Recipe Recommendations with Qdrant & Mistral AI
Creates a personalized recipe recommendation chatbot using Qdrant vector store for similarity search with negative prompts and Mistral for embeddings and LLM.
This n8n workflow builds a recipe recommendation system by scraping HelloFresh's weekly menus, processing recipes into chunks, generating embeddings with Mistral AI, and storing them in a Qdrant vector database alongside full details in SQLite. It enables an AI Agent to deliver tailored recipe suggestions via Qdrant's Recommendation API, which supports negative prompts to exclude unwanted ingredients or recipes, enhancing user satisfaction.
Key benefits include scalable recommendation features
- Platform
- n8n
- Category
- HR & Operations
- Price
- $24.99
- Creator
- Fred Garcia
- Qdrant
- Mistral AI
- Recipe Recommendation
- Vector Database
- AI Agent
- Embeddings
- Chatbot
- Personalization
- Recommendation API
- Web Scraping
How to import this workflow into n8n
- 1Purchase or download the workflow to get the n8n workflow JSON file.
- 2In your n8n instance, open Workflows and choose "Import from File" (or paste the JSON with Ctrl+V on the canvas).
- 3Open each node marked with a credential warning and connect your own accounts and API keys.
- 4Run the workflow once manually to verify the data flow, then toggle it to Active.
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