Legal-Aid-Tool

This prototype explores how Large Language Models (LLMs) can enhance legal workflows by enabling intelligent case analysis, real-time transcription, and contextual feedback. By integrating AI into the legal process, it supports more efficient decision-making, improves accessibility to complex information, and fosters a deeper understanding of legal content through personalized, adaptive assistance.

Index	Description
High Level Architecture	High level overview illustrating component interactions
Deployment	How to deploy the project
User Guide	The working solution
Directories	General project directory structure
API Documentation	Documentation on the API the project uses
Credits	Meet the team behind the solution
License	License details

High-Level Architecture

The following architecture diagram illustrates the various AWS components utilized to deliver the solution. For an in-depth explanation of the frontend and backend stacks, please look at the Architecture Guide.

Deployment Guide

To deploy this solution, please follow the steps laid out in the Deployment Guide

User Guide

Please refer to the Web App User Guide for instructions on navigating the web app interface.

Directories

├── cdk/
│   ├── bin/
│   ├── data_ingestion/
│   ├── lambda/
│   ├── layers/
│   ├── lib/
│   └── graphql/

├── docs/
│   ├── userGuide.md
│   ├── deploymentGuide.md
│   ├── images/
├── frontend/
│   ├── public/
│   └── src/
│       ├── app/
│       └── components/

1. /cdk: Contains the deployment code for the app's AWS infrastructure
   • /bin: Contains the instantiation of CDK stack
   • /data_ingestion: Contains the code required for the Data Ingestion step in retrieval-augmented generation. This folder is used by a Lambda function that runs a container which updates the vectorstore for a course when files are uploaded or deleted.
   • /lambda: Contains the lambda functions for the project
   • /layers: Contains the required layers for lambda functions
   • /lib: Contains the deployment code for all infrastructure stacks
   • /graphql: Contains the GraphQL schema and resolvers for the API.
2. /docs: Contains documentation for the application.
3. /frontend: Contains the user interface of the general public application

API Documentation

Here you can learn about the API the project uses: API Documentation.

Dependency Management

For information on how Python dependencies are locked and managed across Lambda functions, see the Dependency Management Guide.

Modification Guide

Steps to implement optional modifications such as changing the colours of the application can be found here.

Credits

This application was architected and developed by Prajna Nayak, Zayan Sheikh, and Kanish Khanna, with project assistance by Harleen Chahal. Thanks to the UBC Cloud Innovation Centre Technical and Project Management teams for their guidance and support.

License

This project is distributed under the MIT License.

Licenses of libraries and tools used by the system are listed below:

PostgreSQL license

• For PostgreSQL and pgvector
• "a liberal Open Source license, similar to the BSD or MIT licenses."

LLaMa 3 Community License Agreement

• For Llama 3 70B Instruct model