# 3,000 tickets through the real job

job status                     COMPLETED
step: read=3000 write=2987 processSkip=13 commits=30 rollbacks=0
TICKET_RESULT rows             2987
SKIPPED_TICKET rows            13
classified + skipped           3000   (tickets: 3000)

Skipped tickets and why (first one of each kind):
  ticket 46    category not in schema   raw reply: {"category":"Account & Payments","priority":1,"confidence":0.74}
  ticket 234   not JSON                 raw reply: Sure! Here is the classification you asked for: {"category":"BILLING","priority":4,"confidence":0.7}
  ticket 491   missing field            raw reply: {"category":"OTHER","priority":2}

First 3 ledger rows (one per committed chunk):
  tickets      written skipped attempts   429s   503s    bad promptTok complTok         cost
  1-100             99       1      104      1      1      3     10831     1469  0.007619000
  101-200          100       0      100      0      0      0     10574     1453  0.007466500
  201-300           99       1      105      2      1      3     10736     1495  0.007610500

Ledger totals vs the provider's own meter (they must agree when nothing was lost):
                               ledger     provider
  calls received                3,104        3,104
  429 rejections                   39           39
  503 rejections                   14           14
  billed calls                  3,051        3,051
  prompt tokens               324,790      324,790
  completion tokens            44,107       44,107

Cost = prompt tokens x input price + completion tokens x output price, per million tokens.
  table 'EXAMPLE-NOT-A-REAL-PRICE' (input 0.50, output 1.50): 0.228555500   <- the ledger's total
  same tokens under table 'OTHER-EXAMPLE' (input 2.00, output 6.00):  0.914222000
  Both tables are invented inputs. Tokens are the measurement; money is tokens x a table you supply.
  Tokens spent on replies that were then skipped: bad replies billed = 64 of 3051 billed calls.