A killer application of large language models (LLMs) is answering questions about specific documents & datasets. This enables use cases such as customer service bots, question-answering systems about specific domains, & LLMs that can navigate data tasks.
In this code-along, Andrea Valenzuela, Computing Engineer at CERN, and Josep Ferrer Sanchez, Data Scientist at the Catalan Tourist Board, will walk you through building an AI system that can query your documents & data using LangChain & the OpenAI API. Throughout the code-along, they will share best practices for effectively loading & storing documents using LangChain, building a retrieval augmented generation pipeline for querying data, and building a question-answering bot.
Key Takeaways:
- Learn how to effectively load & store documents using LangChain
- Build a retrieval augmented generation pipeline for querying data
- Build a question-answering bot that answers questions based on your documents
Additional Resources
Andrea’s Code Along from 2023 - [CODE ALONG] Optimizing GPT Prompts for Data Science
[TUTORIAL] A Beginner's Guide to Using the ChatGPT API
[SKILL TRACK] OpenAI Fundamentals
