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Offered By: IBMSkillsNetwork

QA Bot with LangChain and LLM to Answer Questions from Doc

Learn to build a question-answering bot using LangChain and large language models (LLMs). This project will guide you through loading documents, creating embeddings, and using vector databases for efficient information retrieval. You’ll integrate tools like document loaders, text splitters, and Gradio to construct a functional QA system capable of delivering accurate, context-aware answers. This hands-on project is perfect for applications in customer support, research, or any domain requiring quick and intelligent data access.

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Guided Project

Artificial Intelligence

5.0
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At a Glance

Learn to build a question-answering bot using LangChain and large language models (LLMs). This project will guide you through loading documents, creating embeddings, and using vector databases for efficient information retrieval. You’ll integrate tools like document loaders, text splitters, and Gradio to construct a functional QA system capable of delivering accurate, context-aware answers. This hands-on project is perfect for applications in customer support, research, or any domain requiring quick and intelligent data access.

In this guided project, discover the exciting world of building a question-answering (QA) bot using LangChain and large language models (LLMs). Harness the power of natural language processing (NLP) to create bots capable of delivering precise and contextually relevant responses. By integrating LangChain's framework with LLMs, you'll revolutionize how information is retrieved, making it perfect for environments where quick data access is crucial, such as customer support or research. This project, which you can complete in just 60 minutes, will elevate your applications by imbuing them with intelligent query-response capabilities, providing significant value to both users and organizations.

What You'll Learn

By the end of this project, you will be able to:
  • Understand how to load documents into the LangChain framework for natural language processing tasks.
  • Use LLMs to generate accurate and contextually appropriate responses.
  • Integrate and streamline information retrieval processes within your applications.
  • Wrap together multiple components like document loaders, text splitters, embedding models, and vector databases to construct a fully functional QA bot.
  • Leverage LangChain and LLMs to solve the problem of retrieving and answering questions based on content from large PDF documents.

What You'll Need

Before starting this project, you should have:
  • Familiarity with Python programming, as it will be used throughout the project.
  • Access to the IBM Skills Network Labs environment, where necessary tools like Docker are pre-installed.
  • A current version of a web browser such as Chrome, Edge, Firefox, Internet Explorer, or Safari to ensure full compatibility with the platform.

Estimated Effort

60 Minutes

Level

Advanced

Skills You Will Learn

Information Retrieval, LangChain, Large Language Models, Natural Language Processing, Python

Language

English

Course Code

GPXX0QWVEN

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