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llama-server API fails to apply tool_choice and stop_sequences correctly

By PulseAugur Editorial · [1 sources] ·

The llama-server project has identified two significant issues when using its Anthropic-compatible API. Firstly, the `tool_choice` parameter, intended to guide model function calls, is not being correctly applied, leading the model to select the wrong tool or ignore the `none` option entirely. Secondly, the `stop_sequences` functionality is prematurely terminating responses by matching against the model's internal reasoning process rather than just its final output, resulting in incomplete or empty answers. These bugs were observed on a specific build of llama.cpp with the Qwen3-0.6B model and share similarities with previously reported issues in vLLM. AI

IMPACT These bugs in llama-server's Anthropic API emulation could hinder its adoption for tool-using LLM applications.

RANK_REASON Bug report and analysis of an open-source LLM serving tool.

Read on dev.to — LLM tag →

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

llama-server API fails to apply tool_choice and stop_sequences correctly

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Bug report and analysis of an open-source LLM serving tool.
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COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · The Homelab Postmortem ·

    llama-server's Anthropic API ignores tool_choice and stops inside reasoning

    <p><strong>TL;DR</strong>: llama-server's Anthropic-compatible <code>/v1/messages</code> endpoint accepts two request controls and doesn't apply them. A forced tool, <code>tool_choice: {"type": "tool", "name": "get_time"}</code>, is treated as "call some tool": with <code>get_wea…

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