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Toolkit for building AI Applications

Project description

phidata

Build applications using open-source tools

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Phidata is a toolkit for building applications using open source tools

🤔 What does that mean?

Open source tools can be used to build powerful software, but are difficult to run in production settings. Phidata is a library that converts OSS like FastApi, Jupyter, Airflow, Superset into python classes that can be put together to build applications like AI Apps, RestAPIs, Django Apps and even full-scale Data Platforms.

With everything in pure python, these applications can then be managed as 1 unit using software engineering best practices.

If you like using open source tools, phidata is for you. It also comes with a library of pre-configured tech stacks that makes it easy to get started with common use cases.

🚀 How it works

  • Phidata provides pre-configured templates for common use cases.
  • Create your codebase from a template using phi ws create
  • Run your app locally using phi ws up dev:docker
  • Run your app on AWS using phi ws up prd:aws
  • Integrate with your front-end or product using APIs.

Example: Run a Jupyter Notebook

Requirements

Setup

Open the terminal and create a python virtual environment

python3 -m venv ~/.venvs/aienv
source ~/.venvs/aienv/bin/activate

Install phidata

pip install phidata

Define DockerConfig that runs a Jupyter app

Create a file resources.py

touch resources.py

Add the following code to resources.py

from phidata.app.jupyter import Jupyter
from phidata.docker.config import DockerConfig


dev_docker_config = DockerConfig(
    apps=[
        # -*- Run Jupyter on port 8888
        Jupyter(mount_workspace=True)
    ],
)

Start the app

phi start resources.py
  • Open the browser and go to http://localhost:8888
  • Password is admin

Stop the app

phi stop resources.py

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