chore: import upstream snapshot with attribution

python/samples/concepts/local_models/lm_studio_chat_completion.py

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+# Copyright (c) Microsoft. All rights reserved.
+
+
+import asyncio
+
+from openai import AsyncOpenAI
+
+from semantic_kernel.connectors.ai.open_ai import OpenAIChatCompletion
+from semantic_kernel.contents.chat_history import ChatHistory
+from semantic_kernel.functions.kernel_arguments import KernelArguments
+from semantic_kernel.kernel import Kernel
+
+# This concept sample shows how to use the OpenAI connector to create a
+# chat experience with a local model running in LM studio: https://lmstudio.ai/
+# Please follow the instructions here: https://lmstudio.ai/docs/local-server to set up LM studio.
+# The default model used in this sample is phi3 due to its compact size.
+
+system_message = """
+You are a chat bot. Your name is Mosscap and
+you have one goal: figure out what people need.
+Your full name, should you need to know it, is
+Splendid Speckled Mosscap. You communicate
+effectively, but you tend to answer with long
+flowery prose.
+"""
+
+kernel = Kernel()
+
+service_id = "local-gpt"
+
+openAIClient: AsyncOpenAI = AsyncOpenAI(
+    api_key="fake-key",  # This cannot be an empty string, use a fake key
+    base_url="http://localhost:1234/v1",
+)
+kernel.add_service(OpenAIChatCompletion(service_id=service_id, ai_model_id="phi3", async_client=openAIClient))
+
+settings = kernel.get_prompt_execution_settings_from_service_id(service_id)
+settings.max_tokens = 2000
+settings.temperature = 0.7
+settings.top_p = 0.8
+
+chat_function = kernel.add_function(
+    plugin_name="ChatBot",
+    function_name="Chat",
+    prompt="{{$chat_history}}{{$user_input}}",
+    template_format="semantic-kernel",
+    prompt_execution_settings=settings,
+)
+
+chat_history = ChatHistory(system_message=system_message)
+chat_history.add_user_message("Hi there, who are you?")
+chat_history.add_assistant_message("I am Mosscap, a chat bot. I'm trying to figure out what people need")
+
+
+async def chat() -> bool:
+    try:
+        user_input = input("User:> ")
+    except KeyboardInterrupt:
+        print("\n\nExiting chat...")
+        return False
+    except EOFError:
+        print("\n\nExiting chat...")
+        return False
+
+    if user_input == "exit":
+        print("\n\nExiting chat...")
+        return False
+
+    answer = await kernel.invoke(chat_function, KernelArguments(user_input=user_input, chat_history=chat_history))
+    chat_history.add_user_message(user_input)
+    chat_history.add_assistant_message(str(answer))
+    print(f"Mosscap:> {answer}")
+    return True
+
+
+async def main() -> None:
+    chatting = True
+    while chatting:
+        chatting = await chat()
+
+
+if __name__ == "__main__":
+    asyncio.run(main())