Block 1 - Structured Output Parser
- Type / Role
- @n8n/n8n-nodes-langchain.outputParserStructured - outputParserStructured
- Config choices
- Version 1.3
Reddit Lead Generator Frontend Integrated (Productized Version) Overview Production ready Reddit lead generation system with progressive data loading for optimal UX. This workflow integrates with a...
@n8n/n8n-nodes-langchain.outputparserstructured, n8n-nodes-base.aggregate, n8n-nodes-base.merge, @n8n/n8n-nodes-langchain.agent, n8n-nodes-base.code, n8n-nodes-base.reddit, n8n-nodes-base.stickynote, n8n-nodes-base.webhook
This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Joseph.
Original n8n.io sourceProduction-ready Reddit lead generation system with progressive data loading for optimal UX. This workflow integrates with a web frontend, sending results in real-time as they're processed instead of waiting for everything to complete.
✅ Progressive Loading - Users see results as they come in (website analysis → keywords → conversations) ✅ 5 Response Stages - Data sent in batches for better UX ✅ Webhook Authentication - Secured with API key headers ✅ Frontend Ready - Built to work with the companion web app ✅ Real-Time Updates - No waiting for 2-minute batch processing
Stage 1: website_analysis - Product details, favicon, summary
Stage 2: keywords_generated - All 10 keywords
Stage 3: conversations_partial1 - First keyword results
Stage 4: conversations_partial2 - Second keyword results
Stage 5: conversations_final - Remaining keywords (3-10) in markdown
BACKEND_API_URL - Your frontend API endpointWEBHOOK_API_KEY - Your webhook security key📖 Complete Setup Guide: https://bit.ly/mediumarticleredditworkflow 🎥 Video Tutorial: https://bit.ly/youtubetutorialredditworkflow 💻 GitHub Repo: https://github.com/juppfy/leads-gen
This workflow requires the companion web app to receive and display results. The frontend handles:
searchIdDeploy instructions and complete code available in the GitHub repo above.
This Version (Frontend):
Batch Version:
Questions? Check the Medium article or YouTube tutorial first. Both have detailed setup instructions and troubleshooting tips.
This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.
Showing the first 24 of 56 workflow blocks. Download the JSON for the full node graph.
| Workflow | Generate Reddit customer leads from a product URL with OpenAI and Firecrawl |
|---|---|
| Complexity | advanced |
| Nodes | 56 |
| Categories | Lead Generation, AI Summarization |
| Author | Joseph |
| Published | 21 Jan 2026 |
Use the JSON export at /data/workflows/12884/12884.json as the source template for this automation.
Open n8n, import the downloaded JSON, and review each node before activating the workflow.
Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.
Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.
Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.
Reddit Lead Generator Frontend Integrated (Productized Version) Overview Production ready Reddit lead generation system with progressive data loading for optimal UX. This workflow integrates with a...
Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.
Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Lead Generation, AI Summarization use case.