GenAI agents can automate parts of business processes that involve tasks like text summarization, question answering, and code generation. This post demonstrates implementing a GenAI agent using two frameworks: Autogen, which treats workflows as conversations between agents, and LangGraph, which represents workflows as graphs. Step-by-step guides include setting up an agent framework to query weather information using APIs, handling location extraction, geocoding, and obtaining the final answer from the NWS API. Both frameworks are showcased with configurations for various AI models.
Table of contents
How to Implement a GenAI Agent using Autogen or LangGraphCurrent weather at a locationStep 1: Setting up AutogenStep 2: Extracting the locationStep 3: Geocoding the locationSteps 4–6: Obtaining the final answerAgentic workflow in LangGraphChoosing between Autogen and LangGraphResourcesSort: