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DataDuck is an innovative AI-powered data analysis tool that empowers users to interact with their data using natural language queries. The project has made significant progress in creating a user-friendly interface that combines the power of o1-preview for natural language processing with Python-based data analysis capabilities. Key achievements so far include: 1. A responsive Next.js frontend with a clean, modern UI using Tailwind CSS for styling. 2. Implementation of a data upload component allowing users to easily add CSV, Excel, or JSON files. 3. A chat interface that enables users to ask questions about their data in plain English. 4. Integration with o1-preview API for interpreting user queries and generating Python code for analysis. 5. Implementation of Pyodide for client-side Python execution, allowing for real-time data analysis in the browser. 6. A code editor and console interface for more advanced users to write and execute custom Python code. 7. Data visualization capabilities using libraries like Plotly and Recharts to create interactive charts based on analysis results. 8. A dashboard view that provides an overview of recent datasets and queries. 9. Modular component architecture for easier maintenance and future expandability. The current implementation focuses on creating a seamless user experience, from data upload to analysis and visualization, all within a single-page application. The project emphasizes best coding practices, including TypeScript for type safety, modular component design, and efficient state management. These practices ensure easier debugging and future enhancements to the DataDuck platform.