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1
Intro
2
Agenda
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What are Agents
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Why Agents
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Typical Implementation
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React Approach
7
Challenges with Agents
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Dont use tools when not needed
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Memory
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Long Observations
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Keeping Agents Focused
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Evaluation
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Like Memory
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Auto GPT
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generative engine
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demo
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code
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Define Agent Model
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Define Agent Variable
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Create Agent Response
Description:
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

Data Science Dojo
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