> ## Documentation Index > Fetch the complete documentation index at: https://docs.galileo.ai/llms.txt > Use this file to discover all available pages before exploring further. # Dataset validation > Schema and content checks Luna Studio runs on every dataset, and how to fix common errors. Every dataset added to Luna Studio — uploaded, fetched, generated, or imported — goes through validation. Validation determines whether the dataset can be used in a run. ## States Validation has four possible end states: | State | Meaning | | ----------------------------- | --------------------------------------------------------------------------------------- | | Validating… | In progress. Usually completes within a few seconds. | | Validated | Ready to use. | | Validated with warnings | Usable, but Luna noticed something worth checking (e.g. mixed casing, partial UTF-8). | | Validation error: `{message}` | Unusable until fixed. The dataset is saved in your org but can't be selected for a run. | The state appears in the run creation flow when Luna Studio checks a selected dataset: * The Selected dataset card in [Step 2](/luna-studio/ui/runs/new-run/step-2-test-set) and [Step 3](/luna-studio/ui/runs/new-run/step-3-training-set) of the run creation flow. ## What Luna checks ### Schema checks * The file parses as CSV or JSONL. * Required columns are present: * **Test sets** — metric-specific feature columns and `label`. * **Training sets** — metric-specific feature columns and `label` when the dataset is already labelled. * Column types match the metric's [output type](/luna-studio/ui/core-concepts#metrics) (e.g. labels are parseable as Boolean for a Boolean metric). ### Content checks * File encoding (UTF-8 expected). * Row count > 0. * Empty rows are flagged as warnings. * Inputs that exceed the model's max token limit are flagged. ### File checks (uploads and URLs) * File size within the upload limit. * For URLs: the URL is reachable; the response content type is appropriate. ## Common errors | Error message | Cause | Fix | | ---------------------------------------------- | --------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------- | | `Missing column "label" in uploaded CSV.` | Test set or labelled training set without a `label` column. | Add the column to your file and re-upload. For unlabelled training logs, use the label-only flow from Step 3. | | `Missing column "input" in uploaded CSV.` | Required `input` column missing. | Rename your input column to `input`, or include one. | | `Could not fetch URL.` | The URL was unreachable, returned a non-2xx status, or required auth. | Check the URL is correct; for cloud URLs, confirm the relevant integration has access. | | `Unsupported file type.` | The file isn't `.csv` or `.jsonl`. | Convert the file to one of the supported formats. | | `Empty dataset.` | The file parsed but had zero data rows. | Confirm the file isn't header-only. | | `Label values don't match metric output type.` | Labels can't be parsed as the metric's expected type. | Re-check labels (e.g. for Boolean: only `true`/`false` or `1`/`0`). | ## Common warnings | Warning | Cause | Action | | ----------------------------------------------- | ---------------------------------------- | --------------------------------------------------------------------------------------- | | `Mixed casing in labels.` | Labels like `True` and `true` are mixed. | Normalize case in your file. Luna will still validate but may produce a noisier metric. | | `Some rows exceed the model's max token limit.` | Long inputs that will be truncated. | Either trim the rows or accept the truncation. | | `Detected non-UTF-8 characters.` | The file isn't pure UTF-8. | Re-export the file as UTF-8. | ## Unlabelled training logs If uploaded or imported training logs are missing labels, Luna Studio does not train on them directly. It opens the label-only generation flow, uses the selected metric prompt to create labels, and saves a labelled training dataset. Generated training sets are always labelled. ## When validation fails mid-run If a dataset that was previously **Validated** later fails (e.g. the originating Galileo dataset changed), the run that consumed it can fail with a validation error. See [Run failed](/luna-studio/ui/reference/troubleshooting#run-failed). ## Re-validating Luna validates a dataset once at add-time and once per run launch. There's no manual "re-validate" button — to re-check a dataset, re-add it (or fetch the URL again). ## Where to go next Walk through the three sources. Run-time failures and how to recover.