Development · Tip
DeepSeek R1 + Firecrawl /extract Workflow
A pattern pairing reasoning models with Firecrawl for structured web scraping
This workflow combines a reasoning model like DeepSeek R1 with Firecrawl's /extract endpoint to gather structured web data. R1 evaluates search results to select the most relevant target URLs, Firecrawl extracts content from them, and R1 reconciles and deduplicates the final output into clean JSON.
How it works
Steps: (1) search Google for the company; (2) ask R1 to select URLs matching the objective; (3) run Firecrawl /extract on selected URLs with company, objective and api key; (4) if success, deduplicate and consolidate with R1 and print JSON; else report failure. Demo: 'get all of the founder' for Firecrawl returned all four founders with roles.
What it's for
- Scrape executive and founder details across company websites
- Extract structured entity data from multiple unstandardized search results
- Filter candidate URLs automatically before running extraction APIs
Key points
- Search web for target company or topic
- Prompt a reasoning model (DeepSeek R1) to evaluate and select the best URLs
- Call Firecrawl /extract on selected pages using a defined objective
- Consolidate and deduplicate extracted content with R1 into structured JSON
- Handle extraction errors with a fallback failure report
Pricing
Free
Details
- Type
- Tip
- Category
- Development
- Topic
- Web Scraping
- Open source
- No
- Platforms
- API
- For
- Developers building AI-powered web scrapers and data enrichment pipelines
- Tags
- firecrawl, deepseek, scraping, llm, extraction, automation
Why it was saved
- @ericciarla: A concrete recipe for getting clean, consolidated structured data from a whole website with minimal code.
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