Install Microsoft Semantic Kernel Locally and Integrate in Your App

 This video installs Semantic Kernel locally and shows how it works. Semantic Kernel is an SDK that integrates LLMs like OpenAI, Azure OpenAI, and Hugging Face with conventional programming languages like C#, Python, and Java.

Code:

import asyncio

from semantic_kernel import Kernel

from semantic_kernel.connectors.ai.open_ai import OpenAIChatCompletion, AzureChatCompletion

from semantic_kernel.prompt_template import PromptTemplateConfig

import os

from dotenv import load_dotenv, find_dotenv

_ = load_dotenv(find_dotenv())

kernel = Kernel()

# Prepare OpenAI service using credentials stored in the `.env` file

service_id="chat-gpt"

kernel.add_service(OpenAIChatCompletion(service_id=service_id,ai_model_id="gpt-3.5-turbo",api_key="sk-",))

# Define the request settings

req_settings = kernel.get_prompt_execution_settings_from_service_id(service_id)

req_settings.max_tokens = 2000

req_settings.temperature = 0.7

req_settings.top_p = 0.8

prompt = """

1) A robot may not injure a human being or, through inaction,

allow a human being to come to harm.

2) A robot must obey orders given it by human beings except where

such orders would conflict with the First Law.

3) A robot must protect its own existence as long as such protection

does not conflict with the First or Second Law.

Give me the TLDR in exactly 5 words."""

prompt_template_config = PromptTemplateConfig(

    template=prompt,

    name="tldr",

    template_format="semantic-kernel",

    execution_settings=req_settings,

)

function = kernel.add_function(

    function_name="tldr_function",

    plugin_name="tldr_plugin",

    prompt_template_config=prompt_template_config,

)

# Run your prompt

# Note: functions are run asynchronously

async def main():

    result = await kernel.invoke(function)

    print(result) # => Robots must not harm humans.

if __name__ == "__main__":

    asyncio.run(main())

# If running from a jupyter-notebook:

# await main()