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Seamlessly log your AI-powered coding conversations. This command-line interface (CLI) tool captures your terminal interactions with AI models like Gemini and Claude, saving entire sessions as clean Markdown documents for easy review and documentation.

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ai-cli-log

Seamlessly log your AI-powered coding conversations. This command-line interface (CLI) tool captures your terminal interactions with AI models like Gemini and Claude, saving entire sessions as clean plain text documents for easy review and documentation.

Installation

npm install -g ai-cli-log

Usage

Wrap any command with ai-cli-log to start a logging session. The core structure is:

ai-cli-log [global-options] run <command-to-log> [args...]

Examples:

  • Basic Logging: Record a session with Google's Gemini CLI.

    ai-cli-log run gemini

    Logs are saved to the .ai-cli-log/ directory.

  • AI-Powered Filenames: Use an AI summary for the log's filename. The options must come before the run command.

    # Enable summary with the default summarizer
ai-cli-log -s run gemini
# or
ai-cli-log --with-summary run gemini

# Enable summary and specify a summarizer
ai-cli-log --by gemini-pro run gemini
# or
ai-cli-log --summarizer gemini-pro run gemini

    This will use your default (or specified) summarizer to generate a descriptive filename like gemini-20250713-153000-fix-database-connection-error.txt.

Alias for Quick Access

For even faster access, you can create shell aliases. This allows you to start a logged session with a short command. Add these to your shell's configuration file (e.g., ~/.bashrc, ~/.zshrc).

# Start a logged Gemini session with an AI-generated summary
alias ag='ai-cli-log -s run gemini'

# Start a logged Claude session with an AI-generated summary
alias ac='ai-cli-log -s run claude'

# You can also omit the -s flag for basic logging
alias ag-log='ai-cli-log run gemini'

Now, you can simply run ag to start a recorded Gemini session.

Configuration

ai-cli-log loads configuration from config.json files. It prioritizes a local (project-specific) configuration over the global one.

Loading Order:

  1. Local Configuration: Looks for .ai-cli-log/config.json in the current directory first.
  2. Global Configuration: If no local configuration is found, it falls back to ~/.config/ai-cli-log/config.json.

You can create these files manually or by using the interactive setup command.

Interactive Setup (init)

The init command helps you create a configuration file. It will scan for available AI tools, guide you through creating summarizer profiles, and set a default.

  • To create a global configuration:

    ai-cli-log init

    This saves the configuration to ~/.config/ai-cli-log/config.json.

  • To create a local (project-specific) configuration:

    ai-cli-log init --local

    This saves the configuration to .ai-cli-log/config.json in the current directory.

Manual Configuration

Here is an example of a manual config.json:

{
  "summarizer": {
    "default": "gemini-pro",
    "summarizers": [
      {
        "name": "gemini-pro",
        "tool": "gemini",
        "prompt": "You are a log summarizer. Your response MUST be a valid JSON object with one key: \"summary\" (a 3-5 word, lowercase, filename-friendly phrase). Example: {\"summary\": \"refactor-database-schema\"}. The session content is:",
        "maxLines": 100
      },
      {
        "name": "ollama",
        "tool": "ollama",
        "model": "llama3",
        "prompt": "You are a log summarizer. Your response MUST be a valid JSON object with one key: \"summary\" (a 3-5 word, lowercase, filename-friendly phrase). Example: {\"summary\": \"refactor-database-schema\"}. The session content is:",
        "maxLines": 50
      },
      {
        "name": "sgpt",
        "tool": "custom",
        "prompt": "You are a log summarizer. Your response MUST be a valid JSON object with one key: \"summary\" (a 3-5 word, lowercase, filename-friendly phrase). Example: {\"summary\": \"refactor-database-schema\"}. The session content is:",
        "command": ["sgpt", "--chat", "session-summary", "\"{{prompt}}\""],
        "maxLines": 50
      }
    ]
  }
}

Features

  • Interactive Session Capture: Faithfully records complex interactive CLI sessions.
  • AI-Powered Summaries: Automatically generates descriptive filenames from session content, making logs easy to find and identify.
  • Accurate Rendering: Uses @xterm/headless to interpret ANSI escape codes, ensuring the log accurately reflects the final terminal state (spinners, progress bars, etc.).
  • Configurable: Supports different AI backends (gemini, sgpt, ollama, etc.) for generating summaries.
  • Performance-Aware: When summarizing long sessions, it intelligently samples the beginning and end of the output to ensure fast and cost-effective summary generation.
  • Plain Text Output: Saves sessions as clean plain text files.

Development Notes

This project was generated with the assistance of Google Gemini. You can review the detailed development process and interactions in the .ai-cli-log directory of the project's GitHub repository: https://github.com/alingse/ai-cli-log/tree/main/.ai-cli-log. The development prompts are primarily in Chinese.

Special thanks to Gemini for its invaluable help in the development of this tool!

TODO

  • Markdown Support: Investigate and potentially implement saving logs in Markdown format, which could include session metadata (e.g., command, timestamp, summary) in a frontmatter block.

ai-cli-log (中文说明)

无缝记录您与 AI 进行的编程对话。本命令行工具 (CLI) 能捕获您在终端中与 Gemini、Claude 等 AI 模型的交互过程，并将整个会话保存为清晰的纯文本文档，便于后续查阅和归档。

安装

npm install -g ai-cli-log

使用方法

使用 ai-cli-log 命令来包装任何您想记录的命令。核心结构是：

ai-cli-log [全局选项] run <要记录的命令> [参数...]

示例:

  • 基本日志记录: 记录与 Google Gemini CLI 的会话。

    ai-cli-log run gemini

    日志将保存到 .ai-cli-log/ 目录中。

  • AI 驱动的文件名: 使用 AI 摘要作为日志文件名。选项必须在 run 命令之前。

    # 使用默认摘要器启用摘要
ai-cli-log -s run gemini
# 或
ai-cli-log --with-summary run gemini

# 启用摘要并指定一个摘要器
ai-cli-log --by gemini-pro run gemini
# 或
ai-cli-log --summarizer gemini-pro run gemini

    这将使用您默认（或指定）的摘要器生成一个描述性的文件名，例如 gemini-20250713-153000-fix-database-connection-error.txt。

快捷别名 (Alias)

为了更快捷地启动，您可以创建 shell 别名。这样，您可以用一个简短的命令开始一个带日志记录的会话。将以下内容添加到您的 shell 配置文件中（例如 ~/.bashrc, ~/.zshrc）。

# 启动一个带 AI 摘要的 Gemini 会话
alias ag='ai-cli-log -s run gemini'

# 启动一个带 AI 摘要的 Claude 会话
alias ac='ai-cli-log -s run claude'

# 您也可以省略 -s 标志以进行基本日志记录
alias ag-log='ai-cli-log run gemini'

现在，您只需运行 ag 即可启动一个被记录的 Gemini 会话。

配置

ai-cli-log 从 config.json 文件中加载配置。它会优先使用本地（项目特定）的配置，其次是全局配置。

加载顺序:

  1. 本地配置: 首先在当前目录中查找 .ai-cli-log/config.json。
  2. 全局配置: 如果未找到本地配置，则会使用 ~/.config/ai-cli-log/config.json。

您可以通过手动或使用交互式设置命令来创建这些文件。

交互式设置 (init)

init 命令可以帮助您创建配置文件。它会扫描可用的 AI 工具，引导您完成摘要器配置的创建，并设置一个默认值。

  • 创建全局配置文件:

    ai-cli-log init

    这会将配置保存到 ~/.config/ai-cli-log/config.json。

  • 创建本地（项目特定）配置文件:

    ai-cli-log init --local

    这会将配置保存到当前目录的 .ai-cli-log/config.json 中。

手动配置

这是一个手动创建 config.json 的示例：

{
  "summarizer": {
    "default": "gemini-pro",
    "summarizers": [
      {
        "name": "gemini-pro",
        "tool": "gemini",
        "prompt": "你是一个日志摘要器。你的响应必须是一个有效的 JSON 对象，其中包含一个键：\"summary\"（一个 3-5 个单词的、小写的、文件名友好的短语）。示例：{\"summary\": \"refactor-database-schema\"}。会话内容是：",
        "maxLines": 100
      },
      {
        "name": "ollama",
        "tool": "ollama",
        "model": "llama3",
        "prompt": "你是一个日志摘要器。你的响应必须是一个有效的 JSON 对象，其中包含一个键：\"summary\"（一个 3-5 个单词的、小写的、文件名友好的短语）。示例：{\"summary\": \"refactor-database-schema\"}。会话内容是：",
        "maxLines": 50
      },
      {
        "name": "sgpt",
        "tool": "custom",
        "command": ["sgpt", "--chat", "session-summary", "\"{{prompt}}\""],
        "prompt": "你是一个日志摘要器。你的响应必须是一个有效的 JSON 对象，其中包含一个键\"summary\"（一个 3-5 个单词的、小写的、文件名友好的短语）。示例：{\"summary\": \"refactor-database-schema\"}。会话内容是：",
        "maxLines": 50
      },
      {
        "name": "my-custom-summarizer",
        "tool": "custom",
        "command": ["my-summarizer-script", "--prompt", "{{prompt}}"],
        "prompt": "You are a log summarizer. Your response MUST be a valid JSON object with one key: \"summary\" (a 3-5 word, lowercase, filename-friendly phrase). Example: {\"summary\": \"refactor-database-schema\"}. The session content is:",
        "maxLines": 200
      }
    ]
  }
}

字段说明:

  • summarizer.default (可选): 默认使用的摘要器配置名称。
  • summarizer.summarizers: 包含不同摘要器配置的数组。
    • name: 您为摘要器配置指定的唯一名称 (例如, gemini-pro, ollama, claude-opus, my-custom-summarizer)。
    • tool: 指定摘要器使用的工具类型。
      • gemini: 使用 gemini CLI 工具。
      • ollama: 使用 ollama CLI 工具。
      • claude: 使用 claude CLI 工具。
      • custom: 使用自定义命令。
    • model (可选): 对于 ollama 工具，指定要使用的模型名称 (例如, llama3)。
    • prompt: 传递给摘要器命令的提示。会话内容将作为标准输入传递。
    • maxLines (可选): 限制传递给摘要器的会话内容行数。如果会话内容超过此限制，将只采样开头和结尾的行。
    • command (可选): 对于 custom 工具，指定要执行的命令数组。会话内容会通过管道传递给该命令的 stdin。{{prompt}} 占位符将被实际的提示字符串替换。例如: ["my-summarizer-script", "--prompt", "{{prompt}}"]。
    • 重要: 摘要器的输出必须是一个有效的 JSON 对象，其中包含一个名为 summary 的键（例如，{"summary": "fix-login-bug"}）。

功能特性

  • 交互式会话捕获: 忠实地记录复杂的交互式 CLI 会话。
  • AI 驱动的摘要: 从会话内容中自动生成描述性文件名，使日志易于查找和识别。
  • 精确渲染: 使用 @xterm/headless 解释 ANSI 转义码，确保日志准确反映最终的终端状态（如加载动画、进度条等）。
  • 可配置: 支持不同的 AI 后端（gemini、sgpt、ollama 等）用于生成摘要。
  • 性能感知: 在总结长会话时，它会智能地抽样输出的开头和结尾，以确保快速且经济高效地生成摘要。
  • 纯文本输出: 将会话保存为清晰的纯文本文档。

开发说明

本项目是在 Google Gemini 的协助下生成的。您可以在本项目的 GitHub 仓库中查看详细的开发过程和交互记录，所有开发记录（中文 Prompt）都保存在 .ai-cli-log 目录中：https://github.com/alingse/ai-cli-log/tree/main/.ai-cli-log。

特别感谢 Gemini 在本项目开发过程中提供的宝贵帮助！

待办事项 (TODO)

  • Markdown 支持: 探寻并实现将日志保存为 Markdown 格式的可能性，可在文件的 frontmatter 中包含会话元数据（如：命令、时间戳、摘要等）。

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Seamlessly log your AI-powered coding conversations. This command-line interface (CLI) tool captures your terminal interactions with AI models like Gemini and Claude, saving entire sessions as clean Markdown documents for easy review and documentation.

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