85bf1341f3
Frontend Enhancements: - Complete React TypeScript frontend with modern UI components - Distributed workflows management interface with real-time updates - Socket.IO integration for live agent status monitoring - Agent management dashboard with cluster visualization - Project management interface with metrics and task tracking - Responsive design with proper error handling and loading states Backend Infrastructure: - Distributed coordinator for multi-agent workflow orchestration - Cluster management API with comprehensive agent operations - Enhanced database models for agents and projects - Project service for filesystem-based project discovery - Performance monitoring and metrics collection - Comprehensive API documentation and error handling Documentation: - Complete distributed development guide (README_DISTRIBUTED.md) - Comprehensive development report with architecture insights - System configuration templates and deployment guides The platform now provides a complete web interface for managing the distributed AI cluster with real-time monitoring, workflow orchestration, and agent coordination capabilities. 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
25 lines
891 B
Python
25 lines
891 B
Python
from sqlalchemy import Column, Integer, String, DateTime, Text
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from sqlalchemy.sql import func
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from ..core.database import Base
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class Project(Base):
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__tablename__ = "projects"
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id = Column(Integer, primary_key=True, index=True)
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name = Column(String, unique=True, index=True, nullable=False)
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description = Column(Text, nullable=True)
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status = Column(String, default="active") # e.g., active, completed, archived
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created_at = Column(DateTime(timezone=True), server_default=func.now())
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updated_at = Column(DateTime(timezone=True), onupdate=func.now())
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# You might also need Pydantic models for request/response validation
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# from pydantic import BaseModel
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# class ProjectCreate(BaseModel):
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# name: str
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# description: str | None = None
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# class ProjectMetrics(BaseModel):
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# total_tasks: int
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# completed_tasks: int
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# # Add other metrics as needed |