This workflow automates the process of generating engaging LinkedIn posts based on the content of uploaded PDFs, such as books or reports. It triggers when a new file is added to Google Drive, extracts and processes the PDF content, creates meaningful post ideas via AI, and schedules the posts for publication. The system uses vector similarity searches against a Pinecone database to find relevant insights, ensuring each post is valuable and contextually accurate. Ideal for content marketers and technical writers, this workflow streamlines social media content creation from detailed document resources.
Automated LinkedIn Post Generation from Book PDFs
| Node Count | >20 Nodes |
|---|---|
| Nodes Used | @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.documentDefaultDataLoader, @n8n/n8n-nodes-langchain.embeddingsOpenAi, @n8n/n8n-nodes-langchain.lmChatOpenAi, @n8n/n8n-nodes-langchain.memoryBufferWindow, @n8n/n8n-nodes-langchain.openAi, @n8n/n8n-nodes-langchain.outputParserStructured, @n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter, @n8n/n8n-nodes-langchain.vectorStorePinecone, aggregate, extractFromFile, googleDrive, googleDriveTrigger, googleSheets, if, limit, linkedIn, scheduleTrigger, splitOut, stickyNote |
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