Utilizing LLM Agents for Efficient Requirement Analysis and Specification

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Utilizing LLM Agents for Efficient Requirement Analysis and Specification

  • Emerging Technologies
    •
  • Tutorial
  • Intermediate
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    By Brain Aboze Elizabeth Ogunyemi

    Data Scientist

    Abstract:

    In this tutorial, we will build a practical application using Streamlit, leveraging open-source LLMs, embedding models, and vector stores—all implemented in Python. Attendees will learn how to integrate these components to create a user-friendly interface that enables seamless interaction with LLM agents. The session will cover the iterative development process, highlight the role of human evaluators in assessing output quality, and demonstrate the creation of efficient query engines for summarizing and semantically searching meeting notes. Additionally, attendees will gain a deep understanding of LLM agents, exploring various tools, tasks, and prompts accessible to the agents to enhance their functionality and effectiveness.

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