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Building conversational agents in LangChain
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Tools and Agents in LangChain
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Notebook setup and prerequisites
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Data preparation
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Initialize LangChain vector store
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Initializing everything needed by agent
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Using RetrievalQA chain in LangChain
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Creating Lex Fridman DB tool
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Initializing a LangChain conversational agent
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Conversational memory prompt
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Testing a conversation with the Lex agent
Description:
Learn how to build a conversational agent using LangChain agents and GPT-3.5 in this comprehensive tutorial video. Explore the process of creating a chatbot that leverages vector search retrieval to find relevant snippets from Lex Fridman's podcast and uses them as context for the language model. Dive into topics such as tools and agents in LangChain, data preparation, vector store initialization, and the implementation of a RetrievalQA chain. Follow along as the instructor demonstrates how to create a Lex Fridman DB tool, initialize a LangChain conversational agent, and set up conversational memory prompts. Conclude the tutorial by testing a conversation with the newly created Lex agent and gain practical insights into building advanced AI-powered chatbots.

Chatbot with LangChain Agents + GPT 3.5

James Briggs
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