Web Science and Digital Libraries Research Group

  This summer, I had the privilege of interning at Amazon with the Alexa Certification Technology (Alexa-Cert-Tech) team located in Sunnyvale, California, USA. My internship was a 13-week program which started on May 28th, 2024. During this internship, I worked mostly as a data scientist intern under the supervision of Praveen Chinnusamy , Bheema Rajulu , and Jingya Li . Throughout this program, I attended weekly meetings with the entire Alexa-Cert-Tech team. The weekly meetings were to update my progress, obtain feedback, resolve issues, or improve the solution. I had one-on-one meetings with my mentors Bheema Rajulu and Jingya Li twice weekly to discuss my progress and any issues I faced. I also met with my manager Praveen Chinnusamy at least once a week. My project was focused on automating Behavior-Driven Development (BDD) test statement generation and improving transcript generation using Large Language Models (LLMs) . This blog post will dive deep into the challenges, s...

Figure 1: LangChain Components In the world of artificial intelligence, one game-changing innovation has been grabbing everyone's attention and transforming the way we interact with language – Large Language Models (LLMs). But for developers, harnessing their full potential has often been very challenging. LangChain is a framework for building applications powered by LLMs that makes it easier for developers to use LLMs. For those skilled in Python, JavaScript, or TypeScript programming languages, LangChain provides packages that developers, software engineers, and data scientists can leverage. Overview of LangChain LangChain offers an advanced framework for engaging with LLMs, external libraries, prompts, and user interfaces. It is available in Python or JavaScript (TypeScript) packages. LangChain's user-friendly architecture allows users to utilize its various components such as agents and chains, and strategically assemble them to fulfill specific tasks like summarization, Q...