Revolutionize LLM Coding with Enhanced Context Mapping

I'm excited to share a new tool I've been working on called `codemapper`. This Python package is designed to map a code repository for LLM (Large Language Model) editing, providing a more efficient and context-aware coding experience.

#### What is `codemapper`?

`codemapper` is a command-line tool that traverses a code repository, extracts relevant information such as docstrings, function signatures, class names, and import statements, and creates a JSON map of the repository. This map can then be used to provide minimal context to an LLM, allowing it to figure out which files need to be edited and ask to see those files.

Why Use `codemapper`?

1. *Improved Context*: By providing a detailed map of the repository, `codemapper` helps LLMs understand the structure and content of your codebase, leading to more accurate and relevant suggestions. 2. *Efficiency*: Instead of providing the entire repository to the LLM, `codemapper` allows you to focus on specific files and functions, reducing the amount of context needed and speeding up the editing process. 3. *Modularity*: The tool is designed to be modular and extensible, making it easy to integrate into existing workflows and adapt to different coding styles.

Contributing

Contributions are welcome! Please open an issue or submit a pull request.

License

This project is licensed under the MIT License.

#### Repository

Check out the repository on GitHub: [codemapper](https://github.com/MikeyBeez/codemapper)

I'm really excited about the potential of `codemapper` to improve the efficiency and accuracy of LLM-based coding. I'd love to hear your thoughts and feedback!

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