Third-party cyber evaluations involving OpenAI models
openai.com·13h ago
Data Science
Towards Data Science·17d ago·5 min read
Loop Engineering with Adaptive PDF Parsing: Start Cheap, Pay for a Heavier Parser Only When the Page Needs It
TL;DR
Parsing PDFs can be costly, especially when dealing with complex documents. A new adaptive parsing approach allows for initial cheap checks to identify parsing failures before committing to more expensive processing.
✦ Why It Matters
Implement adaptive PDF parsing to minimize costs and improve processing speed in document handling applications.
Key Takeaways
- Start with a cheap parser to minimize costs.
- Use a cascade of checks to determine parsing needs.
- Evaluate outputs at multiple stages for accuracy.
- Choose the right parser based on document type.
How It Works
The adaptive parsing system begins with a baseline parser, such as PyMuPDF for native PDFs, and runs a series of checks on the output. If the output fails to meet quality standards, the system escalates to a more complex parser, like a vision LLM, only for those specific pages.
This feedback loop ensures that resources are allocated efficiently, as most pages can be processed quickly without deep parsing.