Deposition Punctuation Aid with LLM Interface

Project Overview This project aims to develop a user-friendly Python application for correcting punctuation in legal deposition text files stored locally on a PC. The application will leverage a Large Language Model (LLM) like ChatGPT or Claude to analyze the text and suggest corrections aligned with Morson's English Guide for Court Reporters. Key Features: LLM-powered Punctuation Correction: Integrate an LLM like ChatGPT or Claude to analyze the deposition text and propose corrections for punctuation, ensuring adherence to Morson's English Guide for Court Reporters. Local File Processing: Allow users to select and upload local text files containing legal depositions. Customizable Prompt: Provide the ability to modify prompts sent to the LLM. Users can define specific prompts or keywords tailored to the legal context of the deposition, potentially improving the accuracy of punctuation suggestions based on Morson's guidelines. User-Friendly GUI: Design a clear and intuitive graphical user interface (GUI) using a Python framework like PyQt or Tkinter. This interface will enable efficient interaction with functionalities and easy understanding of the application's purpose. Modifiable with PyCharm: Ensure the application's code is well-structured and written in Python, allowing straightforward modifications and further development using the PyCharm IDE. Technical Specifications: Programming Language: Python Large Language Model (LLM): Integration with an LLM like ChatGPT or Claude (consider API availability and potential costs). GUI Framework: Utilize a Python GUI framework like PyQt or Tkinter. Additional Libraries: Libraries for file handling, user interface development, and potentially API integration with the chosen LLM may be required. Benefits: Improved accuracy and consistency of punctuation in legal deposition transcripts, adhering to Morson's guidelines. Streamlined workflow for legal professionals by automating punctuation correction tasks. User-friendly interface simplifies application use. Option to customize prompts allows for targeted correction based on legal context and Morson's guidelines. Code written in Python facilitates modification and future enhancements using PyCharm. Client Background: While I have limited programming experience, I have some familiarity with using PyCharm and am interested in exploring the capabilities of LLMs for enhancing legal documents. Next Steps: Research and evaluate the feasibility of integrating a suitable LLM with API access and potential costs. Select a user-friendly Python GUI framework. Develop a detailed technical architecture and implementation plan. Design an intuitive and user-friendly GUI for efficient interaction. Implement core functionalities: Local file processing for uploading deposition transcripts. Prompt customization for specifying Morson's guidelines as context. LLM integration for suggesting punctuation corrections. Display of original text with suggested punctuation based on Morson's guidelines. Test the application thoroughly with various legal deposition files. Please Note: Availability and terms of use for ChatGPT or Claude might need further investigation. Depending on the chosen LLM, additional costs for API access or usage might be involved. This project proposal outlines the development of a valuable tool for legal professionals. By leveraging AI technology and a user-friendly interface, this application can assist in ensuring accurate and consistent punctuation in legal deposition transcripts, adhering to the established guidelines set forth by Morson's English Guide for Court Reporters.