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Building RAG Chatbots for Technical Documentation

Implement retrieval augmented generation (RAG) with LangChain to create a chatbot for answering questions about technical documentation.

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1 Tasks1,500 XP

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Project Description

You'll create a context-aware chatbot by integrating a car manual with an LLM using LangChain and Retrieval Augmented Generation (RAG). The goal is to create a car assistant that can explain dashboard warnings and recommend actions while driving. Say goodbye to boring manuals!

Project Tasks

  1. 1
    Evaluate terms-of-service using LangChain


Python Python


Artificial Intelligence
Mikael Brunila HeadshotMikael Brunila

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James Chapman HeadshotJames Chapman

Curriculum Manager, DataCamp

James is a Curriculum Manager at DataCamp, where he collaborates with experts from industry and academia to create courses on AI, data science, and analytics. He has led nine DataCamp courses on diverse topics in Python, R, AI developer tooling, and Google Sheets. He has a Master's degree in Physics and Astronomy from Durham University, where he specialized in high-redshift quasar detection. In his spare time, he enjoys restoring retro toys and electronics.

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