Dynamic AI web researcher: From plain text to custom CSV with GPT-4 and Linkup
Ready for 3.0Ready for 3.0. This template uses no nodes that n8n 3.0 removes. No removed nodes, versions or helpers found. Static check, last run 2026-10-19.
What this workflow does
This AI workflow has 10 nodes and runs when someone submits an n8n form (“New research”). Along the way it connects OpenAI Chat Model. It also calls api.linkup.so over HTTP.
How it runs
Trigger: When someone submits an n8n form (“New research”).
- Prepare prompts and schema (Basic LLM Chain): sends a prompt to an LLM, with model: OpenAI Chat Model
- Query Linkup to find the list (HTTP Request): calls api.linkup.so (POST)
- Split Out: splits a list into separate items
- Loop Over Items (Loop Over Items (Split in Batches)): loops over the items in batches
- Convert to CSV (Convert to File): converts data to a file
- Get object name and value (Edit Fields (Set)): sets or maps fields
- Query Linkup to find all properties for this item (HTTP Request): calls api.linkup.so (POST)
- Prepare final JSON for that item (Code): runs custom JavaScript code
Services it uses
HTTP calls to: api.linkup.so
Before you upgrade to n8n 3.0
Nothing in this workflow is removed in n8n 3.0, so it should import and run after the upgrade.
Nodes used (9)
- n8n Form Trigger
n8n-nodes-base.formTrigger - OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenAi - Split Out
n8n-nodes-base.splitOut - Loop Over Items (Split in Batches)
n8n-nodes-base.splitInBatches - Edit Fields (Set)
n8n-nodes-base.set - HTTP Request
n8n-nodes-base.httpRequest - Code
n8n-nodes-base.code - Basic LLM Chain
@n8n/n8n-nodes-langchain.chainLlm - Convert to File
n8n-nodes-base.convertToFile
From the author
This template introduces a revolutionary approach to automated web research. Instead of a rigid workflow that can only find one type of information, this system uses a "thinker" and "doer" AI architecture. It dynamically interprets your plain-English research…