Category Archives: RAG
Building a RAG Application with LangChain: Example Code
The combination of Retrieval-Augmented Generation (RAG) and powerful language models enables the development of sophisticated applications that leverage large datasets to answer questions effectively. In this blog, we will explore the steps to build an LLM RAG application using LangChain. Prerequisites Before diving into the implementation, ensure you have the required libraries installed. Execute the following command to install the necessary packages: Setting Up Environment Variables LangChain integrates with various APIs to enable tracing and embedding generation, which are crucial for debugging workflows and creating compact numerical representations of text data for efficient retrieval and processing in RAG applications. Set up the required environment variables for LangChain and OpenAI: Step …
I found it very helpful. However the differences are not too understandable for me