transum-feed / README.md
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metadata
title: Transum Feed
emoji: 
colorFrom: blue
colorTo: green
sdk: gradio
sdk_version: 5.20.0
app_file: src/transum_app.py
pinned: false
license: gpl-3.0
short_description: Summarizing and translating feed content

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

Transum Feed

Transum Feed is a versatile application designed to summarize and translate entries from any user-specified feed. Users can input a feed URL, select source and target languages for translation, and specify the number of entries they wish to display in the output. The application streamlines the process of consuming multilingual content by providing concise summaries and accurate translations.

Getting Started

This guide provides step-by-step instructions to set up and run the project on your local machine for development and testing purposes. For details on deploying the project to a production environment, refer to the Deployment section.

Prerequisites

To set up and run this project, ensure the following software and tools are installed on your system:

  • Python: Version 3.10.12 or higher is required. Verify your Python version by running:

    python3 --version
    
  • Dependencies: Install the required Python packages listed in requirements.txt using pip. Run the following command in your terminal:

    pip install -r requirements.txt
    

Local Development and Testing

To run the application locally for development and testing purposes, execute the following command in your terminal:

python transum_app.py

Ensure you are in the project's src directory before running the script or adapt running path.

Deployment

Deployment on Hugging Face Spaces

To deploy the project on Hugging Face Spaces, follow these steps:

  1. Create an account on Hugging Face if you don’t already have one.

  2. Refer to the official Spaces Overview documentation for detailed instructions on setting up and deploying your project.

Deployment on Other Cloud Platforms

For deployment on other cloud or live systems, consult the documentation provided by your chosen service provider. Each platform may have specific requirements and steps for deploying Python-based applications.

Hardware Recommendations

GPU Usage: It is highly recommended to use GPUs for deployment, especially for resource-intensive tasks like summarization. GPU acceleration significantly reduces processing time compared to CPUs.

CPU Usage: While CPUs can be used for deployment, they may result in slower performance, particularly for computationally demanding processes.

On Hugging Face in order to use GPUs that might be available with your account (depends on your account type), you have to uncomment import spaces and @spaces.GPU lines in transum_app.py file.

Built With

Authors

Vlasios Dimitriadis - Initial work: transum-feed