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Graph Agents

Open In Colab

Compose multiple steps into a DAG the engine runs for you.

Minimal walkthrough

A graph is nodes (functions, tools, or agents) wired by dependencies. The engine runs independent nodes in parallel and feeds outputs downstream:

from neurosurfer.graph import Graph, GraphNode, GraphExecutor

graph = Graph(nodes=[
    GraphNode(id="fetch",   fn=fetch_docs),
    GraphNode(id="summarise", fn=summarise, depends_on=["fetch"]),
    GraphNode(id="report",  fn=make_report, depends_on=["summarise"]),
])

result = await GraphExecutor(graph).run(inputs={"query": "quarterly numbers"})
print(result["report"])

Nodes can be agents, so a step is a full tool-using run. Persisted, runnable Workflow packages wrap a graph with its tools and metadata for reuse.

Full notebook

The Colab notebook builds a multi-node workflow end to end, including agent nodes and parallel branches.

Next: Graph & Workflows guide · Architect · Tutorial 4 →