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Retrieval Augmented Generation with GPT and Milvus

In this session you'll learn how to get started with Milvus and perform Q&A on some documents using GPT and the RAG technique.
Yujian Tang
Yujian Tang

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실습 문제하고 트랙하세요.

Google로 계속하기계속 진행하시면 다음 사항에 동의하는 것으로 간주됩니다: 이용약관 및 개인정보 처리방침 그리고 귀하의 데이터가 미국에 저장된다는 점에 동의하는 것으로 간주됩니다.

Large language models (LLMs) like GPT are the must-have technology of the year. Unfortunately, LLMs can't accurately answer questions about your business because they lack enough domain knowledge. The solution is to combine the LLM with a vector database like Milvus—a technique known as retrieval augmented generation (RAG).

In this session you'll learn how to get started with Milvus and perform Q&A on some documents using GPT and the RAG technique.

Key Takeaways:

  • Learn how to store text in the Milvus vector database.
  • Learn how to use retrieval augmented generation to combine Milvus and GPT.
  • Learn how to ask securely questions about business documents

Notes:

  • Please have Python Version 3.9, 3.10 or 3.11 installed
  • Download and install Visual Studio Code on your local machine. Get started here.

How to get LlamaIndex set up and running with Milvus

Code Along with Us!

Additional Resources

[TUTORIAL] How to Build LLM Applications with LangChain

[TUTORIAL] Using ChatGPT to Moderate ChatGPT Responses

[CODE ALONG] An Introduction to GPT & Whisper with the OpenAI API in Python 

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