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In production, these systems process arbitrary inputs for which no ground-truth code exists, making output quality difficult to assess. We propose a reference-free evaluation framework that monitors flowchart image-to-code generation quality at inference time, using only the input image and the generated output. The framework introduces two automated metrics: $\\text{Recall}{\\text{OCR}}$, which estimates content coverage by extracting text from the input image via OCR as a proxy reference, and $\\text{Precision}{\\text{VE}}$, which detects hallucinated elements through Visual Entailment against the original image. Their harmonic mean, $\\text{F1}{\\text{OCR-VE}}$, provides a unified quality score. 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