django_langchain_accelerator

Description

This project, django_langchain_accelerator, leverages a Language Model (LLM) to expedite the creation of Django projects. It generates necessary boilerplate code for Django projects, taking into account both the user's specifications and existing Django projects as a reference and context. For this purpose, we will use langchain with OpenAI.

Installation

Install poetry:

  pip install poetry

In root of the repository run the following command to install dependencies:

  poetry install --no-root

Setup

In order for the code to work, you need to provide OpenAI API key. You can do this by setting the environment variable:

  export OPENAI_API_KEY=<your_openai_api_key>

Usage

There is prepared example of usage in main.py file. To run it use:

  poetry run python main.py -t <file_with_user_story> -p <path_to_existing_project> -p <path_to_existing_project> -o <output_root_dir>

where

<file_with_user_story> is a file with user story.
<path_to_existing_project> is a path to existing Django project which will be used as a context for the generated code.
<output_root_dir> is a path to the directory where the generated code will be saved. If not provided, the code will be saved under result subdirectory.

Development

To install the linting and type checking tools, run the following command in the root of the repository:

  poetry install --only dev --no-root

To run the formatter execute:

  poetry run ruff format

To run the linter execute:

  poetry run ruff check

To run the type checker execute: