Python: Introduce Pydantic settings (#6193)

### Motivation and Context

SK Python is tightly coupled to the use of a `.env` file to read all
secrets, keys, endpoints, and more. This doesn't scale well for users
who wish to be able to use environment variables with their SK
Applications. By introducing Pydantic Settings, it is possible to use
both environment variables as well as have a fall-back to a `.env` file
(via a `env_file_path` parameter), if desired.

By introducing Pydantic Settings, we are removing the requirement to
have to create Text/Embedding/Chat completion objects with an `api_key`
or other previously required information (in the case of
AzureChatCompletion that means an `endpoint`, an `api_key`, a
`deployment_name`, and an `api_version`). When the AI connector is
created, the Pydantic settings are loaded either via env vars or the
fall-back `.env` file, and that means the user can create a chat
completion object like:

```python
chat_completion = OpenAIChatCompletion(service_id="test")
```

or, to optionally override the `ai_model_id` env var:

```python
chat_completion = OpenAIChatCompletion(service_id="test", ai_model_id="gpt-4-1106")
```
Note: we have left the ability to specific an `api_key`/`org_id` for
`OpenAIChatCompletion` or a `deployment_name`, `endpoint`, `base_url`,
and `api_version` for `AzureChatCompletion` as before, but if your
settings are configured to use env vars/.env file then there is no need
to pass this information.

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### Description

The PR introduces the use of Pydantic settings and removes the use of
the python-dotenv library.
- Closes #1779 
- Updates notebooks, samples, code and tests to remove the explicit
config of api_key or other previous .env files values.
- Adds new unit test config using monkeypatch to simulate env variables
for testing
- All unit and integration tests passing

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### Contribution Checklist

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- [X] The code builds clean without any errors or warnings
- [X] The PR follows the [SK Contribution
Guidelines](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md)
and the [pre-submission formatting
script](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md#development-scripts)
raises no violations
- [X] All unit tests pass, and I have added new tests where possible
- [ ] I didn't break anyone 😄

python/DEV_SETUP.md

@@ -10,17 +10,31 @@ Make sure you have an
 [OpenAI API Key](https://platform.openai.com) or
 [Azure OpenAI service key](https://learn.microsoft.com/azure/cognitive-services/openai/quickstart?pivots=rest-api)
 
-Copy those keys into a `.env` file (see the `.env.example` file):
+There are two methods to manage keys, secrets, and endpoints:
 
-```bash
+1. Store them in environment variables. SK Python leverages pydantic settings to load keys, secrets, and endpoints. This means that there is a first attempt to load them from environment variables. The `.env` file naming applies to how the names should be stored as environment variables.
+
+2. If you'd like to use the `.env` file, you will need to configure the `.env` file with the following keys into a `.env` file (see the `.env.example` file):
+
+```
 OPENAI_API_KEY=""
 OPENAI_ORG_ID=""
-AZURE_OPENAI_DEPLOYMENT_NAME=""
+AZURE_OPENAI_CHAT_DEPLOYMENT_NAME=""
+AZURE_OPENAI_TEXT_DEPLOYMENT_NAME=""
+AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME=""
 AZURE_OPENAI_ENDPOINT=""
 AZURE_OPENAI_API_KEY=""
 ```
 
-We suggest adding a copy of the `.env` file under these folders:
+You will then configure the Text/ChatCompletion class with the keyword argument `env_file_path`:
+
+```python
+chat_completion = OpenAIChatCompletion(service_id="test", env_file_path=<path_to_file>)
+```
+
+This optional `env_file_path` parameter will allow pydantic settings to use the `.env` file as a fallback to read the settings.
+
+If using the second method, we suggest adding a copy of the `.env` file under these folders:
 
 - [python/tests](tests)
 - [./samples/getting_started](./samples/getting_started).