Movie recommendation system using Qdrant and OpenAI

• Generate personalized movie recommendations based on user preferences.
• Utilize AI to process user input for enhanced content discovery.
• Integrate data from external sources for enriched movie databases.

Trigger the workflow manually or through a chat message. Fetch movie data from GitHub and extract relevant information. Generate embeddings for positive and negative movie examples using OpenAI. Store and query embeddings in Qdrant for efficient recommendation retrieval. Return personalized movie suggestions based on user input.

1. 1
   Import the workflow template into your n8n instance.
2. 2
   Configure GitHub credentials to access the movie dataset.
3. 3
   Set up OpenAI credentials for embedding generation.
4. 4
   Configure Qdrant credentials for storing and querying movie data.
5. 5
   Test the workflow to ensure all connections and integrations are functioning.