fucking crazy zshrc

.zshrc

@@ -1,9 +1,23 @@
+# Configuration for Oh My Zsh and custom settings
+# ----------------------------------------------
+# 1. Source the custom git wrapper script
+# 2. Set the path for Oh My Zsh installation
+# 3. Define plugins for extended functionality:
+#    - git: Provides aliases and functions for Git
+#    - autojump: Enables quick navigation to frequently visited directories
+#    - conda-env: Adds support for Conda environment management
+# 4. Set the custom theme for the shell prompt
+
+# Load the custom git wrapper script
 source $HOME/toolkit/git-wrapper.zsh
 
+# Set the path to the Oh My Zsh installation directory
 export ZSH="$HOME/.oh-my-zsh"
 
+# Enable Oh My Zsh plugins for additional features
 plugins=(git autojump conda-env)
 
+# Set the custom theme for the shell prompt
 ZSH_THEME="kade"
 # CASE_SENSITIVE="true"
 # HYPHEN_INSENSITIVE="true"
@@ -14,38 +28,89 @@ ZSH_THEME="kade"
 # COMPLETION_WAITING_DOTS="true"
 # DISABLE_UNTRACKED_FILES_DIRTY="true"
 
+# Set the system language and locale to Japanese UTF-8
 export LANG=ja_JP.UTF-8
 export LC_ALL=ja_JP.UTF-8
+# Set the maximum number of commands to store in the shell history
 export HISTSIZE=500000
-
+# Set the path to the ComfyUI installation
 export COMFYUI_PATH="$HOME/ComfyUI"
+# Set the CUDA version for bitsandbytes library
 export BNB_CUDA_VERSION=126
-
+# Enable full backtrace for Rust programs
 export RUST_BACKTRACE=1
-
+# Opt out of .NET CLI telemetry data collection
 export DOTNET_CLI_TELEMETRY_OPTOUT=1
+# Enable color output in the terminal (value might need adjustment)
 export CLICOLOR=126
 
 # ⚠️ TODO: This needs to be benched but I'm too bad at this!
+
+# Set the maximum number of threads for NumExpr library
+# NumExpr is used for fast numerical array operations
+# This setting can improve performance for multi-threaded NumPy operations
 export NUMEXPR_MAX_THREADS=24 
+# Set the maximum number of threads for Apple's Accelerate framework (VecLib)
+# This affects performance of vector and matrix operations on macOS
+# Note: This setting may not have an effect on non-macOS systems
 export VECLIB_MAXIMUM_THREADS=24
+# Set the number of threads for Intel Math Kernel Library (MKL)
+# MKL is used for optimized mathematical operations, especially in NumPy
+# This can significantly impact performance of linear algebra operations
 export MKL_NUM_THREADS=24
+# Set the number of threads for OpenMP
+# OpenMP is used for parallel programming in C, C++, and Fortran
+# This affects the performance of libraries and applications using OpenMP
 export OMP_NUM_THREADS=24
 
+# Disable parallelism for the Hugging Face Tokenizers library
+# This can help prevent potential deadlocks or race conditions in multi-threaded environments
+# It's particularly useful when using tokenizers in conjunction with DataLoader in PyTorch
+# Setting this to false ensures more predictable behavior, especially in production environments
+# However, it may slightly reduce performance in some scenarios where parallel tokenization is beneficial
 export TOKENIZERS_PARALLELISM=false
 
+# Source the Oh My Zsh script
+# This line loads Oh My Zsh, a popular framework for managing Zsh configuration
+# It sets up various features like themes, plugins, and custom functions
+# The $ZSH variable should be set to the installation directory of Oh My Zsh
+# This is typically done earlier in the .zshrc file, often as: export ZSH="$HOME/.oh-my-zsh"
+# After sourcing, all Oh My Zsh functionality becomes available in your shell session
 source $ZSH/oh-my-zsh.sh
 
+# Extend the system PATH to include various directories:
+# - Custom dataset tools in the user's repository
+# - Rust's Cargo binary directory
+# - Miniconda3 binary directory
+# - User's toolkit directory
+# - Redis and PostgreSQL binary directories
+# - User's local bin directory
+# - CUDA binary directory
 export PATH=$PATH:$HOME/source/repos/dataset-tools/target/x86_64-unknown-linux-gnu/release:$HOME/.cargo/bin:$HOME/miniconda3/bin:$HOME/toolkit:$HOME/db/redis-stable/src:$HOME/db/postgresql/bin:$HOME/.local/bin:/opt/cuda/bin
+
+# Extend the LD_LIBRARY_PATH to include:
+# - Conda environment's library directory
+# - CUDA library directory for x86_64 Linux
+# This ensures that dynamically linked libraries in these locations can be found at runtime
 export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$CONDA_PREFIX/lib:/opt/cuda/targets/x86_64-linux/lib
+
+# Set the path for ComfyUI models
+# This environment variable likely tells ComfyUI where to look for AI models
 export COMFYUI_MODEL_PATH=/home/kade/ComfyUI/models
 
+# Use the UPX executable compression tool from the local bin directory
 alias upx='/home/kade/.local/bin/upx'
+# Always display colorized output for the 'ls' command
 alias ls='ls --color=always'
+# List all files in long format, including hidden files, with human-readable sizes and colorized output
 alias ll="ls -lah --color=always"
+# Use the 'reflink' option for 'cp' to enable copy-on-write when possible, improving efficiency
 alias cp='cp --reflink=auto'
+# Launch TensorBoard with the log directory set to the user's output_dir/logs
 alias t="tensorboard --logdir=$HOME/output_dir/logs"
+# Edit tmux configuration, display a message, and reload the tmux configuration
 alias rt="vim ~/.tmux.conf && echo \"Reloading tmux config\" && tmux source ~/.tmux.conf"
+# Edit zsh configuration, display a message, and reload the zsh configuration
 alias zr="vim ~/.zshrc && echo \"Reloading zsh config\" && source ~/.zshrc"
 
 # The kanji 接 (せつ) [setsu] means "touch," "contact," "adjoin," or "piece together."
@@ -56,28 +121,45 @@ alias zr="vim ~/.zshrc && echo \"Reloading zsh config\" && source ~/.zshrc"
 # 2. Type "setsu" (せつ) in hiragana.
 # 3. Press the spacebar to convert it to the kanji 接.
 alias 接="tmux attach"
+# Alias for attaching to an existing tmux session
+# 'ta' is a shorthand for 'tmux attach'
 alias ta="tmux attach"
 
+# Alias for adding all changes, committing with a signed verbose message, and pushing to remote
 alias ga="git add . && git commit -avs && git push"
+# Alias for checking the current status of the git repository
 alias gs="git status"
+# Alias for displaying word-level differences in git, using a custom regex and the patience algorithm
 alias wd="git diff --word-diff-regex='[^,]+' --patience"
+# Alias for using Neovim instead of Vim
 alias vim="nvim"
+# Another alias for using Neovim instead of Vim
 alias vi="nvim"
+# Short alias for quickly opening Neovim
 alias v="nvim"
+# Alias for resetting the git repository to the last commit, discarding all changes
 alias grh='git reset --hard'
+# Alias for cloning a git repository including all its submodules
 alias gcs='git clone --recurse-submodules'
+# Alias for running the Grabber-cli command
 alias grabber="Grabber-cli"
 
 # 'pie' is a shortcut for installing a Python package in editable mode
 # using the pip command with the --use-pep517 option.
 alias pie='pip install -e . --use-pep517'
+# Alias for creating a signed, verbose git commit
 alias gc="git commit -avs --verbose"
+# Alias for displaying directory contents with colorized output
 alias dir="dir --color=always"
 
+# Alias for quickly editing and reloading the zsh configuration file
 alias ezc="nvim ~/.zshrc && source ~/.zshrc"
 
+# Source the broot launcher script for enhanced file navigation
 source /home/kade/.config/broot/launcher/bash/br
 
+# Source the fzf (Fuzzy Finder) configuration for zsh if it exists
+# This enables fzf functionality in the shell, including keybindings and auto-completion
 [ -f ~/.fzf.zsh ] && source ~/.fzf.zsh
 
 # >>> conda initialize >>>
@@ -110,7 +192,39 @@ display_git_help() {
 }
 display_git_help
 
-# This function, rejiggle_captions, takes two arguments: a tag and a directory.
+# Function: re (Resize SDXL LoRA)
+# Description:
+#   This function resizes an SDXL LoRA (Low-Rank Adaptation) model using the resize_lora.py script.
+#   It applies a specific resizing recipe to reduce the size of the LoRA while maintaining its effectiveness.
+#
+# Usage:
+#   re <target_file>
+#
+# Parameters:
+#   $1 (target_file): Path to the input LoRA safetensors file to be resized.
+#
+# Actions:
+#   1. Calls the resize_lora.py script with the following arguments:
+#      - Verbose output (-vv)
+#      - Custom resizing recipe (-r fro_ckpt=1,thr=-3.55)
+#      - Path to the SDXL checkpoint file (ponyDiffusionV6XL_v6StartWithThisOne.safetensors)
+#      - Path to the input LoRA file
+#
+# Recipe Explanation:
+#   - fro_ckpt=1: Uses the Frobenius norm of the checkpoint layer as the score metric
+#   - thr=-3.55: Sets a threshold for singular values at 10^-3.55 ≈ 0.000282 times the reference
+#
+# Notes:
+#   - This function assumes the resize_lora.py script is located at ~/source/repos/resize_lora/
+#   - The SDXL checkpoint file is expected to be in ~/ComfyUI/models/checkpoints/
+#   - Output will be verbose (-vv) for detailed information during the resizing process
+#   - The resized LoRA will be saved in the same directory as the script by default
+function re() {
+    target_file="$1"
+    python ~/source/repos/resize_lora/resize_lora.py -vv -r fro_ckpt=1,thr=-3.55 ~/ComfyUI/models/checkpoints/ponyDiffusionV6XL_v6StartWithThisOne.safetensors "$target_file"
+}
+
+# This function takes two arguments: a tag and a directory.
 # It searches for all .txt files in the specified directory and its subdirectories.
 # If a file contains the specified tag, the function removes the tag from its original position
 # and prepends it to the beginning of the file.
@@ -162,6 +276,32 @@ update_conda() {
     echo "All environments have been upgraded."
 }
 
+# Function: list_word_freqs
+# Description:
+#   This function analyzes text files in a specified directory and lists the most frequent words (tags).
+#
+# Usage:
+#   list_word_freqs <target_directory>
+#
+# Parameters:
+#   - target_directory: The directory containing the text files to analyze.
+#
+# Functionality:
+#   1. Combines all .txt files in the target directory into a single temporary file.
+#   2. Uses awk to process the combined file:
+#      - Ignores common words like "a", "the", "and", etc.
+#      - Converts all words to lowercase and removes non-alphabetic characters.
+#      - Counts the frequency of each word.
+#   3. Sorts the words by frequency in descending order.
+#   4. Displays the top 40 most frequent words along with their occurrence count.
+#
+# Output:
+#   Prints a list of the 40 most frequent words in the format: <frequency> <word>
+#
+# Note:
+#   - This function is useful for analyzing tag frequencies in image caption files or similar text-based datasets.
+#   - The list of ignored words can be modified to suit specific needs.
+#   - The function creates a temporary file which is automatically removed after processing.
 list_word_freqs() {
     local target_dir=$1
     if [[ -z "$target_dir" ]]; then
@@ -210,6 +350,19 @@ list_word_freqs() {
     rm "$combined_file"
 }
 
+# Function: sample_prompts
+# Description:
+#   This function takes a sample of the tags (or captions) in a target training directory.
+#   It reads and displays the contents of all .txt files in the specified directory,
+#   providing a quick overview of the tags or captions used for training.
+#
+# Usage: sample_prompts <target_directory>
+#
+# Parameters:
+#   - target_directory: The directory containing the .txt files with tags or captions.
+#
+# Output:
+#   Prints the contents of each .txt file in the target directory, separated by newlines.
 sample_prompts() {
     local target_directory="$1"
 
@@ -254,6 +407,11 @@ replace_comma_with_keep_tags() {
   done
 }
 
+# Function: display_custom_help
+# Description:
+#   This function displays a custom help menu with various commands, environment information,
+#   and useful instructions for different tools and services. It provides a quick reference
+#   for commonly used commands, LLM setups, taggers, captioners, and database configurations.
 display_custom_help() {
     echo "----------------------------------------------------------------------------------------------------------------------"
     printf "%s\n" "$(conda env list)"
@@ -421,10 +579,6 @@ oui() {
   open-webui serve --port 6969 
 }
 
-llama() {
-  ~/models/Meta-Llama-3-8B-Instruct.Q5_K_M.llamafile -cb -np 4 -a llama-3-8b --embedding --port 11434
-}
-
 # Function to copy matching .caption files
 copy_matching_caption_files() {
   # Define the target directory
@@ -533,6 +687,45 @@ update_dir() {
     fi
 }
 
+# Function: chop_lora
+# Description:
+#   This function processes a LoRA (Low-Rank Adaptation) model file by selectively
+#   keeping or removing specific layers based on predefined presets. It uses the
+#   chop_blocks.py script to perform the actual layer manipulation.
+#
+# Usage:
+#   chop_lora <input_file>
+#
+# Parameters:
+#   $1 - The input LoRA model file (typically a .safetensors file)
+#
+# Presets:
+#   The function defines several presets, each represented by a 21-digit binary string:
+#   - ringdingding: This vector string was used for the Stoat LoRA.
+#   - squeaker: I really have no idea what this is.
+#   - heavylifter: Keeps only one specific layer that seems to learn the most.
+#   - style1 and style2: Different configurations for style transfer
+#   - beeg: A configuration that keeps only the largest layers.
+#   - all: Keeps all layers
+#   - allin: Keeps only the input layers
+#   - allmid: Keeps only the middle layers
+#   - allout: Keeps only the output layers
+#
+# Actions:
+#   1. Extracts the base name of the input file (without extension)
+#   2. Iterates through each preset
+#   3. For each preset, generates an output filename and runs the chop_blocks.py script
+#   4. The script creates a new LoRA file with only the specified layers retained
+#
+# Output:
+#   Creates multiple output files, one for each preset, named as:
+#   "<base_name>-<preset_name>.safetensors"
+#
+# Notes:
+#   - Requires the chop_blocks.py script to be located at ~/source/repos/resize_lora/chop_blocks.py
+#   - The binary strings represent which layers to keep (1) or remove (0)
+#   - This function allows for quick generation of multiple variants of a LoRA model,
+#     each emphasizing different aspects or effects
 chop_lora() {
     local input_file="$1"
     local base_name="${input_file:r}"  # Remove extension
@@ -559,6 +752,25 @@ chop_lora() {
     done
 }
 
+# Function: swch (Switch Git Branch)
+# Description:
+#   This function facilitates switching between Git branches while ensuring a clean working directory.
+#
+# Usage:
+#   swch <branch_name>
+#
+# Parameters:
+#   $1 - The name of the branch to switch to.
+#
+# Actions:
+#   1. Checks if a branch name is provided.
+#   2. Cleans the working directory, removing untracked files and directories.
+#   3. Pulls the latest changes from the remote repository.
+#   4. Checks out the specified branch.
+#
+# Notes:
+#   - Use with caution as 'git clean -fxd' will remove all untracked files and directories.
+#   - Ensure all important changes are committed or stashed before using this function.
 swch() {
     if [ -z "$1" ]; then
         echo "Please provide a branch name."
@@ -568,6 +780,26 @@ swch() {
     git clean -fxd && git pull && git checkout $branchname
 }
 
+# Function: extract_iframes
+# Description:
+#   This function extracts I-frames from a video file using ffmpeg.
+#
+# Usage:
+#   extract_iframes <input_file> [<scene_change_fraction>]
+#
+# Parameters:
+#   $1 - The input video file (required)
+#   $2 - The scene change fraction threshold (optional, default: 0.1)
+#
+# Actions:
+#   1. Assigns input arguments to variables
+#   2. Extracts the base filename without extension
+#   3. Runs ffmpeg to extract I-frames based on the scene change threshold
+#   4. Saves extracted frames as PNG files with sequential numbering
+#
+# Notes:
+#   - Requires ffmpeg to be installed and accessible via /usr/bin/ffmpeg
+#   - Output files will be named as "<base_name>-XXXXXX.png" in the current directory
 extract_iframes() {
     # Assign input arguments
     input_file="$1"
@@ -580,56 +812,27 @@ extract_iframes() {
     /usr/bin/ffmpeg -i "$input_file" -f image2 -vf "select=eq(pict_type\,PICT_TYPE_I)*gt(scene\,$scene_change_fraction),showinfo" -fps_mode vfr "${base_name}-%06d.png"
 }
 
-convert_to_jxl() {
-    local target_directory="$1"
-
-    # Ensure the target directory exists
-    if [[ ! -d "$target_directory" ]]; then
-        echo "The specified directory does not exist: $target_directory" >&2
-        return 1
-    fi
-
-    # Find all JPG, JPEG, and PNG files in the target directory and all subdirectories
-    find "$target_directory" \( -name "*.jpg" -o -name "*.jpeg" -o -name "*.png" \) -type f | while read -r file; do
-        input_path="$file"
-        output_path="${file%.*}.jxl"
-
-        # Convert to JXL using ImageMagick
-        if magick convert "$input_path" "$output_path"; then
-            echo "Converted: $input_path -> $output_path"
-        else
-            echo "Failed to convert $input_path" >&2
-        fi
-    done
-
-    echo "Conversion complete."
-}
-
-convert_pxl_to_png() {
-    local target_directory="$1"
-
-    # Ensure the target directory exists
-    if [[ ! -d "$target_directory" ]]; then
-        echo "The specified directory does not exist: $target_directory" >&2
-        return 1
-    fi
-
-    # Find all PXL files in the target directory and all subdirectories
-    find "$target_directory" -type f -name "*.pxl" | while read -r file; do
-        input_path="$file"
-        output_path="${file%.pxl}.png"
-
-        # Convert PXL to PNG using ImageMagick
-        if magick convert "$input_path" "$output_path"; then
-            echo "Converted: $input_path -> $output_path"
-        else
-            echo "Failed to convert $input_path" >&2
-        fi
-    done
-
-    echo "Conversion complete."
-}
-
+# Function: seed
+# Description:
+#   This function extracts the seed value from a LoRA (Low-Rank Adaptation) model's metadata.
+#
+# Usage:
+#   seed <file_path>
+#
+# Parameters:
+#   $1 - The path to the LoRA model file (usually a .safetensors file)
+#
+# Actions:
+#   1. Takes the file path as an argument
+#   2. Uses Python to read the safetensors file
+#   3. Extracts the metadata from the file
+#   4. Attempts to retrieve the 'ss_seed' value from the metadata
+#   5. Prints the seed value if found, or 'Not found' if not present
+#
+# Notes:
+#   - Requires Python 3 with the 'safetensors' module installed
+#   - The seed is typically used to reproduce the exact training conditions of the LoRA
+#   - If the seed is not found, it may indicate the LoRA was created without recording this information
 seed() {
     local filePath="$1"
     python3 -c "
@@ -637,27 +840,111 @@ import safetensors, json
 filePath = '$filePath'
 print(json.loads(safetensors.safe_open(filePath, 'np').metadata().get('ss_seed', 'Not found')))"
 }
-
+# Function: png2mp4
+# Description:
+#   This function converts a series of PNG images into an MP4 video file using ffmpeg.
+#
+# Usage:
+#   png2mp4
+#
+# Parameters:
+#   None (uses all PNG files in the current directory)
+#
+# Actions:
+#   1. Sets the frame rate to 8 fps
+#   2. Uses glob pattern to include all PNG files in the current directory
+#   3. Scales the output video to 1024x1024 resolution
+#   4. Sets the Constant Rate Factor (CRF) to 28 for good compression
+#   5. Uses the libx264 codec for H.264 encoding
+#   6. Sets the pixel format to yuv420p for compatibility
+#   7. Outputs the result as 'out.mp4' in the current directory
+#
+# Notes:
+#   - Requires ffmpeg to be installed and accessible in the system path
+#   - PNG files should be in the current directory
+#   - Output video will be named 'out.mp4' and placed in the current directory
+#   - Adjust the framerate, scale, or CRF value as needed for different results
 png2mp4() {
-  ffmpeg -framerate 8 -pattern_type glob -i '*.png' -vf scale=512x512 -crf 28 \
+  ffmpeg -framerate 8 -pattern_type glob -i '*.png' -vf scale=1024x1024 -crf 28 \
   -c:v libx264 -pix_fmt yuv420p out.mp4
 }
 
-c_old() {
-    cd ~/ComfyUI &&
-    python3.12 main.py --listen 0.0.0.0 --preview-method taesd --use-pytorch-cross-attention --disable-xformers --fast
-}
-
+# Function: c
+# Description:
+#   This function launches ComfyUI with specific settings tailored to the user's preferences.
+#
+# Usage:
+#   c
+#
+# Actions:
+#   1. Changes directory to ~/ComfyUI
+#   2. Activates the 'comfyui' conda environment
+#   3. Launches ComfyUI with the following settings:
+#      - Listens on all network interfaces (0.0.0.0)
+#      - Uses 'taesd' as the preview method
+#      - Enables PyTorch cross-attention
+#      - Disables xformers
+#      - Uses the latest version of Comfy-Org/ComfyUI_frontend
+#      - Enables fast mode
+#
+# Parameters:
+#   None
+#
+# Notes:
+#   - Requires ComfyUI to be installed in ~/ComfyUI
+#   - Requires a conda environment named 'comfyui' with necessary dependencies
+#   - The --listen 0.0.0.0 option allows access from other devices on the network
+#   - --preview-method taesd provides better previews
+#   - --use-pytorch-cross-attention and --disable-xformers affect performance and compatibility
+#   - --front-end-version ensures the latest UI is used
+#   - --fast option may improve overall performance
 c() {
     cd ~/ComfyUI &&
     conda activate comfyui
     python main.py --listen 0.0.0.0 --preview-method taesd --use-pytorch-cross-attention --disable-xformers --front-end-version Comfy-Org/ComfyUI_frontend@latest --fast
 }
 
+# Function: conda_prompt_info
+# Description:
+#   This function displays information about the currently active Conda environment.
+#
+# Usage:
+#   conda_prompt_info
+#
+# Returns:
+#   A string containing the name of the active Conda environment, enclosed in parentheses.
+#   If no Conda environment is active, it returns an empty string.
+#
+# Details:
+#   1. Checks if the CONDA_DEFAULT_ENV environment variable is set and non-empty.
+#   2. If CONDA_DEFAULT_ENV is set, it echoes the environment name in parentheses.
+#   3. If CONDA_DEFAULT_ENV is not set or empty, the function returns silently.
+#
+# Example output:
+#   If CONDA_DEFAULT_ENV is set to "myenv", the function will output: (myenv)
+#
+# Notes:
+#   - This function is typically used in command prompts or shell scripts to
+#     visually indicate the active Conda environment to the user.
+#   - It can be incorporated into PS1 or other prompt variables to automatically
+#     display the Conda environment in the shell prompt.
 conda_prompt_info() {
   if [[ -n "$CONDA_DEFAULT_ENV" ]]; then
     echo "(${CONDA_DEFAULT_ENV})"
   fi
 }
 
+# Function: display_custom_help
+# Description:
+#   This function displays custom help information for user-defined functions and aliases.
+#   It provides a quick reference for commonly used commands and their descriptions.
+#
+# Usage:
+#   display_custom_help
+#
+# Output:
+#   Prints a formatted list of custom commands and their brief descriptions.
+#
+# Note:
+#   Add or modify entries in this function to keep your personal command reference up-to-date.
 display_custom_help

password

@@ -1,14 +1,26 @@
 #!/usr/bin/env python
 # -*- coding: utf-8 -*-
 
+"""
+Generate a random strong password with 16 characters.
+"""
+
 import random
 import string
 
+
 def generate_password(length=16):
+    """
+    Generate a random password with the given length.
+
+    :param length: Length of the password to generate (default is 16)
+    :return: A randomly generated password string
+    """
     characters = string.ascii_letters + string.digits + string.punctuation
     password = ''.join(random.choice(characters) for _ in range(length))
     return password
 
+
 # Generate a strong 16-character long password
-strong_password = generate_password()
-print(strong_password)
+STRONG_PASSWORD = generate_password()
+print(STRONG_PASSWORD)

steal_sdscripts_metadata

@@ -0,0 +1,103 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+
+"""
+This script automates the process of updating a Stable Diffusion training
+script with settings extracted from a LoRA model's JSON metadata.
+
+It performs the following main tasks:
+1. Reads a JSON file containing LoRA model metadata
+2. Parses an existing Stable Diffusion training script
+3. Maps metadata keys to corresponding script arguments
+4. Updates the script with values from the metadata
+5. Handles special cases and complex arguments (e.g., network_args)
+6. Writes the updated script to a new file
+
+Usage:
+    python steal_sdscripts_metadata <metadata_file> <script_file> <output_file>
+
+This tool is particularly useful for replicating training conditions or
+fine-tuning existing models based on successful previous runs.
+"""
+
+import json
+import re
+import argparse
+
+# Parse command-line arguments
+parser = argparse.ArgumentParser(
+    description='Update training script based on metadata.'
+)
+parser.add_argument(
+    'metadata_file', type=str, help='Path to the metadata JSON file'
+)
+parser.add_argument(
+    'script_file', type=str, help='Path to the training script file'
+)
+parser.add_argument(
+    'output_file', type=str, help='Path to save the updated training script'
+)
+args = parser.parse_args()
+
+# Read the metadata JSON file
+with open(args.metadata_file, 'r', encoding='utf-8') as f:
+    metadata = json.load(f)
+
+# Read the training script
+with open(args.script_file, 'r', encoding='utf-8') as f:
+    script_content = f.read()
+
+# Define mappings between JSON keys and script arguments
+mappings = {
+    'ss_network_dim': '--network_dim',
+    'ss_network_alpha': '--network_alpha',
+    'ss_learning_rate': '--learning_rate',
+    'ss_unet_lr': '--unet_lr',
+    'ss_text_encoder_lr': '--text_encoder_lr',
+    'ss_max_train_steps': '--max_train_steps',
+    'ss_train_batch_size': '--train_batch_size',
+    'ss_gradient_accumulation_steps': '--gradient_accumulation_steps',
+    'ss_mixed_precision': '--mixed_precision',
+    'ss_seed': '--seed',
+    'ss_resolution': '--resolution',
+    'ss_clip_skip': '--clip_skip',
+    'ss_lr_scheduler': '--lr_scheduler',
+    'ss_network_module': '--network_module',
+}
+
+# Update script content based on metadata
+for json_key, script_arg in mappings.items():
+    if json_key in metadata:
+        value = metadata[json_key]
+
+        # Handle special cases
+        if json_key == 'ss_resolution':
+            value = f'"{value[1:-1]}"'  # Remove parentheses and add quotes
+        elif isinstance(value, str):
+            value = f'"{value}"'
+
+        # Replace or add the argument in the script
+        pattern = f'{script_arg}=\\S+'
+        replacement = f'{script_arg}={value}'
+        if re.search(pattern, script_content):
+            script_content = re.sub(pattern, replacement, script_content)
+        else:
+            script_content = script_content.replace(
+                'args=(', f'args=(\n    {replacement}'
+            )
+
+# Handle network_args separately as it's more complex
+if 'ss_network_args' in metadata:
+    network_args = metadata['ss_network_args']
+    NETWORK_ARGS_STR = ' '.join(
+        [f'"{k}={v}"' for k, v in network_args.items()]
+    )
+    PATTERN = r'--network_args(\s+".+")+'
+    replacement = f'--network_args\n               {NETWORK_ARGS_STR}'
+    script_content = re.sub(PATTERN, replacement, script_content)
+
+# Write the updated script
+with open(args.output_file, 'w', encoding='utf-8') as f:
+    f.write(script_content)
+
+print(f"Updated training script has been saved as '{args.output_file}'")