This n8n workflow automates the process of providing detailed weather forecasts using artificial intelligence and the Open-Meteo API. Designed for practical use cases such as travel planning or event scheduling, it integrates multiple steps from user input to delivering weather data in a seamless conversational experience.

The workflow starts with a webhook trigger, allowing users to send natural language queries like ‘Weather Forecast for the Next 7 Days in São Paulo’. An OpenAI chat model processes these messages, interpreting the user’s intent.

A key component is the ‘Generic AI Tool Agent’, which dynamically decides the next step based on the user’s request. Initially, it calls a geolocation API to find the coordinates of a specified city. Once obtained, it passes this data to another API request to fetch the weather forecast for the upcoming days.

Throughout the workflow, sticky notes provide helpful setup instructions and explanations, making it accessible for workshops or onboarding sessions. The chat memory buffer retains conversational context, enabling more natural interactions.

This automation is particularly valuable for developers and businesses creating conversational weather assistants, integrating weather data into dashboards, or developing travel apps that require real-time, accurate forecasts based on user input.

Node Count	11 – 20 Nodes
Nodes Used	@n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.chatTrigger, @n8n/n8n-nodes-langchain.lmChatOpenAi, @n8n/n8n-nodes-langchain.memoryBufferWindow, @n8n/n8n-nodes-langchain.toolHttpRequest, stickyNote