Setup¶

Step 1: Import Semantic Kernel SDK from pypi.org

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!python -m pip install semantic-kernel==0.3.10.dev0

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import semantic_kernel as sk

kernel = sk.Kernel()

Option 1: using OpenAI¶

Step 2: Add your OpenAI Key key to a .env file in the same folder (org Id only if you have multiple orgs):

OPENAI_API_KEY="sk-..."
OPENAI_ORG_ID=""

and add OpenAI Chat Completion to the kernel:

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from semantic_kernel.connectors.ai.open_ai import OpenAIChatCompletion

api_key, org_id = sk.openai_settings_from_dot_env()

kernel.add_chat_service("chat-gpt", OpenAIChatCompletion("gpt-3.5-turbo", api_key, org_id))

Option 2: using Azure OpenAI¶

Step 2: Add your Azure Open AI Service key settings to a .env file in the same folder:

AZURE_OPENAI_API_KEY="..."
AZURE_OPENAI_ENDPOINT="https://..."
AZURE_OPENAI_DEPLOYMENT_NAME="..."

and add Azure OpenAI Chat Completion to the kernel:

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from semantic_kernel.connectors.ai.open_ai import AzureChatCompletion

deployment, api_key, endpoint = sk.azure_openai_settings_from_dot_env()

kernel.add_chat_service("chat_completion", AzureChatCompletion(deployment, endpoint, api_key))

Run a Semantic Function¶

Step 3: Load a Skill and run a semantic function:

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skill = kernel.import_semantic_skill_from_directory("../../samples/skills", "FunSkill")
joke_function = skill["Joke"]

print(joke_function("time travel to dinosaur age"))