feat: add technical implementation plan
- Technology stack: Python 3.11+ FastAPI Redis - Complete project structure (src/ tests/ docs/) - All constitution gates passed - 7 research topics identified - 30 API endpoints across 6 resources - Deployment strategy defined - Ready for Phase 0 research
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specs/001-surveillance-api/plan.md
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# Implementation Plan: Geutebruck Video Surveillance API
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**Branch**: `001-surveillance-api` | **Date**: 2025-11-13 | **Spec**: [spec.md](./spec.md)
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**Input**: Feature specification from `/specs/001-surveillance-api/spec.md`
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## Summary
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Build a complete RESTful API for Geutebruck GeViScope/GeViSoft video surveillance system control, enabling developers to create custom surveillance applications without direct SDK integration. The API will provide authentication, live video streaming, PTZ camera control, real-time event notifications, recording management, and video analytics configuration through a secure, well-documented REST/WebSocket interface.
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**Technical Approach**: Python FastAPI service running on Windows, translating REST/WebSocket requests to GeViScope SDK actions through an abstraction layer, with JWT authentication, Redis caching, and auto-generated OpenAPI documentation.
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## Technical Context
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**Language/Version**: Python 3.11+
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**Primary Dependencies**:
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- FastAPI 0.104+ (async web framework with auto OpenAPI docs)
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- Pydantic 2.5+ (data validation and settings management)
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- python-jose 3.3+ (JWT token generation and validation)
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- passlib 1.7+ (password hashing with bcrypt)
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- Redis-py 5.0+ (session storage and caching)
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- python-multipart (file upload support for video exports)
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- uvicorn 0.24+ (ASGI server)
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- websockets 12.0+ (WebSocket support built into FastAPI)
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- pywin32 or comtypes (GeViScope SDK COM interface)
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**Storage**:
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- Redis 7.2+ for session management, API key caching, rate limiting counters
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- Optional: SQLite for development / PostgreSQL for production audit logs
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- GeViScope SDK manages video storage (ring buffer architecture)
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**Testing**:
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- pytest 7.4+ (test framework)
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- pytest-asyncio (async test support)
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- httpx (async HTTP client for API testing)
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- pytest-cov (coverage reporting, target 80%+)
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- pytest-mock (mocking for SDK bridge testing)
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**Target Platform**: Windows Server 2016+ or Windows 10/11 (required for GeViScope SDK)
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**Project Type**: Single project (API-only service, clients consume REST/WebSocket)
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**Performance Goals**:
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- 500 requests/second throughput under normal load
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- < 200ms response time for metadata queries (p95)
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- < 500ms for PTZ commands
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- < 100ms event notification delivery
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- Support 100+ concurrent video streams
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- Support 1000+ concurrent WebSocket connections
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**Constraints**:
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- Must run on Windows (GeViScope SDK requirement)
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- Must interface with GeViScope SDK COM/DLL objects
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- Channel-based operations (Channel ID parameter required)
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- Video streaming limited by GeViScope SDK license and hardware
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- Ring buffer architecture bounds recording capabilities
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- TLS 1.2+ required in production
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**Scale/Scope**:
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- 10-100 concurrent operators
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- 50-500 cameras per deployment
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- 30 API endpoints across 6 resource types
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- 10 WebSocket event types
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- 8 video analytics types (VMD, NPR, OBTRACK, etc.)
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## Constitution Check
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*GATE: Must pass before Phase 0 research. Re-check after Phase 1 design.*
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### ✅ Principle I: Security-First (NON-NEGOTIABLE)
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- [x] JWT authentication implemented for all protected endpoints
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- [x] TLS 1.2+ enforced (configured in deployment, not code)
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- [x] RBAC with 3 roles (viewer, operator, administrator)
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- [x] Granular per-camera permissions
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- [x] Audit logging for privileged operations
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- [x] Rate limiting on authentication endpoints
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- [x] No credentials in source code (environment variables)
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**Status**: ✅ **PASS** - Security requirements addressed in architecture
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### ✅ Principle II: RESTful API Design
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- [x] Resources represent surveillance entities (cameras, events, recordings)
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- [x] Standard HTTP methods (GET, POST, PUT, DELETE)
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- [x] URL structure `/api/v1/{resource}/{id}/{action}`
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- [x] JSON data exchange
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- [x] Proper HTTP status codes
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- [x] Stateless JWT authentication
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- [x] API versioning in URL path
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**Status**: ✅ **PASS** - REST principles followed
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### ✅ Principle III: Test-Driven Development (NON-NEGOTIABLE)
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- [x] Tests written before implementation (TDD enforced)
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- [x] 80% coverage target for SDK bridge layer
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- [x] Unit, integration, and E2E tests planned
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- [x] pytest framework selected
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- [x] CI/CD blocks on test failures
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**Status**: ✅ **PASS** - TDD workflow defined
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### ✅ Principle IV: SDK Abstraction Layer
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- [x] SDK Bridge isolates GeViScope SDK from API layer
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- [x] Translates REST → SDK Actions, SDK Events → WebSocket
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- [x] Error code translation (Windows → HTTP)
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- [x] Mockable for testing without hardware
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- [x] No direct SDK calls from route handlers
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**Status**: ✅ **PASS** - Abstraction layer designed
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### ✅ Principle V: Performance & Reliability
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- [x] Performance targets defined and measurable
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- [x] Retry logic with exponential backoff (3 attempts)
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- [x] Circuit breaker pattern for SDK communication
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- [x] Graceful degradation under load (503 vs crash)
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- [x] Health check endpoint planned
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**Status**: ✅ **PASS** - Performance and reliability addressed
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### ✅ Technical Constraints Satisfied
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- [x] Windows platform acknowledged
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- [x] Python 3.11+ selected
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- [x] FastAPI framework chosen
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- [x] Redis for caching
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- [x] Pytest for testing
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- [x] SDK integration strategy defined
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**Status**: ✅ **PASS** - All technical constraints satisfied
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### ✅ Quality Standards Met
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- [x] 80% test coverage enforced
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- [x] Code review via PR required
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- [x] Black formatter + ruff linter
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- [x] Type hints mandatory (mypy)
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- [x] OpenAPI auto-generated
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**Status**: ✅ **PASS** - Quality standards defined
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**Overall Gate Status**: ✅ **PASS** - Proceed to Phase 0 Research
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## Project Structure
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### Documentation (this feature)
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```
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specs/001-surveillance-api/
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├── spec.md # Feature specification (complete)
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├── plan.md # This file (in progress)
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├── research.md # Phase 0 output (pending)
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├── data-model.md # Phase 1 output (pending)
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├── quickstart.md # Phase 1 output (pending)
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├── contracts/ # Phase 1 output (pending)
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│ └── openapi.yaml # OpenAPI 3.0 specification
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└── tasks.md # Phase 2 output (via /speckit.tasks)
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```
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### Source Code (repository root)
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```
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geutebruck-api/
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├── src/
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│ ├── api/
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│ │ ├── v1/
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│ │ │ ├── routes/
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│ │ │ │ ├── auth.py # Authentication endpoints
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│ │ │ │ ├── cameras.py # Camera management & streaming
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│ │ │ │ ├── events.py # Event subscriptions
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│ │ │ │ ├── recordings.py # Recording management
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│ │ │ │ ├── analytics.py # Video analytics config
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│ │ │ │ └── system.py # Health, status endpoints
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│ │ │ ├── dependencies.py # Route dependencies (auth, etc.)
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│ │ │ ├── schemas.py # Pydantic request/response models
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│ │ │ └── __init__.py
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│ │ ├── middleware/
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│ │ │ ├── auth.py # JWT validation middleware
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│ │ │ ├── error_handler.py # Global exception handling
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│ │ │ ├── rate_limit.py # Rate limiting middleware
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│ │ │ └── logging.py # Request/response logging
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│ │ ├── websocket.py # WebSocket connection manager
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│ │ └── main.py # FastAPI app initialization
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│ ├── sdk/
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│ │ ├── bridge.py # Main SDK abstraction interface
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│ │ ├── actions/
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│ │ │ ├── system.py # SystemActions wrapper
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│ │ │ ├── video.py # VideoActions wrapper
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│ │ │ ├── camera.py # CameraControlActions wrapper
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│ │ │ ├── events.py # Event management wrapper
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│ │ │ └── analytics.py # Analytics actions wrapper
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│ │ ├── events/
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│ │ │ ├── dispatcher.py # Event listener and dispatcher
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│ │ │ └── translator.py # SDK Event → JSON translator
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│ │ ├── errors.py # SDK exception types
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│ │ └── connection.py # SDK connection management
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│ ├── services/
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│ │ ├── auth.py # Authentication service (JWT, passwords)
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│ │ ├── permissions.py # RBAC and authorization logic
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│ │ ├── camera.py # Camera business logic
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│ │ ├── recording.py # Recording management logic
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│ │ ├── analytics.py # Analytics configuration logic
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│ │ └── notifications.py # Event notification service
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│ ├── models/
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│ │ ├── user.py # User entity
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│ │ ├── camera.py # Camera entity
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│ │ ├── event.py # Event entity
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│ │ ├── recording.py # Recording entity
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│ │ └── session.py # Session entity
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│ ├── database/
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│ │ ├── redis.py # Redis connection and helpers
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│ │ └── audit.py # Audit log persistence (optional DB)
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│ ├── core/
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│ │ ├── config.py # Settings management (Pydantic Settings)
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│ │ ├── security.py # Password hashing, JWT utilities
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│ │ └── logging.py # Logging configuration
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│ └── utils/
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│ ├── errors.py # Custom exception classes
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│ └── validators.py # Custom validation functions
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├── tests/
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│ ├── unit/
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│ │ ├── test_auth_service.py
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│ │ ├── test_sdk_bridge.py
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│ │ ├── test_camera_service.py
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│ │ └── test_permissions.py
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│ ├── integration/
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│ │ ├── test_auth_endpoints.py
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│ │ ├── test_camera_endpoints.py
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│ │ ├── test_event_endpoints.py
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│ │ ├── test_recording_endpoints.py
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│ │ └── test_websocket.py
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│ ├── e2e/
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│ │ └── test_user_workflows.py # End-to-end scenarios
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│ ├── conftest.py # Pytest fixtures
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│ └── mocks/
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│ └── sdk_mock.py # Mock SDK for testing
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├── docs/
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│ ├── api/ # API documentation
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│ ├── deployment/ # Deployment guides
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│ └── sdk-mapping.md # GeViScope action → endpoint mapping
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├── docker/
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│ ├── Dockerfile # Windows container
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│ └── docker-compose.yml # Development environment
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├── .env.example # Environment variable template
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├── requirements.txt # Python dependencies
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├── pyproject.toml # Project metadata, tool config
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├── README.md # Project overview
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└── .gitignore
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```
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**Structure Decision**: Single project structure selected because this is an API-only service. Frontend/mobile clients will be separate projects that consume this API. The structure separates concerns into:
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- `api/` - FastAPI routes, middleware, WebSocket
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- `sdk/` - GeViScope SDK abstraction and translation
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- `services/` - Business logic layer
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- `models/` - Domain entities
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- `database/` - Data access layer
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- `core/` - Cross-cutting concerns (config, security, logging)
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- `utils/` - Shared utilities
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## Complexity Tracking
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**No constitution violations requiring justification.**
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All technical choices align with constitution principles. The selected technology stack (Python + FastAPI + Redis) directly implements the decisions made in the constitution.
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## Phase 0: Research & Technical Decisions
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**Status**: Pending - To be completed in research.md
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### Research Topics
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1. **GeViScope SDK Integration**
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- Research COM/DLL interface patterns for Python (pywin32 vs comtypes)
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- Document GeViScope SDK action categories and parameters
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- Identify SDK event notification mechanisms
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- Determine video stream URL/protocol format
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2. **Video Streaming Strategy**
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- Research options: Direct URLs vs API proxy vs WebRTC signaling
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- Evaluate bandwidth implications for 100+ concurrent streams
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- Determine authentication method for video streams
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- Document GeViScope streaming protocols
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3. **WebSocket Event Architecture**
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- Research FastAPI WebSocket best practices for 1000+ connections
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- Design event subscription patterns (by type, by channel, by user)
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- Determine connection lifecycle management (heartbeat, reconnection)
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- Plan message batching strategy for high-frequency events
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4. **Authentication & Session Management**
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- Finalize JWT token structure and claims
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- Design refresh token rotation strategy
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- Plan API key generation and storage (for service accounts)
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- Determine Redis session schema and TTL values
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5. **Performance Optimization**
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- Research async patterns for SDK I/O operations
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- Plan connection pooling strategy for SDK
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- Design caching strategy for camera metadata
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- Evaluate load balancing options (horizontal scaling)
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6. **Error Handling & Monitoring**
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- Map Windows error codes to HTTP status codes
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- Design structured logging format
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- Plan health check implementation (SDK connectivity, Redis, resource usage)
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- Identify metrics to expose (Prometheus format)
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7. **Testing Strategy**
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- Design SDK mock implementation for tests without hardware
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- Plan test data generation (sample cameras, events, recordings)
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- Determine integration test approach (test SDK instance vs mocks)
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- Document E2E test scenarios
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**Output Location**: `specs/001-surveillance-api/research.md`
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## Phase 1: Design & Contracts
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**Status**: Pending - To be completed after Phase 0 research
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### Deliverables
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1. **Data Model** (`data-model.md`)
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- Entity schemas (User, Camera, Event, Recording, Stream, etc.)
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- Validation rules
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- State transitions (e.g., Recording states: idle → recording → stopped)
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- Relationships and foreign keys
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2. **API Contracts** (`contracts/openapi.yaml`)
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- Complete OpenAPI 3.0 specification
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- All endpoints with request/response schemas
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- Authentication scheme definitions
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- WebSocket protocol documentation
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- Error response formats
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3. **Quick Start Guide** (`quickstart.md`)
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- Installation instructions
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- Configuration guide (environment variables)
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- First API call example (authentication)
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- Common use cases with curl/Python examples
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4. **Agent Context Update**
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- Run `.specify/scripts/powershell/update-agent-context.ps1 -AgentType claude`
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- Add project-specific context to Claude agent file
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### API Endpoint Overview (Design Phase)
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**Authentication** (`/api/v1/auth/`):
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- `POST /login` - Obtain JWT token
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- `POST /refresh` - Refresh access token
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- `POST /logout` - Invalidate session
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**Cameras** (`/api/v1/cameras/`):
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- `GET /` - List all cameras (filtered by permissions)
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- `GET /{id}` - Get camera details
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- `GET /{id}/stream` - Get live video stream URL/connection
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- `POST /{id}/ptz` - Send PTZ command
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- `GET /{id}/presets` - Get PTZ presets
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- `POST /{id}/presets` - Save PTZ preset
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**Events** (`/api/v1/events/`):
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- `WS /stream` - WebSocket endpoint for event subscriptions
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- `GET /` - Query event history (paginated)
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- `GET /{id}` - Get event details
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**Recordings** (`/api/v1/recordings/`):
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- `GET /` - Query recordings by channel/time range
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- `POST /{channel}/start` - Start recording
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- `POST /{channel}/stop` - Stop recording
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- `GET /{id}` - Get recording details
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- `POST /{id}/export` - Request video export
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- `GET /capacity` - Get recording capacity metrics
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**Analytics** (`/api/v1/analytics/`):
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- `GET /{channel}/config` - Get analytics configuration
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- `PUT /{channel}/config` - Update analytics configuration
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- `POST /{channel}/vmd` - Configure motion detection
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- `POST /{channel}/npr` - Configure license plate recognition
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- `POST /{channel}/obtrack` - Configure object tracking
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**System** (`/api/v1/system/`):
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- `GET /health` - Health check (no auth required)
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- `GET /status` - Detailed system status
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- `GET /metrics` - Prometheus metrics
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**Output Locations**:
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- `specs/001-surveillance-api/data-model.md`
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- `specs/001-surveillance-api/contracts/openapi.yaml`
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- `specs/001-surveillance-api/quickstart.md`
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## Phase 2: Task Breakdown
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**Not created by `/speckit.plan`** - This phase is handled by `/speckit.tasks` command
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The tasks phase will break down the implementation into concrete work items organized by:
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- Setup phase (project scaffolding, dependencies)
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- Foundational phase (SDK bridge, authentication, database)
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- User story phases (P1, P2, P3 stories as separate task groups)
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- Polish phase (documentation, optimization, security hardening)
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## Deployment Considerations
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### Development Environment
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- Python 3.11+ installed
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- GeViScope SDK installed and configured
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- Redis running locally or via Docker (Windows containers)
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- Environment variables configured (.env file)
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### Production Environment
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- Windows Server 2016+ or Windows 10/11
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- GeViScope SDK with active license
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- Redis cluster or managed instance
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- TLS certificates configured
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- Reverse proxy (nginx/IIS) for HTTPS termination
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- Environment variables via system config or key vault
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### Configuration Management
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All configuration via environment variables:
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- `SDK_CONNECTION_STRING` - GeViScope SDK connection details
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- `JWT_SECRET_KEY` - JWT signing key
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- `JWT_ALGORITHM` - Default: HS256
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- `JWT_EXPIRATION_MINUTES` - Default: 60
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- `REDIS_URL` - Redis connection URL
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- `LOG_LEVEL` - Logging level (DEBUG, INFO, WARNING, ERROR)
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- `CORS_ORIGINS` - Allowed CORS origins for web clients
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- `MAX_CONCURRENT_STREAMS` - Concurrent stream limit
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- `RATE_LIMIT_AUTH` - Auth endpoint rate limit
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### Docker Deployment
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```dockerfile
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# Windows Server Core base image
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FROM mcr.microsoft.com/windows/servercore:ltsc2022
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# Install Python 3.11
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# Install GeViScope SDK
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# Copy application code
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# Install Python dependencies
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# Expose ports 8000 (HTTP), 8001 (WebSocket)
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# Run uvicorn server
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```
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## Next Steps
|
||||
|
||||
1. ✅ Constitution defined and validated
|
||||
2. ✅ Specification created with user stories and requirements
|
||||
3. ✅ Implementation plan created (this document)
|
||||
4. ⏭️ **Execute `/speckit.plan` Phase 0**: Generate research.md
|
||||
5. ⏭️ **Execute `/speckit.plan` Phase 1**: Generate data-model.md, contracts/, quickstart.md
|
||||
6. ⏭️ **Execute `/speckit.tasks`**: Break down into actionable task list
|
||||
7. ⏭️ **Execute `/speckit.implement`**: Begin TDD implementation
|
||||
|
||||
---
|
||||
|
||||
**Plan Status**: ✅ Technical plan complete, ready for Phase 0 research
|
||||
**Constitution Compliance**: ✅ All gates passed
|
||||
**Next Command**: Continue with research phase to resolve implementation details
|
||||
Reference in New Issue
Block a user