Generate DDLs (PostgreSQL) from an ER diagram using OpenAI Vision.
OpenAI Vision Documentation: https://platform.openai.com/docs/guides/vision

TBD

You need Python 3.12.4 installed in your system. If you are using pyenv then check the version using the command: pyenv version

1. Install poetry

   # Using pip
   pip install poetry
   
   # Using brew (macOS), if you are using pyenv you should use `pip install poetry`
   brew install poetry

2. Set poetry to create virtual environment within project folder

   poetry config virtualenvs.in-project true

3. Install dependency and create the virtual environment

   poetry install

4. Run the app with poetry

   poetry run python main.py

   or launch the app via VS Code debug menu. VS Code launch config file is also provided for easy debugging 🤓

To update dependencies use: poetry update
If you want to update dependencies in pyproject.toml, then you need to install plugin poetry-plugin-up. Use command below:

poetry self add poetry-plugin-up

Once installed, use command poetry up to install updates and edit pyproject.toml automatically.
To view virtual environment location, use: poetry env info --path
To generate requirements.txt using poetry, you need to have an export plugin installed.

Install the plugin:

poetry self add poetry-plugin-export

Once the plugin is installed, use the export command to generate requirements.txt

poetry export -f requirements.txt --output requirements.txt --without-hashes

There are 2 environment variables you can specify.

1. OPENAI_API_KEY: This is your OpenAI API key.
2. GRADIO_SERVER_PORT: This is the Gradio server port. This is optional if not specified in the launch method.

If you are planning on deploying the app to the cloud, you need a Docker image. To build the same use the Dockerfile provided. The multi-stage build makes sure the resulting image is smaller in size and only includes the libraries that are needed. Also, the use of non-root user makes it more secure.

Build arm64 image (Make sure cloud deployment supports arm64 images):

docker build --no-cache -t erd2ddl_latest .

For amd64 image (most common and widely supported):

docker buildx build --no-cache --platform linux/amd64 -t erd2ddl_latest .

Once the image is built, you can push the same to any cloud provider and use a serverless service to deploy the same easily.

To run the Docker image locally use the below command:

docker run -it \
-e GRADIO_SERVER_PORT=8080 \
-e OPENAI_API_KEY=your_key_here \
-p 8080:8080 \
--name erd2ddl \
erd2ddl_latest

1. UI is built using Gradio
   
2. Sql file icons created by Muhammad_Usman - Flaticon

MIT License

Copyright © 2024 Sumit Sahoo

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

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