Analyze literary texts with cutting-edge natural language processing techniques. Explore word frequencies, sentiment, and the visual story arc of any text!
![App Demo] ()
- Word Frequency Analysis: Dive deep into the most frequent words used in the text.
- Sentiment Analysis: Gauge the overall sentiment of the text using TextBlob.
- Visual Story Arc with BERT: Visualize the sentiment progression throughout the narrative.
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Clone the repository:
git clone https://github.com/rumiallbert/archalyze.git cd archalyze
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Set up a virtual environment:
python -m venv venv source venv/bin/activate # On Windows use `venv\Scripts\activate`
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Install the required packages:
pip install -r requirements.txt
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Run the Streamlit app:
streamlit run app.py
Pull requests are welcome! For major changes, please open an issue first to discuss what you would like to change.
This project is licensed under the MIT License - see the LICENSE.md file for details.