Explore the world of intelligent conversational AI bots using LangChain agents and OpenAI's Language Models (LLMs) in this comprehensive 1-hour 5-minute tutorial. Learn how to create data-aware applications that can understand natural language, answer questions, and provide insights from CSV data. Discover the innovative tools offered by LangChain, delve into the capabilities of OpenAI's LLMs, and follow a step-by-step guide to build and load a chatbot agent using the OpenAI API. Witness firsthand how these technologies empower applications to communicate with users, extract valuable insights, and provide intelligent responses based on given data. Cover topics such as agent types, implementation approaches, challenges, memory management, evaluation techniques, and practical examples like Auto GPT and generative engines.
Agents in LangChain - The Key to Building Conversational AI Applications - OpenAI's Language Models
Overview
Syllabus
Intro
Agenda
What are Agents
Why Agents
Typical Implementation
React Approach
Challenges with Agents
Dont use tools when not needed
Memory
Long Observations
Keeping Agents Focused
Evaluation
Like Memory
Auto GPT
generative engine
demo
code
Define Agent Model
Define Agent Variable
Create Agent Response
Taught by
Data Science Dojo
