> ## 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.
# Luna Studio SDK
> Use the Luna Studio SDK to generate data, fine-tune custom Luna metrics, and deploy them to Galileo.
The Luna Studio SDK gives you a code-first workflow for building custom Luna metrics. You can generate or label training data, fine-tune a Luna metric, evaluate the results, and register the trained metric in Galileo.
## What you can do
Set up the Python package and optional extras for your LLM provider and deployment environment.
Follow the end-to-end workflow for preparing data, configuring the pipeline, and fine-tuning your metric.
Register a trained Luna metric so it can be used across the Galileo platform.
Pick a hands-on guide for your metric input shape, including spans, traces, and sessions.
## Minimal example
Copy this sample config to a YAML file called `config.yaml`:
```yaml theme={null}
run_steps:
- data_generation
- training
pipeline_provider: "local"
metric_name: "custom"
pipeline:
pipeline_name: "galileo-luna-ft-sample-run"
data_generation:
metric:
name: off_topic_detection
description:
type: binary
input_format: single
llmaj_source_prompt: "Detect if the user query is off-topic."
source_data:
dataset:
source_type: "huggingface"
huggingface:
name: "rungalileo/off-topic-sample"
generation:
total_examples: 50
output:
push_to_hub: false
local_path: "./data/generated_data"
dataset:
repo_name: off-topic-sample-training
data_quality_metrics:
enabled: false
training:
metric:
type: boolean
dataset:
name: off-topic-sample-training
local: true
local_path: "./data/generated_data"
prompt_template:
output:
model_name: "off-topic-detection-galileo-luna-ft"
push_to_hub: false
local_path: finetuned_models
training:
num_train_epochs: 1
use_wandb: false
```
## Where to go next
Install the package and choose the right optional extras.
Understand the full workflow for data generation and training.
Learn how to register the trained model in Galileo.
Jump straight to an example that matches your input shape.