https://github.com/hormold/gpt-sql-box
Text to SQL generator GPT-3 (Python + Vue) and also AI chart generator!
https://github.com/hormold/gpt-sql-box
ai charts gpt-3 openai postgres python sql vue
Last synced: about 1 month ago
JSON representation
Text to SQL generator GPT-3 (Python + Vue) and also AI chart generator!
- Host: GitHub
- URL: https://github.com/hormold/gpt-sql-box
- Owner: Hormold
- License: gpl-3.0
- Created: 2023-02-03T19:23:04.000Z (over 3 years ago)
- Default Branch: master
- Last Pushed: 2023-02-05T13:37:42.000Z (over 3 years ago)
- Last Synced: 2025-06-11T04:16:29.353Z (11 months ago)
- Topics: ai, charts, gpt-3, openai, postgres, python, sql, vue
- Language: HTML
- Homepage: https://medium.com/@hormold/make-gpt-3-work-for-you-17a3bf744234
- Size: 633 KB
- Stars: 50
- Watchers: 1
- Forks: 13
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# GPT-3 SQL Query Generator and UI (And AI Chart Generator)
This is simple python application to generate SQL Schema + prompt to ask GPT-3 to generate SQL queries.
It also has a simple UI to show results in a table. And yes, **you can try to generate a chart from the results of query**.
GPT-3 self choose the chart type and prepare the data for it (it is not perfect, but it is a good start).
**It can generate a prompt for you, if you don't know what to ask GPT-3.**
## How it works:
1. Getting SQL schemas from PostgreSQL and compile prompt from SQL Schema
3. Wait for user input
4. Generate SQL query from prompt + user input
5. Show SQL query and ask user to confirm or edit if it is correct before executing it
6. Execute SQL query and show results in a table
## Environment
- DATABASE_URL: PostgreSQL database URL
- OPENAI_TOKEN: OpenAI API token (Not nessessary, you can set it in the UI)
- APP_PORT: Port to run the application (default: 5000)
- OPENAI_ENGINE: OpenAI engine to use (default: text-davinci-003, not nessessary). You can set some free to use model: text-chat-davinci-002-20221122
## How to run
1. It better to create a virtual environment using `python3 -m venv venv`
2. Install dependencies using `pip install -r requirements.txt`
3. Set environment variables in `.env` file in project root or in your system
4. Run the application using `python app.py` and open `http://localhost:5000` in your browser
## Contact
If you have any questions, please contact me at [@define](https://t.me/define) in Telegram.