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LLM frequency penalty breaks JSON output, causing data loss

By PulseAugur Editorial · [1 sources] ·

A developer discovered that setting `frequency_penalty` to a non-zero value in an LLM configuration can cause structured data, like JSON, to be improperly truncated. This occurs because the penalty mechanism, designed to prevent repetitive text, penalizes common JSON syntax tokens (commas, colons, quotes) that appear frequently in structured output. As the JSON array grows, the penalty can cause the model to prematurely emit the closing bracket `]` instead of a comma `,`, resulting in valid JSON but with missing data. The developer recommends setting `frequency_penalty` and `presence_penalty` to zero for structured output tasks and validating item counts independently. AI

IMPACT Highlights a critical configuration issue for developers using LLMs for structured data extraction, potentially leading to silent data loss.

RANK_REASON Developer discovers a bug/misconfiguration in LLM parameter usage affecting structured data output.

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

LLM frequency penalty breaks JSON output, causing data loss

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22 / 100
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Newsworthiness bucket
Tool
Developer discovers a bug/misconfiguration in LLM parameter usage affecting structured data output.
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Single-source cluster
Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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product, infra
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High
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Breaking (< 6h)
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COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · jidonglab ·

    frequency_penalty Broke My JSON: 47 of 88 Long Invoices Lost Items

    <p>The invoice had 34 line items. The JSON my extractor returned had 19. It parsed. It passed schema validation. Nobody noticed for two weeks.</p> <p>The cause was one line in a shared client config: <code>frequency_penalty=0.3</code>. I had added it to stop a summarizer from loo…

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