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/aiagentsv...
‪@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