This n8n workflow automates the process of receiving JSON data via a webhook, analyzing and embedding the data, storing it in a vector database, and updating a Google Sheet with relevant information. The workflow begins when data is POSTed to the webhook endpoint, followed by splitting the text, generating embeddings using OpenAI’s language models, and indexing these embeddings in Pinecone for similarity search. A Retrieval-Augmented Generation (RAG) agent then processes the data to extract meaningful insights or actions. The results are logged into a specified Google Sheet, and errors trigger alerts via Slack. This workflow is ideal for automating data analysis, creating intelligent search indexes, and maintaining real-time logs for data-driven decision-making.
Automated JSON Processing and Data Storage Workflow
Node Count | 11 – 20 Nodes |
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Nodes Used | @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.embeddingsOpenAi, @n8n/n8n-nodes-langchain.lmChatOpenAi, @n8n/n8n-nodes-langchain.memoryBufferWindow, @n8n/n8n-nodes-langchain.textSplitterCharacterTextSplitter, @n8n/n8n-nodes-langchain.toolVectorStore, @n8n/n8n-nodes-langchain.vectorStorePinecone, googleSheets, slack, stickyNote, webhook |
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