Full level

full is standard plus two fields: prompt_text and output_text, the raw message content of the request. It exists for one purpose: capturing a workload faithfully enough to replay it, so a recipe can be tuned against your real traffic rather than a synthetic approximation.

Full ships customer content. The raw prompt and output go to every configured sink: the trace file, and the gen_ai.prompt / gen_ai.completion attributes of exported spans. Enable it only against sinks you control, never in production with customer data.

The record

Same fields as standard, plus:

Field	Meaning
`prompt_text`	The full rendered prompt, system and chat template included
`output_text`	The complete generated text

Example

One record from a support-assistant workload (content abridged):

{"request_id": "chatcmpl-7d3fa9b2", "t_arrival": 1789040231.522, "t_completion": 1789040235.108,
 "prompt_tokens": 634, "output_tokens": 187, "e2e_latency_s": 3.586, "ttft_s": null,
 "queue_wait_s": 0.006, "scheduler_family": "ltr-promptlen", "priority_score": -512.0,
 "prompt_text": "<|im_start|>system\nYou are the support assistant for Northwind Analytics. Answer from the provided context only.<|im_end|>\n<|im_start|>user\nContext: [invoice INV-2093: issued 2026-08-01, net-30, paid 2026-08-19] ...\nQuestion: My dashboard says invoice INV-2093 is overdue but we paid it three weeks ago. Can you check?<|im_end|>\n<|im_start|>assistant\n",
 "output_text": "I checked invoice INV-2093 against the records in the context: it was issued on 2026-08-01 with net-30 terms and marked paid on 2026-08-19, well within terms. The overdue flag on your dashboard is therefore stale rather than a missed payment. Two things usually cause this: ..."}

Note that prompt_text is the rendered prompt: chat-template markup and the system message are included, because that is what the engine actually served and what a replay must reproduce.

How a conversation appears in a trace

Traces carry no session identifier: one span per request, flat. A multi-turn conversation is still visible, because each turn's rendered prompt embeds every prior turn. Two consecutive spans from one session (OTLP export, abridged; <think></think> markers are the chat template's thinking-disabled artifact):

{"name": "llm_request",
 "attributes": [
   {"key": "cf.request_id", "value": {"stringValue": "chatcmpl-850f15e9afd74036-82d9d8e1"}},
   {"key": "gen_ai.usage.prompt_tokens", "value": {"intValue": "36"}},
   {"key": "cf.e2e_latency_s", "value": {"doubleValue": 0.1829}},
   {"key": "cf.queue_wait_s", "value": {"doubleValue": 0.0136}},
   {"key": "gen_ai.prompt", "value": {"stringValue": "system\nYou are the billing assistant. Be brief.\nuser\nWhere do I find my invoice history?\nassistant\n<think>\n\n</think>\n\n"}},
   {"key": "gen_ai.completion", "value": {"stringValue": "Billing > Invoices, top right of the console."}}
 ]}
{"name": "llm_request",
 "attributes": [
   {"key": "cf.request_id", "value": {"stringValue": "chatcmpl-93bcfebf2cf706f4-91470f16"}},
   {"key": "gen_ai.usage.prompt_tokens", "value": {"intValue": "73"}},
   {"key": "cf.e2e_latency_s", "value": {"doubleValue": 0.1221}},
   {"key": "cf.queue_wait_s", "value": {"doubleValue": 0.0099}},
   {"key": "gen_ai.prompt", "value": {"stringValue": "system\nYou are the billing assistant. Be brief.\nuser\nWhere do I find my invoice history?\nassistant\n<think>\n\n</think>\n\nBilling > Invoices, top right of the console.\nuser\nAnd past payment receipts?\nassistant\n<think>\n\n</think>\n\n"}},
   {"key": "gen_ai.completion", "value": {"stringValue": "Same page: each invoice row expands to its receipt."}}
 ]}

The second span's prompt contains the first span's prompt and answer as a prefix. That growing-prefix structure is what lets sessions be reconstructed from a flat trace, and it is also why full-level capture is required for faithful replay: the session grouping lives in the text, not in any metadata field.

Caveats

Scheduler coverage: the ltr, ltr-promptlen, affinity and trace schedulers include the text fields; tie and hybrid currently omit them.
Production guidance: run standard in production and switch to full only for bounded capture windows on traffic you are entitled to record.
On the container pathway, enabling either level is your action and your sinks; see Container tracing.

Full level

The record

Example

How a conversation appears in a trace

Caveats

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