Files
wehub-resource-sync b957a53def
CodeQL / Analyze (csharp) (push) Waiting to run
CodeQL / Analyze (python) (push) Waiting to run
chore: import upstream snapshot with attribution
2026-07-13 13:21:23 +08:00

92 lines
2.9 KiB
Python

# Copyright (c) Microsoft. All rights reserved.
import asyncio
from semantic_kernel.connectors.ai.onnx import OnnxGenAIChatCompletion, OnnxGenAIPromptExecutionSettings
from semantic_kernel.contents import AuthorRole, ChatHistory, ChatMessageContent, ImageContent
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
# If onnxruntime-genai is used:
# (https://huggingface.co/microsoft/Phi-3-vision-128k-instruct-onnx-cpu)
# If onnxruntime-genai-cuda is installed for gpu use:
# (https://huggingface.co/microsoft/Phi-3-vision-128k-instruct-onnx-gpu)
# 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="phi3v")
# Max length property is important to allocate RAM
# If the value is too big, you ran out of memory
# If the value is too small, your input is limited
settings = OnnxGenAIPromptExecutionSettings(max_length=4096)
system_message = """
You are a helpful assistant.
You know about provided images and the history of the conversation.
"""
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
):
print(chunk.content, end="")
if chunk.content:
message += chunk.content
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(message)
return True
async def main() -> None:
chatting = True
image_path = input("Image Path (leave empty if no image): ")
if image_path:
chat_history.add_message(
ChatMessageContent(
role=AuthorRole.USER,
items=[
ImageContent.from_image_path(image_path=image_path),
],
),
)
while chatting:
chatting = await chat()
if __name__ == "__main__":
asyncio.run(main())