Usage analytics 

Opening the module 

Open AI > Operation > Analytics. The submodule sits next to the other LLM sections in the left-hand navigation and is admin-only, like the rest of the module.

A head editor who should see the usage of his own editors, and only theirs, gets a separate module instead of this one: AI usage of assigned groups.

Choosing a date range 

A range switcher at the top of the page selects the reporting window. The range is a plain ?range= link, so changing it is an ordinary page reload — there is no AJAX. Four presets are available:

KPI tiles 

A row of tiles summarises the selected range:

• Total cost — the summed estimated cost across the window.
• Total requests — the number of AI requests recorded.
• Total tokens — prompt plus completion tokens consumed.
• Providers — how many distinct providers were used.
• Models — how many distinct models were used.

These are totals for the chosen range, not all-time figures. From one million on, the request and token counts are shortened in the backend language ("17,5 Mio.", "17.5M"); the full number is shown on hover and read out by screen readers.

Cost and requests trend 

A line chart plots daily estimated cost and daily request count across the range. Days with no usage are filled in as zero so the line is continuous rather than skipping gaps. The points of the chart add up to the cost and request tiles above it: every row of a day counts towards that day, also when one day holds rows under several request_date values (for example local midnight next to a seed written at the database server's midnight).

Breakdown charts 

Four bar charts split the window's usage along different axes:

• By provider — cost and requests per service_provider (OpenAI, Anthropic, Ollama, …).
• By model — cost and requests per model. This dimension is new: it relies on the model_uid / model_id columns added to the usage table, so it only reflects usage recorded after that change.
• By service — cost and requests per service type (chat, vision, translation, speech, image).
• By extension — cost and requests per calling extension, see Per-extension table.

Per-extension table 

A table lists cost, requests and tokens per calling extension, ordered by cost. It answers which piece of software spent what: a consumer names itself with AbstractOptions::withCallerSource() (ADR-177), and that name is stored on the usage row alongside the money (ADR-178).

Where the entries come from:

• The compatibility layer nr-llm-compat tags every call it reroutes, so an intercepted third-party extension (ai_filemetadata, texter, ns_t3ai, …) shows up under its own extension key.
• Any other consumer that annotates its calls appears the same way.
• Everything else — wizard tasks, scheduler runs, playground calls and any consumer that does not annotate — is listed as Unattributed. That is the normal state, not an error.

Per-user table 

A table lists usage grouped by backend user, ordered by cost. Each row shows the user's request count, token total, and estimated cost for the selected range, plus a monthly-budget bar that visualises how much of their per-user budget (see Per-user AI budgets) they have consumed.

Requests made without an authenticated backend user (CLI, scheduler, be_user = 0) are grouped under a system row. Since TYPO3 14.3.8 a console command that authenticates, the scheduler included, records its usage under core's command-line user _cli_ instead, and this table lists that user by name.

Fallback rescues 

A table lists the runs a different configuration answered after the requested one failed — each line is one request the configuration you configured did not serve. It shows what was requested and what answered, each with its provider and model, how many configurations were tried, and how long the whole run took.

Unlike the rest of this module the list is read from the telemetry log (tx_nrllm_telemetry), not from the usage table, so it also covers runs that produced no billable usage.

Two things it deliberately does not show:

• Runs nobody served. A chain that was tried and exhausted names no serving configuration — it is a failure, not a rescue, and appears in the provider health scores instead.
• Runs recorded before this feature existed. Rows written by an older version carry no serving configuration and are left out rather than guessed at.

At most the 200 newest rescues of the period are listed. The limit counts rescues, not failed attempts, so a long outage — which writes one row per request — cannot push the rescues out of the list.

A configuration appearing here repeatedly is the signal to look at: its calls are being answered by a sibling, which may use a different provider, model and price than the one you selected.

A note on cost 

All cost figures are estimated. They are computed from the model pricing you configured (cents per 1M tokens, applied to the recorded prompt/completion token split), not billed back from the provider. Treat them as a planning and trend signal, not as an invoice. Costs are captured at call time, so they reflect the pricing in effect when each request ran. See ADR-029: Usage Analytics Dashboard for the design rationale.

Specialized services record their own units: images, characters or audio duration. Supported OpenAI image/speech/transcription estimates use configured model pricing or the bundled catalogue as applicable. An unknown/unmapped service cost can be stored as 0; this is not evidence of a free call or a complete provider invoice. See ADR-032: Specialized Usage Tracking and Pricing Catalog.

Configuration-bound streaming records usage through the streaming dispatcher, which also writes telemetry when enabled. The dispatcher estimates tokens from prompt and completion size and prices them using the configured model. These are local estimates, not the provider's final token counts. See Streaming support for the streaming contract.

Usage columns in the list views 

The Providers, Models, Configurations, and Tasks list views each carry three extra columns — Cost (30d), Requests (30d) and Tokens (30d) — summarising the last 30 days of usage for that row, so you can spot the heavy hitters without leaving the list.

Two attribution notes:

• The Providers column aggregates by adapter type (the value stored on each usage row), not by individual provider record — two providers that share an adapter therefore show the same figures.
• The Tasks column relies on per-task tracking: each task execution records its task_uid so usage rolls up to the task that triggered it. Calls made outside a task (direct API/service use) are not attributed to any task row.

Demo data for local development 

To populate the module with something to look at during local development, run the dev-only DDEV command:

ddev seed-demo

It generates roughly 90 days of realistic historic usage across providers, models, services, and users so the trend line, breakdown charts, and per-user table all have content. This command is for local DDEV environments only — do not run it against production data. For a calendar-month report, export and markup, open Monthly billing report. Health and circuit state use their own rolling window; see Provider health and circuits.