This n8n workflow automates the process of capturing, analyzing, and storing cryptocurrency price data. Triggered by an HTTP POST webhook, it begins by splitting the input data into manageable chunks using a text splitter. It then generates embeddings for the data through Cohere’s embedding model, and stores these vectors in a Supabase vector database. The workflow utilizes a retrieval-augmented generation (RAG) agent powered by LangChain to interpret the data and generate insights. Results are appended to a Google Sheets log for record-keeping. If any errors occur, notifications are sent via Slack. This workflow is ideal for crypto analysts, investors, or teams tracking digital asset prices and insights in real-time.

Node Count	11 – 20 Nodes
Nodes Used	@n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.embeddingsCohere, @n8n/n8n-nodes-langchain.lmChatAnthropic, @n8n/n8n-nodes-langchain.memoryBufferWindow, @n8n/n8n-nodes-langchain.textSplitterCharacterTextSplitter, @n8n/n8n-nodes-langchain.toolVectorStore, @n8n/n8n-nodes-langchain.vectorStoreSupabase, googleSheets, slack, stickyNote, webhook