Easy-to-Follow RAG Pipeline Tutorial: Invoice Processing with ChromaDB & LangChain

I explain the implementation of the pipeline to process invoice data from PDF documents. The data is loaded into Chroma DB's vector store. Through LangChain API, the data from the vector store is ready to be consumed by LLM as part of the RAG infrastructure. 

 

Vector Database Impact on RAG Efficiency: A Simple Overview

I explain the importance of Vector DB for RAG implementation. I show with a simple example, how data retrieval from Vector DB could affect LLM performance. Before data is sent to LLM, you should verify if quality data is fetched from Vector DB. 

 

JSON Output from Mistral 7B LLM [LangChain, Ctransformers]

I explain how to compose a prompt for Mistral 7B LLM model running with LangChain and Ctransformers to retrieve output as JSON string, without any additional text. 

 

Structured JSON Output from LLM RAG on Local CPU [Weaviate, Llama.cpp, Haystack]

I explain how to get structured JSON output from LLM RAG running using Haystack API on top of Llama.cpp. Vector embeddings are stored in Weaviate database, the same as in my previous video. When extracting data, a structured JSON response is preferred because we are not interested in additional descriptions.