This project contains a collection of examples used in documentation on learn.microsoft.com.
- Python 3.10 and above
- Install Semantic Kernel through PyPi:
pip install semantic-kernel
The samples can be configured with a .env
file in the project which holds api keys and other secrets and configurations.
Make sure you have an Open AI API Key or Azure Open AI service key
Copy the .env.example
file to a new file named .env
. Then, copy those keys into the .env
file:
GLOBAL_LLM_SERVICE="OpenAI" # Toggle between "OpenAI" or "AzureOpenAI"
OPENAI_CHAT_MODEL_ID="gpt-3.5-turbo-0125"
OPENAI_TEXT_MODEL_ID="gpt-3.5-turbo-instruct"
OPENAI_API_KEY=""
OPENAI_ORG_ID=""
AZURE_OPENAI_CHAT_DEPLOYMENT_NAME="gpt-35-turbo"
AZURE_OPENAI_TEXT_DEPLOYMENT_NAME="gpt-35-turbo-instruct"
AZURE_OPENAI_ENDPOINT=""
AZURE_OPENAI_API_KEY=""
AZURE_OPENAI_API_VERSION=""
Note: if running the examples with VSCode, it will look for your .env file at the main root of the repository.
To run the console application within Visual Studio Code, just hit F5
.
Otherwise the sample can be run via the command line:
python.exe <absolute_path_to_sk_code>/python/samples/documentation_examples/planner.py