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 Agent Arc...   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