katanaml/sparrow

Health v2 · maintenance only

Flags: no_readme

Adoption not part of the score

5225 stars · 517 forks observed · 2026-10-19

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Sparrow is an open-source framework for structured data extraction from documents (PDFs, images) using ML, LLMs, and Vision LLMs, with schema-driven extraction and agentic workflows. It combines Vision LLM extraction with Text LLM reasoning for classification, validation, and orchestration without cloud dependencies.

Use cases

• extract structured data from invoices and receipts
• parse tables from financial reports and bank statements
• convert PDF documents to JSON with a defined schema
• classify and extract fields from multi-page documents
• build agentic document processing workflows with LLMs
• validate extracted document values against typed schemas

When to choose

• you need schema-driven structured extraction from PDFs or document images
• you want self-hosted document AI without cloud dependencies
• you need to combine vision LLM extraction with LLM reasoning and validation

When to avoid

• you need a simple turnkey OCR API with no ML setup
• your documents are plain text with no layout or tables
• you require a permissive license for proprietary redistribution (GPL-3.0)

Facets

framework · maturity active

machine-learning ocr nlp llm-inference rag agent-framework computer-vision pdf artificial-intelligence machine-learning computer-vision pdf python self-hosted document-extraction vision-llm structured-data agentic-workflows schema-validation document-ai natural-language-processing documentai docker

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markdown · JSON · MCP: product_card(name="katanaml/sparrow")