May 19, 2026: Full harness update

- Model migration: gemma-4-E4B → qwen3.5-9b-vlm
- Dashboard reorder: Usage Over Time + GPU Metrics to top
- Router counter leak fix (gpu_decr in except handler)
- VLM slot upgrade 1→2
- Automated maintenance cron job
- LiteLLM config update

router/ts_patch.py

@@ -0,0 +1,80 @@
+# Add time-series tracking and endpoint to router
+with open('/opt/inference-harness/router/router.py') as f:
+    code = f.read()
+
+# Add time-series tracking in the chat handler (after Redis incr)
+old_track = '''r.incr('routes:'+model); r.incr('routes:tier:'+tier); r.incr('routes:agent:'+agent)
+                r.lpush('routes:recent', json.dumps'''
+new_track = '''r.incr('routes:'+model); r.incr('routes:tier:'+tier); r.incr('routes:agent:'+agent)
+                # Time-series: hourly bucket
+                hour_key = 'ts:'+model+':'+time.strftime('%Y%m%d%H')
+                r.incr(hour_key)
+                r.expire(hour_key, 86400*31)  # keep 31 days
+                r.lpush('routes:recent', json.dumps'''
+
+code = code.replace(old_track, new_track)
+
+# Add /metrics/timeseries endpoint before if __name__
+ts_endpoint = '''
+@app.route('/metrics/timeseries')
+def metrics_timeseries():
+    period = request.args.get('period', 'day')
+    models = list(GPU_URLS.keys())
+    data = {'models': {}, 'labels': []}
+    
+    if period == 'day':
+        # Last 24 hours, hourly buckets
+        buckets = []
+        for h in range(23, -1, -1):
+            t = time.time() - h * 3600
+            buckets.append(time.strftime('%Y%m%d%H', time.gmtime(t)))
+        data['labels'] = [time.strftime('%H:00', time.gmtime(time.time() - h*3600)) for h in range(23, -1, -1)]
+    elif period == 'week':
+        # Last 7 days, daily buckets
+        buckets = []
+        for d in range(6, -1, -1):
+            t = time.time() - d * 86400
+            buckets.append(time.strftime('%Y%m%d', time.gmtime(t)))
+        data['labels'] = [time.strftime('%a', time.gmtime(time.time() - d*86400)) for d in range(6, -1, -1)]
+    else:
+        # Month — last 30 days, 3-day buckets
+        buckets = []
+        for d in range(29, -1, -3):
+            t = time.time() - d * 86400
+            buckets.append(time.strftime('%Y%m%d', time.gmtime(t)))
+        data['labels'] = [time.strftime('%m/%d', time.gmtime(time.time() - d*86400)) for d in range(29, -1, -3)]
+    
+    if r:
+        for model in models:
+            counts = []
+            for bucket in buckets:
+                if period == 'month':
+                    # Sum 3 consecutive days per bucket
+                    total = 0
+                    base = time.strptime(bucket, '%Y%m%d')
+                    for offset in range(3):
+                        d = time.strftime('%Y%m%d', time.gmtime(time.mktime(base) + offset*86400))
+                        total += int(r.get('ts:'+model+':'+d) or 0)
+                        # Also check hourly keys for today
+                        for hh in range(24):
+                            total += int(r.get('ts:'+model+':'+d+'{:02d}'.format(hh)) or 0)
+                    counts.append(total)
+                else:
+                    key = 'ts:'+model+':'+bucket
+                    if period == 'week':
+                        # Sum all hours in the day
+                        total = sum(int(r.get(key+'{:02d}'.format(h)) or 0) for h in range(24))
+                    else:
+                        total = int(r.get(key) or 0)
+                    counts.append(total)
+            data['models'][model] = counts
+    
+    return jsonify(data)
+'''
+
+# Insert before if __name__
+code = code.replace(if __name__ == __main__:, ts_endpoint + nif __name__ == __main__:)
+
+with open('/opt/inference-harness/router/router.py', 'w') as f:
+    f.write(code)
+print('Time-series tracking and endpoint added')