repo-gpt 0.1.0

Search your code repository using GPT3.5 or GPT4.

Repo GPT

Repo-GPT is a Python CLI tool designed to utilize the power of OpenAI's GPT-3 model. It facilitates the process of code analysis and search within your repositories.

Features

• Code extraction and processing from your repositories.
• Semantic search within your codebase through natural language queries.
• Response generation to natural language queries about your code.
• Specific file analysis within your codebase.

Installation

Repo-GPT can be installed via pip:

pip install repo-gpt

Alternatively, you can clone and install from the source code:

git clone https://github.com/yourusername/repo-gpt.git
cd repo-gpt
poetry install

Setting Up

Before starting, make sure to set up your OpenAI key in your environment variables.

export OPENAI_API_KEY=<insert your openai key>

To set up Repo-GPT, run the following command at the root of the project you want to search. This will create a .repo_gpt directory and store the code embeddings there:

repo-gpt setup

Repo-GPT will only add or update embeddings for new files or changed files. You can rerun the setup command as many times as needed.

Usage

After setup, you can perform various tasks:

• Semantic Search: Find semantically similar code snippets in your codebase:

  repo-gpt search <text/question>
  

• Codebase Query: Ask questions about your codebase:

  repo-gpt query <text/question>
  

• File Analysis: Analyze a specific file:

  repo-gpt analyze <file_path>
  

• Help: Access the help guide:

  repo-gpt help
  

Example:

repo-gpt setup --root_path ./my_project
repo-gpt search "extract handler"
repo-gpt query "What does the function `calculate_sum` do?"
repo-gpt analyze ./my_project/main.py

Contributing

We welcome your contributions! Before starting, please make sure to install Python 3.11 and the latest version of poetry. Pyenv is a convenient tool to manage multiple Python versions on your computer.

Here are the steps to set up your development environment:

1. Export your OpenAI key to your environment variables:

   export OPENAI_API_KEY=<insert your openai key>
   

2. Install dependencies:

   poetry install --no-root
   

3. Install pre-commit hooks:

   poetry run pre-commit install
   

4. Seed data:

   poetry run python cli.py setup
   

5. Query data:

   poetry run python cli.py search <text/question>
   

Debugging

You can view the output of the code_embeddings.pkl using the following command:

pd.read_pickle('./.repo_gpt/code_embeddings.pkl', compression='infer')

Roadmap

Here are the improvements we are currently considering:

• Publishing to PyPi
• Test suite addition
• Add CI/CD
• Prettify output
• Add readme section about how folks can contribute parsers for their own languages
• Save # of tokens each code snippet has so we can ensure we don't pass too many tokens to GPT
• Add SQL file handler
• Add DBT file handler -- this may be a break in pattern as we'd want to use the manifest.json file