The main functionality of the Application is to use Retrieval-Augmented Generation (RAG) technique to make LLM aware of context dynamically. When a query is given to the LLM, instead of answering from the static trained data, the application uses sematic search to find related data from the vector store and give it to the llm along with the prompt. RAG is a key technique to save a lot of compute and time as it does not use any finetuning.

Project Link:   Chat-with-your-docs, Dynamic LLMs

This Car Rental System project is designed to aid the car rental company to enable renting of cars through an online system. It helps the users to search for available cars view profile and book the cars for the time period. It has a user-friendly interface which helps the user to check for cars and rent them for the period specified. They could also make payment online. The rental cars shall be categorized into economy, premium etc. Based on the type of car required by the customer, the user shall be able to make bookings. To develop this project here we are using some aws services like Api Gateway, Lambda, RDS, SES, CloudWatch, EC2, IAM. Along with aws service here we also using other technology like Python, django, html, css, bootstarp, javascript. Application is developed over Django web framework and is hosted over EC2 server.

Project Link:   Car Rental System

The Flight Management System is a web app for managing airline operations, bookings, and flight services, utilizing MongoDB, Flask, and Bootstrap. Administrators manage airport operations, flight schedules, aircraft, and passenger bookings. They ensure efficient service by creating, editing, and deleting essential details, overseeing flight information, and maintaining the fleet. Passengers can register, search flights, book tickets, select seating, manage reservations, and check flight details. The system offers secure payments and cancellation policies with full or partial refunds, depending on timing.

Project Link:   Flight Management System