Loot Box Probability Analysis Workflow

This workflow is designed to analyze loot box probabilities and store related data efficiently. It starts with a webhook trigger that receives POST requests, which can be from a website or app when a user interacts with a loot box feature. The workflow then splits the received text into manageable chunks, processes the text to generate embeddings using Cohere, and stores these embeddings in a Pinecone vector database. It also queries the database to find similar entries to support probability calculations or comparisons. Additionally, the workflow incorporates AI-powered language processing with OpenAI models, which helps define and analyze loot box data, enabling nuanced decision-making or insights. The system maintains context with a memory buffer and utilizes a language agent to dynamically generate responses or actions based on the data. Finally, all relevant information and analysis results are logged into a Google Sheet for record-keeping and further review.