Generative AI - Nomidl

Leveraging RAG Rerank Technique for Prompt Compression and Retrieving Correct Responses

Introduction: The utilization of Large Language Models has increased across various domains of natural language processing. As these models develop, their increased size and complexity present important challenges concerning efficiency, prompt interaction, and response accuracy. Addressing these challenges, the RAG rerank technique emerges as a crucial solution, combining the strengths of retrieval and generation models.…

Introduction to Retrieval Augmented Generation (RAG)

In today’s field of artificial intelligence, where language models are highly valued, one of the most critical requirements is to ensure that the answers generated can be reliably accurate. Retrieval Augmented Generation (RAG) is an innovative artificial intelligence system that aims to improve the quality of responses produced by LLM using additional data sources. But…

Document Loaders in Langchain

In this article, we will be looking at multiple ways which langchain uses to load document to bring information from various sources and prepare it for processing. These loaders act like data connectors, fetching information and converting it into a format Langchain understands. There are a lot of document loaders in LangChain and you can…

A Practitioners Guide to Retrieval Augmented Generation (RAG)

“The power of artificial intelligence is the power to transform humans.” – Fei-Fei Li Welcome to our comprehensive guide on Retrieval Augmented Generation (RAG), a revolutionary technique that combines powerful search capabilities with generative AI to enhance AI systems like langchain, a leading large language model. In this guide, we will explore the concept of…

Building First Prompt Templates with OpenAI Language Models

Introduction In this blog post, we will explore how to build your first prompt and prompt templates using OpenAI Language Models. Language models are powerful tools that can generate text based on the input provided to them. By creating prompts and prompt templates, we can guide the language models to generate specific types of text…

Exploring LangChain: The Framework for Building AI Applications

In this article we will be exploring the framework that we can use to integrate AI intoour applications and build AI-powered applications. AI is being widely used, and it is the future, regardless of the type of application. I’llalso explain the kinds of applications you can build with AI. Integrating AI hasbecome a must to…