Combining AI to make AGI
Text Analysis and Clustering Web App
Description:
This repository contains a web application for text analysis and clustering using various HuggingFace models. The application is built with Python, Flask, and integrates with HuggingFace's API to analyze and process text input. The results are then clustered using the K-Means algorithm, and the output is displayed on a webpage.
We welcome and encourage the open-source community to contribute to this project by forking the repository, fixing bugs, and suggesting improvements. Our goal is to create a powerful and easy-to-use tool for text analysis, and we believe that the collective effort of the community will lead to a better solution.
Some areas where we'd like to improve and expand the project:
Enhance the user interface: Implement a more user-friendly and visually appealing interface using modern front-end frameworks like React or Vue.js.
Extend functionality: Add more advanced text processing and analysis capabilities, such as sentiment analysis, entity recognition, and topic modeling.
Optimize performance: Refactor the codebase to improve efficiency and scalability, and make better use of caching and other performance-enhancing techniques.
Implement authentication and user management: Allow users to create accounts and save their analysis results for future reference.
Add support for additional AI models and frameworks: Integrate with other popular AI frameworks like TensorFlow and PyTorch, and support more pre-trained models from HuggingFace.
We're excited to see how this project evolves with the help of the open-source community. If you have any questions, suggestions, or bug reports, please feel free to open an issue or submit a pull request. Happy coding!