This n8n workflow automates the creation of personalized packing lists based on weather conditions for any location. It leverages a webhook trigger to receive weather data input, then processes and stores relevant information using language models and vector search to generate tailored packing recommendations. The process involves text splitting, embedding creation, and querying a language model to generate summaries. The results are logged into Google Sheets for record-keeping and further analysis.
Step-by-step, the workflow starts when it receives data via a webhook, which can be weather forecast details. The data is split into manageable chunks by a text splitter node, then embedded using OpenAI embeddings for semantic understanding. These embeddings are stored in a Supabase vector database, enabling efficient similarity searches.
Subsequently, the workflow queries this database for previous related weather scenarios, improving the relevance of the packing suggestions. A language model (ChatGPT or similar) is then engaged, with context maintained through a memory buffer, to generate a personalized packing list or advice based on weather. The final generated list is appended to a Google Sheets log for tracking and review.
This workflow is ideal for travel agencies, event planners, or individual travelers who want immediate, customized packing instructions based on current or forecasted weather conditions, streamlining preparation and enhancing travel experience.
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