cd28f94e8f
Major Features: ✅ JWT Bearer Token authentication system with secure token management ✅ API key generation and management with scoped permissions ✅ Complete user management (registration, login, logout, password change) ✅ Frontend authentication components and context integration Backend Architecture Improvements: ✅ CORS configuration via environment variables (CORS_ORIGINS) ✅ Dependency injection pattern for unified coordinator ✅ Database schema fixes with UUID support and SQLAlchemy compliance ✅ Task persistence replaced in-memory storage with database-backed system ✅ Service separation following Single Responsibility Principle ✅ Fixed SQLAlchemy metadata column naming conflicts Infrastructure & Testing: ✅ Comprehensive Jest unit testing and Playwright e2e testing infrastructure ✅ GitHub Actions CI/CD pipeline integration ✅ Enhanced API clients matching PROJECT_PLAN.md specifications ✅ Docker Swarm deployment with proper networking and service connectivity Database & Security: ✅ UUID-based user models with proper validation ✅ Unified database schema with authentication tables ✅ Token blacklisting and refresh token management ✅ Secure password hashing with bcrypt ✅ API key scoping and permissions system API Enhancements: ✅ Authentication endpoints (/api/auth/*) ✅ Task management with database persistence ✅ Enhanced monitoring and health check endpoints ✅ Comprehensive error handling and validation Deployment: ✅ Successfully deployed to Docker Swarm at https://hive.home.deepblack.cloud ✅ All services operational with proper networking ✅ Environment-based configuration support 🛠️ Technical Debt Resolved: - Fixed global coordinator instances with proper dependency injection - Replaced hardcoded CORS origins with environment variables - Unified User model schema conflicts across authentication system - Implemented database persistence for critical task storage - Created comprehensive testing infrastructure This release transforms Hive from a development prototype into a production-ready distributed AI orchestration platform with enterprise-grade authentication, proper architectural patterns, and robust deployment infrastructure. 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
41 lines
1.5 KiB
Python
41 lines
1.5 KiB
Python
"""
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Task model for SQLAlchemy ORM
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"""
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from sqlalchemy import Column, String, Text, Integer, DateTime, ForeignKey, UUID as SqlUUID
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from sqlalchemy.dialects.postgresql import JSONB
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from sqlalchemy.sql import func
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from sqlalchemy.orm import relationship
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from ..core.database import Base
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import uuid
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class Task(Base):
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__tablename__ = "tasks"
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# Primary identification
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id = Column(SqlUUID(as_uuid=True), primary_key=True, index=True, default=uuid.uuid4)
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# Task details
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title = Column(String(255), nullable=False)
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description = Column(Text)
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priority = Column(Integer, default=5)
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status = Column(String(50), default='pending')
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# Relationships
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assigned_agent_id = Column(String(255), ForeignKey("agents.id"), nullable=True)
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workflow_id = Column(SqlUUID(as_uuid=True), ForeignKey("workflows.id"), nullable=True)
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execution_id = Column(SqlUUID(as_uuid=True), ForeignKey("executions.id"), nullable=True)
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# Task metadata (includes context and payload)
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task_metadata = Column("metadata", JSONB, nullable=True)
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# Timestamps
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created_at = Column(DateTime(timezone=True), server_default=func.now())
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started_at = Column(DateTime(timezone=True), nullable=True)
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completed_at = Column(DateTime(timezone=True), nullable=True)
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# Relationships
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assigned_agent = relationship("Agent", back_populates="tasks")
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workflow = relationship("Workflow", back_populates="tasks")
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execution = relationship("Execution", back_populates="tasks") |