### Motivation and Context
This PR introduces streaming methods to TextCompletionBase and
ChatCompletionBase. With this pr, you can stream LLM output in the
following ways:

```
import semantic_kernel as sk
from semantic_kernel.connectors.ai import ChatCompletionClientBase, TextCompletionClientBase, ChatRequestSettings, CompleteRequestSettings
from semantic_kernel.connectors.ai.open_ai import AzureTextCompletion, AzureChatCompletion, OpenAITextCompletion, OpenAIChatCompletion
from semantic_kernel.connectors.ai.hugging_face import HuggingFaceTextCompletion

kernel = sk.Kernel()

# Configure Azure LLM service
deployment, api_key, endpoint = sk.azure_openai_settings_from_dot_env()
text_service = AzureTextCompletion("text-davinci-003", endpoint, api_key)
chat_service = AzureChatCompletion("gpt-35-turbo", endpoint, api_key)

# Configure OpenAI service
api_key, org_id = sk.openai_settings_from_dot_env()
oai_text_service = OpenAITextCompletion("text-davinci-003", api_key, org_id)
oai_chat_service = OpenAIChatCompletion("gpt-3.5-turbo", api_key, org_id)

# Configure Hugging Face service
hf_text_service = HuggingFaceTextCompletion("gpt2", task="text-generation")

request_settings = CompleteRequestSettings(
    max_tokens=1000,
    temperature=0.7,
    top_p=1,
    frequency_penalty=0.5,
    presence_penalty=0.5
)

stream = oai_text_service.complete_stream_async("Write an essay on why AI is awesome:", request_settings)
async for text in stream:
    print(text, end = "") # end = "" to avoid newlines

chat_request_settings = ChatRequestSettings(
    max_tokens=1000,
    temperature=0.7,
    top_p=1,
    frequency_penalty=0.5,
    presence_penalty=0.5,
)

stream = oai_chat_service.complete_chat_stream_async([("user","Write an essay on why AI is awesome:")], chat_request_settings)
async for text in stream:
    print(text, end = "") # end = "" to avoid newlines

request_settings = CompleteRequestSettings(
    max_tokens=256,
    temperature=0.7,
    top_p=1,
    frequency_penalty=0.5,
    presence_penalty=0.5
)

stream = hf_text_service.complete_stream_async("Hi my name is ", request_settings)
async for text in stream:
    print(text, end = "") # end = "" to avoid newlines
```
**Out of Scope**: Improving the chat history interface with come in a
future PR

### Description
- added the method complete_stream_async to TextCompletionBase
- added the method complete_chat_stream_async to ChatCompletionBase
- Updated OpenAI and Hugging Face text completion service classes to
support new streaming methods
- Added new __init__.py to make importing service classes