Session
- User
-
yordan@dext.com
· Yordan Todorov Ivanov
- Started
- 2026-08-05 07:39
- Last activity
- 2026-08-05 07:48
- Questions
-
4
- Grouping
- backfill — reconstructed from timing by migration 011
- session_id
- bc0a3682-c41b-4ecd-a58e-d3d81bd330b9
Transcript
-
For every partner practice account, grouped by parent_account_crn, show the count of client accounts under it and the count of those client accounts that have a paid subscription. Return the full result set for all practices, not limited.
No answer recorded.
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For every partner practice, grouped by parent_account_crn, show total number of distinct client accounts under it, and separately the number of those client accounts with a paid Dext subscription. Do not filter to only paid accounts - I need both the total and the paid subset as two columns. Return full result set, no limit.
No answer recorded.
-
For every partner practice account, grouped by parent_account_crn, show the total number of distinct client accounts under it (do not filter by paid subscription status at all). Return the full result set, no limit.
No answer recorded.
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Using omni_dbt__eds_all_accounts, grouped by parent_account_crn, excluding demo accounts, excluding suspended accounts, excluding reseller salesforce_account_type, where has_dext_parent is true, finance_account_type is Corporate, and is_latest_available_date is true, show total_clients (distinct client count) with NO filter on parent_or_client_has_dext_paid_subscription. Return the full result set, no limit.
No answer recorded.
Cost is the LLM completion spend LiteLLM priced for each call, summed per
request.
Chandler is running on the Codex CLI, which draws ChatGPT plan quota
rather than per-token API billing, so this figure is not money paid —
it is what the same traffic would have cost on the API, priced from the
token counts Codex reports. Read it as the size of the bill avoided.
Two known limits: embedding spend is not recorded, so
retrieval and matching cost is missing, and because the figure is one sum
per request it cannot be split by model within a request — a
request's classifier and agent calls can use different models while
llm_model holds only one name.
Only authenticated calls are logged, USAGE_LOG_ENABLED can
switch logging off, and log writes are fail-soft — this is not a complete
record of traffic. Questions are grouped into sessions: a session is
exact when the caller echoed its id back to us and otherwise inferred from
a 30-minute gap in that user’s activity, so a grouping is only as
good as the source shown on the session itself. A call with no
attributable user gets no session at all; those questions are listed
separately rather than dropped.