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feat: implement FraudShield MVP — backend API + frontend alerts
Backend (Python 3.12/FastAPI): - 5 models: Transaction, DetectionRule, FraudAlert, AuditLog, RuleSnapshot - Rule engine: 4 rule types (amount, location, time, pattern) - 11 API routes: health, auth, transactions, alerts - Sync ingestion pipeline with explanation generation - JWT auth with 3 roles (analyst, admin, senior) - Seed script with 5 default rules + 50 synthetic transactions Frontend (React 19/TypeScript/Tailwind): - Auth: login page, JWT token management, role-based routing - Alerts: queue with filters, detail panel, decision workflow - Layout: responsive sidebar, top bar, protected routes - Full TypeScript, zero ts-ignore, Tailwind CSS Build: Backend imports clean, Frontend tsc --noEmit passes, vite build produces 296KB production bundle.
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backend/pyproject.toml
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backend/pyproject.toml
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[project]
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name = "fraudshield"
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version = "0.1.0"
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description = "Motor de detecção de fraudes bancárias"
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requires-python = ">=3.12"
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dependencies = [
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"fastapi[standard]>=0.115.0",
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"uvicorn[standard]>=0.32.0",
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"sqlalchemy[asyncio]>=2.0.36",
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"asyncpg>=0.30.0",
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"alembic>=1.14.0",
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"pydantic-settings>=2.6.0",
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"redis[hiredis]>=5.2.0",
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"python-jose[cryptography]>=3.3.0",
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"passlib[bcrypt]>=1.7.4",
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"structlog>=24.4.0",
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]
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[project.optional-dependencies]
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dev = [
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"pytest>=8.3.0",
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"pytest-asyncio>=0.24.0",
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"httpx>=0.28.0",
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]
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[tool.pytest.ini_options]
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asyncio_mode = "auto"
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testpaths = ["tests"]
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