> ## Documentation Index
> Fetch the complete documentation index at: https://docs.oumi.ai/llms.txt
> Use this file to discover all available pages before exploring further.
# INFERENCE LOGS
> Review the requests your deployment has served, and turn real production traffic into a training dataset
Every call your deployment serves can be recorded, giving you the actual prompts your model receives in production. Those logs are useful twice: first for debugging what went wrong on a specific request, then as raw material for your next training run.
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## ENABLE LOGGING
Inference logging is a per-deployment setting, on by default, that records the requests and responses your deployment serves. Turn it off to keep production traffic out of the logs entirely. It works the same way for models you train and for [external models](/guides/deployment/deploy-a-model#external-model) served by OpenAI or Anthropic.
Logging also feeds the deployment's observability features: [health metrics](/guides/deployment/health-metrics) are computed from the logs, and [quality monitoring](/guides/deployment/monitoring) scores a sample of them. Turning logging off turns those off too.
Turning logging on affects future requests. Traffic served while it was off was never recorded and cannot be recovered.
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## READ THE LOGS
The **Inference Logs** tab lists one row per request, with a preview of the exchange alongside its status, timing, and token counts.
Open a single entry to see the full input and output messages, the token counts and latency for that call, and the error message if it failed.
To debug a failure, open the failed request and read its error message alongside the input that produced it.
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## EXPORT LOGS TO A DATASET
This is how the loop closes. Take a slice of real production traffic and turn it into a dataset you can evaluate against, synthesize from, or fine-tune on.
From the **Inference Logs** tab, click `Export as Dataset`:
1. Choose `Create new dataset` and give it a name, or switch to the other tab to append to an existing dataset.
2. Set `Maximum Logs`. The most recent logs are included first, so this acts as a "latest N requests" cap.
3. Set a `Start Date` and `End Date` to bound the window.
4. Click `Generate Dataset`.
The export runs in the background, and the dataset appears on your **Datasets** page when it finishes.
You can also ask the Oumi Agent to export logs for you, and to summarize traffic or find failing calls without leaving chat.
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## WHAT'S NEXT
Score a sample of these logs with LLM judges and watch quality trends.
Inspect and validate the dataset your exported logs produced.