Generate and evaluate AI prompts with Gemini, OpenRouter, Groq, Cohere and Supabase

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Built by Kanishka Shrivastava Kanishka Shrivastava
Created on June 05, 2026

Description

Quick overview
This workflow receives a goal via webhook, generates three prompt candidates using Google Gemini, OpenRouter, and Groq, has Cohere evaluate and select the best prompt, then returns the result to the caller and stores the goal and winning prompt in Supabase.

How it works
Receives a POST webhook request containing a JSON body with a goal value.
Sends the goal to three parallel prompt-engineering agents backed by Google Gemini, OpenRouter, and Groq to generate creative, marketing, and technical prompt candidates.
Combines the three generated prompt candidates into a single structured payload.
Uses a Cohere-powered evaluator to compare the candidates and return the best prompt (and a reason) as JSON.
Responds to the webhook caller with the evaluator output.
Creates a new row in a Supabase prompts table, saving the original goal and the selected best prompt.

Setup
Add credentials for Google Gemini (PaLM), OpenRouter, Groq, and Cohere so the agents and evaluator can run.
Add your Supabase API credentials and ensure a prompts table exists with fields/columns for goal and best_prompt.
Copy the production webhook URL and send POST requests with { "goal": "..." } from your client or source app.

Nodes Used (7)

AI Agent
@n8n/n8n-nodes-langchain.agent
Code
n8n-nodes-base.code
Cohere Chat Model
@n8n/n8n-nodes-langchain.lmChatCohere
Google Gemini Chat Model
@n8n/n8n-nodes-langchain.lmChatGoogleGemini
Groq Chat Model
@n8n/n8n-nodes-langchain.lmChatGroq
OpenRouter Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenRouter
Supabase
n8n-nodes-base.supabase