Article Summarizer App

Project Description

The Article Summarizer App is a simple Streamlit-based application that helps users quickly find and preview articles based on their interests. Users can input one or more tags, and the app will return relevant articles along with a short summary. This is especially useful when dealing with large volumes of text data and you want to get a quick gist of the content.

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Features

• 🔍 Tag-based Search: Enter one or more tags to filter articles.
• ✍️ Automatic Summarization: Displays a short summary (first 20 words) of each matched article.
• 📚 Streamlit Interface: Clean and interactive front-end powered by Streamlit.
• 🗂️ Data Source: Uses a .parquet file containing articles and associated tags.

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🛠️ How It Works

1. Loads article data from a .parquet file into a Pandas DataFrame.
2. Cleans the article text and normalizes tags.
3. Accepts comma-separated tag inputs from the user.
4. Filters articles based on tag matches.
5. Displays the ID, tags, and a dummy-generated summary for each match.

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Dependencies

Make sure you have the following Python packages installed:

pip install streamlit pandas pyarrow

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Running the App

streamlit run app.py

Replace app.py with your actual filename.

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Folder Structure

project-directory/
├── final_data.parquet
├── app.py
└── README.md