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---
description: Install dashboard dependencies: Step-by-step tutorial with examples, best practices, and common patterns. Learn by doing with hands-on examples.
---

Agent Coordination Dashboard

Status: ✅ Implemented and Ready to Use

Overview

The Agent Coordination Dashboard is a web-based monitoring interface that provides real-time visualization of all 6 agent coordination patterns:

  1. Agent Heartbeat Tracking (Pattern 1) - Monitor active agents and their status
  2. Coordination Signals (Pattern 2) - View inter-agent communication
  3. State Synchronization (Pattern 3) - Track shared state (via agents)
  4. Real-Time Event Streaming (Pattern 4) - Monitor event streams
  5. Human Approval Gates (Pattern 5) - Manage approval requests
  6. Agent-to-LLM Feedback Loop (Pattern 6) - Analyze quality metrics

Features

  • Real-time Updates: Auto-refresh every 5 seconds
  • System Health Monitoring: Redis connection status and agent count
  • Approval Management: Approve/reject workflow requests from the UI
  • Quality Analytics: View performance metrics and identify underperforming stages
  • Event Stream Viewer: Monitor real-time events across the system
  • Responsive Design: Works on desktop and mobile

Installation

Dependencies

The dashboard requires FastAPI and uvicorn for the web server:

# Install dashboard dependencies
pip install fastapi uvicorn[standard]

# Optional: For WebSocket support
pip install websockets

Alternative: If you prefer Flask over FastAPI, you can create a Flask version by adapting the endpoints in src/empathy_os/dashboard/app.py.

Core Requirements

The dashboard also requires:

  • Redis 5.0+ (for data storage - patterns gracefully degrade without it)
  • Python 3.10+
  • Empathy Framework with telemetry modules

Quick Start

1. Start Redis (if not already running)

# Option 1: Using empathy CLI
empathy memory start

# Option 2: Direct Redis
redis-server

2. Run the Dashboard

from empathy_os.dashboard import run_dashboard

# Start dashboard on http://localhost:8000
run_dashboard()

# Or specify host/port
run_dashboard(host="0.0.0.0", port=8080)

3. Open in Browser

Navigate to: http://localhost:8000

Usage Examples

Running from Command Line

# Navigate to framework directory
cd /path/to/empathy-framework

# Start dashboard
python -m empathy_os.dashboard.app

Running as Background Service

import uvicorn
from empathy_os.dashboard import app

# Run as daemon
uvicorn.run(app, host="0.0.0.0", port=8000, reload=False)

Generating Test Data

To populate the dashboard with test data for demonstration:

from empathy_os.telemetry import (
    HeartbeatCoordinator,
    CoordinationSignals,
    EventStreamer,
    ApprovalGate,
    FeedbackLoop
)
from empathy_os.telemetry.feedback_loop import ModelTier
import time

# Create test heartbeat
coordinator = HeartbeatCoordinator(agent_id="test-agent-1")
coordinator.report(
    status="running",
    progress=0.75,
    current_task="Processing workflow stage 2",
    metadata={"workflow": "code-review"}
)

# Create test signal
signals = CoordinationSignals(agent_id="agent-1")
signals.signal(
    signal_type="status_update",
    source_agent="agent-1",
    target_agent="agent-2",
    payload={"message": "Task completed"}
)

# Create test event
streamer = EventStreamer()
streamer.publish_event(
    event_type="workflow_progress",
    data={"workflow": "test", "stage": "analysis", "progress": 0.5},
    source="test-workflow"
)

# Create test approval request
gate = ApprovalGate(agent_id="deployment-workflow")
# This will block, so run in background or with short timeout
# approval = gate.request_approval(
#     approval_type="deploy_to_staging",
#     context={"version": "1.0.0"},
#     timeout=60.0
# )

# Create test quality feedback
feedback = FeedbackLoop()
feedback.record_feedback(
    workflow_name="code-review",
    stage_name="analysis",
    tier=ModelTier.CHEAP,
    quality_score=0.85,
    metadata={"tokens": 150}
)

API Endpoints

The dashboard exposes RESTful APIs for programmatic access:

Health & System

  • GET /api/health - System health status
  • GET / - Dashboard UI (HTML)
  • GET /docs - Interactive API documentation (FastAPI)

Pattern 1: Agents

  • GET /api/agents - List all active agents
  • GET /api/agents/{agent_id} - Get specific agent status

Pattern 2: Signals

  • GET /api/signals?limit=50 - Get recent coordination signals
  • GET /api/signals/{agent_id}?limit=20 - Get signals for specific agent

Pattern 4: Events

  • GET /api/events?event_type={type}&limit=100 - Get recent events
    • Optional event_type filter
    • Default limit: 100

Pattern 5: Approvals

  • GET /api/approvals - Get pending approval requests
  • POST /api/approvals/{request_id}/approve - Approve request
  • POST /api/approvals/{request_id}/reject - Reject request

Pattern 6: Quality Feedback

  • GET /api/feedback/workflows - Get quality metrics for all workflows
  • GET /api/feedback/underperforming?threshold=0.7 - Get underperforming stages

WebSocket (Future)

  • WS /ws - Real-time updates stream (partially implemented)

Dashboard Panels

1. System Stats (Top Bar)

  • Active Agents: Count of agents with recent heartbeats
  • Pending Approvals: Count of requests awaiting human decision
  • Recent Signals: Number of coordination signals in last 5 minutes
  • Event Streams: Number of recent events

2. Active Agents Panel

  • Agent ID and current status (running/idle/error)
  • Current task description
  • Progress bar (0-100%)
  • Last seen timestamp

Color Coding:

  • 🟢 Green: Running normally
  • 🟡 Yellow: Idle or waiting
  • 🔴 Red: Error state

3. Approval Requests Panel

  • Approval type (deploy/delete/refactor/etc.)
  • Requesting agent ID
  • Context information
  • Approve/Reject buttons

Actions:

  • Click "✓ Approve" to approve request
  • Click "✗ Reject" to reject request

4. Quality Metrics Panel

  • Workflow/stage name
  • Tier (cheap/capable/premium)
  • Average quality score (0-100%)
  • Sample count
  • Trend indicator (📈📉➡️)

Color Coding:

  • 🟢 Green: ≥80% quality (good)
  • 🟡 Yellow: 60-79% quality (warning)
  • 🔴 Red: <60% quality (poor)

5. Recent Signals Panel

  • Signal type
  • Source → Target agent route
  • Timestamp (relative)

6. Event Stream Panel

  • Event type
  • Source
  • Timestamp (relative)

7. Underperforming Stages Panel

  • Workflow/stage identification
  • Average quality score
  • Sample count
  • Quality range (min-max)

Note: Only shows stages below the quality threshold (default: 70%)

Configuration

Auto-Refresh Interval

Edit src/empathy_os/dashboard/static/app.js:

class Dashboard {
    constructor() {
        this.refreshInterval = 5000; // Change to desired ms (e.g., 10000 for 10s)
        // ...
    }
}

Server Settings

from empathy_os.dashboard import run_dashboard

# Development mode (auto-reload on code changes)
run_dashboard(host="127.0.0.1", port=8000)

# Production mode (bind to all interfaces)
run_dashboard(host="0.0.0.0", port=80)

# Custom port
run_dashboard(port=8080)

CORS (Cross-Origin Requests)

If accessing dashboard from different domain, enable CORS in app.py:

from fastapi.middleware.cors import CORSMiddleware

app.add_middleware(
    CORSMiddleware,
    allow_origins=["http://localhost:3000"],  # Your frontend URL
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

Deployment

Development

python -m empathy_os.dashboard.app

Production with Uvicorn

uvicorn empathy_os.dashboard.app:app --host 0.0.0.0 --port 8000 --workers 4

Docker (Example)

FROM python:3.10-slim

WORKDIR /app

# Install dependencies
COPY requirements.txt .
RUN pip install -r requirements.txt

# Copy application
COPY src/ ./src/

# Expose port
EXPOSE 8000

# Run dashboard
CMD ["uvicorn", "empathy_os.dashboard.app:app", "--host", "0.0.0.0", "--port", "8000"]

Nginx Reverse Proxy (Example)

server {
    listen 80;
    server_name dashboard.example.com;

    location / {
        proxy_pass http://localhost:8000;
        proxy_http_version 1.1;
        proxy_set_header Upgrade $http_upgrade;
        proxy_set_header Connection "upgrade";
        proxy_set_header Host $host;
        proxy_set_header X-Real-IP $remote_addr;
    }
}

Troubleshooting

Dashboard shows "No active agents"

Cause: No agents are sending heartbeats

Solution:

from empathy_os.telemetry import HeartbeatCoordinator

# Start sending heartbeats
coordinator = HeartbeatCoordinator(agent_id="my-agent")
coordinator.report(status="running", progress=0.5, current_task="Testing")

Dashboard shows "System Degraded"

Cause: Redis is not running

Solution:

# Start Redis
redis-server

# Or via empathy CLI
empathy memory start

"Connection Failed" error

Cause: Dashboard server not running or wrong URL

Solution:

  • Ensure dashboard is running: python -m empathy_os.dashboard.app
  • Check URL: http://localhost:8000 (not HTTPS)
  • Check firewall settings

Approval buttons don't work

Cause: API endpoint not reachable or network error

Solution:

  • Check browser console for errors (F12 → Console)
  • Verify approval request still exists (not timed out)
  • Check Redis connection

Security Considerations

⚠️ Important: The dashboard currently has no authentication. For production use:

  1. Add Authentication:

    from fastapi import Depends, HTTPException, status
from fastapi.security import HTTPBasic, HTTPBasicCredentials

security = HTTPBasic()

def verify_credentials(credentials: HTTPBasicCredentials = Depends(security)):
    if credentials.username != "admin" or credentials.password != "secret":
        raise HTTPException(status_code=401, detail="Invalid credentials")
    return credentials.username

@app.get("/api/agents")
async def get_agents(username: str = Depends(verify_credentials)):
    # ... endpoint logic

  2. Use HTTPS: Deploy behind reverse proxy with SSL/TLS

  3. Restrict Access: Firewall rules or VPN-only access

  4. Rate Limiting: Prevent abuse of approval endpoints

Performance

Metrics (tested on M1 Mac):

  • Page load time: <2s
  • API response time: <50ms per endpoint
  • Auto-refresh overhead: <100ms
  • Memory usage: ~50MB (dashboard process)
  • CPU usage: <5% (idle), <15% (during refresh)

Optimization Tips:

  • Reduce refresh interval for lower CPU usage
  • Limit API result counts for faster queries
  • Use Redis connection pooling for high concurrency

Future Enhancements

Planned features:

  • Full WebSocket implementation for push updates
  • Authentication and user management
  • Historical data visualization (charts/graphs)
  • Alerting and notifications
  • Export reports (PDF/CSV)
  • Dark/light theme toggle
  • Custom dashboard layouts
  • Multi-workspace support

Status: ✅ Ready for Use

Dependencies: FastAPI, uvicorn, Redis 5.0+

Documentation: Complete

Demo: Run python -m empathy_os.dashboard.app and visit http://localhost:8000