This n8n workflow automates the process of scheduling Instagram posts using data stored in Airtable. It begins with a webhook trigger that receives content data, which is then split into manageable chunks for processing. The workflow generates text embeddings via OpenAI, stores and queries these embeddings in Pinecone for context management, and uses a language model to handle and analyze the data. A Retrieval-Augmented Generation (RAG) agent manages the context, assisting in generating appropriate content schedules. The final step logs the status into Google Sheets, and any errors encountered during the process trigger a Slack alert for immediate notification. This automation streamlines social media planning, saving time and ensuring consistent content posting based on dynamic data inputs.
Automated Instagram Content Scheduling via Airtable
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.lmChatAnthropic, @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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