Artificial Intelligence Agents! The new trend in AI and language model innovation, giving LLMs the ability to reason through problems, call external functions/api, use tools to attack a problem, and even automatically managing other agents themselves.

This video is broken into two parts, a high level overview of what it means to refer to an application as an Agent, and the second being a comprehensive deep dive into my own example, an supervisor architecture with a central manager agent that controls a social media analysis subagent, and a report writing subagent.

Additional Resources -
Github: https://github.com/ALucek/ai-agents-v...
@LangChain LangGraph Tutorial Series:    • LangGraph (Python)  
OpenAI Function Calling: https://platform.openai.com/docs/guid...
OpenAI Tools: https://platform.openai.com/docs/assi...
LangChain Agents Documentation: https://python.langchain.com/docs/mod...
LangGraph Documentation: https://python.langchain.com/docs/lan...
LangSmith Trace From Example: https://smith.langchain.com/public/b6...


Chapters:
00:00 - Part 1: Intro to Agents
02:06 - ReAct Paper
03:30 - ChatGPT Is An Agent
04:39 - Function Calling Overview
06:36 - Function Calling & Tools
08:15 - Artistic Interpretation
10:26 - Part 2: Code Example
11:10 - Agent Supervisor Architecture
13:38 - Creating Custom Tools
16:37 - Defining Agents
19:03 - Supervisor Agent Creation
21:39 - Sub Agent Creation & Graphing
23:54 - Graph Workflow Setup
24:28 - Defining Agent Edges
26:38 - Trying it out!
27:45 - Behind the Scenes with LangSmith
32:35 - Concluding Thoughts