Building RAG Chatbot for Movie Recommendations with Qdrant and Open AI

Automated workflow: Building RAG Chatbot for Movie Recommendations with Qdrant and Open AI. This workflow integrates 20 different services: stickyNote, vectorStoreQdrant, merge, lmChatOpenAi, github. It contains 38 nodes and follows best practices for error handling and security.

Workflow Structure (25 nodes)
100%
Manual Trigger
When clicking ‘Test workflow’
Github
GitHub
Extract From File
Extract from File
No Op
Embeddings OpenAI
No Op
Qdrant Vector Store
No Op
Default Data Loader
No Op
When chat message received
No Op
OpenAI Chat Model
No Op
AI Agent
No Op
Window Buffer Memory
No Op
Call n8n Workflow Tool
Execute Workflow Trigger
Execute Workflow Trigger
No Op
Token Splitter
Http Request
Embedding Recommendation Request with Open AI
Http Request
Embedding Anti-Recommendation Request with Open AI
Set
Extracting Embedding
Set
Extracting Embedding1
Merge
Merge
Http Request
Calling Qdrant Recommendation API
Http Request
Retrieving Recommended Movies Meta Data
Split Out
Split Out1
Split Out
Split Out
Merge
Merge1
Set
Selecting Fields Relevant for Agent
Aggregate
Aggregate
Node Types:
trigger
default
logic
transform
http
Requires credentials

Prerequisites

Required Credentials (3)

Github

Used by: GitHub

Docs

OpenAI

Used by: Embeddings OpenAI, OpenAI Chat Model +2 more

Docs

Qdrant

Used by: Qdrant Vector Store, Calling Qdrant Recommendation API +1 more

Docs

Multiple services required

This workflow needs 3 different credentials. Make sure you have accounts for all services before importing.

Complexity

Advanced

Expert level. Custom code, complex logic, many integrations.

Setup time: ~50 min
Score: 65/100
Conditional Logic
7 Integrations

When to Use This Workflow

Real-time Response

React instantly when events happen - new orders, form submissions, or API calls.

Zero delay between trigger and action for time-sensitive workflows.

Time Savings

Replace repetitive manual tasks with reliable automation.

Reclaim hours every week for higher-value work.

Error Reduction

Eliminate human error from routine processes with consistent automation.

Improve accuracy and reliability across your workflows.

workflow.json
{
  "id": "a58HZKwcOy7lmz56",
  "meta": {
    "instanceId": "workflow-ed4f8fd3",
    "versionId": "1.0.0",
    "createdAt": "2025-09-29T07:07:53.859035",
    "updatedAt": "2025-09-29T07:07:53.859049",
    "owner": "n8n-user",
    "license": "MIT",
    "category": "automation",
    "status": "active",
    "priority": "high",
    "environment": "production"
  },
  "name": "Building RAG Chatbot for Movie Recommendations with Qdrant and Open AI",
  "tags": [
    "automation",
    "n8n",
    "production-ready",
    "excellent",
...

Workflow Details

Nodes
27
Trigger
Event
Source
community
Added
Sep 29, 2025

Need Help?

Check out the official n8n documentation for detailed guides.

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