Better RAG: Hybrid Search in Chat with Documents

In this video, Prompt Engineering delves into advanced Retrieval-Augmented Generation (RAG) concepts, focusing on hybrid search to enhance chat with document systems. The video provides a comprehensive guide on implementing hybrid search using LangChain, BM25 algorithm, and ensemble retrievers. Here’s a detailed breakdown:

1. **Introduction to RAG Pipelines**: The video begins with an overview of basic RAG pipelines, explaining how documents are loaded, chunked, and embedded into a vector store. The vector store is then used for semantic search to retrieve relevant document chunks based on user queries.

2. **Hybrid Search Enhancement**: The video introduces hybrid search as an advanced technique to improve RAG pipelines. Hybrid search combines traditional keyword-based search with embedding-based semantic search, providing a more robust retrieval mechanism.

3. **Implementing Hybrid Search**: A step-by-step code example is provided to implement hybrid search using LangChain. The necessary packages are installed, including rank BM25 for keyword search and chroma DB for vector storage.

4. **Loading and Processing PDF Files**: The video demonstrates how to load and process PDF files using unstructured PDF loader and recursive character text splitter to create document chunks.

5. **Creating Embeddings and Vector Store**: Embeddings are created using a hugging face inference API, and the document chunks are stored in a vector store using chroma.

6. **Setting Up Retrievers**: The video explains how to set up both semantic and keyword-based retrievers. An ensemble retriever is then created to combine the results from both retrievers, with the ability to assign different weights to each.

7. **Running the Model and Analyzing Output**: The final step involves setting up the language model (Zer 7B beta) using the hugging face API and creating a prompt template. The video shows how to run the model and analyze the output, demonstrating the improved retrieval capabilities of the hybrid search.

The video provides a detailed and practical approach to enhancing RAG pipelines with hybrid search, making it a valuable resource for developers looking to build more efficient chat with document systems.