{
 "schema_version": 1,
 "generated": "2026-10-20",
 "repo": "rollroyces/py-idp",
 "name": "py-idp",
 "owner": "rollroyces",
 "slug": "rollroyces-py-idp",
 "github": "https://github.com/rollroyces/py-idp",
 "what": "py-idp is an open-source Python library for intelligent document processing that uses LLM backends and Pydantic schemas to pull structured fields out of documents.",
 "why": "",
 "language": "Python",
 "requirements": [
  "Python with pip available",
  "An API key for a hosted LLM backend such as OpenAI, or a local backend such as Ollama (the zero-config path runs on the in-tree mock backend without a key)",
  "A sample PDF or text file to test with, such as invoice.pdf"
 ],
 "audience_note": "Python developers and back-office teams who turn invoices, contracts, and other PDFs into validated structured data.",
 "risk": "none",
 "section": "earlier",
 "weekly_rank": null,
 "category": "Work and operations",
 "url": "https://dedupedai.com/use-cases/rollroyces-py-idp/",
 "use_case_count": 4,
 "use_cases": [
  {
   "id": "rollroyces-py-idp--extract-invoice-fields-to-pydantic",
   "title": "Extract invoice fields into a validated schema",
   "best": true,
   "url": "https://dedupedai.com/use-cases/rollroyces-py-idp/extract-invoice-fields-to-pydantic/",
   "json": "https://dedupedai.com/use-cases/u/rollroyces-py-idp/extract-invoice-fields-to-pydantic.json"
  },
  {
   "id": "rollroyces-py-idp--review-low-confidence-fields-with-hitl",
   "title": "Route low-confidence fields to a human reviewer",
   "best": false,
   "url": "https://dedupedai.com/use-cases/rollroyces-py-idp/review-low-confidence-fields-with-hitl/",
   "json": "https://dedupedai.com/use-cases/u/rollroyces-py-idp/review-low-confidence-fields-with-hitl.json"
  },
  {
   "id": "rollroyces-py-idp--measure-extraction-accuracy-with-eval",
   "title": "Measure extraction accuracy with the eval harness",
   "best": false,
   "url": "https://dedupedai.com/use-cases/rollroyces-py-idp/measure-extraction-accuracy-with-eval/",
   "json": "https://dedupedai.com/use-cases/u/rollroyces-py-idp/measure-extraction-accuracy-with-eval.json"
  },
  {
   "id": "rollroyces-py-idp--serve-extraction-over-http-with-fastapi",
   "title": "Serve document extraction through a FastAPI endpoint",
   "best": false,
   "url": "https://dedupedai.com/use-cases/rollroyces-py-idp/serve-extraction-over-http-with-fastapi/",
   "json": "https://dedupedai.com/use-cases/u/rollroyces-py-idp/serve-extraction-over-http-with-fastapi.json"
  }
 ],
 "disclaimer": "Third-party repos we don't own or vouch for. AI-generated use cases can be wrong: review everything and run at your own risk."
}