Automated Virtual Economy Price Monitoring Workflow

This n8n workflow is designed to automatically track and analyze prices within a virtual economy, such as in online games or digital marketplaces. It captures data through a webhook, processes the information with language models and vector similarity tools, and logs relevant insights into a Google Sheet for ongoing monitoring.

The workflow begins with an HTTP POST webhook where data related to virtual economy prices is received. This data is then split into manageable chunks for processing. Each chunk is converted into embeddings using the Cohere API, enabling semantic understanding and similarity matching.

These embeddings are stored in a Pinecone vector database, which allows efficient searching and comparison of new data against previously stored information. A query operation retrieves relevant stored data, which is then processed with language models to generate meaningful insights or decisions.

A conversational AI component, utilizing Hugging Face models, provides natural language understanding and interaction capabilities. The entire process is managed with a memory buffer to handle context and state. Finally, the results, insights, or decisions are logged into a Google Sheet for record-keeping and further analysis.

This workflow is especially useful for game developers, digital marketplace managers, or anyone monitoring fluctuating virtual asset prices to make informed decisions or automate price alerts and updates.