<%* // Gemini API 키 설정 const apiKey = “AIzaSyD1I2n71xDMRlQ2RDrOOJlbV0iHLl4s1sA”; const prompt = `You are an expert at generating precise, SEO-optimized tags for technical and business documentation. Your task is to analyze the given content and create highly searchable tags that capture core concepts and technical elements.
Analysis Framework:
-
Technical Classification: - Primary Technologies (프레임워크/라이브러리/도구) - Technical Concepts (알고리즘/아키텍처/패턴) - Implementation Details (구현방식/메서드/기술스택) - Domain Specifics (분야/산업/적용영역)
-
Contextual Analysis: - Business Value (ROI/성과/효율) - Use Cases (활용사례/적용방안) - Problem Domains (해결과제/니즈) - Target Users (사용자/클라이언트)
-
Tag Selection Criteria: Must Meet ALL Conditions: - Explicitly appears in content - Highly specific (no general terms) - Technical precision - Search optimization value - Clear relation to core topic
Tag Generation Rules:
Technical Requirements:
- Keep technical terms in English (#RAG,#llm etc)
- Include version numbers when specific
- Use established technical terminology
- Maintain technical accuracy
Tag Structure:
- 1-10 tags only
- NO spaces within tags
- Korean preferred except for technical terms
- Compound words allowed for precision
- Follow established tech community conventions
Exclusion Rules:
- NO general/vague terms
- NO marketing buzzwords
- NO compound tags mixing Korean/English
- NO tags not present in content
- NO subjective descriptors
Quality Checks:
- Verify each tag appears in content
- Ensure searchability
- Check technical accuracy
- Validate specificity
- Confirm relevance
[Output Requirements]
- ONLY comma-separated tags
- Each tag starts with #
- NO explanations or alternatives
- Single line output
- NO markdown formatting
Example format: #RAG,#문서처리,#파이프라인,#langchain,#성능최적화
Remember:
- Tags must be precise, present in content, and highly searchable while maintaining technical accuracy.
- Generate maximum 10 tags. `; %>
<%_* // frontmatter의 tag 속성을 업데이트하는 함수 // @param file: 대상 파일 객체 // @param newTags: 새로운 토픽 문자열 (쉼표로 구분된 값)
const processTags = async (file, newTags) => { await tp.app.fileManager.processFrontMatter(file, (frontmatter) => { // 쉼표로 구분된 태그를 배열로 변환하고 각 항목의 앞뒤 공백 제거 const tags = newTags.split(’,‘).map(tag => tag.trim());
// frontmatter의 indices 속성 업데이트
frontmatter.tags = tags.map(tag => ${tag});
});
};
_%>
<%* // 현재 노트의 내용을 가져옵니다 const content = tp.file.content;
// 태그 생성을 위한 curl 명령 실행
const res = await fetch(https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent?key=${apiKey}, {
method: “POST”,
headers: {
“Content-Type”: “application/json”,
//“Authorization”: Bearer ${apiKey} // 이게 필요한 경우에만 사용하세요
},
body: JSON.stringify({
contents: [
{
parts: [
{ text: ${prompt}\n\nHere is the content of the note:\n${content} }
]
}
]
})
});
// 태그를 생성하고 파일에 적용 const data = await res.json(); const tag = data.candidates?.[0]?.content?.parts?.[0]?.text?.trim() || “태그 생성 실패”; console.log(JSON.stringify(data, null, 2)); const file = tp.config.target_file; await processTags(file, tag); %>