Automated Recipe Recommendation Engine with Bright Data and OpenAI
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This n8n workflow leverages Bright Data's advanced web scraping capabilities and OpenAI's AI to create a powerful recipe recommendation engine. It automates the process of discovering recipes, extracting relevant data, and structuring it for intelligent use.
About This Workflow
This sophisticated n8n workflow revolutionizes recipe discovery and recommendation by integrating cutting-edge technologies. It begins by utilizing Bright Data's MCP (Metrics Collection Platform) to access tools for data extraction. The workflow then targets a specific recipe website, like Tesco's realfood.com, to gather initial search results. Leveraging OpenAI's language models via the Langchain nodes, it intelligently parses paginated data, identifying links to individual recipe pages. Subsequently, it employs Bright Data's scraping tool to fetch the HTML content of each recipe page. Finally, a structured output parser, powered by JSON schema, transforms the scraped recipe data into a clean, usable format, ready for further AI-driven analysis or direct recommendation to users.
Key Features
- Automated Recipe Discovery: Automatically searches for recipes based on defined criteria (e.g., 'tomato pasta' sorted by rating).
- Intelligent Data Extraction: Employs Bright Data's robust scraping capabilities to extract raw HTML content from websites.
- AI-Powered Parsing: Utilizes OpenAI's language models to intelligently parse paginated data and extract structured recipe information.
- Structured Output: Delivers recipe data in a well-defined JSON format, including details like title, rating, dietary options, and healthy indicators.
- Scalable and Flexible: Built on n8n, allowing for easy customization and integration with other tools and services.
How To Use
- Configure Bright Data Credentials: Ensure your Bright Data MCP client is properly authenticated within n8n.
- Set Initial Search Parameters: In the 'Set the Recipe Extract URL' node, define the
urlfor your initial recipe search and thebase_urlfor constructing internal links. - Execute Initial Scrape: The workflow will first use the 'Bright Data MCP Client For Recipe Extract' node to scrape the provided search URL.
- Parse Paginated Results: The 'Paginated Data Extract' and 'Structured Output Parser for Paginated Data' nodes will intelligently identify and extract links to individual recipe pages from the initial scrape.
- Loop Through Recipes: The 'Loop Over Items' node will iterate through each identified recipe link.
- Scrape Individual Recipes: Within the loop, the 'Bright Data MCP Client For Recipe Extract Within The Loop' node will scrape the HTML content of each recipe URL.
- Structure Recipe Data: The 'Structured Output Parser for Recipe Data Extract' node will process the scraped recipe content and parse it into a structured JSON format according to the defined schema.
- Utilize Output: The resulting structured recipe data can then be processed further, saved, or used for downstream applications.
Apps Used
Workflow JSON
{
"id": "ad15d19f-b448-4b9d-ba3a-aef3c45ba2b7",
"name": "Automated Recipe Recommendation Engine with Bright Data and OpenAI",
"nodes": 28,
"category": "Operations",
"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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ID: ad15d19f-b448...
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