Skip to content

Latest commit

 

History

History
96 lines (62 loc) · 2.67 KB

README.md

File metadata and controls

96 lines (62 loc) · 2.67 KB
Raw

DataBase AI Processor

Simple tool that extracts information from an SQLite source using human language queries. The stack uses a NextJs frontend and a Django (API) for users management and OpenAI interface.


Download Sources: private repository, for access contact AppSeed

$ git clone https://github.com/app-generator/priv-ai-processor.git
$ cd priv-ai-processor

Django Backend

Edit backend/.env and add you own OpenAI API KEY.

$ cd backend                       # change DIR to the backend code 
$ virtualenv env                   # create a new virtual environment  
$ source env/bin/activate          # activate the VENV
$ pip install -r requirements.txt  # install modules 
$ python manage.py makemigrations  # migrate DB
$ python manage.py migrate         # apply DB changes 
$ python manage.py runserver       # Start the development Server

The backend starts on Django's default address: http://localhost:8000


NextJS UI

$ cd frontend                # change DIR to the frontend code  
$ npm install -g next        # Install NextJs globally
$ npm i                      # install dependencies
$ npm run dev                # Start the development Next Server

How to use the tool

Create a new user or authenticate using the default one:

Add your own OPEN API Key

Access the settings page and save your OpenAI API key

Upload a new SQLite file

Navigate to the SQLite Uploads file and add a new file. Once uploaded, we can query start quering the database.

Query the information using OpenAI console

Here are some query samples:

  • List all tables registered in the database
  • List all products starting with the cheapest

Once another SQLite file is uploaded, we can query other specific questions.


Tools

Outside UI, we can query different sources like PDF files or distant APIs:

$ cd tools
$ virtualenv env                   # create a new virtual environment  
$ source env/bin/activate          # activate the VENV
$ pip install -r requirements.txt  # install modules 
$ vi .env                          # Save OpenAI KEY
$ python ai-over-api-meteo.py      # Extract METEO information using distant API
$ python ai-over-pdf.py            # Extract information from a local PDF file

License

@EULA


DataBase AI Processor - AI/ML Starter provideed AppSeed.