Build a RAG Chatbot for Movie Recommendations with Qdrant and OpenAI
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Develop an AI-powered RAG chatbot for movie recommendations. This workflow uses GitHub for data, OpenAI for embeddings and chat, and Qdrant as a vector store.
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About This Workflow
Overview
This n8n workflow empowers you to build a sophisticated Retrieval-Augmented Generation (RAG) chatbot capable of providing personalized movie recommendations. It leverages the power of OpenAI's embedding models and language models, combined with Qdrant as a vector database for efficient similarity search. The workflow starts by fetching movie data from a CSV file hosted on GitHub. This data is then processed, embedded using OpenAI, and stored in Qdrant. When a user provides input, the chatbot generates embeddings for both positive and negative recommendation examples, queries the Qdrant vector store to find similar movies, and uses an AI Agent with the OpenAI Chat Model to generate a coherent and relevant movie recommendation response.
Key Features
- Fetches movie data from GitHub.
- Utilizes OpenAI Embeddings for vector representation.
- Stores and retrieves data using Qdrant Vector Store.
- Employs an AI Agent with OpenAI Chat Model for response generation.
- Supports both positive and negative recommendation queries.
- Integrates with a chat trigger for interactive use.
How To Use
- Setup Credentials: Ensure your OpenAI API key and Qdrant API credentials are set up in n8n.
- Configure GitHub Node: Update the
GitHubnode with your repository and file path (e.g.,mrscoopers/n8n_demo,Top_1000_IMDB_movies.csv). - Configure Qdrant Node: Set the
qdrantCollectionto 'imdb' in theQdrant Vector Storenode. - Trigger the Workflow: You can either trigger the initial data ingestion by running the workflow manually or use the
When chat message receivedtrigger for interactive use. - Interact with the Chatbot: Once deployed, send messages to the chatbot, providing movie preferences. The chatbot will then return movie recommendations.
Apps Used
Workflow JSON
{
"id": "6af3f407-0bef-4939-8726-5e58770ea55a",
"name": "Build a RAG Chatbot for Movie Recommendations with Qdrant and OpenAI",
"nodes": 0,
"category": "AI Research, RAG, and Data Analysis",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
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