RAG Framework Comparison: Langchain vs Llama-Index Techniques

The video presents a comprehensive comparison of two Retrieval-Augmented Generation (RAG) frameworks, Langchain and Llama-Index. These frameworks are instrumental in the design of chatbots. The presenter evaluates eight different RAG techniques from both frameworks to identify the most effective one for initiating a project. The video underscores the adoption of these frameworks by industry giants like Google and Microsoft. It outlines the process of designing a RAG system, which includes preparing documents, creating a vector database, and evaluating techniques. The video also discusses the significance of chunking strategies and retrieval methods in the context of large language models and embedding models.

• [2312.10997v1] Retrieval-Augmented Generation for Large Language Models: A Survey (arxiv.org)
• [2312.10997] Retrieval-Augmented Generation for Large Language Models: A Survey (arxiv.org)