Movie recommendation chatbot using OpenAI and Qdrant wi

This automation provides personalized movie recommendations via chat using semantic search based on plot descriptions. Built on RAG technology with a LangChain agent, vector database Qdrant, and OpenAI embeddings, it´s ideal for creating smart assistants that understand context and can process both desired and unwanted genres in user queries.

## Who it´s for
- Users seeking personalized movie recommendations through chat
- Developers building RAG systems on open datasets
- Teams testing integration of AI agents with vector databases
- Film critics and content creators automating content curation

## What the automation does
- Loads movie data from a CSV file hosted on GitHub
- Converts film descriptions into embeddings using OpenAI
- Stores vector representations in Qdrant for fast semantic search
- On receiving a chat message, analyzes the query considering both positive and negative examples
- Finds the most relevant movies using a LangChain agent
- Returns top-3 matching film recommendations to the user

## What´s included
- Ready-to-use n8n workflow
- Trigger logic: incoming chat message, manual execution, test trigger
- Integrations with GitHub, OpenAI, Qdrant, and a chat interface
- Basic textual guide for setup and adaptation

## Requirements for setup
- GitHub account with access to the movie dataset CSV
- OpenAI API key
- Access to a Qdrant instance (local or cloud)
- Chat interface capable of sending HTTP requests to n8n
- Running n8n instance with external service connectivity

## Benefits and outcomes
- Personalized recommendations without requiring exact movie titles
- Support for both positive and negative preferences in a single query
- Fast semantic search over a vector database
- Easy updates to the movie catalog via CSV editing
- Automation of content curation based on natural language descriptions
- Ready-to-test RAG architecture with LangChain integration

## Important: template only
Important: you are purchasing a ready-made automation workflow template only. Rollout into your infrastructure, connecting specific accounts and services, 1:1 setup help, custom adjustments for non-standard stacks and any consulting support are provided as a separate paid service at an individual rate. To discuss custom work or 1:1 help, contact via Telegram: @gleb923.