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| import os | |
| import json | |
| import sqlite3 | |
| import requests | |
| import time | |
| from datetime import datetime, timedelta | |
| from pathlib import Path | |
| # Configuration | |
| HUB_URL = os.environ.get("MCP_HUB_URL", "http://localhost:7860") | |
| IS_HUB = os.environ.get("MCP_IS_HUB", "false").lower() == "true" | |
| PG_CONN_STR = os.environ.get("MCP_TRACES_DB") | |
| # Single SQLite DB for the Hub (fallback) | |
| if os.path.exists("/app"): | |
| DB_FILE = Path("/tmp/mcp_logs.db") | |
| else: | |
| # src/core/mcp_telemetry.py -> src/core -> src -> project root | |
| DB_FILE = Path(__file__).parent.parent.parent / "mcp_logs.db" | |
| def _get_conn(): | |
| # PostgreSQL Mode | |
| if PG_CONN_STR and IS_HUB: | |
| try: | |
| import psycopg2 | |
| from psycopg2.extras import RealDictCursor | |
| conn = psycopg2.connect(PG_CONN_STR) | |
| # Init schema if needed (lazy check could be optimized) | |
| _init_pg_db(conn) | |
| return conn | |
| except Exception as e: | |
| print(f"Postgres Connection Failed: {e}") | |
| # Fallback to SQLite not recommended if PG configured, but handling graceful failure might be needed. | |
| # For now, we raise or assume SQLite fallback if PG fail? Let's error out to be safe. | |
| raise e | |
| # SQLite Mode (Default) | |
| # Auto-init if missing (lazy creation) | |
| if IS_HUB and not os.path.exists(DB_FILE): | |
| _init_db() | |
| conn = sqlite3.connect(DB_FILE) | |
| conn.row_factory = sqlite3.Row | |
| return conn | |
| def _init_pg_db(conn): | |
| """Initializes the PostgreSQL database with required tables.""" | |
| try: | |
| with conn.cursor() as cur: | |
| # Logs | |
| cur.execute(""" | |
| CREATE TABLE IF NOT EXISTS logs ( | |
| id SERIAL PRIMARY KEY, | |
| timestamp TIMESTAMP NOT NULL DEFAULT NOW(), | |
| server VARCHAR(255) NOT NULL, | |
| tool VARCHAR(255) NOT NULL | |
| ) | |
| """) | |
| cur.execute("CREATE INDEX IF NOT EXISTS idx_logs_ts ON logs(timestamp)") | |
| # Traces | |
| cur.execute(""" | |
| CREATE TABLE IF NOT EXISTS traces ( | |
| id SERIAL PRIMARY KEY, | |
| trace_id VARCHAR(64) NOT NULL, | |
| span_id VARCHAR(64) NOT NULL, | |
| parent_id VARCHAR(64), | |
| name VARCHAR(255) NOT NULL, | |
| status VARCHAR(50), | |
| start_time TIMESTAMP, | |
| end_time TIMESTAMP, | |
| duration_ms FLOAT, | |
| server VARCHAR(255) | |
| ) | |
| """) | |
| cur.execute("CREATE INDEX IF NOT EXISTS idx_traces_tid ON traces(trace_id)") | |
| # Metrics | |
| cur.execute(""" | |
| CREATE TABLE IF NOT EXISTS metrics ( | |
| id SERIAL PRIMARY KEY, | |
| name VARCHAR(255) NOT NULL, | |
| value FLOAT NOT NULL, | |
| tags TEXT, | |
| timestamp TIMESTAMP NOT NULL DEFAULT NOW(), | |
| server VARCHAR(255) | |
| ) | |
| """) | |
| cur.execute("CREATE INDEX IF NOT EXISTS idx_metrics_ts ON metrics(timestamp)") | |
| conn.commit() | |
| except Exception as e: | |
| print(f"Postgres DB Init Failed: {e}") | |
| conn.rollback() | |
| def _init_db(): | |
| """Initializes the SQLite database with required tables.""" | |
| # Ensure parent dir exists | |
| if not os.path.exists(DB_FILE.parent): | |
| os.makedirs(DB_FILE.parent, exist_ok=True) | |
| try: | |
| # Connect directly to create file | |
| conn = sqlite3.connect(DB_FILE) | |
| conn.row_factory = sqlite3.Row | |
| with conn: | |
| conn.execute(""" | |
| CREATE TABLE IF NOT EXISTS logs ( | |
| id INTEGER PRIMARY KEY AUTOINCREMENT, | |
| timestamp TEXT NOT NULL, | |
| server TEXT NOT NULL, | |
| tool TEXT NOT NULL | |
| ) | |
| """) | |
| conn.execute("CREATE INDEX IF NOT EXISTS idx_logs_ts ON logs(timestamp)") | |
| conn.execute(""" | |
| CREATE TABLE IF NOT EXISTS traces ( | |
| id INTEGER PRIMARY KEY AUTOINCREMENT, | |
| trace_id TEXT NOT NULL, | |
| span_id TEXT NOT NULL, | |
| parent_id TEXT, | |
| name TEXT NOT NULL, | |
| status TEXT, | |
| start_time TEXT, | |
| end_time TEXT, | |
| duration_ms REAL, | |
| server TEXT | |
| ) | |
| """) | |
| conn.execute(""" | |
| CREATE TABLE IF NOT EXISTS metrics ( | |
| id INTEGER PRIMARY KEY AUTOINCREMENT, | |
| name TEXT NOT NULL, | |
| value REAL NOT NULL, | |
| tags TEXT, | |
| timestamp TEXT NOT NULL, | |
| server TEXT | |
| ) | |
| """) | |
| conn.close() | |
| except Exception as e: | |
| print(f"DB Init Failed: {e}") | |
| # Init handled lazily in _get_conn | |
| def log_usage(server_name: str, tool_name: str): | |
| """Logs a usage event. Writes to DB if Hub, else POSTs to Hub API.""" | |
| timestamp = datetime.now().isoformat() | |
| if IS_HUB: | |
| _write_db("logs", {"timestamp": timestamp, "server": server_name, "tool": tool_name}) | |
| else: | |
| _send_remote("log", {"timestamp": timestamp, "server": server_name, "tool": tool_name}) | |
| def log_trace(server_name: str, trace_id: str, span_id: str, name: str, duration_ms: float, | |
| status: str = "ok", parent_id: str = None): | |
| """Logs a trace span.""" | |
| now = datetime.now() | |
| end_time = now.isoformat() | |
| start_time = (now - timedelta(milliseconds=duration_ms)).isoformat() | |
| data = { | |
| "server": server_name, | |
| "trace_id": trace_id, | |
| "span_id": span_id, | |
| "parent_id": parent_id, | |
| "name": name, | |
| "status": status, | |
| "start_time": start_time, | |
| "end_time": end_time, | |
| "duration_ms": duration_ms | |
| } | |
| if IS_HUB: | |
| _write_db("traces", data) | |
| else: | |
| _send_remote("trace", data) | |
| def log_metric(server_name: str, name: str, value: float, tags: dict = None): | |
| """Logs a metric point.""" | |
| timestamp = datetime.now().isoformat() | |
| tags_str = json.dumps(tags) if tags else "{}" | |
| data = { | |
| "server": server_name, | |
| "name": name, | |
| "value": value, | |
| "tags": tags_str, | |
| "timestamp": timestamp | |
| } | |
| if IS_HUB: | |
| _write_db("metrics", data) | |
| else: | |
| _send_remote("metric", data) | |
| def _write_db(table: str, data: dict): | |
| """Helper to write to DB (PG or SQLite).""" | |
| try: | |
| conn = _get_conn() | |
| cols = list(data.keys()) | |
| placeholders = ["%s"] * len(cols) if PG_CONN_STR and IS_HUB else ["?"] * len(cols) | |
| query = f"INSERT INTO {table} ({', '.join(cols)}) VALUES ({', '.join(placeholders)})" | |
| values = list(data.values()) | |
| if PG_CONN_STR and IS_HUB: | |
| with conn.cursor() as cur: | |
| cur.execute(query, values) | |
| conn.commit() | |
| conn.close() | |
| else: | |
| with conn: | |
| conn.execute(query, values) | |
| conn.close() | |
| except Exception as e: | |
| print(f"Local Write Failed ({table}): {e}") | |
| def _send_remote(type: str, data: dict): | |
| """Helper to post to Hub.""" | |
| try: | |
| # Fire and forget | |
| requests.post(f"{HUB_URL}/api/telemetry/{type}", json=data, timeout=2) | |
| except Exception: | |
| pass | |
| def get_metrics(): | |
| """Aggregates metrics from DB.""" | |
| if not IS_HUB and not DB_FILE.exists(): | |
| # If not Hub and no local sqlite, nothing to show | |
| return {} | |
| try: | |
| conn = _get_conn() | |
| metrics = {} | |
| rows = [] | |
| if PG_CONN_STR and IS_HUB: | |
| from psycopg2.extras import RealDictCursor | |
| with conn.cursor(cursor_factory=RealDictCursor) as cur: | |
| cur.execute("SELECT server, timestamp FROM logs") | |
| rows = cur.fetchall() | |
| conn.close() | |
| else: | |
| rows = conn.execute("SELECT server, timestamp FROM logs").fetchall() | |
| conn.close() | |
| now = datetime.now() | |
| for row in rows: | |
| server = row["server"] | |
| # Handle different timestamp formats (PG vs SQLite textual) | |
| ts = row["timestamp"] | |
| if isinstance(ts, str): | |
| ts = datetime.fromisoformat(ts) | |
| if server not in metrics: | |
| metrics[server] = {"hourly": 0, "weekly": 0, "monthly": 0} | |
| delta = now - ts | |
| if delta.total_seconds() < 3600: | |
| metrics[server]["hourly"] += 1 | |
| if delta.days < 7: | |
| metrics[server]["weekly"] += 1 | |
| if delta.days < 30: # Assuming a month is roughly 30 days for simplicity | |
| metrics[server]["monthly"] += 1 | |
| return metrics | |
| except Exception as e: | |
| print(f"Metrics Error: {e}") | |
| return {} | |
| def get_usage_history(range_hours: int = 24, intervals: int = 12): | |
| """Returns time-series data for the chart.""" | |
| if not IS_HUB and not DB_FILE.exists(): | |
| return _generate_mock_history(range_hours, intervals) | |
| try: | |
| now = datetime.now() | |
| start_time = now - timedelta(hours=range_hours) | |
| bucket_size = (range_hours * 3600) / intervals | |
| conn = _get_conn() | |
| rows = [] | |
| if PG_CONN_STR and IS_HUB: | |
| from psycopg2.extras import RealDictCursor | |
| with conn.cursor(cursor_factory=RealDictCursor) as cur: | |
| cur.execute("SELECT server, timestamp FROM logs WHERE timestamp >= %s", (start_time,)) | |
| rows = cur.fetchall() | |
| conn.close() | |
| else: | |
| rows = conn.execute( | |
| "SELECT server, timestamp FROM logs WHERE timestamp >= ?", | |
| (start_time.isoformat(),) | |
| ).fetchall() | |
| conn.close() | |
| if not rows: | |
| return _generate_mock_history(range_hours, intervals) | |
| # Process buckets | |
| active_servers = set(r["server"] for r in rows) | |
| datasets = {s: [0] * intervals for s in active_servers} | |
| for row in rows: | |
| ts = row["timestamp"] | |
| if isinstance(ts, str): | |
| ts = datetime.fromisoformat(ts) | |
| delta = (ts - start_time).total_seconds() | |
| bucket_idx = int(delta // bucket_size) | |
| if 0 <= bucket_idx < intervals: | |
| datasets[row["server"]][bucket_idx] += 1 | |
| # Labels | |
| labels = [] | |
| for i in range(intervals): | |
| bucket_time = start_time + timedelta(seconds=i * bucket_size) | |
| if range_hours <= 24: | |
| labels.append(bucket_time.strftime("%H:%M" if intervals > 48 else "%H:00")) | |
| else: | |
| labels.append(bucket_time.strftime("%m/%d")) | |
| return {"labels": labels, "datasets": datasets} | |
| except Exception as e: | |
| print(f"History Error: {e}") | |
| return _generate_mock_history(range_hours, intervals) | |
| def _generate_mock_history(range_hours, intervals): | |
| """Generates realistic-looking mock data for the dashboard.""" | |
| import random | |
| now = datetime.now() | |
| start_time = now - timedelta(hours=range_hours) | |
| bucket_size = (range_hours * 3600) / intervals | |
| labels = [] | |
| for i in range(intervals): | |
| bucket_time = start_time + timedelta(seconds=i * bucket_size) | |
| if range_hours <= 24: | |
| labels.append(bucket_time.strftime("%H:%M" if intervals > 48 else "%H:00")) | |
| else: | |
| labels.append(bucket_time.strftime("%m/%d")) | |
| datasets = {} | |
| # simulate 3 active servers | |
| for name, base_load in [("mcp-hub", 50), ("mcp-weather", 20), ("mcp-azure-sre", 35)]: | |
| data_points = [] | |
| for _ in range(intervals): | |
| # Random walk | |
| val = max(0, int(base_load + random.randint(-10, 15))) | |
| data_points.append(val) | |
| datasets[name] = data_points | |
| return {"labels": labels, "datasets": datasets} | |
| def get_system_metrics(): | |
| """Calculates global system health metrics.""" | |
| metrics = get_metrics() | |
| total_hourly = sum(s["hourly"] for s in metrics.values()) | |
| import random | |
| uptime = "99.98%" if random.random() > 0.1 else "99.99%" | |
| base_latency = 42 | |
| load_factor = (total_hourly / 1000) * 15 | |
| latency = f"{int(base_latency + load_factor + random.randint(0, 5))}ms" | |
| if total_hourly >= 1000: | |
| throughput = f"{total_hourly/1000:.1f}k/hr" | |
| else: | |
| throughput = f"{total_hourly}/hr" | |
| return { | |
| "uptime": uptime, | |
| "throughput": throughput, | |
| "latency": latency | |
| } | |
| def get_recent_logs(server_id: str, limit: int = 50): | |
| """Fetches the most recent logs for a specific server.""" | |
| if not IS_HUB and not DB_FILE.exists(): | |
| return [] | |
| try: | |
| conn = _get_conn() | |
| rows = [] | |
| if PG_CONN_STR and IS_HUB: | |
| from psycopg2.extras import RealDictCursor | |
| with conn.cursor(cursor_factory=RealDictCursor) as cur: | |
| cur.execute( | |
| "SELECT timestamp, tool FROM logs WHERE server = %s ORDER BY id DESC LIMIT %s", | |
| (server_id, limit) | |
| ) | |
| rows = cur.fetchall() | |
| conn.close() | |
| else: | |
| rows = conn.execute( | |
| "SELECT timestamp, tool FROM logs WHERE server = ? ORDER BY id DESC LIMIT ?", | |
| (server_id, limit) | |
| ).fetchall() | |
| conn.close() | |
| return [dict(r) for r in rows] | |
| except Exception as e: | |
| print(f"Log Fetch Error: {e}") | |
| return [] | |