Extracting and Validating Code Blocks from LLM-Generated Markdown in Python

LLMs produce inconsistent Markdown. A prompt that returns a clean python ` block on one run might return `Python, `python, or a bare block with no language tag on the next. If your pipeline ingests that output and tries to save or execute the code, inconsistency breaks everything downstream. This article shows how to extract fenced code blocks reliably, validate them, fix common LLM-introduced errors, and integrate the whole thing into a chapter-level pipeline. Why LLMs Hallucinate Cod...