#prompt #llm #ai #gpt #code #cli-tool #language-model

app code2prompt

A command-line (CLI) tool to generate an LLM prompt from codebases of any size, fast

2 stable releases

1.1.0 Apr 15, 2024
1.0.0 Mar 11, 2024

#220 in Development tools

Download history 176/week @ 2024-03-10 100/week @ 2024-03-17 32/week @ 2024-03-24 49/week @ 2024-03-31 26/week @ 2024-04-07 189/week @ 2024-04-14 36/week @ 2024-04-21 25/week @ 2024-04-28 13/week @ 2024-05-05 18/week @ 2024-05-12 31/week @ 2024-05-19

90 downloads per month

MIT license

756 lines


A CLI tool to convert your codebase into a single LLM prompt with source tree, prompt templating, and token counting.

You can run this tool on the entire directory and it would generate a well-formatted Markdown prompt detailing the source tree structure, and all the code. You can then upload this document to either GPT or Claude models with higher context windows and ask it to:

  • Rewrite the code to another language.
  • Find bugs/security vulnerabilities.
  • Document the code.
  • Implement new features.

You can customize the prompt template to achieve any of the desired use cases. It essentially traverses a codebase and creates a prompt with all source files combined. In short, it automates copy-pasting multiple source files into your prompt and formatting them along with letting you know how many tokens your code consumes.

I initially wrote this for personal use to utilize Claude 3.0's 200K context window and it has proven to be pretty useful so I decided to open-source it!

crates.io LICENSE


Table of Contents


  • Quickly generate LLM prompts from codebases of any size.
  • Customize prompt generation with Handlebars templates. (See the default template)
  • Follows .gitignore.
  • Filter and exclude files by extension.
  • Display the token count of the generated prompt. (See Tokenizers for more details)
  • Optionally include the Git diff output (staged files) in the generated prompt.
  • Copy the generated prompt to the clipboard on generation.
  • Save the generated prompt to an output file.
  • Exclude files and folders by name or path.
  • Add line numbers to source code blocks.


Download the latest binary for your OS from Releases OR install with cargo:

cargo install code2prompt


Generate a prompt from a codebase directory:

code2prompt path/to/codebase

Use a custom Handlebars template file:

code2prompt path/to/codebase -t path/to/template.hbs

Filter files by extension:

code2prompt path/to/codebase -f rs,toml

Exclude files by extension:

code2prompt path/to/codebase -e txt,md

Exclude files by name:

code2prompt path/to/codebase --exclude-files "file1.txt,file2.txt"

Exclude files by folder/directory path:

code2prompt path/to/codebase --exclude-folders "tests,docs"

Display token count of the generated prompt:

code2prompt path/to/codebase --tokens

Specify tokenizer for token count:

code2prompt path/to/codebase --tokens --encoding p50k

Supported tokenizers: cl100k, p50k, p50k_edit, r50k_base.

See Tokenizers for more details.

Save the generated prompt to an output file:

code2prompt path/to/codebase -o output.txt  

Generate git commit message (for staged files):

code2prompt path/to/codebase --diff -t "templates/write-git-commit.hbs"    

Add line numbers to source code blocks:

code2prompt path/to/codebase --line-number


code2prompt comes with a set of built-in templates for common use cases. You can find them in the templates directory.


Use this template to generate prompts for documenting the code. It will add documentation comments to all public functions, methods, classes and modules in the codebase.


Use this template to generate prompts for finding potential security vulnerabilities in the codebase. It will look for common security issues and provide recommendations on how to fix or mitigate them.


Use this template to generate prompts for cleaning up and improving the code quality. It will look for opportunities to improve readability, adherence to best practices, efficiency, error handling, and more.


Use this template to generate prompts for fixing bugs in the codebase. It will help diagnose issues, provide fix suggestions, and update the code with proposed fixes.


Use this template to generate a high-quality README file for the project, suitable for hosting on GitHub. It will analyze the codebase to understand its purpose and functionality, and generate the README content in Markdown format.


Use this template to generate git commits from the staged files in your git directory. It will analyze the codebase to understand its purpose and functionality, and generate the git commit message content in Markdown format.


Use this template to generate prompts for improving the performance of the codebase. It will look for optimization opportunities, provide specific suggestions, and update the code with the changes.

You can use these templates by passing the -t flag followed by the path to the template file. For example:

code2prompt path/to/codebase -t templates/document-the-code.hbs

User Defined Variables

code2prompt supports the use of user defined variables in the Handlebars templates. Any variables in the template that are not part of the default context (absolute_code_path, source_tree, files) will be treated as user defined variables.

During prompt generation, code2prompt will prompt the user to enter values for these user defined variables. This allows for further customization of the generated prompts based on user input.

For example, if your template includes {{challenge_name}} and {{challenge_description}}, you will be prompted to enter values for these variables when running code2prompt.

This feature enables creating reusable templates that can be adapted to different scenarios based on user provided information.


Tokenization is implemented using tiktoken-rs. tiktoken supports these encodings used by OpenAI models:

Encoding name OpenAI models
cl100k_base ChatGPT models, text-embedding-ada-002
p50k_base Code models, text-davinci-002, text-davinci-003
p50k_edit Use for edit models like text-davinci-edit-001, code-davinci-edit-001
r50k_base (or gpt2) GPT-3 models like davinci

For more context on the different tokenizers, see the OpenAI Cookbook

How is it useful?

code2prompt makes it easy to generate prompts for LLMs from your codebase. It traverses the directory, builds a tree structure, and collects information about each file. You can customize the prompt generation using Handlebars templates. The generated prompt is automatically copied to your clipboard and can also be saved to an output file. code2prompt helps streamline the process of creating LLM prompts for code analysis, generation, and other tasks.

Build From Source


For building code2prompt from source, you need to have these tools installed:

  • Git
  • Rust
  • Cargo (Automatically installed when installing Rust)
$ git clone https://github.com/mufeedvh/code2prompt.git
$ cd code2prompt/
$ cargo build --release

The first command clones the code2prompt repository to your local machine. The next two commands change into the code2prompt directory and build it in release mode.


Ways to contribute:

  • Suggest a feature
  • Report a bug
  • Fix something and open a pull request
  • Help me document the code
  • Spread the word


Licensed under the MIT License, see LICENSE for more information.

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~715K SLoC