Abiba
28fc57c5c7
- 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
81 lines
3.4 KiB
Python
81 lines
3.4 KiB
Python
# Add time-series tracking and endpoint to router
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with open('/opt/inference-harness/router/router.py') as f:
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code = f.read()
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# Add time-series tracking in the chat handler (after Redis incr)
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old_track = '''r.incr('routes:'+model); r.incr('routes:tier:'+tier); r.incr('routes:agent:'+agent)
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r.lpush('routes:recent', json.dumps'''
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new_track = '''r.incr('routes:'+model); r.incr('routes:tier:'+tier); r.incr('routes:agent:'+agent)
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# Time-series: hourly bucket
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hour_key = 'ts:'+model+':'+time.strftime('%Y%m%d%H')
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r.incr(hour_key)
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r.expire(hour_key, 86400*31) # keep 31 days
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r.lpush('routes:recent', json.dumps'''
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code = code.replace(old_track, new_track)
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# Add /metrics/timeseries endpoint before if __name__
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ts_endpoint = '''
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@app.route('/metrics/timeseries')
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def metrics_timeseries():
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period = request.args.get('period', 'day')
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models = list(GPU_URLS.keys())
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data = {'models': {}, 'labels': []}
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if period == 'day':
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# Last 24 hours, hourly buckets
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buckets = []
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for h in range(23, -1, -1):
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t = time.time() - h * 3600
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buckets.append(time.strftime('%Y%m%d%H', time.gmtime(t)))
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data['labels'] = [time.strftime('%H:00', time.gmtime(time.time() - h*3600)) for h in range(23, -1, -1)]
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elif period == 'week':
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# Last 7 days, daily buckets
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buckets = []
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for d in range(6, -1, -1):
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t = time.time() - d * 86400
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buckets.append(time.strftime('%Y%m%d', time.gmtime(t)))
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data['labels'] = [time.strftime('%a', time.gmtime(time.time() - d*86400)) for d in range(6, -1, -1)]
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else:
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# Month — last 30 days, 3-day buckets
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buckets = []
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for d in range(29, -1, -3):
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t = time.time() - d * 86400
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buckets.append(time.strftime('%Y%m%d', time.gmtime(t)))
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data['labels'] = [time.strftime('%m/%d', time.gmtime(time.time() - d*86400)) for d in range(29, -1, -3)]
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if r:
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for model in models:
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counts = []
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for bucket in buckets:
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if period == 'month':
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# Sum 3 consecutive days per bucket
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total = 0
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base = time.strptime(bucket, '%Y%m%d')
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for offset in range(3):
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d = time.strftime('%Y%m%d', time.gmtime(time.mktime(base) + offset*86400))
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total += int(r.get('ts:'+model+':'+d) or 0)
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# Also check hourly keys for today
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for hh in range(24):
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total += int(r.get('ts:'+model+':'+d+'{:02d}'.format(hh)) or 0)
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counts.append(total)
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else:
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key = 'ts:'+model+':'+bucket
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if period == 'week':
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# Sum all hours in the day
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total = sum(int(r.get(key+'{:02d}'.format(h)) or 0) for h in range(24))
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else:
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total = int(r.get(key) or 0)
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counts.append(total)
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data['models'][model] = counts
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return jsonify(data)
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'''
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# Insert before if __name__
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code = code.replace(if __name__ == __main__:, ts_endpoint + nif __name__ == __main__:)
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with open('/opt/inference-harness/router/router.py', 'w') as f:
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f.write(code)
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print('Time-series tracking and endpoint added')
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