These are my projects during my time as an undergraduate student at UCLA. In addition to the projects in this repository:
- I contributed to several important projects as a software engineering intern at Vectara.
- I developed Enterprise Deep Research, a Python package that implements a deep research framework intended to be used with internal company documents. Although the code is not publicly available, you can see some of the use cases and sample output from this package in my blog articles (Introducing Enterprise Deep Research, Responding to RFPs with Enterprise Deep Research, and Stop Scrambling: Generate Onboarding Guides with Enterprise Deep Research).
- I helped develop and maintain
vecatara-agentic, an open-source Python library for developing AI assistants and agents that is built on top of the LlamaIndex Agent framework and Vectara's API to create RAG and retrieval tools to get information from stored documents. - I created several AI assistants that can be used to research specific topics using
vectara-agenticagents, including a Legal Assistant that can gather information from over 6 million US court cases and an Electric Vehicles Assistant, which can provide information about how electric vehicles work, their impact to the environment, and legal incentives and regulations surrounding EVs. It can also query a database detailing electric vehicle registrations in the state of Washington using a text-to-SQL tool. - I contributed to Vectara's API integration with LlamaIndex. Some of my most important contributions are updgrading the main API integration from API v1 to API v2 and creating a Vectara Query Tool that others can use when building their own AI agents.
- I have helped with many other projects as well. You can check out my company account to see all of my contributions.
- I led a group project to create a neural-based product search engine.
- I was also a group member on a project to investigate catastrophic forgetting in the training of Convolutional Neural Networks.