Prettygraph

What is Prettygraph?

Prettygraph is a web application built with Python that introduces a new UI pattern to dynamically convert text input into a knowledge graph. This project serves as a quick prototype aimed at providing a simple UI concept where text highlights update in real-time to generate a knowledge graph.

Who Can Benefit from Prettygraph?

Researchers and data scientists can use Prettygraph to quickly transform text data into visual knowledge graphs for analysis and understanding.

Educators can utilize Prettygraph to demonstrate complex concepts and relationships through interactive visuals.

Developers interested in integrating knowledge graph generation features into their applications can explore Prettygraph as an experimental starting point.

Example Scenarios:

Transform academic paper abstracts into knowledge graphs to help researchers grasp key points swiftly.

Use Prettygraph to convert textbook content into graphical representations to aid student learning and retention.

Convert market research reports into graphs to reveal trends and competitive dynamics in business intelligence.

Key Features:

Text-to-Graph Generation: Converts user-input text into a knowledge graph.

Dynamic UI Updates: Updates the graph after each sentence.

Color-Coded Visualization: Nodes and edges are color-coded for clear distinction.

Real-Time Updates: Provides an interactive experience by updating the graph after each sentence.

Dependency Management: Uses Poetry for easy setup.

Environment Variables: Requires setting the OPENAIAPIKEY environment variable to run.

Open Source: The project follows the MIT license.

Getting Started:

1. Clone the repository using Git.

2. Navigate to the cloned project directory via command line.

3. Install dependencies with Poetry.

4. Create a .env file in the root directory and add OPENAIAPIKEY.

5. Run the Flask application with poetry run python main.py.

6. Access the app at http://localhost/ and start typing to see the graph update in real-time.