{"categories":[{"label":"Libraries","url":"https://skillfed.io/packages/category/software-development-libraries/8"},{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/8"},{"label":"Image Processing","url":"https://skillfed.io/packages/category/scientific-engineering-image-processing"}],"enrichment":{"capability":"Provides a catalog of pre-defined Pydantic schemas for extracting structured data from images, videos, and documents using Vision Language Models.","skillfed_tags":["vision-language-models","structured-extraction","document-processing"],"use_cases":["Extract invoice line items, dates, and customer details from receipt images for accounting automation.","Parse driver's license or passport images into structured fields for identity verification workflows.","Convert medical insurance cards into validated data for claims processing systems.","Extract product information and pricing from retail catalogs or ecommerce images.","Automate document classification and field extraction for document management systems.","Build visual ETL pipelines that feed validated structured data directly into downstream databases or APIs."],"what_it_does":"VLM Run Hub is a library of pre-built Pydantic data models designed to standardize the extraction of structured information from visual content\u2014images, videos, and documents. Rather than writing custom parsing logic for each extraction task, you import a schema from the hub (e.g., Invoice, DriverLicense, MedicalInsuranceCard) and pass it to a Vision Language Model's structured output API. The model returns data conforming to that schema, which Pydantic automatically validates.\n\nThe library covers real-world domains: document processing (invoices, receipts, passports), accounting and finance (W2 forms, balance sheets), healthcare (insurance cards, pathology reports), retail (product catalogs), media (sports game states), and logistics. Each schema has been tested across industry use cases. The schemas are model-agnostic\u2014use the same Invoice schema with OpenAI's GPT-4o, Anthropic's Claude Vision, or the VLM Run SDK without rewriting prompts.","worth_installing":"Yes, if you are building applications that extract structured data from images or documents using Vision Language Models. The pre-built schemas save significant development time and eliminate the need to design and validate extraction formats for common document types. The library is permissively licensed, has low install friction, and covers a broad range of real-world domains. Maintenance is aging but not stalled; evaluate whether the schema catalog meets your specific use cases before committing."},"id":"vlmrun-hub","links":{"html":"https://skillfed.io/packages/vlmrun-hub","md":"https://skillfed.io/packages/vlmrun-hub.md","pypi":"https://pypi.org/project/vlmrun-hub/"},"maintenance":{"status":"aging"},"meta":{"latest_release":"2025-12-15","license_spdx":null,"license_treatment":"permissive","name":"vlmrun-hub","python_support":"supports_current","summary":"VLM Run Hub for various industry-specific schemas"},"popularity":{"monthly_downloads":174239,"position":10285,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.1.35"}