The sk-python-azure-functions application demonstrates how to execute a semantic function within an Azure Function.

• Python >=3.8 and <3.11
• Azure Functions
• Azurite. Run the services from the VS Code status bar.
• Semantic Kernel Tools

The starter 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:

OPENAI_API_KEY=""
OPENAI_ORG_ID=""
AZURE_OPENAI_DEPLOYMENT_NAME=""
AZURE_OPENAI_ENDPOINT=""
AZURE_OPENAI_API_KEY=""

To run the console application within Visual Studio Code, run Azurite from the status bar or command pallette, then just hit F5. As configured in launch.json and tasks.json, Visual Studio Code will create a virtual environment at .venv and run pip install requirements.txt.

To run from command line, run the following:

python -m venv .venv
.venv\Scripts\python -m pip install -r requirements.txt # Location of python within venv depends on OS
.venv\Scripts\activate
func host start

In your browser, visit http://localhost:7071/api/skills/{skill_name/functions/{function_name} to execute a skill. For example, http://localhost:7071/api/skills/FunSkill/functions/Joke will execute the example Joke function in the FunSkill skill.

To provide input, send a POST request with a JSON body, e.g. provide this as input to the Joke function: {"input": "time traveling to dinosaur age", "style": "deadpan"}