wehub-resource-sync
130 lines
5.6 KiB
Python
130 lines
5.6 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
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import asyncio
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from samples.concepts.setup.chat_completion_services import (
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Services,
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get_chat_completion_service_and_request_settings,
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)
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from semantic_kernel.contents import AuthorRole, ChatHistory, ChatMessageContent, ImageContent, TextContent
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# This sample shows how to create a chatbot that responds to user messages with image input.
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# This sample uses the following three main components:
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# - a ChatCompletionService: This component is responsible for generating responses to user messages.
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# - a ChatHistory: This component is responsible for keeping track of the chat history.
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# - an ImageContent: This component is responsible for representing image content.
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# The chatbot in this sample is called Mosscap.
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# You can select from the following chat completion services:
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# - Services.OPENAI
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# - Services.AZURE_OPENAI
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# - Services.AZURE_AI_INFERENCE
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# - Services.ANTHROPIC
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# - Services.BEDROCK
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# - Services.GOOGLE_AI
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# - Services.MISTRAL_AI
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# - Services.OLLAMA
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# - Services.ONNX
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# - Services.VERTEX_AI
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# Please make sure you have configured your environment correctly for the selected chat completion service.
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# [NOTE]
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# Not all models support image input. Make sure to select a model that supports image input.
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# Not all services support image input from an image URI. If your image is saved in a remote location,
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# make sure to use a service that supports image input from a URI.
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chat_completion_service, request_settings = get_chat_completion_service_and_request_settings(Services.AZURE_OPENAI)
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IMAGE_URI = "https://raw.githubusercontent.com/microsoft/semantic-kernel/main/python/tests/assets/sample_image.jpg"
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IMAGE_PATH = "samples/concepts/resources/sample_image.jpg"
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# Create an image content with the image URI.
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image_content_remote = ImageContent(uri=IMAGE_URI)
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# You can also create an image content with a local image path.
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image_content_local = ImageContent.from_image_file(IMAGE_PATH)
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# This is the system message that gives the chatbot its personality.
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system_message = """
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You are an image reviewing chat bot. Your name is Mosscap and you have one goal critiquing images that are supplied.
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"""
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# Create a chat history object with the system message and an initial user message with an image input.
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chat_history = ChatHistory(system_message=system_message)
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chat_history.add_message(
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ChatMessageContent(
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role=AuthorRole.USER,
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items=[TextContent(text="What is in this image?"), image_content_local],
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)
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)
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async def chat(skip_user_input: bool = False) -> bool:
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"""Chat with the chatbot.
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Args:
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skip_user_input (bool): Whether to skip user input. Defaults to False.
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"""
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if not skip_user_input:
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try:
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user_input = input("User:> ")
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except KeyboardInterrupt:
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print("\n\nExiting chat...")
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return False
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except EOFError:
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print("\n\nExiting chat...")
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return False
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if user_input == "exit":
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print("\n\nExiting chat...")
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return False
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# Add the user message to the chat history so that the chatbot can respond to it.
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chat_history.add_user_message(user_input)
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# Get the chat message content from the chat completion service.
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response = await chat_completion_service.get_chat_message_content(
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chat_history=chat_history,
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settings=request_settings,
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)
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if response:
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print(f"Mosscap:> {response}")
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# Add the chat message to the chat history to keep track of the conversation.
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chat_history.add_message(response)
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return True
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async def main() -> None:
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# Start the chat with the image input.
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await chat(skip_user_input=True)
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# Continue the chat. The chat loop will continue until the user types "exit".
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chatting = True
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while chatting:
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chatting = await chat()
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# Sample output:
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# Mosscap:> The image features a large, historic building that exhibits a traditional half-timbered architectural
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# style. The structure is located near a dense forest, characterized by lush green trees. The sky above
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# is partly cloudy, suggesting a pleasant day. The building itself appears well-maintained, with distinct
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# features such as a turret or spire and decorative wood framing, creating an elegant and charming
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# appearance in its natural setting.
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# User:> What do you think about the composition of the photo?
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# Mosscap:> The composition of the photo is quite effective. Here are a few observations:
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# 1. **Framing**: The building is positioned slightly off-center, which can create a more dynamic and
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# engaging image. This drawing of attention to the structure, while still showcasing the surrounding
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# landscape.
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# 2. **Foreground and Background**: The green foliage and trees in the foreground provide a nice contrast
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# to the building, enhancing its visual appeal. The dense forest in the background adds depth and context
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# to the scene.
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# 3. **Lighting**: The light appears to be favorable, suggesting a well-lit scene. The clouds add texture
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# to the sky without overwhelming the overall brightness.
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# 4. **Perspective**: The angle from which the photo is taken allows viewers to appreciate both the
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# architecture of the building and its natural environment, creating a harmonious balance.
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# Overall, the composition successfully highlights the building while incorporating its natural
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# surroundings, inviting viewers to appreciate both elements together.
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if __name__ == "__main__":
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asyncio.run(main())
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