inference_graph provides a few main items:

• a Graph definition.
• a way to add Nodes to the Graph with graph.stage_node.
• a way to execute the Graph with some input.
• a wrap! macro to turn your async function into an op-compatible function.

The nodes also will need to specify an op, which is almost a async fn(Vec<String>) -> String, but because of rust type aliases not liking async functions, is not quite that exact type. Luckily, we also provide a wrap! that lets you pass in a async fn(Vec<String>) -> String and converts it to the exact type needed.

Creating a graph, adding some nodes that use an op to concatenate the strings passed in for the argument, and retrieving the output might look something like this:

use inference_graph::graph::Graph;
use inference_graph::wrap;

async fn concat(x: Vec<String>) -> String {
  x.concat()
}

#[tokio::main]
async fn main() {
  let mut graph = Graph::default();
  graph.stage_node("A".into(), vec!["entrypoint".into()], wrap!(concat));
  graph.stage_node("B".into(), vec!["entrypoint".into()], wrap!(concat));
  graph.stage_node("C".into(), vec!["A".into(), "B".into()], wrap!(concat));
  let output = graph.run("hubba".into(), "C".into()).await;
  assert_eq!(output.unwrap(), "hubbahubba".to_string());
}