AI Movie Recommender — n8n Workflow with Gemini & GPT
Pick a genre and get the top 20 IMDb-rated films with posters, plots, ratings, runtimes and cast — an n8n workflow pairing Gemini with a GPT-5 Mini fallback and live OMDb data.
Built by Redoan Uzzaman, Full-Stack Developer & AI Engineer.
Overview
AI Movie Recommender is an n8n-powered recommendation tool: a user selects a favorite genre from a cinema-themed web form and instantly receives a curated list of top-rated films with rich details.
How it works
The workflow starts with an n8n form trigger offering 19 genres. An AI agent generates a list of the 20 highest-rated films for the chosen genre, using Google Gemini as the primary chat model with OpenAI GPT-5 Mini as a fallback for resilience. A code node parses the model's output into clean titles.
Each title is then enriched with live data from the OMDb API — poster, IMDb rating, release year, runtime, cast and plot summary — so the results are based on real metadata rather than model memory alone. A final code node assembles the results into a styled HTML page that is returned through an n8n form completion screen, giving users a polished, embeddable experience.
The project shows how a small workflow can combine LLM reasoning with an external data API and multi-model fallback to deliver a reliable, user-facing AI feature.
Key Features
- Cinema-themed web form with 19 genres
- Top 20 IMDb-rated films per genre
- Google Gemini primary model with GPT-5 Mini fallback
- Live OMDb enrichment: posters, ratings, runtime, cast, plots
- Styled HTML results page generated in a code node
- Embeddable n8n form interface
Tech Stack
- n8n
- Google Gemini
- OpenAI GPT-5 Mini
- OMDb API
- JavaScript
- AI Agents
Want something like this built?
Redoan Uzzaman takes on AI, automation and full-stack projects for clients worldwide.