DeepSonnet AI is an interactive web application that leverages artificial intelligence to analyze poetry and short stories. Users can input their own poems or short stories, or use randomly generated ones for analysis, exploring various aspects such as themes, sentiment, style, and more.

• Poem Analysis: Submit your own poems for in-depth AI-powered analysis.
• Multiple Analysis Types: Choose from different analysis options:
  • Themes
  • Sentiment
  • Style
  • Rhyme Scheme
  • Meter
• Visual Representations:
  • Theme cloud for thematic analysis
  • Sentiment meter for emotional tone
  • Style timeline for literary techniques
• Poem Structure Visualization: Visual representation of the poem's structure based on line lengths.
• Random Poem Generator: Explore and rate randomly generated poems.
• Test Poem Option: Quick access to a pre-defined test poem for demonstration purposes.

• Short Story Analysis: Submit your own short stories for comprehensive AI-powered analysis.
• Multiple Analysis Types: Choose from various analysis options:
  • Sentiment
  • Themes
  • Style
  • Character Analysis
  • Plot Analysis
  • General Analysis
• Visual Representations:
  • Sentiment meter for emotional tone
  • Theme cloud for key themes
  • Story structure visualization
• PDF Upload: Option to upload short stories in PDF format.

• Responsive Design: User-friendly interface that adapts to different screen sizes.
• Dark Mode: Toggle between light and dark themes for comfortable viewing.
• Word and Character Counter: Real-time counting for both poems and short stories.
• Leaderboard: View top-rated poems analyzed by the system.
• About Page: Detailed information about DeepSonnet AI and its features.

• Frontend: HTML, CSS, JavaScript, Bootstrap
• Backend: Python with Flask
• AI/ML: OpenAI API, NLTK for NLP tasks
• Hosting: Render
• Additional Libraries: D3.js for visualizations, Showdown for Markdown conversion

1. Choose between Poetry Analysis or Short Story Analysis.
2. Enter a title and text in the provided form.
3. Select the type of analysis you want to perform.
4. Click "Analyze" to submit the text for analysis.
5. View the results in the two-column layout:
   • Left column: Displays the submitted text
   • Right column: Shows the analysis results and visualizations

Contributions to DeepSonnet AI are welcome! Please follow these steps:

1. Fork the repository.
2. Create a new branch: git checkout -b feature-branch-name.
3. Make your changes and commit them: git commit -m 'Add some feature'.
4. Push to the branch: git push origin feature-branch-name.
5. Submit a pull request.

MIT License

Boden Moraski - bodenmoraski@gmail.com

Project Link: https://github.com/betezz/DeepSonnet-AI

• Huge thank you to all of the developers at OpenAI, this would not have been possible without you
• Special thanks to Lawson Cale, Johnathan Samar, Benjamin Klick, Mr. Baber, Tom Rush, and of course Trevor "King" Cantlin. You guys have all been great.