Building Agentic RAG with CrewAI and Langchain

Building Agentic RAG with CrewAI and Langchain

In the rapidly evolving field of AI, the ability to provide accurate, context-aware responses to user queries is a game changer. Retrieval-Augmented Generation (RAG) is a powerful paradigm that combines the retrieval of relevant information from external sources with the generative capabilities of large language models (LLMs). However, as queries become increasingly complex and diverse, … Read more

Mastering RAG: The Basics of Retrieval-Augmented Generation

Mastering RAG: The Basics of Retrieval-Augmented Generation

LLM (Large Language Model) is a powerful new platform, but they are not always trained on data relevant to our tasks or the latest data. RAG (Retrieval Augmented Generation) is a general method that connects LLMs with external data sources (such as private or up-to-date data). It allows LLMs to use external data to generate … Read more

Building Data Analysis Agents with LangChain, CrewAI, and AutoGen

Building Data Analysis Agents with LangChain, CrewAI, and AutoGen

Building a data analysis agent using LangChain, CrewAI, and AutoGen. Long press to follow ‘AI Technology Forum’ The data analysis agent can automatically conduct analysis tasks, execute code, and provide adaptive responses to data queries. LangChain, CrewAI, and AutoGen are the three popular frameworks for building such AI agents. This article utilizes and compares these … Read more