EasyLease

Inspiration

We as international students face a lot of problems when coming to new country. One of them is finding a place to stay. During recent times, we have been hearing a lot of news about students and marginalized group of people suffering from housing scams. And moreover, normal people are also not aware of all the rights they have and what are things they can, can not or allowed and not allowed to do as a tenant. Furthermore, people also do not know where to find these information or feel overwhelmed to surf the internet because of so many information and data. So, we decided to solve that problem by doing two things, which both creates awareness and helps tenants to know these things and also help them stay away from scammers.

What it does

Our website does three things:

It verifies the pictures of the house the landlord has posted are theirs and that they are the rightful owner of the property by using their ID, a piece of document determining the ownership of the landlord and the location of photos uploaded at that time.
There is also a chatbot specially built and trained with co:here to give you all the right and correct legal and normal questions you have about the renting process.
It also creates the listing of different rent-able places of two categories i.e. verified(From our website) and not verified(From other online sources)

How we built it

We used Cohere API for our chatbot and trained with specific data to give us more accurate results to our needs. We used Python and Django for our backend and React and TailWindCss for our frontend.

Challenges we ran into

Lack of proper sleep was definitely our major challenge. Besides that, we had some trouble while training our ChatBot using Cohere as it was our first time using it. We also faced some trouble while integrating the frontend with the backend and creating the proper API and also some difficulty while deploying and trying to figure out which service to use.

Accomplishments that we're proud of

We are proud that we completed the project in time despite a short time frame and successfully hosted our web app.

What we learned

Throughout the development of EasyLease, our team gained invaluable insights and skills in utilizing pre-trained language models like Co:here for our chatbot, understanding vector embeddings to enhance semantic understanding, and mastering full-stack development with Python, Django, React, and TailWindCSS. Despite facing challenges such as sleep deprivation and technical hurdles, we embraced a problem-solving mindset and collaborated effectively to meet project deadlines. Our deployment and service integration experiences equipped us with valuable knowledge in deploying web applications and integrating various services. These learning experiences serve as catalysts for continuous growth and innovation as we strive to address emerging challenges and create impactful solutions in the realm of housing accessibility and tenant empowerment.

What's next for EasyLease

In the future we are going to implement more features like, Integrating a proper map and searching homes in the selected areas. Furthermore we will try to implement more advance verification process and Expansion of legal knowledge base.

Built With

Submitted to

NSBEHacks 2024

Created by

I am the so-called manager of the team, who did not do much of code but managed things like making demo video, filing out dev post and helping them with legal data collection and assisting team wherever they needed me.

Sujal Acharya
I contributed to a project focused on creating a chat bot that understands the rules and responsibilities of landlords and tenants in Ontario. My main task involved training the LLM using a technique called Retrieval-Augmented Generation (RAG) to generate accurate responses based on input questions. Additionally, I handled deploying the trained models to Digital Ocean, a cloud hosting platform, using the Django framework, which allowed us to create a user-friendly interface for accessing the LLM's capabilities.

Binaya Chaudhary
Idea generation, ML and Idea pitching

Varnika Tyagi
I worked on the frontend.

Ashok Chapagai
ashok cpg