# SK Python Documentation Examples

This project contains a collection of examples used in documentation on [learn.microsoft.com](https://learn.microsoft.com/en-us/semantic-kernel/).

## Prerequisites

- [Python](https://www.python.org/downloads/) 3.10 and above
- Install Semantic Kernel through PyPi:
  ```bash
  pip install semantic-kernel
  ```

## Configuring the sample

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](https://platform.openai.com) or
[Azure Open AI service key](https://azure.microsoft.com/en-us/products/ai-services/openai-service)

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._

## Running the sample

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/learn_resources/plugin.py
```