Kyros Dashboard

A comprehensive AI-powered content generation and scheduling platform with a modern React frontend and robust FastAPI backend. The dashboard provides tools for content repurposing, automated scheduling, and extensible tool management.

🚀 Features

Core Functionality

• Modern Dashboard: Clean, responsive UI with dark theme and professional design
• Content Generation: Transform source content into multiple channel formats (LinkedIn, Twitter, Newsletter, Blog)
• Variant Management: Edit, accept, copy, and export generated content variants
• Job Monitoring: Track and manage content repurposing jobs with real-time status updates
• Preset Management: Create and manage custom content generation presets

Advanced Features

• Scheduler System: Automated job scheduling with recurrence patterns and timezone support
• Tool Registry: Extensible plugin system for custom tools and integrations
• Authentication: Secure JWT-based authentication with user management
• Rate Limiting: Built-in rate limiting and quota management
• Database Integration: PostgreSQL with Alembic migrations
• Real-time Updates: Live KPI tracking and job status updates
• Error Handling: Comprehensive error handling with Sentry integration

🛠️ Tech Stack

Frontend: React 18, Vite (port 3001), Tailwind CSS, TanStack Query, TypeScript Backend: FastAPI, PostgreSQL, Redis, Celery, JWT Auth (Poetry-managed) Testing: Playwright, Vitest, pytest Deployment: GitHub Actions, Vercel, Railway/Render

📁 Project Structure

kyros-dashboard/
├── frontend/          # React app (pages, components, hooks)
├── backend/           # FastAPI app (core, scheduler, tools, utils)
├── docs/              # Documentation
└── scripts/           # Development scripts

🚀 Getting Started

Prerequisites

• Node.js 18+ and npm
• Python 3.12+
• PostgreSQL (for production)
• Redis (for caching and rate limiting)

Quick Start

The easiest way to get started is using the provided scripts:

# Start both frontend and backend
./scripts/start-both.sh

# Or start them separately
./scripts/start-frontend.sh  # Terminal 1
./scripts/start-backend.sh   # Terminal 2

Manual Setup

Frontend (port 3001):

cd frontend && npm install && npm run dev

Backend (Poetry):

cd backend
poetry install
cp env.example .env  # Edit with your config
poetry run alembic upgrade head
poetry run uvicorn main:app --reload --port 8000

Environment Variables

Frontend: VITE_API_BASE_URL=http://localhost:8000 Backend: See backend/env.example for required variables (database, Redis, OpenAI, JWT, etc.)

📱 Key Features

• Dashboard - KPIs, recent jobs, quick content generation
• Studio - Content repurposing with channel-specific formatting
• Scheduler - Automated job scheduling with recurrence patterns
• Jobs - Job monitoring, history, and management
• Settings - Presets, configuration, and tool management

🔌 API

RESTful API with endpoints for authentication, content generation, scheduling, and tool management. See http://localhost:8000/docs for interactive API documentation.

🧪 Testing

# Run all tests (backend, frontend, E2E)
./scripts/run-tests.sh

# Backend (Poetry):
cd backend && poetry run pytest -q

# Frontend (Vitest + Playwright on port 3001):
cd frontend && npm run test && npm run test:e2e

🧠 MCP Servers & Collaboration

This repo ships MCP servers under mcp/ and a collaboration model under collaboration/.

• Install servers locally:
  • python -m pip install -e mcp
  • Start (recommended): python -m mcp.kyros_collab_server (collaboration), python -m mcp.linear_server, python -m mcp.railway_server, python -m mcp.vercel_server, python -m mcp.coderabbit_server
• Import CodeRabbit/GitHub PR feedback to tasks:
  • python scripts/import_coderabbit_feedback.py --owner ORG --repo REPO --pr 123 --assign
    • Creates tasks from review changes/PR comments, links PR number, and (optionally) auto‑assigns.
• Link external IDs to tasks via collab RPC:
  • collab.link_external({"id": "task-001", "provider": "linear", "value": "LIN-123"})
  • collab.link_external({"id": "task-001", "provider": "vercel", "key": "deployment", "value": "dpl_..."})

See mcp/README.md and agents.md for details.

🚀 Deployment

Automatic: GitHub Actions deploys on merge to main Manual: Frontend (Vercel), Backend (Railway/Render) Setup: See Deployment Guide

📝 Status

Production Ready with authentication, database integration, and comprehensive testing. Extensible plugin-based architecture with CI/CD pipeline.

🤝 Contributing

1. Fork the repository
2. Create a feature branch: git checkout -b feature/amazing-feature [[memory:7928543]]
3. Commit frequently with clear messages [[memory:7940605]]
4. Open a Pull Request targeting main

Requirements: All code must pass tests, linting, and security checks. PRs require code review approval.

📄 License

This project is part of the kyros Repurposer suite. All rights reserved.

📚 Documentation

• Quick Start - Get running in 2 minutes
• Deployment - Complete setup guide
• Testing - Testing strategies
• User Guide - End-user documentation
• Architect Prompt - AI agent planning prompt
• Governance - Development process and guidelines