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Building RAG chatbot for movie recommendations with Qdrant and Open AI

n8nn8n25 modulesv1.0
OpenAIGitHub

Create a recommendation tool without hallucinations based on RAG with the Qdrant Vector database. This example is based on movie recommendations on the IMDB-top1000 dataset. You can provide your wishes and your "big no's" to the chatbot, for example: "A movie about wizards but not Harry Potter", and get top-3 recommendations. How it works - a video with the full design process - Upload IMDB-1000 dataset to Qdrant Vector Store, embedding movie descriptions with OpenAI; - Set up an AI agent with a

At a glance

Building RAG chatbot for movie recommendations with Qdrant and Open AI is a ready-made n8n workflow you import as a workflow JSON file — no build required. It connects OpenAI, GitHub. It's free to download. Follow the 5-step import below to go live in minutes.

Platform
n8n
Connects
OpenAI, GitHub
Modules
25
Price
Free
Version
v1.0
Building RAG chatbot for movie recommendations with Qdrant and Open AI workflow diagram

About this workflow

Create a recommendation tool without hallucinations based on RAG with the Qdrant Vector database. This example is based on movie recommendations on the IMDB-top1000 dataset. You can provide your wishes and your "big no's" to the chatbot, for example: "A movie about wizards but not Harry Potter", and get top-3 recommendations. How it works - a video with the full design process - Upload IMDB-1000 dataset to Qdrant Vector Store, embedding movie descriptions with OpenAI; - Set up an AI agent with a chat. This agent will call a workflow tool to get movie recommendations based on a request written in the chat; - Create a workflow which calls Qdrant's Recommendation API to retrieve top-3 recommendations of movies based on your positive and negative examples. Set Up Steps - You'll need to create a free tier Qdrant Cluster (Qdrant can also be used locally; it's open-sourced) and set up API credentials - You'll OpenAI credentials - You'll need GitHub credentials & to upload the IMDB Kaggle dataset to your GitHub.

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How to import this n8n workflow

  1. 1

    Download the workflow JSON file after purchase.

  2. 2

    Open n8n → click the menu → Import from File.

  3. 3

    Select the downloaded JSON and import.

  4. 4

    Set up credentials for each node that requires them.

  5. 5

    Click Execute Workflow to test, then activate.

Setup guide

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