Skillget

Auto_Translator

agent
Security Audit
Warn
Health Warn
  • No license — Repository has no license file
  • Description — Repository has a description
  • Active repo — Last push 0 days ago
  • Low visibility — Only 5 GitHub stars
Code Pass
  • Code scan — Scanned 12 files during light audit, no dangerous patterns found
Permissions Pass
  • Permissions — No dangerous permissions requested
Purpose
This tool is an AI-powered agent that translates PDF files while preserving their original formatting. It splits documents into pages, uses external LLMs to process the content, and reassembles them into a final translated document.

Security Assessment
Overall risk is Medium. The tool requires an external OpenRouter API key to function, which you must provide via an environment variable or configuration file. It makes regular network requests to the OpenRouter API to send document content and receive translations. While the automated code scan found no dangerous patterns or hardcoded secrets, and the tool does not request broad system permissions, you should be aware that the contents of your PDFs will be transmitted to a third-party AI provider. No malicious execution of local shell commands was detected.

Quality Assessment
The project is actively maintained, with its most recent code push happening today. However, it has very low community visibility, currently sitting at only 5 GitHub stars. Additionally, the repository lacks a formal open-source license. This means that while the code is publicly viewable, legal usage rights, modification terms, and distribution limits are undefined. Without a license, it is technically proprietary, which may be a blocker for corporate or commercial use.

Verdict
Use with caution due to the lack of a software license and the inherent privacy considerations of sending local document contents to a third-party AI API.
SUMMARY

Agentic PDF content translator, delivers perfectly formatted documents.

README.md

auto-translation

基于多 Agent 的自动翻译工具。

English Version

安装

1. 安装 Docker

  • Windows: 使用 Docker Desktop
  • Linux: 参考 Docker 官方安装指南

2. 安装 uv

# Windows
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

# Linux / macOS
curl -LsSf https://astral.sh/uv/install.sh | sh

3. 安装依赖

uv sync

4. 配置 API Key

export OPENROUTER_API_KEY="sk-......"

启动

uv run cli.py

当前目录结构

  • core/: Agent、运行时、限流、配置、日志、提示词
  • ui/: CLI 会话与终端渲染
  • tools/: 工具定义、目录扫描、工具工厂
  • inputs/: 输入文件目录
  • workspaces/: 页面级工作区目录
  • output/: 最终产物目录
  • logs/: 每次 CLI 启动后的会话日志目录
  • fonts/: Typst 字体目录

说明

  • 调度器会在 CLI 中显示思考内容、普通输出和工具调用。
  • 执行器状态以固定行展示；运行完成后会显示“正常提交结果 / 未提交成果 / 传输报错 / 用户中断”。
  • 执行器默认工作路径是自身 workspace，但允许在项目根目录范围内跨 workspace 查看其他页面。
  • read_image / crop_image 会自动压缩上一张同类图像消息，节省 token。
  • color_sample 的 x/y 使用 1-1000 的归一化相对坐标。

配置文件

config.json 示例：

{
  "base_url": "https://openrouter.ai/api/v1",
  "api_key": "OPENROUTER_API_KEY",
  "model": "google/gemini-3.1-pro-preview",
  "scheduler_model": "google/gemini-3.1-pro-preview",
  "executor_model": "google/gemini-3.1-pro-preview",
  "concurrency": {
    "max_parallel_agents": 4,
    "max_concurrent_requests": 4,
    "qps": 1.0,
    "qpm": 30
  }
}

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