LLMs are frozen at training time, so they return confident answers that may already be out of date. This free, self-paced Dapr University track shows you how to close that gap in Python by giving an agent access to the live web.
You'll build an expert agent with Dapr Agents that calls a Tavily search tool to fetch current information, then reasons over those results through the provider-agnostic Dapr Conversation API. Combining tool calls with agent reasoning keeps answers grounded in today's data.
This university track requires an OpenAI API key and a free Tavily key.
Start the free track here!
