Tool Calling 101: Unlocking Context-Aware LLMs with Real-Time Data #ai #llm #realtimedata

Summary: The video discusses how to enhance large language models (LLMs) by making them context-aware through real-time data integration using tool calling. This technique allows LLMs to access external information such as weather, web data, and databases, while also considering the limitations of traditional and embedded tool calling methods.

Keypoints:

• Tool calling enables large language models to access real-time data from APIs and databases.
• It allows LLMs to provide context-aware responses, such as checking the weather or pulling specific data.
• There are two types of tool calling: traditional tool calling and embedded tool calling.
• Embedded tool calling involves a framework that defines and executes the tools more efficiently.
• The video provides insights into the advantages and limitations of using tool calling with LLMs.