({
dataset,
logger,
}: {
dataset?: string
logger: Logger
})
| 36 | } |
| 37 | |
| 38 | export async function setupBigQuery({ |
| 39 | dataset, |
| 40 | logger, |
| 41 | }: { |
| 42 | dataset?: string |
| 43 | logger: Logger |
| 44 | }) { |
| 45 | if (client) { |
| 46 | return |
| 47 | } |
| 48 | const resolvedDataset = dataset ?? DATASET |
| 49 | try { |
| 50 | client = new BigQuery() |
| 51 | |
| 52 | // Ensure dataset exists |
| 53 | const [ds] = await client.dataset(resolvedDataset).get({ autoCreate: true }) |
| 54 | |
| 55 | // Ensure tables exist |
| 56 | await ds.table(TRACES_TABLE).get({ |
| 57 | autoCreate: true, |
| 58 | schema: TRACES_SCHEMA, |
| 59 | timePartitioning: { |
| 60 | type: 'MONTH', |
| 61 | field: 'created_at', |
| 62 | }, |
| 63 | clustering: { |
| 64 | fields: ['user_id', 'agent_step_id'], |
| 65 | }, |
| 66 | }) |
| 67 | await ds.table(RELABELS_TABLE).get({ |
| 68 | autoCreate: true, |
| 69 | schema: RELABELS_SCHEMA, |
| 70 | timePartitioning: { |
| 71 | type: 'MONTH', |
| 72 | field: 'created_at', |
| 73 | }, |
| 74 | clustering: { |
| 75 | fields: ['user_id', 'agent_step_id'], |
| 76 | }, |
| 77 | }) |
| 78 | await ds.table(MESSAGE_TABLE).get({ |
| 79 | autoCreate: true, |
| 80 | schema: MESSAGE_SCHEMA, |
| 81 | timePartitioning: { |
| 82 | type: 'MONTH', |
| 83 | field: 'finished_at', |
| 84 | }, |
| 85 | clustering: { |
| 86 | fields: ['user_id'], |
| 87 | }, |
| 88 | }) |
| 89 | await ds.table(CHAT_COMPLETION_TRACES_TABLE).get({ |
| 90 | autoCreate: true, |
| 91 | schema: CHAT_COMPLETION_TRACES_SCHEMA, |
| 92 | timePartitioning: { |
| 93 | type: 'MONTH', |
| 94 | field: 'created_at', |
| 95 | }, |
no test coverage detected