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Extract the structured part out of a model response: JSON objects, fenced code blocks, markdown tables, lists, and strip reasoning or thinking tags that wrap the actual answer.
Clean and extract structured data from raw AI output. Pull JSON from markdown, convert tables to CSV, strip thinking/reasoning tags, extract code blocks, and convert lists to arrays. All in one tool.
Paste AI output on the left...
Even with an explicit instruction to return only JSON, models routinely wrap output in a markdown fence, prefix it with a sentence of explanation, or append a helpful note. Naive parsing then fails on valid JSON that simply is not the whole string. Extraction before parsing is what makes the pipeline robust.
The durable fix is upstream: use structured output or constrained decoding where the provider supports it, so the response is schema-conformant by construction. Where that is not available (older endpoints, open models, streaming edge cases) extraction is the fallback, and it earns its place in the pipeline regardless as a defense against format drift.