This workflow automates the process of capturing Twitter mentions through a webhook trigger, processing and embedding the data, and storing it in Notion and Google Sheets. It also employs advanced language models and vector databases to handle natural language understanding and retrieval. Practical for monitoring social media activity, this workflow provides insights and automated logging for social media and team analytics.
Automated Twitter Mentions Logging in Notion and Google Sheets
Node Count | 11 – 20 Nodes |
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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.vectorStoreWeaviate, googleSheets, slack, stickyNote, webhook |
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