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

# Trellis

**Trellis is an [open-source](#) framework for programmatically
orchestrating LLM workflows as Directed Acyclic Graphs (DAGs) in Python.** We've intentionally designed it to give
developers as much control as possible, and we've written documentation to make it incredibly easy to
get started.

Trellis is composed of only three abstractions: `Node`, `DAG`, and `LLM`.

* Node: the atomic unit of Trellis. Nodes are chained together to form a DAG.
  `Node` is an abstract class with only *one* method required to implement.
* DAG: a directed acyclic graph of `Node`s. It is the primary abstraction for orchestrating LLM workflows. When you
  add edges between `Node`s, you can specify a transformation function to reuse `Node`s and connect any two `Node`s.
  Trellis verifies the data flowing between `Nodes` in a `DAG` to ensure the flow of data is validated.
* LLM: a wrapper around a large language model with simple catches for common OpenAI errors. Currently, the only provider
  that Trellis supports is OpenAI.