LLM Function Calling - AI Tools Deep Dive

Tool and Function calling with LLMs is becoming one of the most crucial to understand capabilities, and can elevate the way you interact with and build AI applications to the next level. I’ve put together this video to give a comprehensive overview of what tool calling is, how it works, and how you can make your own. Cheers!

I put these videos together on my own time with my own funding, if you find these resources useful and have the means, consider leaving a donation via the Super Thanks function!

Resources:
Code: https://github.com/ALucek/tool-callin...
OAI Docs: https://platform.openai.com/docs/guid...
Pydantic: https://docs.pydantic.dev/latest/conc...
LangChain Tools: https://python.langchain.com/v0.1/doc...
LangChain Agents: https://python.langchain.com/v0.1/doc...
Breaking Down Agent Architectures:    • Breaking Down & Testing FIVE LLM Agen...  

Chapters:
00:00 - What is Tool/Function Calling?
03:09 - Defining Custom Tools
05:51 - LLM Tool Response
08:20 - Executing Tools
12:59 - Additional Tool Behavior
14:45 - Advanced Tools with Pydantic Schemas
17:53 - Executing Advanced Tools
19:58 - Universal Tools and Functions
20:57 - Defining Models & Tools w/LangChain
22:42 - Binding Tools w/LangChain
24:27 - Executing Tools w/LangChain
26:56 - Tools & LLMs as Agents
27:40 - Tool Calling Agent
29:13 - ReAct Agent
30:47 - Outro

#ai #coding #openai