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Hugging Face & Raspbery Pi Flask App

This example Flask app provides an interface for any user to submit text to a field in a browser and see the model predictions rendered in a table. The code to run this app as is requires connection to a running, OMI-compliant Docker container on localhost:45000.

Setting up SSH Tunnel

If you followed these instructions for running a Docker container on your Raspberry Pi, all you have to do is set up a simple SSH tunnel to connect your local server to the port serving the container on the Pi.

ssh -L 45000:localhost:45000 <user@ip-address-of-pi>

Replace <user@ip-address-of-pi> with the username and IP address of your device. In doing so, your SSH tunnel will connect. Now, follow the below instructions to spin up your Flask App with a connection to your edge device.

Flask App Instructions

The following instructions will generate a simple Python Flask web application that makes inference calls to a Hugging Face Text Classification model running on a Raspberry Pi.

  • Download or clone this project from github: git clone https://github.com/modzy/hugging-face-raspberry-pi.git
  • In your terminal, navigate to the project directory: cd hugging-face-raspberry-pi/flask-app
  • Install Python
    • If you already have Python installed, you may skip this step.
    • If you don't have Python installed, install it now. You can download an installer from the Python official website or on a Mac you can install with Homebrew.
  • Create and Activate Virtual Environment
    • Create virtual environment: python -m venv venv
    • Activate environment source venv/bin/activate (Linux & MacOS) or .\venv\Scripts\activate (Windows)
  • Install Requirements & Set Environment Variables
    • Install Python packages by running pip install -r requirements.txt
    • Now start flask with the command flask run
  • Open your new Web server!
    • Using a web browser of your choice, navigate to http://127.0.0.1:5000/
    • Type any text into the 'My Text' box and hit Analyze.

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