README.md

metadata

license: apache-2.0
title: GoEmotions Dashboard
sdk: streamlit
sdk_version: 1.22.0
app_file: app.py

GoEmotions Dashboard - Analyzing Emotions in Text

This is a Python script that uses Streamlit, Plotly, and the Hugging Face Inference API to create a web-based dashboard for analyzing emotions in text. Finally this dashboard is deployed on Hugging Face Spaces using GitHub Actions.

Pre-requisites:

• Python 3.7 or higher

Project Structure:

GoEmotions/
├── app.py
├── requirements.txt
├── .env
├── README.md
├── assets/
└── .github/workflows

Setup

Step 1 - Clone this repository to your local machine using the following command, or open the repository in GitHub Codespaces.

git clone https://github.com/SudhanshuBlaze/GoEmotions.git

Step 2 - Create and activate a new python virtual environment: (This step can be skipped if working on GitHub Codespaces!)

python -m venv venv

venv\Scripts\activate

Step 3 - Install the required packages using pip: (This step can be skipped if working on GitHub Codespaces as it automatically installs the requirements!)

pip install -r requirements.txt

Step 4- Create a free account on the Hugging Face website and generate an API key (read).

Step 5 - Navigate to the root directory of the project.

cd GoEmotions

Step 6

• Create a .env file in the root directory of the project and add your
• Hugging Face API key like this: HF_API_KEY=<your_api_key_here>

Step 7 - Run the Streamlit app.

streamlit run app.py

or

python -m streamlit run app.py

• If you want to run this application on GitHub Codespaces, you will need to add the following flags to the streamlit run command:

python -m streamlit run app.py --server.enableCORS false --server.enableXsrfProtection false

Deployment to Spaces (CI/CD)

Step 1 Commit your code and push it to your GitHub repository

Step 2 Create a new Space on Hugging Face, add it as an additional remote to git and force push your code on Spaces:

git remote add space https://huggingface.co/spaces/HF_USERNAME/SPACE_NAME

git push --force space main

Step 3 In the main.yml, add your Hugging Face username and Space name to the variables 'HF_username' and 'HF_space_name'

Step 4 Create a new API key on Hugging Face (write) and add it as a secret to your GitHub Repository naming it as 'HF_TOKEN'.

Step 5 Trigger the CI/CD pipeline by a push or a pull request to your main branch.

Usage:

• A web-based dashboard will open in your default browser.
• Type or paste a text input in the text box provided.
• The dashboard will visualise the detected emotions in a set of gauges, with each gauge representing the intensity of a specific emotion category. The gauge colors are based on a predefined color map for each emotion category.
• Moreover, the dashboard will display the results from Hate Speech Analysis and Sexism Detection models.