Metrics Dashboard Command

Display comprehensive system metrics and performance statistics.

Usage

No arguments required.

Instructions

Shows system health, query performance, cache stats, and recent activity.

Implementation

import httpx
import json

try:
    # Get all metrics
    response = httpx.get(
        "http://127.0.0.1:8765/metrics",
        timeout=10.0
    )

    if response.status_code == 200:
        metrics = response.json()

        print("=" * 70)
        print("[=] RAG SYSTEM METRICS DASHBOARD".center(70))
        print("=" * 70)
        print()

        # Health Status
        health = metrics.get("health", {})
        if health:
            status = health.get("status", "unknown").upper()
            status_emoji = "[OK]" if status == "HEALTHY" else "[!]"

            print(f"{status_emoji} SYSTEM HEALTH: {status}")

            error_rate = health.get("error_rate", 0)
            memory_mb = health.get("memory_usage_mb", 0)
            latency = health.get("avg_query_latency_ms", 0)

            print(f"   Error Rate: {error_rate:.2%}")
            print(f"   Memory: {memory_mb:.1f} MB")
            print(f"   Avg Latency: {latency:.1f} ms")
            print()

        # Query Performance
        perf = metrics.get("performance", {})
        if perf:
            print("[!] QUERY PERFORMANCE (7 days)")

            total = perf.get("total_queries", 0)
            qpd = perf.get("queries_per_day", 0)
            avg_time = perf.get("avg_execution_time_ms", 0)
            p95_time = perf.get("p95_execution_time_ms", 0)

            print(f"   Total Queries: {total}")
            print(f"   Queries/Day: {qpd:.1f}")
            print(f"   Avg Time: {avg_time:.1f} ms")
            print(f"   P95 Time: {p95_time:.1f} ms")

            feedback = perf.get("avg_feedback_score")
            if feedback is not None:
                print(f"   Avg Feedback: {feedback:.2f}/1.0")

            print()

        # Cache Statistics
        cache = metrics.get("cache", {})
        if cache:
            print("[@] CACHE STATISTICS")

            entries = cache.get("total_entries", 0)
            size_mb = cache.get("total_size_mb", 0)
            avg_access = cache.get("average_access_count", 0)

            print(f"   Total Entries: {entries}")
            print(f"   Total Size: {size_mb:.2f} MB")
            print(f"   Avg Access Count: {avg_access:.1f}")
            print()

        # Get popular queries
        try:
            history_response = httpx.get(
                "http://127.0.0.1:8765/query-history?days=1",
                timeout=5.0
            )

            if history_response.status_code == 200:
                history = history_response.json()
                popular = history.get("popular_queries", [])

                if popular:
                    print("[FIRE] TOP QUERIES (24h)")
                    for i, query_info in enumerate(popular[:5], 1):
                        query = query_info.get("query", "")
                        count = query_info.get("count", 0)

                        if len(query) > 50:
                            query = query[:47] + "..."

                        print(f"   {i}. {query} ({count}x)")

                    print()

        except:
            pass

        print("=" * 70)

        print("\n[i] Refresh with: /rag-metrics")

    else:
        print(f"[X] Server error: {response.status_code}")

except Exception as e:
    print(f"[X] Error: {e}")
    print("Make sure the MCP server is running on port 8000.")

Execute this code to display the metrics dashboard.