chore: import upstream snapshot with attribution

python/samples/concepts/prompt_templates/configuring_prompts.py

@@ -0,0 +1,91 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+import asyncio
+
+from semantic_kernel import Kernel
+from semantic_kernel.connectors.ai.open_ai import OpenAIChatCompletion, OpenAIChatPromptExecutionSettings
+from semantic_kernel.contents import ChatHistory
+from semantic_kernel.functions import KernelArguments
+from semantic_kernel.prompt_template import InputVariable, PromptTemplateConfig
+
+kernel = Kernel()
+
+useAzureOpenAI = False
+model = "gpt-35-turbo" if useAzureOpenAI else "gpt-3.5-turbo"
+
+kernel.add_service(
+    OpenAIChatCompletion(service_id=model, ai_model_id=model),
+)
+
+template = """
+
+Previous information from chat:
+{{$chat_history}}
+
+User: {{$request}}
+Assistant:
+"""
+
+print("--- Rendered Prompt ---")
+prompt_template_config = PromptTemplateConfig(
+    template=template,
+    name="chat",
+    description="Chat with the assistant",
+    template_format="semantic-kernel",
+    input_variables=[
+        InputVariable(
+            name="chat_history",
+            description="The conversation history",
+            is_required=False,
+            default="",
+            allow_dangerously_set_content=True,
+        ),
+        InputVariable(name="request", description="The user's request", is_required=True),
+    ],
+    execution_settings=OpenAIChatPromptExecutionSettings(service_id=model, max_tokens=4000, temperature=0.2),
+)
+
+chat_function = kernel.add_function(
+    function_name="chat",
+    plugin_name="ChatBot",
+    prompt_template_config=prompt_template_config,
+)
+
+chat_history = ChatHistory()
+
+
+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(
+        function=chat_function,
+        arguments=KernelArguments(
+            request=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())