Today we are launching smolagents, a very simple library that unlocks agentic capabilities for language models. (View Highlight)
Any efficient system using AI will need to provide LLMs some kind of access to the real world: for instance the possibility to call a search tool to get external information, or to act on certain programs in order to solve a task. In other words, LLMs should have agency. Agentic programs are the gateway to the outside world for LLMs. (View Highlight)
AI Agents are programs where LLM outputs control the workflow. (View Highlight)
Any system leveraging LLMs will integrate the LLM outputs into code. The influence of the LLM’s input on the code workflow is the level of agency of LLMs in the system.
Note that with this definition, “agent” is not a discrete, 0 or 1 definition: instead, “agency” evolves on a continuous spectrum, as you give more or less power to the LLM on your workflow. (View Highlight)
