Traditional language models (LLMs) are passive and can generate text based on patterns learned during training, whereas AI agents can take action in the world.
smolagents is a lightweight library that simplifies AI agent development by implementing the brain and body architecture with minimal overhead.
It enables the creation of agents that adapt to circumstances and take appropriate actions, allowing developers to build powerful AI agents with a simple approach.
smolagents provides a code-first approach, allowing LLMs to analyze weather patterns and solve complex problems efficiently.