# 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')