samples: add DaoXE OpenAI-compatible chat completion example

python/samples/concepts/README.md

@@ -163,13 +163,14 @@
 
 - [Grounded](./grounding/grounded.py)
 
-### Local Models - Using the [`OpenAI connector`](https://github.com/microsoft/semantic-kernel/blob/main/python/semantic_kernel/connectors/ai/open_ai/services/open_ai_chat_completion.py) and [`OnnxGenAI connector`](https://github.com/microsoft/semantic-kernel/blob/main/python/semantic_kernel/connectors/ai/onnx/services/onnx_gen_ai_chat_completion.py) to talk to models hosted locally in Ollama, OnnxGenAI, and LM Studio
+### Local Models - Using the [`OpenAI connector`](https://github.com/microsoft/semantic-kernel/blob/main/python/semantic_kernel/connectors/ai/open_ai/services/open_ai_chat_completion.py) and [`OnnxGenAI connector`](https://github.com/microsoft/semantic-kernel/blob/main/python/semantic_kernel/connectors/ai/onnx/services/onnx_gen_ai_chat_completion.py) to talk to models hosted locally in Ollama, OnnxGenAI, and LM Studio, plus OpenAI-compatible gateways such as DaoXE
 
 - [ONNX Chat Completion](./local_models/onnx_chat_completion.py)
 - [LM Studio Text Embedding](./local_models/lm_studio_text_embedding.py)
 - [LM Studio Chat Completion](./local_models/lm_studio_chat_completion.py)
 - [ONNX Phi3 Vision Completion](./local_models/onnx_phi3_vision_completion.py)
 - [Ollama Chat Completion](./local_models/ollama_chat_completion.py)
+- [DaoXE Chat Completion (OpenAI-compatible gateway)](./local_models/daoxe_chat_completion.py)
 - [ONNX Text Completion](./local_models/onnx_text_completion.py)
 
 ### Logging - Showing how to set up logging

python/samples/concepts/local_models/daoxe_chat_completion.py

@@ -0,0 +1,102 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+"""OpenAI-compatible multi-model gateway sample using DaoXE.
+
+DaoXE exposes OpenAI Chat Completions at https://daoxe.com/v1 (and other protocols
+such as OpenAI Responses / Anthropic Messages for other clients). This sample uses
+Semantic Kernel's OpenAIChatCompletion connector with a custom AsyncOpenAI client,
+the same pattern as the Ollama / LM Studio samples.
+
+Requirements:
+- DAOXE_API_KEY environment variable
+- An exact model ID from your DaoXE account catalog (GET /v1/models)
+
+Docs / examples: https://github.com/seven7763/DaoXE-AI
+"""
+
+import asyncio
+import os
+
+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
+
+system_message = """
+You are a helpful assistant. Keep answers concise and practical.
+"""
+
+api_key = os.environ.get("DAOXE_API_KEY")
+if not api_key:
+    raise SystemExit("Set DAOXE_API_KEY to your DaoXE dashboard API key.")
+
+# Exact model ID from your account catalog — do not hardcode a public price list.
+ai_model_id = os.environ.get("DAOXE_MODEL")
+if not ai_model_id:
+    raise SystemExit(
+        "Set DAOXE_MODEL to an exact model ID from your DaoXE account catalog "
+        '(GET /v1/models), e.g. '
+        '`curl -H "Authorization: Bearer $DAOXE_API_KEY" https://daoxe.com/v1/models`.'
+    )
+
+kernel = Kernel()
+service_id = "daoxe"
+
+openAIClient: AsyncOpenAI = AsyncOpenAI(
+    api_key=api_key,
+    base_url="https://daoxe.com/v1",
+)
+kernel.add_service(
+    OpenAIChatCompletion(
+        service_id=service_id,
+        ai_model_id=ai_model_id,
+        async_client=openAIClient,
+    )
+)
+
+settings = kernel.get_prompt_execution_settings_from_service_id(service_id)
+settings.max_tokens = 256
+settings.temperature = 0.7
+
+chat_function = kernel.add_function(
+    plugin_name="ChatBot",
+    function_name="Chat",
+    prompt="{{$chat_history}}{{$user_input}}",
+    template_format="semantic-kernel",
+    prompt_execution_settings=settings,
+)
+
+chat_history = ChatHistory(system_message=system_message)
+
+
+async def chat() -> bool:
+    try:
+        user_input = input("User:> ")
+    except (KeyboardInterrupt, 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"Assistant:> {answer}")
+    return True
+
+
+async def main() -> None:
+    chatting = True
+    while chatting:
+        chatting = await chat()
+
+
+if __name__ == "__main__":
+    asyncio.run(main())