Retrieval-Augmented Generation (RAG) has revolutionized how language models provide responses by incorporating external knowledge retrieval. However, traditional RAG pipelines often follow a static approach, retrieving a fixed set of documents and generating responses without…
Retrieval-Augmented Generation (RAG) improves AI responses by integrating relevant documents. LangGraph enhances traditional RAG with a dynamic, graph-based framework, allowing adaptive reasoning and multi-agent collaboration. It supports iterative decision-making, facilitating better context retrieval and…
LangGraph is an innovative library that enhances AI-driven applications through a graph-based approach for managing complex conversational flows. It allows the creation of dynamic workflows and stateful interactions, enabling adaptive, non-linear processes. Key advantages…
