IT Technical Translation

Objectives

•Translate technical documents accurately while preserving meaning
•Maintain consistency of technical terminology
•Create bilingual documentation with proper formatting
•Handle code blocks, formulas, and technical diagrams appropriately

Core Translation Rules

Technical Term Handling

On first use, add English in parentheses:

•"智能体 (agent)" not just "智能体"
•Use standard Chinese translations
•Maintain consistency throughout document

Never translate:

•Variable names, function names, class names
•Code blocks and syntax
•Mathematical formulas
•URLs, file paths, commands
•Configuration keys

Always translate:

•Explanatory text and descriptions
•Section headings and titles
•Image captions
•Error messages

For comprehensive term database: See references/terminology-database.md

Bilingual Format (Recommended)

Use sequential format for readability:

markdown

## Introduction

This is an introduction to the agent system.

这是对智能体 (agent) 系统的介绍。

---

## Getting Started

Follow these steps to begin.

按照以下步骤开始。

Quality Requirements

Before finalizing:

• Technical terms consistent
• Code blocks unchanged
• Formulas preserved
• Chinese reads naturally (not word-for-word)
• Terminology matches industry standards

Translation Workflow

•Analyze structure - Identify sections, code blocks, technical terms
•Create glossary - Build consistent term mapping for this document
•Translate section by section - Preserve structure, add Chinese below English
•Validate - Check consistency, formatting, and readability

Using LLM APIs

Recommended Free/Cheap APIs

•Gemini API: 1500 requests/day free, good quality
•DeepSeek API: ~$0.001/request, excellent Chinese
•Groq API: Free tier, ultra-fast

Translation Prompt Template

python

prompt = f"""请将以下英文技术文档翻译成中文。要求：

1. 保持技术术语的准确性
2. 专业术语后面用括号标注英文，如：智能体 (agent)
3. 翻译要流畅自然，符合中文表达习惯
4. 不要翻译代码、公式、变量名
5. 保持 Markdown 格式

英文原文：
{english_text}

中文翻译："""

Batch Translation Pattern

python

def translate_markdown(input_path, output_path):
    content = read_file(input_path)
    sections = split_by_markers(content)

    for section in sections:
        chinese = call_llm_api(section)
        append_translation(section, chinese)
        time.sleep(4)  # Rate limiting

    write_file(output_path, translated_content)

Common Patterns

Academic Paper

markdown

## Abstract | 摘要

English text...
中文翻译...

API Documentation

markdown

## `getUserById(id)` | 根据 ID 获取用户

Returns user info. | 返回用户信息。

Tutorial

markdown

## Installation | 安装

Install using npm: | 使用 npm 安装：
\`\`\`bash
npm install package
\`\`\`

Common Mistakes

❌ Translating code:

python

# Bad: 定义 函数(参数)
# Good: def function(parameter)

❌ Inconsistent terms:

code

Bad: 智能体, 代理, agent (mixed)
Good: 智能体 (agent) (consistent)

❌ English grammar in Chinese:

code

Bad: 这个函数返回一个 user 对象
Good: 这个函数返回一个用户 (user) 对象

References

For detailed examples: See references/translation-examples.md For comprehensive IT terms: See references/terminology-database.md For API integration: See references/api-integration.md