feat: 대역폭 추정 및 DAU 표시 기능 추가
- 동시접속자 기반 월간 대역폭 자동 추정 - DAU(일일활성사용자) 추정치 표시 (동접 × 10-14) - 대역폭 기반 Linode/Vultr 자동 선택 로직 - 비용 분석에 대역폭 비용 포함 - 지역 미선택시 서울/도쿄/오사카/싱가포르 기본 표시 - 지역별 서버 분리 표시 (GROUP BY instance + region) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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kappa
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CLAUDE.md
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# CLAUDE.md
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This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
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## Project Overview
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Cloudflare Worker-based AI server recommendation service. Uses Workers AI (Llama 3.1 8B), D1 database, and VPS benchmark data to recommend cost-effective servers based on natural language requirements.
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**Production URL**: `https://server-recommend.kappa-d8e.workers.dev`
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## Commands
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```bash
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# Development
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npm run dev # Start local development server (wrangler dev)
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npm run deploy # Deploy to Cloudflare Workers
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npm run typecheck # TypeScript type checking
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# Database operations (D1)
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npx wrangler d1 execute cloud-instances-db --file=schema.sql # Apply schema
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npx wrangler d1 execute cloud-instances-db --file=seed.sql # Seed data
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npx wrangler d1 execute cloud-instances-db --command="SELECT ..." # Ad-hoc queries
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# View logs
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npx wrangler tail
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```
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## Architecture
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```
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src/index.ts (single file Worker)
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├── handleHealth() GET /api/health
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├── handleGetServers() GET /api/servers - List servers with filtering
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└── handleRecommend() POST /api/recommend - AI-powered recommendations
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├── validateRecommendRequest()
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├── queryCandidateServers() → D1: instance_types + providers + pricing + regions
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├── queryBenchmarkData() → D1: benchmark_results + benchmark_types
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├── queryVPSBenchmarks() → D1: vps_benchmarks (Geekbench 6)
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└── getAIRecommendations() → Workers AI (Llama 3.1 8B)
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```
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### Key Data Flow
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1. User sends natural language request (`tech_stack`, `expected_users`, `use_case`, `region_preference`)
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2. `queryCandidateServers()` finds matching servers with **flexible region matching** (supports country codes, names, city names)
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3. `queryVPSBenchmarks()` retrieves Geekbench 6 scores, **prioritizing same provider match**
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4. AI analyzes and returns 3 tiers: Budget, Balanced, Premium
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### D1 Database Tables (cloud-instances-db)
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- `providers` - Cloud providers (50+)
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- `instance_types` - Server specifications
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- `pricing` - Regional pricing
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- `regions` - Geographic regions
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- `vps_benchmarks` - Geekbench 6 benchmark data (269 records, manually seeded)
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- `benchmark_results` / `benchmark_types` / `processors` - Phoronix benchmark data
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## Key Implementation Details
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### Flexible Region Matching (`queryCandidateServers`)
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Region matching supports multiple input formats:
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```sql
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LOWER(r.region_code) = ? OR
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LOWER(r.region_code) LIKE ? OR
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LOWER(r.region_name) LIKE ? OR
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LOWER(r.country_code) = ?
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```
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Valid inputs: `"korea"`, `"KR"`, `"seoul"`, `"ap-northeast-2"`
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### Provider-Priority Benchmark Matching (`queryVPSBenchmarks`)
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1. First tries exact provider match
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2. Falls back to similar spec match from any provider
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3. Used to attach real benchmark data to recommendations
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### AI Prompt Strategy
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- System prompt emphasizes cost-efficiency and minimum viable specs
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- Tech stack → resource guidelines (e.g., "Nginx: 1 vCPU per 1000 users")
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- Scoring: Cost efficiency (40%) + Capacity fit (30%) + Scalability (30%)
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- Budget option should score highest if viable
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## Bindings (wrangler.toml)
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```toml
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[ai]
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binding = "AI"
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[[d1_databases]]
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binding = "DB"
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database_name = "cloud-instances-db"
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database_id = "bbcb472d-b25e-4e48-b6ea-112f9fffb4a8"
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# KV Cache (optional, not configured)
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# binding = "CACHE"
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```
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## Testing
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```bash
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# Health check
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curl https://server-recommend.kappa-d8e.workers.dev/api/health
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# Recommendation
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curl -X POST https://server-recommend.kappa-d8e.workers.dev/api/recommend \
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-H "Content-Type: application/json" \
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-d '{
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"tech_stack": ["php", "mysql"],
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"expected_users": 1000,
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"use_case": "community forum",
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"region_preference": ["korea"]
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}'
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```
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## Known Limitations
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- AI recommendations may be inaccurate for specialized workloads (game servers, Minecraft)
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- KV cache is not currently configured (CACHE binding commented out in wrangler.toml)
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- `src/types.ts` contains legacy type definitions (not actively used, actual types inline in index.ts)
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