swarmauri_tool_jupyterstartkernel 0.11.0.dev1

Swarmauri notebook-orchestration tool for starting Jupyter kernels programmatically with jupyter_client.

Swarmauri Tool Jupyter Start Kernel

swarmauri_tool_jupyterstartkernel is a Swarmauri notebook-orchestration tool for starting a Jupyter kernel programmatically through jupyter_client. It is useful for notebook automation, code-execution workflows, agent-controlled kernel sessions, and CI flows that need a fresh kernel before running cells.

Why Use Swarmauri Tool Jupyter Start Kernel

• Start isolated Jupyter kernels inside Swarmauri workflows.
• Acquire a kernel ID programmatically for downstream notebook tooling.
• Prepare execution environments for cell-running and notebook-conversion tools.
• Keep kernel lifecycle control behind a reusable Swarmauri tool interface.

FAQ

What inputs does the tool accept?
kernel_name and an optional kernel_spec dictionary.

What does the tool return on success?
A dictionary containing kernel_name and kernel_id.

Does the tool expose the running KernelManager?
Yes. The instance stores the active manager and exposes it through get_kernel_manager().

How are startup failures reported?
The tool returns {"error": ...} if the kernel cannot be started.

Features

• Swarmauri ToolBase implementation registered as JupyterStartKernelTool.
• Starts Jupyter kernels by kernel name, defaulting to python3.
• Stores the active KernelManager for follow-on interactions.
• Returns simple, orchestration-friendly kernel identity metadata.
• Supports Python 3.10, 3.11, 3.12, 3.13, and 3.14.

Installation

uv add swarmauri_tool_jupyterstartkernel

pip install swarmauri_tool_jupyterstartkernel

Usage

from swarmauri_tool_jupyterstartkernel import JupyterStartKernelTool

tool = JupyterStartKernelTool()
result = tool(kernel_name="python3")

print(result)

Examples

Start a default Python kernel

from swarmauri_tool_jupyterstartkernel import JupyterStartKernelTool

tool = JupyterStartKernelTool()
result = tool()

print(result["kernel_id"])

Start a kernel and keep the manager reference

from swarmauri_tool_jupyterstartkernel import JupyterStartKernelTool

tool = JupyterStartKernelTool()
result = tool("python3")
manager = tool.get_kernel_manager()

print(result, manager)

Register the tool in a Swarmauri collection

from swarmauri_standard.tools.ToolCollection import ToolCollection
from swarmauri_tool_jupyterstartkernel import JupyterStartKernelTool

tools = ToolCollection(tools=[JupyterStartKernelTool()])
print(tools)

Related Packages

• swarmauri_tool_jupytershutdownkernel
• swarmauri_tool_jupyterexecutecell
• swarmauri_tool_jupyterruncell
• swarmauri_tool_jupyterclearoutput

Swarmauri Foundations

• swarmauri
• swarmauri_core
• swarmauri_base
• swarmauri_standard

More Documentation

• jupyter_client documentation
• IPython kernel documentation
• Swarmauri SDK repository

Best Practices

• Ensure the requested kernelspec exists before starting automation flows.
• Shut down kernels explicitly after use to avoid orphaned processes.
• Keep per-task kernels isolated when multiple workflows run concurrently.
• Store the returned kernel ID if other tools need to interact with the same session later.

License

This project is licensed under the Apache-2.0 License.