Bumps
[xt0rted/slash-command-action](https://github.com/xt0rted/slash-command-action)

Bumps [ad-m/github-push-action](https://github.com/ad-m/github-push-action) from 0.5.0 to 0.6.0.

Bumps
[xt0rted/pull-request-comment-branch](https://github.com/xt0rted/pull-request-comment-branch) from 1 to 2.

…174.8 to 8.0.0-preview.4.23259.5 in /dotnet (#1164)

Bumps
[Microsoft.Extensions.DependencyInjection](https://github.com/dotnet/runtime)
from 8.0.0-preview.3.23174.8 to 8.0.0-preview.4.23259.5.

### 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

### Description
Removing the DocFX csproj and associated files. Replacing this with a
**GitHub Actions** job that does not require this csproj in the repo.
Having this project in the repo takes time when running dotnet format,
and is additional code and complexity requiring maintenance. Removing
for cleanup.

Bumps [Pgvector](https://github.com/pgvector/pgvector-dotnet) from 0.1.2 to 0.1.3.

…p-server (#1159)

Bumps [requests](https://github.com/psf/requests) from 2.27.1 to 2.31.0.

Bumps [requests](https://github.com/psf/requests) from 2.30.0 to 2.31.0.