Classify LinkedIn posts as quality or slop with OpenAI and Qdrant

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](https://chromewebstore.google.com/detail/pbflmnidhehgfpcjhcplegpcfohcnbjk) 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.