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Session

User
chris.scott@dext.com · Chris Scott
Started
2026-09-05 16:19
Last activity
2026-09-05 16:19
Questions
1
Grouping
time_gap — inferred — consecutive questions from this user with no long gap
session_id
9cb715ef-e82d-4b24-9bb4-5d9c4b85b994

Transcript

  1. 2026-09-05 16:21 ask success $1.6469 159.5 s full detail →
    What was UK churn (churned MRR) by month from April 2024 through August 2026? Please use the UK finance country grouping and return monthly churn value and, if available, the number of churned accounts per month.
    I can’t accurately return UK monthly churned MRR for April 2024–August 2026 from the provided documentation. The available approved query covers **Direct Channel Transfer**, but it does not document the UK finance-country grouping field, the value used to identify churn in `dynamic_churn_type`, or a measure for the number of churned accounts. Substituting fields would risk an incorrect result. - **Available month field:** `omni_dbt__eds_bookings_prepare_channel_transfer.churn_date[month]` - **Available MRR-change measure:** `omni_dbt__eds_bookings_prepare_channel_transfer.total_prepare_bookings_mrr_change_amount` - **Missing:** UK finance-country grouping field - **Missing:** documented churn classification/filter value - **Missing:** churned-account count measure or account-level grain - **Required period:** April 2024 through August 2026 Please contact the Analytics team to confirm these fields and the correct topic. **Warning: This answer was generated by AI and should be double-checked.**
    Bookings

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.