Build: Create a kernel with plugins

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◆ Before you start

Prerequisites

Python 3.11+Required
python --version
semantic-kernel>=1.0Required
pip install semantic-kernel
OPENAI_API_KEYRequired
export OPENAI_API_KEY=sk-...

🧩

Step 1 of 1

Create a kernel with plugins

Initialize a Semantic Kernel instance, add an AI service, and define a native plugin with Python functions that the kernel can call.

Tasks

Create a Kernel and add OpenAIChatCompletion service

Define a MathPlugin class with an add_numbers function decorated with @kernel_function

Invoke the function directly via kernel.invoke

Use auto function calling to let the LLM call the function from a chat message

🎯 What You'll Learn

▸Set up Kernel with OpenAI chat service
▸Create a native plugin using @kernel_function decorator
▸Invoke plugin functions directly and via natural language

Code

Pythonsk_demo.py
1 import asyncio
2 from semantic_kernel import Kernel
3 from semantic_kernel.connectors.ai.open_ai import OpenAIChatCompletion
4 from semantic_kernel.functions import kernel_function
5  
6 kernel = Kernel()
7 kernel.add_service(OpenAIChatCompletion(service_id="chat", ai_model_id="gpt-4o-mini"))
8  
9 class MathPlugin:
10     @kernel_function(name="add", description="Add two numbers")
11     def add(self, a: float, b: float) -> float:
12         return a + b
13  
14     @kernel_function(name="multiply", description="Multiply two numbers")
15     def multiply(self, a: float, b: float) -> float:
16         return a * b
17  
18 kernel.add_plugin(MathPlugin(), plugin_name="math")
19  
20 async def main():
21     result = await kernel.invoke("math", "add", a=3.5, b=2.5)
22     print(f"3.5 + 2.5 = {result}")
23  
24 asyncio.run(main())
25

💡 Pro Tips

▸Use kernel.add_plugin(MyPlugin(), plugin_name="my_plugin") to register
▸Auto function calling requires tool_choice="auto" — SK handles this automatically

Discussion

1 import asyncio 2 from semantic_kernel import Kernel 3 from semantic_kernel.connectors.ai.open_ai import OpenAIChatCompletion 4 from semantic_kernel.functions import kernel_function 5 6 kernel = Kernel() 7 kernel.add_service(OpenAIChatCompletion(service_id="chat", ai_model_id="gpt-4o-mini")) 8 9 class MathPlugin: 10 @kernel_function(name="add", description="Add two numbers") 11 def add(self, a: float, b: float) -> float: 12 return a + b 13 14 @kernel_function(name="multiply", description="Multiply two numbers") 15 def multiply(self, a: float, b: float) -> float: 16 return a * b 17 18 kernel.add_plugin(MathPlugin(), plugin_name="math") 19 20 async def main(): 21 result = await kernel.invoke("math", "add", a=3.5, b=2.5) 22 print(f"3.5 + 2.5 = {result}") 23 24 asyncio.run(main()) 25

1	import asyncio
2	from semantic_kernel import Kernel
3	from semantic_kernel.connectors.ai.open_ai import OpenAIChatCompletion
4	from semantic_kernel.functions import kernel_function
5
6	kernel = Kernel()
7	kernel.add_service(OpenAIChatCompletion(service_id="chat", ai_model_id="gpt-4o-mini"))
8
9	class MathPlugin:
10	@kernel_function(name="add", description="Add two numbers")
11	def add(self, a: float, b: float) -> float:
12	return a + b
13
14	@kernel_function(name="multiply", description="Multiply two numbers")
15	def multiply(self, a: float, b: float) -> float:
16	return a * b
17
18	kernel.add_plugin(MathPlugin(), plugin_name="math")
19
20	async def main():
21	result = await kernel.invoke("math", "add", a=3.5, b=2.5)
22	print(f"3.5 + 2.5 = {result}")
23
24	asyncio.run(main())
25