chore: import upstream snapshot with attribution

python/samples/concepts/local_models/onnx_chat_completion.py

@@ -0,0 +1,75 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+
+import asyncio
+
+from semantic_kernel.connectors.ai.onnx import OnnxGenAIChatCompletion, OnnxGenAIPromptExecutionSettings
+from semantic_kernel.contents.chat_history import ChatHistory
+from semantic_kernel.kernel import Kernel
+
+# This concept sample shows how to use the Onnx connector with
+# a local model running in Onnx
+
+kernel = Kernel()
+
+service_id = "phi3"
+#############################################
+# Make sure to download an ONNX model
+# (https://huggingface.co/microsoft/Phi-3-mini-4k-instruct-onnx)
+# If onnxruntime-genai is used:
+# use the model stored in /cpu folder
+# If onnxruntime-genai-cuda is installed for gpu use:
+# use the model stored in /cuda folder
+# Then set ONNX_GEN_AI_CHAT_MODEL_FOLDER environment variable to the path to the model folder
+#############################################
+streaming = True
+
+chat_completion = OnnxGenAIChatCompletion(ai_model_id=service_id, template="phi3")
+settings = OnnxGenAIPromptExecutionSettings()
+
+system_message = """You are a helpful assistant."""
+chat_history = ChatHistory(system_message=system_message)
+
+
+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
+    chat_history.add_user_message(user_input)
+    if streaming:
+        print("Mosscap:> ", end="")
+        message = ""
+        async for chunk in chat_completion.get_streaming_chat_message_content(
+            chat_history=chat_history, settings=settings, kernel=kernel
+        ):
+            if chunk:
+                print(str(chunk), end="")
+                message += str(chunk)
+        chat_history.add_assistant_message(message)
+        print("")
+    else:
+        answer = await chat_completion.get_chat_message_content(
+            chat_history=chat_history, settings=settings, kernel=kernel
+        )
+        print(f"Mosscap:> {answer}")
+        chat_history.add_message(answer)
+    return True
+
+
+async def main() -> None:
+    chatting = True
+    while chatting:
+        chatting = await chat()
+
+
+if __name__ == "__main__":
+    asyncio.run(main())