Automated Hello Fresh Recipe Recommendation with Qdrant & Mistral AI
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AI ToolsAIAutomationData IntegrationHello FreshLLMMistral AIQdrantRecipe Recommendation
Integrate Qdrant and Mistral AI to automatically recommend Hello Fresh recipes based on your preferences.
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About This Workflow
How it Works
This n8n workflow automates the process of recommending Hello Fresh recipes by leveraging the power of Qdrant for efficient data retrieval and Mistral AI for intelligent language processing. The workflow begins by fetching the current week's menu from a Qdrant database. It then uses a Python script to insert recipe data into a local SQLite database, categorizing and tagging them for better organization. Subsequently, it utilizes Mistral AI to split and process recipe instructions and metadata. Finally, it queries Qdrant again to recommend recipes based on user-defined positive and negative criteria, acting as a personalized recipe bot for Hello Fresh.
Key Features
- Dynamic Weekly Menu Fetching: Automatically retrieves the latest weekly menu from your Qdrant instance.
- Intelligent Recipe Data Ingestion: Processes and stores recipe information, including instructions, cuisine, category, and tags, into a SQLite database.
- AI-Powered Text Splitting: Employs Mistral AI's text splitting capabilities for efficient processing of recipe instructions.
- Personalized Recipe Recommendations: Uses Mistral AI to understand user preferences (positive and negative inputs) and recommend suitable Hello Fresh recipes.
- Qdrant Integration: Leverages Qdrant for fast and scalable retrieval of recipe data and recommendations.
- SQLite Database Management: Manages recipe data locally with SQLite for persistent storage and easy querying.
- Customizable User Input: Allows users to specify desired ingredients, flavors, or meal types, and also what to avoid.
How To Use
- Configure Qdrant Connection: Ensure your Qdrant endpoint (
http://qdrant:6333) and collection (hello_fresh) are correctly set up. - Set up Mistral AI Credentials: Provide your Mistral AI API credentials.
- Define Recipe Preferences: When interacting with the workflow (e.g., via a webhook or trigger), provide
positiveandnegativeparameters to describe your desired recipe.positive: Ingredients, flavors, meal types, etc.negative: Flavors to avoid, allergens, etc.
- Execute the Workflow: Trigger the workflow to receive personalized Hello Fresh recipe recommendations.
- Review Recommendations: The output will provide recommended recipes based on your input and the current week's menu.
Frequently Asked Questions
To run this workflow, you will need API credentials for Mistral AI. Additionally, you need to ensure your Qdrant instance is accessible at the specified endpoint (`http://qdrant:6333`) and that the `hello_fresh` collection exists. No specific database credentials are required for the local SQLite database as it's managed by the script itself.
The `systemMessage` for the Mistral AI model explicitly states: 'Do not recommend any recipes other from the current week's menu. If there are no recipes to recommend, please ask the user to visit the website instead https://hellofresh.com.' This ensures a graceful fallback when no suitable recipes are found.
Yes, the workflow includes a JavaScript code snippet within the `ai_textSplitter` node that extracts the first 10 courses from the parsed page data (`pageData.props.pageProps.ssrPayload.courses.slice(0, 10)`). You can modify the `slice` parameters to adjust how many courses are processed. The `jsCode` and `pythonCode` sections offer further customization points for data handling and insertion.
Reddit User Reviews
R
u/recipe_automator_dev35
This is a fantastic starting point for building a personalized recipe bot! The Qdrant integration for recommendations is super fast. Been tweaking the Mistral prompts to get even better suggestions. Thanks for sharing!
Reddit
N
u/n8n_enthusiast_8812
Anyone else struggling with the Qdrant connection? Mine keeps timing out. Is there a specific Qdrant setup I should be aware of for this workflow?
Reddit
C
u/codemancer_pro28
Really clean implementation of AI-driven recommendations. The SQLite part is a neat addition for local persistence. Could easily extend this to include user ratings or history for even more accurate suggestions.
Reddit
Apps Used
A
AIA
AutomationD
Data IntegrationH
Hello FreshL
LLMM
Mistral AIQ
QdrantR
Recipe RecommendationWorkflow JSON
{
"id": "4248ab3f-0f3b-4ed3-8dc8-b853541f908b",
"name": "Automated Hello Fresh Recipe Recommendation with Qdrant & Mistral AI",
"nodes": 0,
"category": "AI Tools",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
Get This Workflow
ID: 4248ab3f-0f3b...
About the Author
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Statistics
Views234
Downloads11
Rating
5/5
Verification Info
Community Verified
This workflow has been verified by the community
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