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Trigger Graph

Once you have created a graph template, you can trigger its execution by sending trigger states to the state manager. This guide shows you how to trigger graphs and monitor their execution.

📚 Getting Started: For a complete local setup guide covering both the state manager and dashboard, see our Local Setup Guide.

The recommended way to trigger graphs is using the Exosphere Python SDK, which provides a clean interface to the State Manager API.

from exospherehost import StateManager, TriggerState

async def trigger_graph():
    # Initialize state manager
    state_manager = StateManager(
        namespace="MyProject",
        state_manager_uri=EXOSPHERE_STATE_MANAGER_URI,
        key=EXOSPHERE_API_KEY
    )

    try:
        # Trigger the graph with optional store 
        result = await state_manager.trigger(
            "my-graph",
            inputs={"user_id": "123"},
            store={"cursor": "0"}  # persisted across nodes
        )
        print(f"Graph triggered successfully!")
        print(f"Run ID: {result['run_id']}")
        return result
    except Exception as e:
        print(f"Error triggering graph: {e}")
        raise

# Run the function
import asyncio
asyncio.run(trigger_graph())

Monitoring on Exosphere Dashboard

The Exosphere dashboard provides a powerful web-based interface for monitoring your graphs in real-time.

For more details on using the Exosphere dashboard see the Dashboard Guide.

Next Steps

  • Dashboard - Use the Exosphere dashboard for monitoring
  • Architecture - Learn about Exosphere's architecture
  • Fanout - Create parallel execution paths dynamically
  • Unite - Synchronize parallel execution paths
  • Retry Policy - Build resilient workflows
  • Store - Persist data across workflow execution