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
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What Is Retrieval Augmented Generation (RAG)? A Complete Guide
Understand how RAG grounds LLM outputs in external data to reduce hallucinations, with a guide to the RAG pipeline, advanced techniques, and real-world applications.
Учебное руководство
Boost LLM Accuracy with Retrieval Augmented Generation (RAG) and Reranking
Discover the strengths of LLMs with effective information retrieval mechanisms. Implement a reranking approach and incorporate it into your own LLM pipeline.

совместная сессия кодирования
Retrieval Augmented Generation with LlamaIndex
In this session you'll learn how to get started with Chroma and perform Q&A on some documents using Llama 2, the RAG technique, and LlamaIndex.



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:
Notes:
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