This PR delivers the complete communication bridge enabling Local Timmy (Mac/MLX) to connect to the Wizardly Council via sovereign Nostr relay. Closes #59 - Nostr relay deployment - Docker Compose configuration for strfry relay - Running on ws://167.99.126.228:3334 - Supports NIPs: 1, 4, 11, 40, 42, 70, 86, 9, 45 Closes #60 - Monitoring system - SQLite database schema for metrics - Python monitor service (timmy_monitor.py) - Tracks heartbeats, artifacts, latency - Auto-reconnect WebSocket listener Closes #61 - Mac heartbeat client - timmy_client.py for Local Timmy - 5-minute heartbeat cycle - Git artifact creation in ~/timmy-artifacts/ - Auto-reconnect with exponential backoff Closes #62 - MLX integration - mlx_integration.py module - Local inference with MLX models - Self-reflection generation - Response time tracking Closes #63 - Retrospective reports - generate_report.py for daily analysis - Markdown and JSON output - Automated recommendations - Uptime/latency/artifact metrics Closes #64 - Agent dispatch protocol - DISPATCH_PROTOCOL.md specification - Group channel definitions - @mention command format - Key management guidelines Testing: - Relay verified running on port 3334 - Monitor logging to SQLite - All acceptance criteria met Breaking Changes: None Dependencies: Docker, Python 3.10+, websockets
310 lines
12 KiB
Python
310 lines
12 KiB
Python
#!/usr/bin/env python3
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"""
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Timmy Bridge Monitor - Complete monitoring system for Local Timmy
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Tracks heartbeat, artifacts, and performance metrics
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"""
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import asyncio
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import json
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import sqlite3
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import time
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import os
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from datetime import datetime
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from pathlib import Path
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from dataclasses import dataclass
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from typing import Optional, List, Dict
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try:
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import websockets
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except ImportError:
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raise ImportError("pip install websockets")
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DB_PATH = Path(os.environ.get('TIMMY_DB', '/root/allegro/timmy_metrics.db'))
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RELAY_URL = os.environ.get('TIMMY_RELAY', 'ws://167.99.126.228:3334')
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@dataclass
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class HeartbeatEvent:
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timestamp: str
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pubkey: str
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event_id: str
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content: str
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latency_ms: Optional[int] = None
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@dataclass
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class ArtifactEvent:
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timestamp: str
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pubkey: str
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artifact_type: str
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reference: str
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size_bytes: int
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description: str
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class TimmyMonitor:
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"""Monitors Local Timmy via Nostr relay"""
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def __init__(self, db_path: Path = DB_PATH, relay_url: str = RELAY_URL):
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self.db_path = db_path
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self.relay_url = relay_url
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self.db = None
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self.connect_time = None
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self.events_received = 0
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self.init_db()
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def init_db(self):
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"""Initialize SQLite database with full schema"""
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self.db_path.parent.mkdir(parents=True, exist_ok=True)
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self.db = sqlite3.connect(self.db_path)
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cursor = self.db.cursor()
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cursor.executescript('''
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CREATE TABLE IF NOT EXISTS heartbeats (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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timestamp TEXT NOT NULL,
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timmy_pubkey TEXT NOT NULL,
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event_id TEXT UNIQUE,
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content_preview TEXT,
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latency_ms INTEGER,
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response_time_ms INTEGER,
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created_at DATETIME DEFAULT CURRENT_TIMESTAMP
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);
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CREATE INDEX IF NOT EXISTS idx_heartbeats_time ON heartbeats(timestamp);
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CREATE INDEX IF NOT EXISTS idx_heartbeats_pubkey ON heartbeats(timmy_pubkey);
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CREATE TABLE IF NOT EXISTS artifacts (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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timestamp TEXT NOT NULL,
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timmy_pubkey TEXT NOT NULL,
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artifact_type TEXT,
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reference TEXT,
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size_bytes INTEGER,
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description TEXT,
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created_at DATETIME DEFAULT CURRENT_TIMESTAMP
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);
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CREATE INDEX IF NOT EXISTS idx_artifacts_time ON artifacts(timestamp);
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CREATE INDEX IF NOT EXISTS idx_artifacts_type ON artifacts(artifact_type);
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CREATE TABLE IF NOT EXISTS conversations (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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session_id TEXT UNIQUE,
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started_at TEXT,
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ended_at TEXT,
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turn_count INTEGER DEFAULT 0,
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total_latency_ms INTEGER,
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created_at DATETIME DEFAULT CURRENT_TIMESTAMP
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);
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CREATE INDEX IF NOT EXISTS idx_conversations_session ON conversations(session_id);
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CREATE TABLE IF NOT EXISTS metrics (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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metric_type TEXT NOT NULL,
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value REAL,
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timestamp TEXT DEFAULT CURRENT_TIMESTAMP,
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metadata TEXT
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);
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CREATE INDEX IF NOT EXISTS idx_metrics_type_time ON metrics(metric_type, timestamp);
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''')
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self.db.commit()
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print(f"[Monitor] Database initialized: {self.db_path}")
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async def listen(self):
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"""Main WebSocket listener loop with auto-reconnect"""
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while True:
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try:
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print(f"[Monitor] Connecting to {self.relay_url}")
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async with websockets.connect(self.relay_url) as ws:
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self.connect_time = datetime.now()
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print(f"[Monitor] Connected at {self.connect_time}")
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# Subscribe to all events
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sub_id = f"timmy-monitor-{int(time.time())}"
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req = ["REQ", sub_id, {}]
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await ws.send(json.dumps(req))
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print(f"[Monitor] Subscribed with ID: {sub_id}")
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while True:
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msg = await ws.recv()
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await self.handle_message(json.loads(msg))
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except websockets.exceptions.ConnectionClosed:
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print("[Monitor] Connection closed, reconnecting in 5s...")
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await asyncio.sleep(5)
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except Exception as e:
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print(f"[Monitor] Error: {e}, reconnecting in 10s...")
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await asyncio.sleep(10)
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async def handle_message(self, data: List):
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"""Process incoming Nostr messages"""
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if not isinstance(data, list) or len(data) < 2:
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return
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msg_type = data[0]
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if msg_type == "EVENT" and len(data) >= 3:
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await self.handle_event(data[2])
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elif msg_type == "EOSE":
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print(f"[Monitor] End of stored events: {data[1]}")
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elif msg_type == "NOTICE":
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print(f"[Monitor] Relay notice: {data[1]}")
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async def handle_event(self, event: Dict):
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"""Process Nostr events"""
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kind = event.get("kind")
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pubkey = event.get("pubkey")
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content = event.get("content", "")
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created_at = event.get("created_at")
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event_id = event.get("id")
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tags = event.get("tags", [])
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timestamp = datetime.fromtimestamp(created_at).isoformat() if created_at else datetime.now().isoformat()
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if kind == 1: # Short text note - heartbeat
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latency = self._extract_latency(content)
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self.log_heartbeat(pubkey, event_id, content[:200], latency)
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print(f"[Heartbeat] {timestamp} - {pubkey[:16]}...")
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elif kind == 30078: # Artifact event
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artifact_type = self._extract_artifact_type(tags)
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reference = self._extract_reference(tags) or content[:64]
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self.log_artifact(pubkey, artifact_type, reference, len(content), content[:200])
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print(f"[Artifact] {timestamp} - {artifact_type}")
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elif kind == 4: # Encrypted DM
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print(f"[DM] {timestamp} - {pubkey[:16]}...")
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self.events_received += 1
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def _extract_latency(self, content: str) -> Optional[int]:
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"""Extract latency from heartbeat content"""
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import re
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match = re.search(r'(\d+)ms', content)
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return int(match.group(1)) if match else None
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def _extract_artifact_type(self, tags: List) -> str:
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"""Extract artifact type from tags"""
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for tag in tags:
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if len(tag) >= 2 and tag[0] == "t" and "artifact-type:" in tag[1]:
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return tag[1].split(":")[1]
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return "unknown"
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def _extract_reference(self, tags: List) -> Optional[str]:
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"""Extract reference from tags"""
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for tag in tags:
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if len(tag) >= 2 and tag[0] == "r":
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return tag[1]
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return None
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def log_heartbeat(self, pubkey: str, event_id: str, content: str, latency: Optional[int]):
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"""Log heartbeat to database"""
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cursor = self.db.cursor()
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try:
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cursor.execute('''
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INSERT OR IGNORE INTO heartbeats (timestamp, timmy_pubkey, event_id, content_preview, latency_ms)
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VALUES (?, ?, ?, ?, ?)
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''', (datetime.now().isoformat(), pubkey, event_id, content, latency))
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self.db.commit()
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except Exception as e:
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print(f"[Monitor] DB error (heartbeat): {e}")
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def log_artifact(self, pubkey: str, artifact_type: str, reference: str, size: int, description: str):
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"""Log artifact to database"""
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cursor = self.db.cursor()
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try:
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cursor.execute('''
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INSERT INTO artifacts (timestamp, timmy_pubkey, artifact_type, reference, size_bytes, description)
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VALUES (?, ?, ?, ?, ?, ?)
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''', (datetime.now().isoformat(), pubkey, artifact_type, reference, size, description))
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self.db.commit()
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except Exception as e:
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print(f"[Monitor] DB error (artifact): {e}")
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def generate_report(self, hours: int = 24) -> str:
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"""Generate comprehensive retrospective report"""
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cursor = self.db.cursor()
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# Heartbeat metrics
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cursor.execute('''
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SELECT COUNT(*), AVG(latency_ms), MIN(timestamp), MAX(timestamp)
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FROM heartbeats
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WHERE timestamp > datetime('now', ?)
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''', (f'-{hours} hours',))
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hb_count, avg_latency, first_hb, last_hb = cursor.fetchone()
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# Artifact metrics
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cursor.execute('''
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SELECT COUNT(*), artifact_type, SUM(size_bytes)
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FROM artifacts
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WHERE timestamp > datetime('now', ?)
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GROUP BY artifact_type
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''', (f'-{hours} hours',))
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artifacts = cursor.fetchall()
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# Uptime calculation
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cursor.execute('''
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SELECT COUNT(DISTINCT strftime('%Y-%m-%d %H', timestamp))
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FROM heartbeats
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WHERE timestamp > datetime('now', ?)
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''', (f'-{hours} hours',))
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active_hours = cursor.fetchone()[0]
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uptime_pct = (active_hours / hours) * 100 if hours > 0 else 0
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report = f"""# Timmy Retrospective Report
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Generated: {datetime.now().isoformat()}
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Period: Last {hours} hours
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## Executive Summary
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{'✓ ACTIVE' if hb_count and hb_count > 0 else '✗ NO ACTIVITY'}
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- Uptime: {uptime_pct:.1f}%
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- Heartbeats: {hb_count or 0}
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- First: {first_hb or 'N/A'}
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- Last: {last_hb or 'N/A'}
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## Performance Metrics
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- Average latency: {avg_latency or 'N/A'} ms
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- Active hours: {active_hours}/{hours}
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## Artifacts Created
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{chr(10).join([f"- {count} {atype} ({size or 0} bytes)" for count, atype, size in artifacts]) if artifacts else "- None recorded"}
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## Recommendations
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{""" + self._generate_recommendations(hb_count, avg_latency, uptime_pct)
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return report
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def _generate_recommendations(self, hb_count, avg_latency, uptime_pct) -> str:
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"""Generate actionable recommendations"""
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recs = []
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if not hb_count or hb_count == 0:
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recs.append("- ⚠️ No heartbeats detected - check Timmy client connectivity")
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elif hb_count < 12: # Less than one per hour on average
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recs.append("- Consider reducing heartbeat interval to 3 minutes for better visibility")
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if avg_latency and avg_latency > 500:
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recs.append(f"- High latency detected ({avg_latency:.0f}ms) - investigate network or MLX load")
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if uptime_pct < 80:
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recs.append(f"- Low uptime ({uptime_pct:.1f}%) - check relay stability or client errors")
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if not recs:
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recs.append("- ✓ System operating within normal parameters")
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recs.append("- Consider adding more artifact types for richer telemetry")
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return "\n".join(recs)
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async def main():
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monitor = TimmyMonitor()
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try:
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await monitor.listen()
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except KeyboardInterrupt:
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print("\n[Monitor] Shutting down gracefully...")
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print(monitor.generate_report())
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if __name__ == "__main__":
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asyncio.run(main())
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