32 lines
1.6 KiB
Markdown
32 lines
1.6 KiB
Markdown
# Inventory PWA System Implementation Plan
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This document outlines the technical architecture for the unified Inventory System (FastAPI + PWA).
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## Proposed Architecture
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### 1. Backend Server (Linux / Docker)
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- **Framework:** Python + FastAPI
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- **Database:** SQLite (SQLAlchemy ORM)
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- **Key Modules:**
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- `Items / Interventions`: Standard CRUD logic.
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- `Audit`: Every payload that mutates data writes an immutable log row.
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- `AI-OCR`: Endpoint integrating Google Gemini Vision API (via Google AI Studio key) for complex label extraction onboarding.
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### 2. Unified Web Application (PWA)
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- **Framework:** React + Next.js (or equivalent).
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- **Offline Engine:** Service Workers, IndexedDB local storage map.
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- **Desktop Mode:** Full width dashboard, management, and settings.
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- **Mobile Mode (Browser / Add to Homescreen):** Dedicated full-screen scanner using `html5-qrcode`.
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### 3. AI Cost Strategy
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- **Routine Scans (Check-ins/Outs):** Client-side HTML5 barcode scanner. **Cost: $0.**
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- **Label Scanning (New Item):** Proxies a request to the Gemini API to parse the SFP label into JSON template fields.
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## Implementation Phases
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- **Phase 1: Database & Backend Foundation** - SQLite schemas, User management, and Python API structures.
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- **Phase 2: Core Inventory API** - Endpoints to Add/Remove items, offline sync-merge logic, Audit triggers.
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- **Phase 3: The PWA Frontend** - PWA manifest, offline capabilities, UI scaffolding for Desktop/Mobile.
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- **Phase 4: Client-Side Scanning** - Integration of local JS barcode reading for routine stock scanning.
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- **Phase 5: Gemini AI Vision Integration** - Server-side Gemini API integration and the text-mapping frontend view.
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