This n8n workflow automates the process of posting blog content to LinkedIn and Twitter, enhancing content distribution and engagement. It starts with a webhook trigger to receive new blog data, then uses language models and embeddings for content analysis and context understanding. The workflow splits the blog text for detailed processing, stores related embeddings in a Supabase database for quick retrieval, and leverages vector search to find relevant content. A Retrieval-Augmented Generation (RAG) agent, powered by a language model, generates tailored social media posts based on the blog content. The generated posts are then published directly to LinkedIn and Twitter, with error handling and logging through Google Sheets and Slack notifications. This workflow is ideal for bloggers, digital marketers, and content managers looking to automate and optimize their social media sharing process.
Automated Blog Posting to LinkedIn and Twitter
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.vectorStoreSupabase, googleSheets, slack, stickyNote, webhook |
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