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Request logging keeps a full-content record of your chat completions, prompts and responses, browsable in the dashboard and exportable as JSONL. It’s the raw material for improving your models: review real traffic, build evaluation sets, and curate fine-tuning datasets from what your users actually ask. It is off by default. Omnia’s standing posture is content-free: we never retain prompts or completions unless you explicitly choose it. Request logging is one of exactly two opt-in exceptions (the other is response caching).

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Enabling it

In the dashboard → Settings → Workspace → Request logging (owner/admin only):
1

Turn on the toggle

Takes effect at the gateway within a few seconds.
2

Pick a retention window

7, 30, or 90 days. Every logged request carries its own deletion deadline; retention is enforced row by row, automatically.

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What gets stored

Each entry also records the model, tag and trace id, token counts, and finish reason: the signals you filter by when curating. Credential-shaped strings are scrubbed before storage: API keys, bearer tokens, and similar patterns in your prompts are replaced with [redacted] automatically. This is defense-in-depth, not a guarantee; avoid sending secrets to models in the first place.

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Per-request opt-out

With logging enabled, any individual call can stay out:
The header can only reduce logging: with the workspace toggle off it does nothing.

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Browsing and exporting

The Logs page in the dashboard lists your logged traffic newest-first, filterable by model, tag, auto-detected segment (the system-prompt family a request belongs to: zero setup, works retroactively), time range, finish reason, and cache hits. Click any row for the full conversation, message by message, tool calls included. Export JSONL downloads the current filter as chat-format lines, one {"messages": [...]} object per exchange, with the assistant’s reply as the final message. That’s the standard shape for fine-tuning and evaluation pipelines, ours or anyone else’s. Exports are capped at 10,000 exchanges per download. Create dataset curates the current filter into a managed dataset instead: errored, truncated, empty, and duplicate exchanges are dropped automatically and every drop is reported by reason. The dataset keeps its provenance: including the segment it was cut from, so you always know which application surface trained on it. Optionally hold out 10% as a second, disjoint -eval dataset. No example appears in both, which is what makes it a valid set to evaluate against later. A dataset is a frozen snapshot: it does not age out when the logs it was curated from expire. The same asymmetry applies to grades (labels in the API); grades are permanent, while the logged conversations they graded are deleted on your retention window. Curate and grade what matters before it ages out.

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Multi-turn conversations are folded, not repeated

A chat application resends the whole history on every turn, so a 3-turn conversation is logged as three exchanges whose messages are nested:
Training on those as three separate examples would teach the model turn 1 three times and the final turn once, an implicit bias toward the start of every conversation. So we reconstruct them into one training example with a weight on each assistant turn:
Every turn survives and every turn is learned exactly once. The curation summary tells you when this happened (“842 earlier turns folded into 210 conversations”), so a dataset with fewer lines than exchanges is never a mystery.
Conversations are reconstructed from the message content itself, so this works without any tagging on your side. Independent steps of an agent run are not folded: they aren’t continuations of one another, so they stay as separate training examples.

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Tagging your traffic

Label each request with the task it belongs to, and every downstream surface (logs, datasets, evals) can be scoped to that one task:
Tags are content-free labels (≤64 chars). X-Omnia-Trace-Id groups the steps of one multi-step agent run. Neither is ever forwarded upstream. Didn’t tag? Auto-detected segments group logged traffic by system-prompt family with zero setup, retroactively. The tag stays the deliberate override. The two compose, so you can filter by both at once.

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From the API

Everything on the Logs page is available to a workspace API key:
Every returned row carries its segment (the auto-detected system-prompt family) and segment_exact (the exact prompt variant within it); pass a row’s segment back as ?segment=, or as filters.segment on POST /v1/datasets/from_logs, to slice traffic you never tagged. These endpoints return 409 while request logging is off, because an empty list would read as “no traffic” when the truth is “nothing is being captured”. See the Logs & datasets API reference.

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Privacy posture

  • Logged content is workspace-scoped: stored under your workspace’s key, never visible to any other tenant, never used by Omnia for anything.
  • Retention is per-row: each entry is deleted when its window expires, regardless of later settings changes.
  • Turning the toggle off stops all writes immediately; existing entries simply age out.
  • Telemetry and observability remain content-free exactly as before; this feature adds a separate, consented store; it doesn’t change the default.