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Streamlines loading and processing text files from a directory for efficient batch handling by AI artists.
The AD_TextListToString
node is designed to streamline the process of loading and processing text files from a specified directory. It is particularly useful for AI artists who need to handle large batches of text data efficiently. This node allows you to specify a directory containing text files, such as .txt
and .csv
, and then processes these files to extract their contents, names, and paths. The node is capable of handling a large number of files by setting a load capacity and can skip a specified number of files if needed. The primary function of this node is to read the contents of these files, merge them into a single string, and provide various outputs that include file names, contents, paths, and a count of the processed files. This functionality is essential for tasks that require batch processing of text data, enabling users to manage and utilize text information effectively in their creative projects.
The Directory
parameter specifies the path to the folder containing the text files you wish to process. It is a string input where you provide the directory path. This parameter is crucial as it determines the source location from which the node will load the text files. The default value is an empty string, indicating that you need to specify a valid directory path for the node to function correctly.
The Load_Cap
parameter defines the maximum number of text files to load from the specified directory. It is an integer input with a default value of 100, and it can range from a minimum of 1 to a maximum of 1000. This parameter allows you to control the number of files processed in a single batch, which can be useful for managing memory usage and processing time.
The Skip_Frame
parameter allows you to skip a certain number of files at the beginning of the directory listing. It is an integer input with a default value of 0, and it can range from 0 to 100. This parameter is useful if you want to bypass a specific number of files and start processing from a particular point in the directory.
The seed
parameter is an integer input used for randomization purposes, although its specific function in this context is not detailed. It has a default value of 0 and can range from 0 to 0xffffffffffffffff. This parameter might be used for operations that require a random element, ensuring consistent results across different runs when the same seed is used.
The File_Names
output provides a list of the base names of the processed text files, without their extensions. This output is useful for identifying the files that have been processed and can be used for further reference or logging purposes.
The File_Contents
output contains a list of the contents of each processed text file. This output is essential for accessing the actual text data within the files, which can then be used for analysis, transformation, or other creative processes.
The File_Paths
output provides a list of the full paths to each processed text file. This output is important for tracking the location of each file and can be used for verification or further file operations.
The File_Names_Suffix
output includes a list of the full names of the processed text files, including their extensions. This output is useful for distinguishing between files with similar base names but different extensions.
The Count
output is an integer that represents the total number of text files that have been processed. This output is helpful for understanding the scope of the batch operation and ensuring that the expected number of files has been handled.
The Merged_Content
output is a single string that contains the concatenated contents of all processed text files, separated by double newlines. This output is particularly useful for tasks that require a unified text input, such as text analysis or generation.
Directory
parameter is set to a valid path containing the text files you wish to process to avoid errors.Load_Cap
parameter based on your system's memory capacity to optimize performance and prevent overloading.Skip_Frame
parameter to manage large datasets by processing files in segments, which can help in organizing and analyzing data incrementally.<file_path>
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