BlueMoxon

A modern platform for managing rare and valuable book collections

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Why "BlueMoxon"?

A name that honors the heritage of the printed word

Moxon

Edward Moxon (1801-1858) was the preeminent Victorian publisher who brought Tennyson, Wordsworth, Shelley, Keats, and Browning to the reading public. His Dover Street publishing house became synonymous with quality poetry editions and fine bookmaking.

"Moxon published the very poets whose works fill this collection - a fitting tribute to Victorian literary heritage."

Blue

Blue represents dependability and quiet excellence - the steady hand that preserves, catalogs, and protects. In rare book circles, "blue chip" denotes items of enduring value.

"BlueMoxon aspires to be that reliable foundation: always available, carefully organized, built to last."

122
Books Cataloged
500+
Images Stored
99.9%
Uptime
<200ms
API Response

Platform Screenshots

A visual tour of the BlueMoxon collection management system

View All Features →
Dashboard

Dashboard

Collection statistics, analytics charts, and quick access to all features at a glance.

Collection Browser

Collection Browser

Filterable grid view with search, sort, and advanced filtering by author, publisher, and binding type.

Book Detail

Book Detail

Complete metadata, valuation tracking, provenance history, and image gallery with lightbox.

Analysis View

Analysis Documents

Rich markdown analysis with full formatting, rendered beautifully alongside book details.

Analysis Editor

Analysis Editor

Markdown editor with live preview for creating and updating book valuations and assessments.

Reports

Insurance Reports

Generate insurance valuation reports with collection summaries, volume counts, and estimate ranges.

Swagger UI

API Documentation

Interactive Swagger UI with try-it-now functionality for all 57 REST endpoints.

Image Gallery

Image Gallery

CDN-delivered images with swipe gestures, thumbnails, and full-screen lightbox viewing.

End-to-End Book Collection Management

From discovery to delivery to valuation - one integrated platform

Acquisition Pipeline

Watchlist → Purchase → Delivery → On Hand - track every book through the complete acquisition lifecycle. Paste an eBay URL to instantly import listing details. Record purchase prices, order numbers, and estimated delivery dates. Know exactly what's in transit and what's arrived.

"No more spreadsheets - a purpose-built system for collectors who are serious about their acquisitions."

AI-Powered Valuations

Generate professional-grade valuations using the Napoleon Framework. Claude analyzes book images, metadata, and comparable sales to produce detailed condition assessments, market analysis, and fair market value estimates. Perfect for insurance documentation and informed buying decisions.

"Every high-value acquisition gets a thorough analysis - binding quality, condition notes, comparable sales."

Investment Scoring

Each book receives an Investment Grade (0-100) and Strategic Fit (0-7) score based on binding quality, acquisition discount, collection alignment, and more. Scores are captured at acquisition time for historical tracking. Know which pieces are your best investments.

"Data-driven collecting - understand the value proposition of every acquisition."

Reference Library

Build your target author list with priority scores for guided acquisitions. Track publisher tiers (Moxon, Pickering, Dent) and authenticated binderies (Zaehnsdorf, Rivière, Sangorski & Sutcliffe). The system knows your collection focus and scores accordingly.

"Define your collecting strategy, let the system help you execute it."

See All Features → Admin Guide →

System Architecture

Serverless, scalable, and cost-optimized for a personal collection

Infrastructure Overview

graph TB subgraph Client["Client Layer"] Browser[Browser] end subgraph CDN["CDN Layer"] CF[CloudFront
Global Edge] end subgraph App["Application Layer"] APIGW[API Gateway] Lambda[Lambda
Python 3.x] end subgraph Data["Data Layer"] Aurora[(Aurora PostgreSQL
Serverless v2)] S3_Img[S3 Images] S3_Web[S3 Static Site] Secrets[Secrets Manager] end subgraph Auth["Auth Layer"] Cognito[Cognito
User Pool] end Browser -->|HTTPS| CF CF -->|Static| S3_Web CF -->|Images| S3_Img CF -->|API| APIGW APIGW -->|Invoke| Lambda Lambda -->|Query| Aurora Lambda -->|Read/Write| S3_Img Lambda -->|Secrets| Secrets APIGW -->|Validate JWT| Cognito Browser -->|Authenticate| Cognito style CF fill:#9C27B0,color:#fff style Lambda fill:#FF9800,color:#fff style Aurora fill:#2196F3,color:#fff style Cognito fill:#4CAF50,color:#fff

AI-Powered Valuation Flow (AWS Bedrock + Claude Sonnet 4)

flowchart TB subgraph Input["Acquisition Input"] eBay[eBay Listing URL] Manual[Manual Entry] end subgraph Import["Data Import"] Parse[Parse Listing
Title, Price, Images] Archive[Wayback Archive
Snapshot Storage] end subgraph AI["AWS Bedrock AI Layer"] Bedrock[AWS Bedrock
Claude Sonnet 4] Napoleon[Napoleon Framework
Valuation Prompt] end subgraph Analysis["Valuation Output"] Condition[Condition Assessment
Binding, Pages, Foxing] Market[Market Analysis
Comparable Sales] FMV[Fair Market Value
Low/Mid/High Range] end subgraph Scoring["Investment Scoring"] Grade[Investment Grade
0-100 Score] Fit[Strategic Fit
0-7 Collection Match] end subgraph Storage["Data Layer"] DB[(Aurora PostgreSQL)] S3[S3 Images] end eBay --> Parse Manual --> Parse Parse --> Archive Parse --> Bedrock Napoleon --> Bedrock Bedrock --> Condition Bedrock --> Market Condition --> FMV Market --> FMV FMV --> Grade Grade --> Fit Fit --> DB Parse --> S3 Archive --> S3 style Bedrock fill:#FF9800,color:#fff style Napoleon fill:#8b5cf6,color:#fff style Grade fill:#10b981,color:#fff style Fit fill:#3b82f6,color:#fff style DB fill:#2196F3,color:#fff

Frontend

  • Vue 3 - Composition API
  • TypeScript - Type safety
  • Pinia - State management
  • Tailwind CSS - Utility-first styling
  • Vite - Build tooling

Backend

  • FastAPI - Async REST API
  • Python 3.x - Runtime
  • SQLAlchemy 2.0 - Async ORM
  • Pydantic v2 - Validation
  • Alembic - Migrations

Infrastructure

  • AWS Lambda - Serverless compute
  • Aurora Serverless v2 - Auto-scaling DB
  • CloudFront - Global CDN
  • Cognito - Authentication
  • Terraform - Infrastructure as code

Security

  • SAST - Bandit + Semgrep
  • Dependency Scan - pip-audit
  • Secret Scan - Gitleaks
  • JWT Auth - Cognito tokens
  • TLS 1.3 - Encryption in transit

CI/CD Pipeline

Automated testing, security scanning, and deployment on every push

gh run view - Deploy Workflow
✓ main Deploy · 19950842156 Triggered via push about 1 hour ago JOBS ✓ CI Checks / Backend Lint in 29s ✓ CI Checks / Backend Tests in 1m10s ✓ CI Checks / Backend Type Check in 36s ✓ CI Checks / SAST Security Scan in 1m24s ✓ CI Checks / Secret & Vulnerability Scan in 32s ✓ CI Checks / Frontend Build in 42s ✓ CI Checks / Frontend Lint in 28s ✓ CI Checks / Backend Validation in 24s ✓ CI Checks / Frontend Tests in 28s ✓ CI Checks / Dependency Security Scan in 38s ✓ CI Checks / Frontend Type Check in 31s ✓ CI Checks / CI Complete in 4s ✓ Build Frontend in 40s ✓ Build Lambda Package in 51s ✓ Deploy to Production in 55s ✓ Smoke Tests in 43s ✓ Create Release Tag in 6s ARTIFACTS gitleaks-results.sarif semgrep-report bandit-report frontend-dist lambda-package

Staging-First Deployment Strategy

flowchart LR subgraph Dev["Development"] Feature[Feature Branch] end subgraph PR1["PR to Staging"] CI1[CI Checks
12 parallel jobs] end subgraph Staging["Staging Environment"] Deploy1[Deploy to Staging] Test1[Smoke Tests] Validate[Manual Validation] end subgraph PR2["PR to Production"] CI2[CI Checks] end subgraph Prod["Production"] Deploy2[Deploy to Prod] Test2[Smoke Tests] Tag[Release Tag
v2025.12.10-abc123] end Feature -->|PR| CI1 CI1 -->|Merge| Deploy1 Deploy1 --> Test1 Test1 --> Validate Validate -->|PR main| CI2 CI2 -->|Merge| Deploy2 Deploy2 --> Test2 Test2 --> Tag style Feature fill:#4CAF50,color:#fff style CI1 fill:#3b82f6,color:#fff style Staging fill:#f59e0b,color:#000 style Prod fill:#9C27B0,color:#fff style Tag fill:#10b981,color:#fff

CI/CD Pipeline Detail

flowchart LR subgraph Trigger Push[Push to branch] end subgraph CI["CI Checks (Parallel)"] Lint[Lint
Ruff + ESLint] Test[Tests
pytest + vitest] Type[Type Check
mypy + vue-tsc] SAST[SAST
Bandit + Semgrep] Deps[Dependency Scan
pip-audit + npm] Secrets[Secret Scan
Trivy + Gitleaks] end subgraph Build Lambda[Lambda Package
Python 3.12] Vue[Frontend Dist
Vite build] end subgraph Deploy S3[S3 Sync] Fn[Update Lambda] CF[Invalidate CDN] end subgraph Verify Smoke[Smoke Tests] Tag[Release Tag] end Push --> Lint Push --> Test Push --> Type Push --> SAST Push --> Deps Push --> Secrets Lint --> Lambda Test --> Lambda Type --> Lambda SAST --> Lambda Deps --> Lambda Secrets --> Lambda Lint --> Vue Test --> Vue Type --> Vue Lambda --> Fn Vue --> S3 Fn --> CF S3 --> CF CF --> Smoke Smoke --> Tag style Push fill:#4CAF50,color:#fff style SAST fill:#f44336,color:#fff style Secrets fill:#f44336,color:#fff style Tag fill:#9C27B0,color:#fff
curl api.bluemoxon.com/api/v1/health/deep | jq 
{
  "status": "healthy",
  "timestamp": "2025-12-05T04:12:57.196850+00:00",
  "version": "0.1.0",
  "environment": "development",
  "total_latency_ms": 877.41,
  "checks": {
    "database": {
      "status": "healthy",
      "latency_ms": 459.8,
      "book_count": 122
    },
    "s3": {
      "status": "healthy",
      "bucket": "bluemoxon-images",
      "latency_ms": 263.81,
      "has_objects": true
    },
    "config": {
      "status": "healthy",
      "environment": "development",
      "debug": false
    }
  }
}

REST API

50+ endpoints for complete collection management

Books & Collection

Method Endpoint Description
GET /api/v1/books List all books with pagination and filtering
GET /api/v1/books/{id} Get complete book details with images and analysis
POST /api/v1/books Create a new book record
PUT /api/v1/books/{id} Update book metadata
PATCH /api/v1/books/{id}/status Update delivery status (IN_TRANSIT, ON_HAND)
POST /api/v1/books/{id}/images Upload book images to CDN
PUT /api/v1/books/{id}/analysis/raw Update markdown analysis document

Acquisitions & Scoring

Method Endpoint Description
GET /api/v1/acquisitions List acquisitions with status filter (watchlist, in_transit, on_hand)
POST /api/v1/acquisitions Create new acquisition with automatic scoring
POST /api/v1/acquisitions/parse-order Parse eBay order text to extract listing details
PATCH /api/v1/acquisitions/{id} Update acquisition status or details
POST /api/v1/acquisitions/{id}/convert Convert acquisition to collection book entry
POST /api/v1/acquisitions/{id}/archive Save listing to Wayback Machine

AI Valuations (AWS Bedrock)

Method Endpoint Description
POST /api/v1/books/{id}/valuation Generate AI valuation using Napoleon Framework (Claude Sonnet 4)
POST /api/v1/acquisitions/{id}/score Calculate Investment Grade and Strategic Fit scores

Health & Export

Method Endpoint Description
GET /api/v1/export/csv Export collection as CSV
GET /api/v1/health/deep Deep health check with all dependencies
GET /api/v1/health/version Get deployed version and build info
View API Docs (Swagger) View Source on GitHub