CLI tool using LLMs to apply an instruction to a list of files while considering the context of each file.
Useful if you have a list of files that all require a similar change, but differ in ways that would usually require manual processing.
Be aware that the tool changes files in place, so ideally you have version control setup. This makes it also easy to proof-read the changes before committing them.
Install the package with pip install . or pip install -e . for development.
Make sure to store your OpenAI API key in an OPENAI_API_KEY environment variable.
Usage: llm-batch-edit [OPTIONS]
Apply a change to a list of files, powered by OpenAI's LLMs.
Options:
-l, --filelist PATH File containing a list of filenames to apply the change to. [required]
-i, --instruction TEXT Instruction to follow. [required]
-o, --example_original PATH File containing an example of an original file. [required]
-c, --example_changed PATH File containing an example of the changed original file. [required]
-m, --model TEXT OpenAI model to use for the change.
--help Show this message and exit.In the example/src directory we have three files that all contain a function with a number in its name. We want to extend a print statement in each function so that it also prints the next number after the one referenced in the function name. Basically just a task that would be hard to automate with normal refactoring tools.
Therefore, we can simply prepare an example of the original file (example/original.py) and an example of the changed file (example/changed.py), add all the files that should be changed to a list (example/filelist) and run the following command:
llm-batch-edit \
--filelist ./example/filelist \
--instruction "In the print statement, add (next number is X) where X is the next number after the one referenced in the function name" \
--example_original ./example/original.py \
--example_changed ./example/changed.py