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This course explains how agents give large language models access to capabilities such as logic, calculation, and search. It demonstrates building LangChain agents in Python with custom and prebuilt tools, SQL databases, and multiple ReAct-based approaches.
Syllabus
Why LLMs need tools
What are agents?
LangChain agents in Python
Initializing a calculator tool
Initializing a LangChain agent
Asking our agent some questions
Adding more tools to agents
Custom and prebuilt tools
Francisco's definition of agents
Creating a SQL DB tool
Zero shot ReAct agents in LangChain
Conversational ReAct agent in LangChain
ReAct docstore agent in LangChain
Self-ask with search agent
Final thoughts on LangChain agents
Taught by
James Briggs