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

# Core Concepts

> Understand the core ideas behind the Runtime

Inworld's Unreal Runtime is a powerful tool for building AI-powered experiences in Unreal. Key features include:

* **AI Component Library**: A library of powerful AI components, such as LLMs, Text-to-Speech (TTS), and Speech-to-Text (STT), that can be constructed into **Graphs** to power conversational characters, interactive agents, and other advanced AI-driven experiences in your Unreal projects.
* **Rich Observability**: Dashboards, traces, and logs with no extra setup required. These enable you to debug, observe, and improve your AI interactions.
* **Playgrounds**: Quickly test different models and prompts before adding them to your experience.

## Graphs

At the core of Inworld's Runtime is a high-performance, C++ based graph execution engine. The engine executes **Graphs** organized from **Nodes** and **Edges**, where each node performs a specific processing task—often an AI operation such as language generation (LLM), speech-to-text (STT), or text-to-speech (TTS)—and edges define the flow of data between them.

A graph:

* Contains a collection of nodes
* Defines edges between nodes
* Must have at least one start node
* Must have at least one end node
* Supports both linear and non-linear execution paths

The Runtime comes with a **[visual graph editor](/unreal-engine/runtime/graph-editor)** to make it easy to construct and modify your graphs.

### Nodes

Nodes are building blocks that perform a specific processing task, such as speech-to-text conversion, intent detection, or language model interaction. **Built-in Nodes** are provided with pre-built functionality for common use cases, with the option to create **Custom Nodes** to extend the runtime's capabilities.

Nodes:

* Encapsulate ML models or transformations with standard interfaces
* Process input data and produce output data
* Include built-in telemetry to support performance monitoring and debugging capabilities
* Have built-in error handling
* Handle lifecycle management, including standardized initialization and cleanup on graph shutdown

See the [Runtime Reference](/unreal-engine/runtime/runtime-reference/InworldNode/InworldNode) for more details on available nodes.

#### Primitives

Many of the built-in nodes rely upon **primitives**: fundamental components like Large Language Models (LLMs), Text-to-Speech (TTS), and Text Embedders. These are the "raw ingredients" of any AI-powered application.

Think of them as a library of high-performance AI modules, designed to abstract away the complexities of working with various providers, models, and hardware—allowing you to build on a consistent, provider-agnostic foundation. We recommend using primitives through our built-in nodes, but you can also leverage them directly in custom nodes.

See this [guide](/unreal-engine/runtime/configuring-primitives) for more details about configuring primitives.

### Edges

Edges define the flow of data between nodes, creating a processing pipeline. The runtime supports sophisticated edge configurations including:

* **Conditions**: Control data flow based on conditions
* **Connection Types**: Optional vs. required connections
* **Loops**: Iterative processing capabilities

## Observability

Runtime provides rich observability tools with no extra setup required. You can monitor your AI interactions through:

* **[Traces](/portal/traces)**: Understand the flow of your application with detailed execution traces. Use them to identify latency bottlenecks and debug issues when they arise.
* **[Logs](/portal/logs)**: Review historical data to monitor errors and debug issues.
* **[Dashboards](/portal/dashboards)**: Get real-time visibility into your application health. Track performance, resource usage, and application KPIs through comprehensive dashboards and detailed data views.

## Experiments

Runtime lets you iterate on prompts, models, and other configs (for example LLM and TTS) without redeploying code for already shipped builds. See the [Experiments guide](/unreal-engine/runtime/experiments) for detailed information on setting up and running A/B experiments.

## Playgrounds

Inworld Portal provides interactive **Playgrounds** that let you experiment with different models and tune prompts before deploying them in graph variants:

* **LLM Playground**: Experiment with different language models, prompts, and response settings.
* **TTS Playground**: Try different models, voices, and clone your own voice.