Purpose This workflow is the official backend for the StopSlopIn Chrome extension – it classifies LinkedIn posts as quality or slop using a strict LLM quality gate and learns from user votes over time via a Qdrant vector store. What this is for This runs the webhook that powers the StopSlopIn Chrome extension on the Chrome Web Store. The extension sends LinkedIn posts here for analysis and user votes here for training – everything stays on your own n8n instance. Setup Add your OpenAI credentials to the chat model and embeddings nodes Add your Qdrant credentials to both vector store nodes, pointing to a collection named stopslopin Activate the workflow, copy the webhook URL, and paste it into the StopSlopIn Chrome extension settings Follow the instructions on the yellow sticky notes for anything else How it works A single webhook exposes two actions, selected via a ?action= query parameter: analyze for classification, vote for training.
Tags
Embeddings OpenAI
OpenAI Chat Model
Qdrant Vector Store
Structured Output ParserRelated workflows
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