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

# Introduction

> Check out how prompts work on Basalt, how to interact with them and what are the available features in the SDK.

# What are prompts?

In Basalt, a **prompt** is a reusable, versioned template that describes how your AI should behave in a given context.

Instead of hard‑coding strings like "You are a support bot…" all over your codebase, you define prompts once in Basalt, give them a stable slug, and reference them from your applications via the SDK or API.

A prompt typically combines:

* **System behavior** – role, tone, and constraints (e.g. “You are a senior support agent…”)
* **Task instructions** – what the model should do (e.g. “Summarize this ticket in 3 bullet points…”)
* **Examples** – optional few-shot examples to steer behavior
* **Variables** – placeholders like `{{customer_message}}` filled at runtime
* **Model configuration** – provider, model name, and parameters (temperature, max tokens, etc.)

Prompts become first-class, shareable building blocks you can reuse across:

* User-facing features (assistants, copilots, search, recommendations)
* Internal tools (support, operations, data quality checks)
* Background workflows (cron jobs, pipelines, agents)

## Prompts Management

Basalt’s Prompts API lets you manage these templates like code:

* Prompts are **versioned** so you always know what is running.
* You **deploy** versions to environments using **tags** (for example `production`, `staging`, `latest`).
* You can evolve prompts safely over time while keeping older versions available for rollback or comparison.

With the Prompts API you can:

* **Create and update prompts** as your product or use cases evolve
* **Track versions** to understand which behavior is live in each environment
* **Deploy using tags** instead of hard-coding version numbers in your application
* **Roll out changes gradually** by pointing different services or environments at different tags
* **Attach model settings** directly to prompts so configuration travels with the template

## Overview

At a high level, the Prompts API enables you to:

* **Store prompts centrally** with full version history
* **Deploy prompts with tags** (e.g. `production`, `staging`, `latest`)
* **Substitute variables dynamically** using Jinja2 templates
* **Cache prompts for performance** with graceful fallback
* **Manage model configurations** alongside prompt content

In the rest of this section you’ll see:

* How to **define** prompts and variables in Basalt
* How to **fetch** prompts from the SDK by slug, tag, or version
* How to **safely update and roll back** prompts with versioning
* How to **test and iterate** on prompt changes without risking production