chore: import upstream snapshot with attribution

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+# 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
+```