OpenClaw PDF Extraction Agent
Budget: $250 – $750 USD
I’m building a personal AI agent on top of the OpenClaw framework and I want its very first super-power to be deep PDF understanding. The immediate milestone is simple and focused:
• Accept a PDF (single or batch)
• Reliably extract all text, tables, and embedded data
• Return structured output (JSON or CSV) that downstream routines can consume
Accuracy, speed, and graceful handling of malformed files matter more to me than a flashy UI at this stage. If you can also keep hooks in place for future features—annotation, summarisation, broader document types—that would be ideal.
Preferred stack: Python, OpenClaw, and any open-source OCR or parsing libraries you trust (e.g., PyPDF2, pdfplumber, Tesseract). Clean, well-commented code and a brief README showing how to run the agent locally are required for acceptance.
I’ll provide sample PDFs and edge-case docs for testing. Looking forward to seeing how you’d approach rock-solid text and data extraction as the foundation of a larger agent ecosystem.
• Accept a PDF (single or batch)
• Reliably extract all text, tables, and embedded data
• Return structured output (JSON or CSV) that downstream routines can consume
Accuracy, speed, and graceful handling of malformed files matter more to me than a flashy UI at this stage. If you can also keep hooks in place for future features—annotation, summarisation, broader document types—that would be ideal.
Preferred stack: Python, OpenClaw, and any open-source OCR or parsing libraries you trust (e.g., PyPDF2, pdfplumber, Tesseract). Clean, well-commented code and a brief README showing how to run the agent locally are required for acceptance.
I’ll provide sample PDFs and edge-case docs for testing. Looking forward to seeing how you’d approach rock-solid text and data extraction as the foundation of a larger agent ecosystem.