> ## Documentation Index
> Fetch the complete documentation index at: https://agent-observability-docs.splunk.com/llms.txt
> Use this file to discover all available pages before exploring further.

# FAQ

> Common questions about Luna Studio — datasets, models, integrations, and more.

If your question isn't answered here, check [Troubleshooting](/luna-studio/ui/reference/troubleshooting) for runtime issues.

## General

<AccordionGroup>
  <Accordion title="What is Luna Studio?">
    Luna Studio is Splunk Agent Observability's web app for **fine-tuning custom evaluators** for LLM applications. You bring a human-labelled test set, optionally generate a training set, fine-tune a Luna base model, and register eligible evaluators in the [Splunk Agent Observability evaluators store](/concepts/evaluators/overview). See [Welcome](/luna-studio/ui/index) for the longer pitch.
  </Accordion>

  <Accordion title="Who is it for?">
    Data scientists, ML engineers, and AI engineers who need evaluators tailored to a specific domain (legal, healthcare, RAG over internal docs, etc.). Use the [Luna Studio UI](/luna-studio/ui/index) for a guided, no-code workflow. Use the [Luna Studio SDK](/luna-studio/sdk/overview) when you want more control or need to run fine-tuning on your own infrastructure.
  </Accordion>

  <Accordion title="How is Luna Studio different from Splunk Agent Observability?">
    Splunk Agent Observability is the broader platform — evaluation, observability, guardrails. Luna Studio is the evaluator-fine-tuning workspace inside Splunk Agent Observability. Evaluators produced in Luna Studio are registered to the Splunk Agent Observability evaluators store, where they're usable
    across the rest of the platform.
  </Accordion>

  <Accordion title="How do I get Luna Studio for my organization?">
    Luna Studio is part of the enterprise tier of Splunk Agent Observability and is deployed by Splunk Agent Observability into your own cluster or cloud. See [Availability and deployment](/luna-studio/ui/availability), or [contact us](https://www.splunk.com/en_us/about-splunk/contact-us.html) to get started.
  </Accordion>
</AccordionGroup>

## Test sets and training sets

<AccordionGroup>
  <Accordion title="How big should my test set be?">
    Aim for 1,000-3,000 representative samples with a good class distribution when possible. Luna Studio enforces a minimum of 300 human-labelled rows total and at least 100 samples per class.
  </Accordion>

  <Accordion title="Do I have to upload a training set?">
    Not necessarily. If you have a training set, then sure, but if not, you can choose to generate data using **Generate from test set** — Luna Studio synthetically generates a training set from 20% of your test set. See [Step 3](/luna-studio/ui/runs/new-run/step-3-training-set#generate-from-test-set).

    Upload your own training set when you have labelled production logs that better represent the distribution you want to evaluate.
  </Accordion>

  <Accordion title="Can my training set be unlabelled?">
    Yes, for uploaded or imported logs. If validation finds that the label column is missing, choose **Label with evaluator prompt instead**, configure the provider and model, and start the labelling pass. Luna Studio saves the labelled result as a training dataset and uses that result for training. Generated training sets are always labelled.
  </Accordion>

  <Accordion title="Can I reuse a test set across multiple projects?">Yes. Datasets are organization-wide, not project-scoped. Once you've added a test set, every project in your organization can use it.</Accordion>

  <Accordion title="What file formats are supported?">
    CSV is the current end-to-end format for run validation and processing. The source picker accepts `.jsonl` during ingestion, but downstream run processing reads CSV, so convert JSONL to CSV before using it in a run. See [Add a dataset](/luna-studio/ui/datasets/add-a-dataset#format-reference).
  </Accordion>
</AccordionGroup>

## Evaluators

<AccordionGroup>
  <Accordion title="What's the difference between a predefined evaluator and a custom evaluator?">
    Predefined evaluators use battle-tested LLM-as-judge prompts curated by Splunk Agent Observability (e.g. Toxicity, Context adherence). Custom evaluators let you write your own prompt. Both fine-tune the same way.
  </Accordion>

  <Accordion title="What's a 'step' on an evaluator?">
    Luna Studio now describes this contract with **Input level** and **Evaluator shape**. The input level identifies where the evaluator evaluates data, while the evaluator shape identifies the required dataset columns. See [Custom prompts in Step
    1](/luna-studio/ui/runs/new-run/step-1-evaluator#input-levels-in-detail).
  </Accordion>

  <Accordion title="Can I edit a registered evaluator?">
    No. Once registered, the evaluator is snapshotted in the Splunk Agent Observability evaluators store. To iterate, launch a new run with the same evaluator template and register it under a new name (or unregister the old one in Splunk Agent Observability first).
  </Accordion>
</AccordionGroup>

## Training

<AccordionGroup>
  <Accordion title="How long does training take?">Depends on the base model, training set size and GPU availability. Most runs take a few hours, and larger models or larger datasets can take longer.</Accordion>

  <Accordion title="Can I cancel a training run?">
    Not from the current UI after fine-tuning has been launched. You can cancel a draft from the run wizard, including while training data is queued or being generated. The run details header and Training runs table do not currently expose cancellation for **Queued** or **Training** runs. A run can still appear as **Cancelled** when an API or the underlying platform records a cancellation. See [Run lifecycle](/luna-studio/ui/runs/lifecycle#cancelled).
  </Accordion>
</AccordionGroup>

## Integrations

<AccordionGroup>
  <Accordion title="Which LLM providers does Luna Studio support?">
    The current UI can configure OpenAI, Anthropic, Google Gemini, and Groq. Splunk Agent Observability is a separate deployment connection for dataset import and evaluator registration. Other provider cards are marked **Coming soon**. See [Integrations overview](/luna-studio/ui/integrations/overview).
  </Accordion>

  <Accordion title="Can I configure a custom model integration?">
    Not through the current Luna Studio UI. The Custom card is marked **Coming soon** and does not accept credentials yet. Contact your deployment administrator or Splunk Agent Observability representative about deployment-specific model access.
  </Accordion>
</AccordionGroup>

## Where to go next

<CardGroup cols={2}>
  <Card title="Troubleshooting" icon="bug" href="/luna-studio/ui/reference/troubleshooting">
    Runtime errors and how to recover.
  </Card>

  <Card title="Quickstart" icon="rocket" href="/luna-studio/ui/quickstart">
    End-to-end walkthrough.
  </Card>
</CardGroup>