Shravan KumarAdaptive RAG with Self-ReflectionHere is the basic traditional RAG architecture.1d ago1d ago
Shravan KumarMultimodal RAG with GPT-4-Vision and LangChainMultimodal RAG with GPT-4-Vision and LangChain refers to a framework that combines the capabilities of GPT-4-Vision (a multimodal version…5d ago5d ago
Shravan KumarFramework to Choose the Right LLM for your BusinessAs we see a tremendous increase in the hype around AI and LLM usage we all need to be aware that it is just going to be a matter of time…Aug 30Aug 30
Shravan KumarAgent & Tools — ReAct DocStoreThe ReAct DocStore integrates the ReAct (Reasoning and Acting) agent framework with document retrieval and question-answering capabilities…Aug 29Aug 29
Shravan KumarAgent & Tools — ReAct ChatAgent & Tools — ReAct Chat refers to a framework used in conversational AI where an agent (usually powered by a language model) interacts…Aug 28Aug 28
Shravan KumarAgent & Tools — Basic Code using LangChainIn LangChain, an “Agent” is an AI entity that interacts with various “Tools” to perform tasks or answer queries. Tools are essentially…Aug 25Aug 25
Shravan KumarMastering RAG : Applying RAG to Webscraped InformationApplying Retrieval-Augmented Generation (RAG) to webscraped information involves combining the power of web scraping with advanced AI…Aug 21Aug 21
Shravan KumarMastering RAG: One off question to ConversationalA typical RAG application has two main components:Aug 21Aug 21
Shravan KumarMastering RAG: A Deep Dive into RetrieverHere is the sample RAG architecture.Aug 18Aug 18
Shravan KumarMastering RAG: A Deep Dive into EmbeddingsHere is the sample RAG architecture.Aug 18Aug 18