Skip to content
    AI engineering roles via the DiamantAI Collective.See open roles
    BeginnerGenAI Agents

    Simple Question Answering

    This tutorial introduces a basic Question-Answering (QA) agent using LangChain and OpenAI's language model. The agent is designed to understand user queries and provide relevant, concise answers.

    In the era of AI-driven interactions, creating a simple QA agent serves as a fundamental stepping stone towards more complex AI systems. This project aims to: - Demonstrate the basics of AI-driven question-answering - Introduce key concepts in building AI agents - Provide a foundation for more advanced agent architectures

    What you'll learn

    • 1
      Language Model: Utilizes OpenAI's GPT model for natural language understanding and generation.
    • 2
      Prompt Template: Defines the structure and context for the agent's responses.
    • 3
      LLMChain: Combines the language model and prompt template for streamlined processing.

    About this tutorial

    This hands-on Jupyter notebook is part of GenAI Agents, a free open-source repository by Nir Diamant covering ai agents techniques with runnable code examples and detailed explanations.

    Free and open-sourceRunnable Jupyter notebookActive community support
    Go deeper · Amazon Bestseller in Generative AI

    RAG Made Simple

    Nir Diamant's complete visual guide to Retrieval-Augmented Generation — essential for any GenAI engineer building systems that retrieve and ground responses on real data.

    Get it on Amazon

    ⭐ 4.4 stars · 1,500+ readers · Kindle $9.99 · Paperback $24.99 · Free with Kindle Unlimited

    More Beginner tutorials

    More from GenAI Agents