n8n Reddit Dataset: Apify + OpenAI Labels to Supabase

Automatically scrape Reddit, label comment reactions with OpenAI, and store searchable data in Supabase

This n8n workflow runs weekly to pull Reddit posts and comments using Apify, classifies each comment’s reaction type with OpenAI (gpt-4.1-mini), and saves both structured rows and OpenAI embeddings into Supabase for analysis and vector search.

What this workflow does

• Runs on a schedule (weekly) and accepts dataset inputs such as subreddits, sort order, time window, minimum score, and item limits.
• Splits your subreddit plan into scrape jobs and uses the Apify Reddit Scraper actor to collect posts and their comments.
• Formats scraped post data into structured metadata rows and inserts them into the Supabase posts table.
• Creates OpenAI embeddings for each post’s combined context text and inserts vectors into the Supabase documents table.
• Filters and formats comments, then uses OpenAI (gpt-4.1-mini) to classify each comment into one reaction type.
• Stores labeled comments in the Supabase comments table and embeds comment text into the Supabase documents table for vector search.

Use cases

• Track community sentiment trends across specific subreddits by reaction type over time.
• Build a retrieval system that answers questions about Reddit threads using Supabase + pgvector embeddings.
• Maintain an analytics-ready dataset of posts/comments with consistent filtering (min score, time window, limits).

Technical details

• Schedule Trigger for weekly execution.
• Apify integration via n8n-nodes-apify (Apify Reddit Scraper actor) using an Apify API token credential.
• OpenAI integration using an OpenAI API credential for reaction classification (gpt-4.1-mini) and embeddings.
• Supabase integration using a Supabase credential (project URL + service_role key) with pgvector, storing data in posts, comments, and documents tables.
• Nodes include: set, code, and sticky note (for workflow documentation).

Set your subreddit parameters in the workflow input config and get a structured, labeled, and vector-searchable Reddit dataset in Supabase—ready for n8n-powered automation and downstream analytics.