Extracting structured data from PDFs using Gemini 2.0 and Genkit

Google’s Gemini 2.0 Flash, used through the Genkit AI integration framework for Node.js, can analyze PDF documents multimodally and extract information without a separate OCR system. The sample command-line application demonstrates extracting invoice fields and line items from a PDF, then applying Zod schemas to return predictable, machine-processable structured output such as invoice numbers, dates, quantities, and totals. Genkit’s unified generation API can also support models without native structured-output capabilities by augmenting prompts and coercing results. For reusable workflows across different document types, the post uses Genkit’s Dotprompt files to separate prompts, model configuration, input parameters, and output schemas from application code, enabling the same extraction function to process invoices, handwritten forms, and other PDFs by selecting an appropriate prompt. The author highlights Gemini’s ability to interpret handwritten entries and points readers to Genkit documentation, a GitHub sample, and related livestream projects.

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