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llm-echo 0.5

8.5内容质量

TL;DR · AI 摘要

llm-echo 0.5更新了模拟token使用计数，支持工具调用和系统提示，提供LLM调试新功能。

核心要点

  • 5版本新增工具调用、系统提示的token计数模拟
  • 示例命令uvx --with llm-echo可验证模型行为
  • token使用统计包含输入2、输出24的精确数据

结构提纲

按章节快速跳转。

  1. §版本更新说明

    介绍llm-echo 0.5的核心改进内容

  2. ·Echo模型机制

    描述不依赖LLM的纯回声模型实现方式

  3. ›Token计数优化

    新增对工具调用和系统提示的token统计

  4. ·使用示例

    展示uvx命令行调用及输出结果解析

思维导图

用一张图看清主题之间的关系。

查看大纲文本（无障碍 / 无 JS 友好）
  • llm-echo 0.5更新
    • 核心功能
      • Echo模型实现
      • Token计数模拟
    • 改进内容
      • 支持工具调用统计
      • 系统提示计数
    • 使用示例
      • uvx命令行调用
      • 输出结果解析

金句 / Highlights

值得收藏与分享的关键句。

#LLM#调试工具#Python#AI
打开原文

Release: llm-echo 0.5

Simon Willison’s Weblog

Newsletter

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18th October 2026

Release

llm-echo 0.5

— Debug plugin for LLM providing an echo model

I'm working towards a new LLM release, and testing PRs caused me to revisit the llm-echo debug plugin. This plugin provides a "model" which doesn't involve an LLM at all - it just repeats back the prompts that have been fed to it. The new release now updates the simulated token usage counts to take tool calls, system prompts, and reasoning tokens into account.

Example usage:

code
uvx --with llm-echo llm -m echo 'hi there' -o thinking 1 --usage

Outputs:

code
First I consider the prompt, then I decide what to say.
{
  "prompt": "hi there",
  "system": "",
  "attachments": [],
  "stream": true,
  "previous": []
}
Token usage: 2 input, 24 output

Posted

at 11:16 pm

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This is a beat by Simon Willison, posted on 18th October 2026 .

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