Project: AI-FAQ Lab: GUI implementation and prototype deployment
I had the incredible opportunity to work on AI-FAQ, a proof-of-concept LLM ChatBot designed to answer questions about Hyperledger project documentation. Now an LD Decentralized Trust Lab, AI-FAQ aims to support users by streamlining access to critical information, reducing the need to navigate extensive documentation manually.
Project Motivation
Developers often waste time searching internal documentation, such as wiki pages, for simple answers. This inefficiency inspired the community to create an open-source conversational AI tool capable of answering context-specific questions quickly and accurately.
At the start of the mentorship program, the initial implementation was a basic solution running on a Google Colab Notebook. Our primary goal was to enhance this into a robust system with a standard ChatBot GUI and deploy it on a cloud server, making it more user-friendly and scalable.
Project Description
The system is an open-source Python project that implements an AI chatbot to respond to HTTP requests. It serves as a flexible framework or template for communities, organizations, or companies to customize and enhance using advanced AI techniques such as Retrieval-Augmented Generation (RAG). Recent advancements in Large Language Models (LLMs) have enabled excellent performance even with common hardware resources.
For my mentorship project, I analyzed the existing solution to identify areas for improvement and divided the project into three main tasks: developing a front-end component prototype, designing a containerized architecture, and producing high-quality documentation for deployment. Guided by my mentor and the LF Decentralized Trust community, I overcame challenges inherent in large-scale open-source projects, refined my understanding of LLM technologies, and embraced the collaborative open-source philosophy.
What I Learned and Accomplished
During this project, I successfully developed a Proof-of-Concept API leveraging LLMs to analyze project documentation, dynamically generating questions and answers for an FAQ ChatBot. Additionally, I implemented an intuitive front-end interface using JavaScript and TypeScript and deployed the solution on a cloud server. These deliverables marked a significant milestone in creating a reusable, scalable, and open-source chatbot solution for the LF Decentralized Trust ecosystem.
A key challenge was integrating the backend with the frontend interface. Through perseverance and guidance from my mentor, I enhanced my skills in front-end development, cloud architecture, and creating detailed technical documentation. This experience deepened my appreciation for collaborative problem solving within open-source communities.
Working with a Mentor and the Community
My mentor Gianluca played a pivotal role in my growth, providing valuable technical advice and insights into navigating open-source collaboration. Their guidance not only accelerated my learning but also helped me cultivate a problem-solving mindset essential for tackling complex technical challenges. Additionally, the community enriched my experience by fostering inclusivity, shared knowledge, and opportunities for skill development.
Looking Ahead
This experience has inspired me to continue contributing to AI-FAQ and other open-source initiatives, particularly those involving LLMs and scalable cloud solutions. I envision the AI-FAQ ChatBot evolving into a comprehensive resource for the LF Decentralized Trust ecosystem, integrating multilingual capabilities and advanced contextual understanding. Looking ahead, I aim to deepen my expertise in cloud technologies and LLMs while remaining an active member of the LF Decentralized Trust community, driving impactful innovations.