):
-    text_input: str = Field(..., max_length=1000, description="text_input needs to be 1000 characters or less.")
+    text_input: str = Field(..., max_length=2000, description="text_input needs to be 2000 characters or less.")
     text_filtering: str = Field(..., pattern="^(none|standard|html)$", description="text_filtering needs to be 'none', 'standard' or 'html'.")
     character_voice_gen: str = Field(..., pattern="^.*\.wav$", description="character_voice_gen needs to be the name of a wav file e.g. mysample.wav.")
     narrator_enabled: bool = Field(..., description="narrator_enabled needs to be true or false.")
     narrator_voice_gen: str = Field(..., pattern="^.*\.wav$", description="narrator_voice_gen needs to be the name of a wav file e.g. mysample.wav.")
     text_not_inside: str = Field(..., pattern="^(character|narrator)$", description="text_not_inside needs to be 'character' or 'narrator'.")
-    language: str = Field(..., pattern="^(ar|zh-cn|cs|nl|en|fr|de|hu|it|ja|ko|pl|pt|ru|es|tr)$", description="language needs to be one of the following ar|zh-cn|cs|nl|en|fr|de|hu|it|ja|ko|pl|pt|ru|es|tr.")
+    language: str = Field(..., pattern="^(ar|zh-cn|cs|nl|en|fr|de|hu|hi|it|ja|ko|pl|pt|ru|es|tr)$", description="language needs to be one of the following ar|zh-cn|cs|nl|en|fr|de|hu|hi|it|ja|ko|pl|pt|ru|es|tr.")
     output_file_name: str = Field(..., pattern="^[a-zA-Z0-9_]+$", description="output_file_name needs to be the name without any special characters or file extension e.g. 'filename'")
     output_file_timestamp: bool = Field(..., description="output_file_timestamp needs to be true or false.")
     autoplay: bool = Field(..., description="autoplay needs to be a true or false value.")
@@ -936,8 +1006,8 @@ def combine(output_file_timestamp, output_file_name, audio_files):
         output_cache_url = f'http://{params["ip_address"]}:{params["port_number"]}/audiocache/{output_file_name}_{timestamp}_combined.wav'
     else:
         output_file_path = os.path.join(this_dir / "outputs" / f'{output_file_name}_combined.wav')
-        output_file_url = f'http://{params["ip_address"]}:{params["port_number"]}/audio/{output_file_name}.wav'
-        output_cache_url = f'http://{params["ip_address"]}:{params["port_number"]}/audiocache/{output_file_name}.wav'
+        output_file_url = f'http://{params["ip_address"]}:{params["port_number"]}/audio/{output_file_name}_combined.wav'
+        output_cache_url = f'http://{params["ip_address"]}:{params["port_number"]}/audiocache/{output_file_name}_combined.wav'
     try:
         sf.write(output_file_path, audio, samplerate=sample_rate)
         # Clean up unnecessary files
@@ -979,12 +1049,17 @@ async def tts_generate(
             "autoplay_volume": autoplay_volume,
             "streaming": streaming,
         }
+        global tts_narrator_generatingtts
         JSONresult = TTSGenerator.validate_json_input(json_input_data)
         if JSONresult is None:
             pass
         else:
+            print(f"[{params['branding']}API] \033[91mError with API request:\033[0m", JSONresult)
             return JSONResponse(content={"error": JSONresult}, status_code=400)
         if narrator_enabled:
+            if params["low_vram"] and device == "cpu":
+                await switch_device()
+            tts_narrator_generatingtts = True
             processed_parts = process_text(text_input)
             audio_files_all_paragraphs = []
             for part_type, part in processed_parts:
@@ -1004,44 +1079,61 @@ async def tts_generate(
                     voice_description = "\033[36mCharacter (Text-not-inside)\033[0m" if text_not_inside == "character" 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)
+                cleaned_part = re.sub(r'([!?.\u3002\uFF1F\uFF01\uFF0C])\1+', r'\1', part)
+                # Replace "Chinese ellipsis" with a single dot
+                cleaned_part = re.sub(r"\u2026{1,2}", ". ", cleaned_part)
                 # Further clean to remove any other unwanted characters
-                cleaned_part = re.sub(r'[^a-zA-Z0-9\s\.,;:!?\-\'"\u0400-\u04FFÀ-ÿ\u0150\u0151\u0170\u0171\$]', '', cleaned_part)
+                cleaned_part = re.sub(r'[^a-zA-Z0-9\s.,;:!?\-\'"$\u0400-\u04FF\u00C0-\u00FF\u0150\u0151\u0170\u0171\u0900-\u097F\u2018\u2019\u201C\u201D\u3001\u3002\u3040-\u309F\u30A0-\u30FF\u4E00-\u9FFF\u3400-\u4DBF\uF900-\uFAFF\u0600-\u06FF\u0750-\u077F\uFB50-\uFDFF\uFE70-\uFEFF\uAC00-\uD7A3\u1100-\u11FF\u3130-\u318F\uFF01\uFF0c\uFF1A\uFF1B\uFF1F]', '', cleaned_part)
                 # Remove all newline characters (single or multiple)
                 cleaned_part = re.sub(r'\n+', ' ', cleaned_part)
                 output_file = this_dir / "outputs" / f"{output_file_name}_{uuid.uuid4()}_{int(time.time())}.wav"
                 output_file_str = output_file.as_posix()
-                response = await generate_audio(cleaned_part, voice_to_use, language, output_file_str, streaming)
+                response = await generate_audio(cleaned_part, voice_to_use, language,temperature, repetition_penalty, output_file_str, streaming)
                 audio_path = output_file_str
                 audio_files_all_paragraphs.append(audio_path)
             # Combine audio files across paragraphs
             output_file_path, output_file_url, output_cache_url = combine(output_file_timestamp, output_file_name, audio_files_all_paragraphs)
+            tts_narrator_generatingtts = False
+            # Move model back to cpu system ram if needed.
+            if params["low_vram"] and device == "cuda":
+                await switch_device()
         else:
             if output_file_timestamp:
                 timestamp = int(time.time())
-                output_file_path = this_dir / "outputs" / f"{output_file_name}_{timestamp}.wav"
-                output_file_url = f'http://{params["ip_address"]}:{params["port_number"]}/audio/{output_file_name}_{timestamp}.wav'
-                output_cache_url = f'http://{params["ip_address"]}:{params["port_number"]}/audiocache/{output_file_name}_{timestamp}.wav'
+                # Generate a standard UUID
+                original_uuid = uuid.uuid4()
+                # Hash the UUID using SHA-256
+                hash_object = hashlib.sha256(str(original_uuid).encode())
+                hashed_uuid = hash_object.hexdigest()
+                # Truncate to the desired length, for example, 16 characters
+                short_uuid = hashed_uuid[:5]
+                output_file_path = this_dir / "outputs" / f"{output_file_name}_{timestamp}{short_uuid}.wav"
+                output_file_url = f'http://{params["ip_address"]}:{params["port_number"]}/audio/{output_file_name}_{timestamp}{short_uuid}.wav'
+                output_cache_url = f'http://{params["ip_address"]}:{params["port_number"]}/audiocache/{output_file_name}_{timestamp}{short_uuid}.wav'
             else:
                 output_file_path = this_dir / "outputs" / f"{output_file_name}.wav"
                 output_file_url = f'http://{params["ip_address"]}:{params["port_number"]}/audio/{output_file_name}.wav'
-                output_cache_url = f'http://{params["ip_address"]}:{params["port_number"]}/audiocache/{output_file_name}_{timestamp}.wav'
+                output_cache_url = f'http://{params["ip_address"]}:{params["port_number"]}/audiocache/{output_file_name}.wav'
             if text_filtering == "html":
                 cleaned_string = html.unescape(standard_filtering(text_input))
-                cleaned_string = re.sub(r'([!?.])\1+', r'\1', text_input)
+                cleaned_string = re.sub(r'([!?.\u3002\uFF1F\uFF01\uFF0C])\1+', r'\1', text_input)
+                # Replace "Chinese ellipsis" with a single dot
+                cleaned_string = re.sub(r"\u2026{1,2}", ". ", cleaned_string)
                 # Further clean to remove any other unwanted characters
-                cleaned_string = re.sub(r'[^a-zA-Z0-9\s\.,;:!?\-\'"\u0400-\u04FFÀ-ÿ\u0150\u0151\u0170\u0171\$]', '', cleaned_string)
+                cleaned_string = re.sub(r'[^a-zA-Z0-9\s.,;:!?\-\'"$\u0400-\u04FF\u00C0-\u00FF\u0150\u0151\u0170\u0171\u0900-\u097F\u2018\u2019\u201C\u201D\u3001\u3002\u3040-\u309F\u30A0-\u30FF\u4E00-\u9FFF\u3400-\u4DBF\uF900-\uFAFF\u0600-\u06FF\u0750-\u077F\uFB50-\uFDFF\uFE70-\uFEFF\uAC00-\uD7A3\u1100-\u11FF\u3130-\u318F\uFF01\uFF0c\uFF1A\uFF1B\uFF1F]', '', cleaned_string)
                 # Remove all newline characters (single or multiple)
                 cleaned_string = re.sub(r'\n+', ' ', cleaned_string)
             elif text_filtering == "standard":
-                cleaned_string = re.sub(r'([!?.])\1+', r'\1', text_input)
+                cleaned_string = re.sub(r'([!?.\u3002\uFF1F\uFF01\uFF0C])\1+', r'\1', text_input)
+                # Replace "Chinese ellipsis" with a single dot
+                cleaned_string = re.sub(r"\u2026{1,2}", ". ", cleaned_string)
                 # Further clean to remove any other unwanted characters
-                cleaned_string = re.sub(r'[^a-zA-Z0-9\s\.,;:!?\-\'"\u0400-\u04FFÀ-ÿ\u0150\u0151\u0170\u0171\$]', '', cleaned_string)
+                cleaned_string = re.sub(r'[^a-zA-Z0-9\s.,;:!?\-\'"$\u0400-\u04FF\u00C0-\u00FF\u0150\u0151\u0170\u0171\u0900-\u097F\u2018\u2019\u201C\u201D\u3001\u3002\u3040-\u309F\u30A0-\u30FF\u4E00-\u9FFF\u3400-\u4DBF\uF900-\uFAFF\u0600-\u06FF\u0750-\u077F\uFB50-\uFDFF\uFE70-\uFEFF\uAC00-\uD7A3\u1100-\u11FF\u3130-\u318F\uFF01\uFF0c\uFF1A\uFF1B\uFF1F]', '', cleaned_string)
                 # Remove all newline characters (single or multiple)
                 cleaned_string = re.sub(r'\n+', ' ', cleaned_string)
             else:
                 cleaned_string = text_input
-            response = await generate_audio(cleaned_string, character_voice_gen, language, output_file_path, streaming)
+            response = await generate_audio(cleaned_string, character_voice_gen, language, temperature, repetition_penalty, output_file_path, streaming)
         if sounddevice_installed == False or streaming == True:
             autoplay = False
         if autoplay:
@@ -1053,11 +1145,105 @@ async def tts_generate(
         return JSONResponse(content={"status": "generate-failure", "error": "An error occurred"}, status_code=500)
 
 
+##########################
+#### Current Settings ####
+##########################
+# Define the available models
+models_available = [
+    {"name": "Coqui", "model_name": "API TTS"},
+    {"name": "Coqui", "model_name": "API Local"},
+    {"name": "Coqui", "model_name": "XTTSv2 Local"}
+]
+
+@app.get('/api/currentsettings')
+def get_current_settings():
+    # Determine the current model loaded
+    if params["tts_method_api_tts"]:
+        current_model_loaded = "API TTS"
+    elif params["tts_method_api_local"]:
+        current_model_loaded = "API Local"
+    elif params["tts_method_xtts_local"]:
+        current_model_loaded = "XTTSv2 Local"
+    else:
+        current_model_loaded = None  # or a default value if no method is active
+
+    settings = {
+        "models_available": models_available,
+        "current_model_loaded": current_model_loaded,
+        "deepspeed_available": deepspeed_available,
+        "deepspeed_status": params["deepspeed_activate"],
+        "low_vram_status": params["low_vram"],
+        "finetuned_model": finetuned_model
+    }
+    return settings  # Automatically converted to JSON by Fas
+
 #############################
 #### Word Add-in Sharing ####
 #############################
 # Mount the static files from the 'word_addin' directory
-app.mount("/api/word_addin", StaticFiles(directory=os.path.join(this_dir / 'templates' / 'word_addin')), name="word_addin")
+app.mount("/api/word_addin", StaticFiles(directory=os.path.join(this_dir / 'system' / 'word_addin')), name="word_addin")
+
+#############################################
+#### TTS Generator Comparision Endpoints ####
+#############################################
+import subprocess
+import aiofiles
+
+class TTSItem(BaseModel):
+    id: int
+    fileUrl: str
+    text: str
+    characterVoice: str
+    language: str
+
+class TTSData(BaseModel):
+    ttsList: List[TTSItem]
+
+@app.post("/api/save-tts-data")
+async def save_tts_data(tts_data: List[TTSItem]):
+    # Convert the list of Pydantic models to a list of dictionaries
+    tts_data_list = [item.dict() for item in tts_data]
+    # Serialize the list of dictionaries to a JSON string
+    tts_data_json = json.dumps(tts_data_list, indent=4)
+    async with aiofiles.open(this_dir / "outputs" / "ttsList.json", 'w') as f:
+        await f.write(tts_data_json)
+    return {"message": "Data saved successfully"}
+
+import sys
+
+@app.get("/api/trigger-analysis")
+async def trigger_analysis(threshold: int = Query(default=98)):
+    venv_path = sys.prefix
+    env = os.environ.copy()
+    env["PATH"] = os.path.join(venv_path, "bin") + ":" + env["PATH"]
+    ttslist_path = this_dir / "outputs" / "ttsList.json"
+    wavfile_path = this_dir / "outputs"
+    subprocess.run(["python", "tts_diff.py", f"--threshold={threshold}", f"--ttslistpath={ttslist_path}", f"--wavfilespath={wavfile_path}"], cwd=this_dir / "system" / "tts_diff", env=env)
+    # Read the analysis summary
+    try:
+        with open(this_dir / "outputs" / "analysis_summary.json", "r") as summary_file:
+            summary_data = json.load(summary_file)
+    except FileNotFoundError:
+        summary_data = {"error": "Analysis summary file not found."}
+    return {"message": "Analysis Completed", "summary": summary_data}
+
+#################################################
+#### TTS Generator SRT Subtitiles generation ####
+#################################################
+@app.get("/api/srt-generation")
+async def srt_generation():
+    venv_path = sys.prefix
+    env = os.environ.copy()
+    env["PATH"] = os.path.join(venv_path, "bin") + ":" + env["PATH"]
+    ttslist_path = this_dir / "outputs" / "ttsList.json"
+    wavfile_path = this_dir / "outputs"
+    subprocess.run(["python", "tts_srt.py", f"--ttslistpath={ttslist_path}", f"--wavfilespath={wavfile_path}"], cwd=this_dir / "system" / "tts_srt", env=env)
+    
+    srt_file_path = this_dir / "outputs" / "subtitles.srt"
+    if not srt_file_path.exists():
+        raise HTTPException(status_code=404, detail="Subtitle file not found.")
+    
+    return FileResponse(path=srt_file_path, filename="subtitles.srt", media_type='application/octet-stream')
 
 ###################################################
 #### Webserver Startup & Initial model Loading ####

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» ).