Inclusive Aid

Inspiration

The idea behind Inclusive Aid was to create a tool that provides personalized financial assistance resources to users based on their background and income. We were inspired by the need for a solution that could guide individuals towards the right services, especially those who might not know where to start when seeking financial help.

What it does

Inclusive Aid asks users about their background and current income to suggest websites and resources that can help them with financial assistance. The tool is designed to give users tailored recommendations based on their specific needs and situations.

How we built it

We built the project using Python, Streamlit for the user interface, the OpenAI API to power our dynamic AI-driven recommendations, and LangGraph's Langchain for our OpenAI API prompt engineering. The combination of these technologies allowed us to create an interactive, user-friendly platform that provides meaningful suggestions.

Challenges we ran into

We faced a few challenges while developing Inclusive Aid. One of the main issues was ensuring that the OpenAI API consistently provided accurate and relevant results to the users’ queries. Additionally, designing a clean and intuitive user interface using Streamlit, with interactive buttons and forms, required a fair amount of tweaking to get right.

Accomplishments that we're proud of

We’re proud of the seamless integration between OpenAI, Streamlit, and LangGraph, and how the project evolved into a practical, user-friendly tool. We’re especially proud of how we tailored the recommendations based on individual needs and offered multi-language support, ensuring the tool is accessible to a wider audience.

What we learned

Through this project, we learned a great deal about prompt engineering to get the best results from the OpenAI API via langchain. We also gained experience in designing intuitive user interfaces using Streamlit.

What's next for Inclusive Aid

Moving forward, we aim to refine the AI-driven recommendations by improving the underlying data and logic. We also plan to expand the range of financial assistance programs and resources available through the platform. Finally, we hope to improve the user experience further, potentially introducing more customization options and expanding support for more languages.