This n8n workflow automates the process of tracking commodity prices by receiving data through a webhook, processing and analyzing it using AI-driven embeddings and language models, and logging the information into Google Sheets.
The workflow begins with a webhook node that captures incoming data related to commodity prices. The data is then split into manageable chunks using a character-based text splitter. These chunks are passed through an embeddings node, which converts the text into vector representations for semantic analysis.
The workflow integrates Redis-based vector storage for efficient similarity searches and data retrieval, enabling the system to compare current data with stored information. An AI agent, powered by a language model, is employed to interpret and define the data, providing insightful analysis.
The insights generated are stored into a Redis vector database for ongoing reference and comparison. Concurrently, the workflow logs the details into a Google Sheet for record-keeping and easy access.
This automation is ideal for businesses, market analysts, or traders who need real-time monitoring and analysis of commodity prices, allowing for timely decision-making based on AI-driven insights and historical data logging.
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