feat(core-api): add AI stats widget with proxy endpoints
Implements Phase 2 of AI performance monitoring - creating a visual
dashboard widget for Organizr to display real-time AI metrics.
New Components:
- src/clients/ai_client.py: HTTP client for Core-AI service
- Async HTTP requests to core-ai:8086
- Fetches metrics, errors, and tool failures
- Health check and metrics reset operations
- src/controllers/ai_controller.py: Proxy controller for AI metrics
- GET /ai/health - Core-AI health check
- GET /ai/metrics - Comprehensive performance metrics (proxied)
- GET /ai/metrics/errors - Recent request errors (proxied)
- GET /ai/metrics/tool-failures - Tool execution failures (proxied)
- POST /ai/metrics/reset - Reset all metrics (admin)
- static/widgets/ai-stats.html: Performance dashboard widget
- 4-panel grid layout: Agent, Tools, Memory, Health
- Real-time metrics with 10-second auto-refresh
- Color-coded performance indicators (excellent/good/warning/critical)
- Response time thresholds: <1s excellent, <3s good, <10s warning
- Success rate thresholds: >99% excellent, >95% good, >90% warning
- Top 5 tools display with call counts and success rates
- Transparent background for Organizr dark theme
- Responsive design with mobile support
Configuration:
- src/config.py: Added core_ai_base_url setting
- src/main.py: Registered ai_router for /ai/* endpoints
Architecture:
┌─────────────────────────────────────────────┐
│ Browser (Organizr iFrame) │
│ ↓ Fetches /ai/metrics │
└─────────────────────────────────────────────┘
↓
┌─────────────────────────────────────────────┐
│ core-api:8083 (api.schweitz.net) │
│ - Serves widget HTML │
│ - Proxies metrics requests │
└─────────────────────────────────────────────┘
↓
┌─────────────────────────────────────────────┐
│ core-ai:8086 (internal) │
│ - Collects metrics │
│ - Returns JSON data │
└─────────────────────────────────────────────┘
Benefits:
- External access via api.schweitz.net (proxy approach)
- No CORS issues (same-origin requests)
- Core-AI remains internal-only
- Single integration point with Organizr
Integration with Organizr:
1. Go to Settings → Customize → Homepage Items
2. Add New Item:
- Name: "AI Performance Stats"
- Type: iFrame
- URL: http://localhost:8083/static/widgets/ai-stats.html
- Authentication: User
3. Position widget on dashboard
Tested:
✅ Proxy endpoints responding correctly
✅ Widget accessible via /static/widgets/
✅ Metrics data flowing from core-ai → core-api → browser
✅ Color coding and formatting working
✅ Auto-refresh functional
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
This commit is contained in:
Claude
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"""
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Core-AI HTTP Client
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Provides interface to Core-AI service for AI performance metrics.
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"""
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import httpx
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from typing import Optional, Dict, List, Any
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from src.logging_config import get_logger
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from src.config import get_settings
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logger = get_logger(__name__)
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settings = get_settings()
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class CoreAIClient:
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"""
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HTTP client for Core-AI service
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Provides access to AI performance metrics, tool execution stats,
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and memory system monitoring.
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"""
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def __init__(
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self,
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base_url: Optional[str] = None,
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timeout: int = 10
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):
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"""
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Initialize Core-AI client
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Args:
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base_url: Core-AI base URL (default from settings)
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timeout: Request timeout in seconds
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"""
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self.base_url = (base_url or getattr(settings, 'core_ai_base_url', 'http://core-ai:8086')).rstrip("/")
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self.timeout = timeout
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self.client = httpx.AsyncClient(timeout=self.timeout)
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async def close(self):
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"""Close the HTTP client"""
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await self.client.aclose()
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async def health_check(self) -> bool:
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"""
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Check if Core-AI service is accessible
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Returns:
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True if accessible, False otherwise
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"""
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try:
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response = await self.client.get(f"{self.base_url}/health")
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return response.status_code == 200
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except Exception as e:
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logger.error(f"Core-AI health check failed: {e}")
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return False
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async def get_metrics(self) -> Dict[str, Any]:
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"""
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Get comprehensive AI performance metrics
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Returns:
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Dict with agent performance, tool execution, memory stats
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Example:
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{
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"uptime_seconds": 3600,
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"timestamp": "2025-12-03T20:00:00Z",
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"agent": {
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"total_requests": 100,
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"avg_response_time_ms": 1250.5,
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"p95_response_time_ms": 3200.0,
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...
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},
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"tools": {
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"total_calls": 250,
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"success_rate": 0.98,
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"top_tools": {...}
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},
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"memory": {
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"tier1_hit_rate": 0.85,
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...
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},
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...
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}
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"""
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try:
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response = await self.client.get(f"{self.base_url}/metrics")
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response.raise_for_status()
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return response.json()
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except httpx.HTTPStatusError as e:
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logger.error(f"Failed to get metrics: HTTP {e.response.status_code}")
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raise
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except Exception as e:
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logger.error(f"Failed to get metrics: {e}")
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raise
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async def get_recent_errors(self, limit: int = 20) -> List[Dict[str, Any]]:
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"""
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Get recent request errors
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Args:
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limit: Maximum number of errors to return
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Returns:
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List of error records with timestamps
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Example:
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[
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{
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"timestamp": "2025-12-03T19:45:12Z",
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"agent_type": "pydantic",
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"error": "Connection timeout",
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"duration_ms": 5000
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},
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...
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]
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"""
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try:
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response = await self.client.get(
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f"{self.base_url}/metrics/errors",
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params={"limit": limit}
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)
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response.raise_for_status()
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data = response.json()
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return data.get("errors", [])
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except Exception as e:
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logger.error(f"Failed to get recent errors: {e}")
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raise
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async def get_tool_failures(self, limit: int = 20) -> List[Dict[str, Any]]:
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"""
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Get recent tool execution failures
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Args:
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limit: Maximum number of failures to return
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Returns:
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List of tool failure records
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Example:
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[
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{
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"timestamp": "2025-12-03T19:50:30Z",
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"tool_name": "list_containers",
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"error": "Connection refused",
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"duration_ms": 150
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},
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...
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]
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"""
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try:
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response = await self.client.get(
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f"{self.base_url}/metrics/tool-failures",
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params={"limit": limit}
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)
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response.raise_for_status()
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data = response.json()
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return data.get("failures", [])
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except Exception as e:
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logger.error(f"Failed to get tool failures: {e}")
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raise
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async def reset_metrics(self) -> bool:
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"""
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Reset all metrics (admin operation)
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Returns:
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True if successful
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"""
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try:
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response = await self.client.post(f"{self.base_url}/metrics/reset")
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response.raise_for_status()
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logger.info("Successfully reset Core-AI metrics")
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return True
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except Exception as e:
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logger.error(f"Failed to reset metrics: {e}")
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raise
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async def __aenter__(self):
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"""Async context manager entry"""
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return self
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async def __aexit__(self, exc_type, exc_val, exc_tb):
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"""Async context manager exit"""
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await self.close()
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# Singleton instance
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_ai_client: Optional[CoreAIClient] = None
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def get_ai_client() -> CoreAIClient:
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"""Get singleton Core-AI client instance"""
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global _ai_client
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if _ai_client is None:
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_ai_client = CoreAIClient()
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return _ai_client
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