The provided code illustrates a weather and activity planning tool built using LangGraph and LangChain integrations. It utilizes tools like get_weather, web_search, and think to generate activity suggestions based on weather forecasts and events in a specified city.
The get_weather function fetches weather data through the Open-Meteo API, offering a daily forecast that includes minimum and maximum temperatures. The tool ensures that weather calls are made before any general web searches. An agent node manages the sequence of tool execution, ensuring a structured flow by requiring an initial thought process before action.
The routing logic maintains strict control over the state, guiding the application through stages such as requesting weather information or ending if insufficient data is available. This robust architecture optimizes interactions, making it user-friendly for planning activities based on real-time weather conditions.
The application is demonstrated with an example, querying for activities in Boston.
