Base kernel for pydantic-ai kernels
Project description
Pydantic AI Base Kernel
This is wrapper around pydantic-ai agent, that allows to requests it through jupyter kernel.
It is meant to be subclassed to create new kernel-based agent, for adding tools or any special application.
Getting started
Within a python venv,
pip install pydantic-ai-kernel
In order to specify information about the agent, you have to set up a config file, and place it in : ~/.jupyter/jupyter_pydantic_ai_kernel_config.yaml. Here is an example :
agent_name: Cooking specialist
system_prompt: You are a specialist in cooking, and you are always ready to help people creating new cooking recipees.
model_name: qwen3:1.7b
provider:
name: ollama
url: http://localhost:11434/v1
Then, any jupyter frontend should be able to treat with this agent, for example :
• Notebook (you might need to restart the IDE) : select 'pydantic_ai' on top right of the notebook
• CLI : Install jupyter-console (pip install jupyter-console); and run jupyter console --kernel pydantic_ai
• Silik Signal Messaging : Access the kernel through Signal Message Application.
Creating your own agents
In order to create custom agents, you just need to create a new kernel, and subclass PydanticAIBaseKernel from this library.
You can then create tools, or any mechanism you want. We provide here juste the communication protocol between agent and user, through well known and proven jupyter kernels.
The configuration file for any subclass of PydanticAIBaseKernel will be fetched from : ~/.jupyter/jupyter_<kernel_name>_config.yaml; and must follows the same scheme as the one of pydantic_ai_kernel.
Dealing with multi-agents
Multi-agents means ear several agents that have access to the same context. To do so, you can for example use silik-kernel; an other kernel that allows several kernels to be started and managed through a single one.
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