This workflow automates the process of receiving, summarizing, indexing, and analyzing breaking news articles using AI-driven tools within n8n. Starting with a webhook trigger, the workflow captures news content submitted via HTTP POST, then splits the text into manageable chunks. These segments are embedded into vector representations using Hugging Face’s embeddings, facilitating semantic search and retrieval from a Weaviate vector database. The workflow further interacts with language models from OpenAI to generate summaries or insights and logs the processed data into Google Sheets for record-keeping. This setup is ideal for news organizations, content aggregators, or agencies aiming to automate news analysis and maintain an organized history of their AI-generated summaries and insights.
Automated Breaking News Summarizer with AI Insights
| Node Count | 11 – 20 Nodes |
|---|---|
| Nodes Used | @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.embeddingsHuggingFace, @n8n/n8n-nodes-langchain.lmChatOpenAi, @n8n/n8n-nodes-langchain.memoryBufferWindow, @n8n/n8n-nodes-langchain.textSplitterCharacterTextSplitter, @n8n/n8n-nodes-langchain.toolVectorStore, @n8n/n8n-nodes-langchain.vectorStoreWeaviate, googleSheets, stickyNote, webhook |
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