wehub-resource-sync
649 lines
25 KiB
Python
649 lines
25 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
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import os
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import tempfile
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from copy import deepcopy
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from unittest.mock import patch
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import pytest
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from semantic_kernel.connectors.ai.open_ai.services.open_ai_chat_completion import OpenAIChatCompletion
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from semantic_kernel.connectors.ai.open_ai.services.open_ai_text_completion import OpenAITextCompletion
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from semantic_kernel.connectors.ai.prompt_execution_settings import PromptExecutionSettings
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from semantic_kernel.const import METADATA_EXCEPTION_KEY
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from semantic_kernel.contents import AuthorRole
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from semantic_kernel.contents.chat_message_content import ChatMessageContent
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from semantic_kernel.contents.streaming_chat_message_content import StreamingChatMessageContent
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from semantic_kernel.contents.text_content import TextContent
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from semantic_kernel.exceptions import FunctionInitializationError
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from semantic_kernel.filters.functions.function_invocation_context import FunctionInvocationContext
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from semantic_kernel.filters.kernel_filters_extension import _rebuild_function_invocation_context
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from semantic_kernel.filters.prompts.prompt_render_context import PromptRenderContext
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from semantic_kernel.functions.kernel_arguments import KernelArguments
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from semantic_kernel.functions.kernel_function_from_prompt import KernelFunctionFromPrompt
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from semantic_kernel.kernel import Kernel
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from semantic_kernel.prompt_template.input_variable import InputVariable
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from semantic_kernel.prompt_template.kernel_prompt_template import KernelPromptTemplate
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from semantic_kernel.prompt_template.prompt_template_config import PromptTemplateConfig
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def test_init_minimal_prompt():
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function = KernelFunctionFromPrompt(
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function_name="test",
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plugin_name="test",
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prompt="test",
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)
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assert function.name == "test"
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assert function.plugin_name == "test"
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assert function.description is None
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assert function.prompt_template.prompt_template_config.template == "test"
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def test_init_minimal_prompt_template():
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function = KernelFunctionFromPrompt(
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function_name="test",
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plugin_name="test",
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prompt_template=KernelPromptTemplate(prompt_template_config=PromptTemplateConfig(template="test")),
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)
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assert function.name == "test"
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assert function.plugin_name == "test"
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assert function.description is None
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assert function.prompt_template.prompt_template_config.template == "test"
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def test_init_minimal_prompt_template_config():
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function = KernelFunctionFromPrompt(
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function_name="test", plugin_name="test", prompt_template_config=PromptTemplateConfig(template="test")
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)
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assert function.name == "test"
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assert function.plugin_name == "test"
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assert function.description is None
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assert function.prompt_template.prompt_template_config.template == "test"
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def test_init_no_prompt():
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with pytest.raises(FunctionInitializationError):
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KernelFunctionFromPrompt(
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function_name="test",
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plugin_name="test",
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)
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def test_init_invalid_name():
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with pytest.raises(FunctionInitializationError):
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KernelFunctionFromPrompt(function_name="test func", plugin_name="test", prompt="test")
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def test_init_prompt_execution_settings_none():
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function = KernelFunctionFromPrompt(
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function_name="test",
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plugin_name="test",
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prompt="test",
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prompt_execution_settings=None,
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)
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assert function.name == "test"
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assert function.plugin_name == "test"
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assert function.description is None
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assert function.prompt_template.prompt_template_config.template == "test"
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def test_init_prompt_execution_settings_none_with_prompt_template():
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function = KernelFunctionFromPrompt(
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function_name="test",
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plugin_name="test",
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prompt_template=KernelPromptTemplate(
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prompt_template_config=PromptTemplateConfig(template="test", execution_settings={})
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),
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prompt_execution_settings=None,
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)
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assert function.name == "test"
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assert function.plugin_name == "test"
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assert function.description is None
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assert function.prompt_template.prompt_template_config.template == "test"
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def test_init_prompt_execution_settings():
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function = KernelFunctionFromPrompt(
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function_name="test",
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plugin_name="test",
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prompt="test",
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prompt_execution_settings=PromptExecutionSettings(service_id="test"),
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)
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assert function.name == "test"
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assert function.plugin_name == "test"
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assert function.description is None
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assert function.prompt_template.prompt_template_config.template == "test"
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def test_init_prompt_execution_settings_list():
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function = KernelFunctionFromPrompt(
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function_name="test",
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plugin_name="test",
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prompt="test",
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prompt_execution_settings=[PromptExecutionSettings(service_id="test")],
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)
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assert function.name == "test"
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assert function.plugin_name == "test"
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assert function.description is None
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assert function.prompt_template.prompt_template_config.template == "test"
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def test_init_prompt_execution_settings_dict():
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function = KernelFunctionFromPrompt(
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function_name="test",
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plugin_name="test",
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prompt="test",
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prompt_execution_settings={"test": PromptExecutionSettings(service_id="test")},
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)
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assert function.name == "test"
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assert function.plugin_name == "test"
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assert function.description is None
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assert function.prompt_template.prompt_template_config.template == "test"
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async def test_invoke_chat_stream(openai_unit_test_env):
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kernel = Kernel()
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kernel.add_service(OpenAIChatCompletion(service_id="test", ai_model_id="test"))
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function = KernelFunctionFromPrompt(
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function_name="test",
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plugin_name="test",
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prompt="test",
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prompt_execution_settings=PromptExecutionSettings(service_id="test"),
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)
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# This part remains unchanged - for synchronous mocking example
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with patch(
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"semantic_kernel.connectors.ai.open_ai.services.open_ai_chat_completion.OpenAIChatCompletion.get_chat_message_contents"
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) as mock:
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mock.return_value = [ChatMessageContent(role=AuthorRole.ASSISTANT, content="test", metadata={})]
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result = await function.invoke(kernel=kernel)
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assert str(result) == "test"
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with patch(
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"semantic_kernel.connectors.ai.open_ai.services.open_ai_chat_completion.OpenAIChatCompletion.get_streaming_chat_message_contents"
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) as mock:
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mock.return_value = [
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StreamingChatMessageContent(choice_index=0, role=AuthorRole.ASSISTANT, content="test", metadata={})
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]
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async for result in function.invoke_stream(kernel=kernel):
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assert str(result) == "test"
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async def test_invoke_exception(openai_unit_test_env):
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kernel = Kernel()
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kernel.add_service(OpenAIChatCompletion(service_id="test", ai_model_id="test"))
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function = KernelFunctionFromPrompt(
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function_name="test",
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plugin_name="test",
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prompt="test",
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prompt_execution_settings=PromptExecutionSettings(service_id="test"),
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)
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with patch(
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"semantic_kernel.connectors.ai.open_ai.services.open_ai_chat_completion.OpenAIChatCompletion.get_chat_message_contents",
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side_effect=Exception,
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) as mock:
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mock.return_value = [ChatMessageContent(role=AuthorRole.ASSISTANT, content="test", metadata={})]
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with pytest.raises(Exception, match="test"):
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await function.invoke(kernel=kernel)
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with patch(
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"semantic_kernel.connectors.ai.open_ai.services.open_ai_chat_completion.OpenAIChatCompletion.get_streaming_chat_message_contents",
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side_effect=Exception,
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) as mock:
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mock.return_value = [
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StreamingChatMessageContent(choice_index=0, role=AuthorRole.ASSISTANT, content="test", metadata={})
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]
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with pytest.raises(Exception):
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async for result in function.invoke_stream(kernel=kernel):
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assert isinstance(result.metadata[METADATA_EXCEPTION_KEY], Exception)
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async def test_invoke_text(openai_unit_test_env):
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kernel = Kernel()
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kernel.add_service(OpenAITextCompletion(service_id="test", ai_model_id="test"))
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function = KernelFunctionFromPrompt(
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function_name="test",
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plugin_name="test",
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prompt="test",
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prompt_execution_settings=PromptExecutionSettings(service_id="test"),
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)
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with patch(
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"semantic_kernel.connectors.ai.open_ai.services.open_ai_text_completion.OpenAITextCompletion.get_text_contents",
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) as mock:
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mock.return_value = [TextContent(text="test", metadata={})]
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result = await function.invoke(kernel=kernel)
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assert str(result) == "test"
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with patch(
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"semantic_kernel.connectors.ai.open_ai.services.open_ai_text_completion.OpenAITextCompletion.get_streaming_text_contents",
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) as mock:
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mock.return_value = [TextContent(text="test", metadata={})]
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async for result in function.invoke_stream(kernel=kernel):
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assert str(result) == "test"
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async def test_invoke_exception_text(openai_unit_test_env):
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kernel = Kernel()
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kernel.add_service(OpenAITextCompletion(service_id="test", ai_model_id="test"))
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function = KernelFunctionFromPrompt(
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function_name="test",
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plugin_name="test",
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prompt="test",
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prompt_execution_settings=PromptExecutionSettings(service_id="test"),
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)
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with patch(
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"semantic_kernel.connectors.ai.open_ai.services.open_ai_text_completion.OpenAITextCompletion.get_text_contents",
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side_effect=Exception,
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) as mock:
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mock.return_value = [TextContent(text="test", metadata={})]
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with pytest.raises(Exception, match="test"):
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await function.invoke(kernel=kernel)
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with patch(
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"semantic_kernel.connectors.ai.open_ai.services.open_ai_text_completion.OpenAITextCompletion.get_streaming_text_contents",
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side_effect=Exception,
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) as mock:
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mock.return_value = []
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with pytest.raises(Exception):
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async for result in function.invoke_stream(kernel=kernel):
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assert isinstance(result.metadata[METADATA_EXCEPTION_KEY], Exception)
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async def test_invoke_defaults(openai_unit_test_env):
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kernel = Kernel()
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kernel.add_service(OpenAIChatCompletion(service_id="test", ai_model_id="test"))
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function = KernelFunctionFromPrompt(
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function_name="test",
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plugin_name="test",
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prompt_template_config=PromptTemplateConfig(
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template="{{$input}}",
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input_variables=[InputVariable(name="input", type="str", default="test", is_required=False)],
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),
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prompt_execution_settings=PromptExecutionSettings(service_id="test"),
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)
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with patch(
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"semantic_kernel.connectors.ai.open_ai.services.open_ai_chat_completion.OpenAIChatCompletion.get_chat_message_contents"
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) as mock:
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mock.return_value = [ChatMessageContent(role=AuthorRole.ASSISTANT, content="test", metadata={})]
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result = await function.invoke(kernel=kernel)
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assert str(result) == "test"
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def test_create_with_multiple_settings():
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function = KernelFunctionFromPrompt(
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function_name="test",
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plugin_name="test",
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prompt_template_config=PromptTemplateConfig(
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template="test",
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execution_settings=[
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PromptExecutionSettings(service_id="test", temperature=0.0),
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PromptExecutionSettings(service_id="test2", temperature=1.0),
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],
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),
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)
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assert (
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function.prompt_template.prompt_template_config.execution_settings["test"].extension_data["temperature"] == 0.0
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)
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assert (
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function.prompt_template.prompt_template_config.execution_settings["test2"].extension_data["temperature"] == 1.0
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)
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async def test_create_with_multiple_settings_one_service_registered(openai_unit_test_env):
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kernel = Kernel()
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kernel.add_service(OpenAIChatCompletion(service_id="test2", ai_model_id="test"))
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function = KernelFunctionFromPrompt(
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function_name="test",
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plugin_name="test",
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prompt_template_config=PromptTemplateConfig(
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template="test",
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execution_settings=[
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PromptExecutionSettings(service_id="test", temperature=0.0),
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PromptExecutionSettings(service_id="test2", temperature=1.0),
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],
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),
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)
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with patch(
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"semantic_kernel.connectors.ai.open_ai.services.open_ai_chat_completion.OpenAIChatCompletion.get_chat_message_contents"
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) as mock:
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mock.return_value = [ChatMessageContent(role=AuthorRole.ASSISTANT, content="test", metadata={})]
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result = await function.invoke(kernel=kernel)
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assert str(result) == "test"
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def test_from_yaml_fail():
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with pytest.raises(FunctionInitializationError):
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KernelFunctionFromPrompt.from_yaml("template_format: something_else")
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def test_from_directory_prompt_only():
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with pytest.raises(FunctionInitializationError):
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KernelFunctionFromPrompt.from_directory(
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path=os.path.join(
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os.path.dirname(__file__),
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"../../assets",
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"test_plugins",
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"TestPlugin",
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"TestFunctionPromptOnly",
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),
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plugin_name="test",
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)
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def test_from_directory_config_only():
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with pytest.raises(FunctionInitializationError):
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KernelFunctionFromPrompt.from_directory(
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path=os.path.join(
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os.path.dirname(__file__),
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"../../assets",
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"test_plugins",
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"TestPlugin",
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"TestFunctionConfigOnly",
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),
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plugin_name="test",
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)
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async def test_prompt_render(kernel: Kernel, openai_unit_test_env):
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kernel.add_service(OpenAIChatCompletion(service_id="default", ai_model_id="test"))
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function = KernelFunctionFromPrompt(
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function_name="test",
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plugin_name="test",
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prompt="test",
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template_format="semantic-kernel",
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)
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_rebuild_function_invocation_context()
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context = FunctionInvocationContext(function=function, kernel=kernel, arguments=KernelArguments())
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prompt_render_result = await function._render_prompt(context)
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assert prompt_render_result.rendered_prompt == "test"
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async def test_prompt_render_with_filter(kernel: Kernel, openai_unit_test_env):
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kernel.add_service(OpenAIChatCompletion(service_id="default", ai_model_id="test"))
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@kernel.filter("prompt_rendering")
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async def prompt_rendering_filter(context: PromptRenderContext, next):
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await next(context)
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context.rendered_prompt = f"preface {context.rendered_prompt or ''}"
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function = KernelFunctionFromPrompt(
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function_name="test",
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plugin_name="test",
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prompt="test",
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template_format="semantic-kernel",
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)
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_rebuild_function_invocation_context()
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context = FunctionInvocationContext(function=function, kernel=kernel, arguments=KernelArguments())
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prompt_render_result = await function._render_prompt(context)
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assert prompt_render_result.rendered_prompt == "preface test"
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@pytest.mark.parametrize(
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("mode"),
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[
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("python"),
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("json"),
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],
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)
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def test_function_model_dump(mode: str):
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function = KernelFunctionFromPrompt(
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function_name="test",
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plugin_name="test",
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prompt="test",
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template_format="semantic-kernel",
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prompt_template_config=PromptTemplateConfig(
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template="test",
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input_variables=[InputVariable(name="input", type="str", default="test", is_required=False)],
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),
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)
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model_dump = function.model_dump(mode=mode)
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assert isinstance(model_dump, dict)
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assert "metadata" in model_dump
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assert len(model_dump["metadata"]["parameters"]) == 1
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def test_function_model_dump_json():
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function = KernelFunctionFromPrompt(
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function_name="test",
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plugin_name="test",
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prompt="test",
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template_format="semantic-kernel",
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)
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model_dump_json = function.model_dump_json()
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assert isinstance(model_dump_json, str)
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assert "test" in model_dump_json
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def test_from_directory_utf8_encoding_default():
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"""Test loading plugin with default UTF-8 encoding."""
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with tempfile.TemporaryDirectory() as temp_dir:
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prompt_path = os.path.join(temp_dir, "skprompt.txt")
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config_path = os.path.join(temp_dir, "config.json")
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# UTF-8 content with international characters
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prompt_content = """Hello! I can help with questions in multiple languages:
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English: Hello world!
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Spanish: ¡Hola mundo!
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Chinese: 你好世界!
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Japanese: こんにちは世界!
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Question: {{$input}}
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"""
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config_content = """{
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"schema": 1,
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"description": "A multilingual assistant function",
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"input_variables": [
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{
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"name": "input",
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"description": "User's question",
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"required": true
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}
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]
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}"""
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# Write files with UTF-8 encoding
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with open(prompt_path, "w", encoding="utf-8") as f:
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f.write(prompt_content)
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with open(config_path, "w", encoding="utf-8") as f:
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f.write(config_content)
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# Test default behavior (should use UTF-8)
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function = KernelFunctionFromPrompt.from_directory(temp_dir)
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assert function.name == os.path.basename(temp_dir)
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assert function.description == "A multilingual assistant function"
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assert "你好世界" in function.prompt_template.prompt_template_config.template
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assert "こんにちは世界" in function.prompt_template.prompt_template_config.template
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def test_from_directory_explicit_utf8_encoding():
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"""Test loading plugin with explicit UTF-8 encoding."""
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with tempfile.TemporaryDirectory() as temp_dir:
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prompt_path = os.path.join(temp_dir, "skprompt.txt")
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config_path = os.path.join(temp_dir, "config.json")
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prompt_content = "Hello with UTF-8 characters: ñáéíóú {{$input}}"
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config_content = '{"schema": 1, "description": "Test with UTF-8 characters"}'
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with open(prompt_path, "w", encoding="utf-8") as f:
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f.write(prompt_content)
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with open(config_path, "w", encoding="utf-8") as f:
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f.write(config_content)
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# Test explicit UTF-8 encoding
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function = KernelFunctionFromPrompt.from_directory(temp_dir, encoding="utf-8")
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assert function.description == "Test with UTF-8 characters"
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assert "ñáéíóú" in function.prompt_template.prompt_template_config.template
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def test_from_directory_latin1_encoding():
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"""Test loading plugin with Latin-1 encoding."""
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with tempfile.TemporaryDirectory() as temp_dir:
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prompt_path = os.path.join(temp_dir, "skprompt.txt")
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config_path = os.path.join(temp_dir, "config.json")
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# Content with Latin-1 characters (Western European)
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prompt_content = """Assistant for Western European languages:
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French: café, naïve, résumé
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German: Müller, Größe, weiß
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Spanish: niño, señora, años
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Question: {{$input}}
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"""
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config_content = """{
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"schema": 1,
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"description": "Western European language assistant",
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"input_variables": [
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{
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"name": "input",
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"description": "User's question",
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"required": true
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}
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]
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}"""
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# Write files with Latin-1 encoding
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with open(prompt_path, "w", encoding="latin-1") as f:
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f.write(prompt_content)
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with open(config_path, "w", encoding="latin-1") as f:
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f.write(config_content)
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# Load with Latin-1 encoding
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function = KernelFunctionFromPrompt.from_directory(temp_dir, encoding="latin-1")
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assert function.description == "Western European language assistant"
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assert "café" in function.prompt_template.prompt_template_config.template
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assert "Müller" in function.prompt_template.prompt_template_config.template
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assert "niño" in function.prompt_template.prompt_template_config.template
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def test_from_directory_cp1252_encoding():
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"""Test loading plugin with Windows-1252 encoding."""
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with tempfile.TemporaryDirectory() as temp_dir:
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prompt_path = os.path.join(temp_dir, "skprompt.txt")
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config_path = os.path.join(temp_dir, "config.json")
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# Content with Windows-1252 specific characters
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prompt_content = """Windows text processing assistant:
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Smart quotes: "Hello" and 'world'
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Em dash: Yes—absolutely!
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Ellipsis: Wait…
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Question: {{$input}}
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"""
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config_content = """{
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"schema": 1,
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"description": "Windows text processing assistant",
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"input_variables": [
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{
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"name": "input",
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"description": "User's question about text processing",
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"required": true
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}
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]
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}"""
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# Write files with Windows-1252 encoding
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with open(prompt_path, "w", encoding="cp1252") as f:
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f.write(prompt_content)
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with open(config_path, "w", encoding="cp1252") as f:
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f.write(config_content)
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# Load with Windows-1252 encoding
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function = KernelFunctionFromPrompt.from_directory(temp_dir, encoding="cp1252")
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assert function.description == "Windows text processing assistant"
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assert '"Hello"' in function.prompt_template.prompt_template_config.template
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assert "Yes—absolutely" in function.prompt_template.prompt_template_config.template
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assert "Wait…" in function.prompt_template.prompt_template_config.template
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def test_from_directory_with_plugin_name_and_encoding():
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"""Test loading plugin with both plugin name and encoding specified."""
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with tempfile.TemporaryDirectory() as temp_dir:
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prompt_path = os.path.join(temp_dir, "skprompt.txt")
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config_path = os.path.join(temp_dir, "config.json")
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prompt_content = "Simple assistant: {{$input}}"
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config_content = '{"schema": 1, "description": "Simple assistant"}'
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with open(prompt_path, "w", encoding="utf-8") as f:
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f.write(prompt_content)
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with open(config_path, "w", encoding="utf-8") as f:
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f.write(config_content)
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# Load with both plugin name and encoding specified
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function = KernelFunctionFromPrompt.from_directory(
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path=temp_dir, plugin_name="MyCustomPlugin", encoding="utf-8"
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)
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assert function.metadata.plugin_name == "MyCustomPlugin"
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assert function.description == "Simple assistant"
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assert function.prompt_template.prompt_template_config.template == "Simple assistant: {{$input}}"
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def test_from_directory_encoding_error_handling():
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"""Test that incorrect encoding raises appropriate error."""
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with tempfile.TemporaryDirectory() as temp_dir:
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prompt_path = os.path.join(temp_dir, "skprompt.txt")
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config_path = os.path.join(temp_dir, "config.json")
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# Write UTF-8 content
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prompt_content = "Hello with UTF-8: 你好世界 {{$input}}"
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config_content = '{"schema": 1, "description": "UTF-8 content"}'
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with open(prompt_path, "w", encoding="utf-8") as f:
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f.write(prompt_content)
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with open(config_path, "w", encoding="utf-8") as f:
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f.write(config_content)
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# Try to read with ASCII encoding - should fail
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with pytest.raises(UnicodeDecodeError):
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KernelFunctionFromPrompt.from_directory(temp_dir, encoding="ascii")
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def test_from_directory_backward_compatibility():
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"""Test that existing code without encoding parameter still works."""
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with tempfile.TemporaryDirectory() as temp_dir:
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prompt_path = os.path.join(temp_dir, "skprompt.txt")
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config_path = os.path.join(temp_dir, "config.json")
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prompt_content = "Basic ASCII content: {{$input}}"
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config_content = '{"schema": 1, "description": "Basic function"}'
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with open(prompt_path, "w", encoding="utf-8") as f:
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f.write(prompt_content)
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with open(config_path, "w", encoding="utf-8") as f:
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f.write(config_content)
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# Test that old calling style still works
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function = KernelFunctionFromPrompt.from_directory(temp_dir)
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assert function.description == "Basic function"
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assert function.prompt_template.prompt_template_config.template == "Basic ASCII content: {{$input}}"
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def test_kernel_function_from_prompt_deepcopy():
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"""Test deepcopying a KernelFunctionFromPrompt."""
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|
function = KernelFunctionFromPrompt(
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function_name="test_function",
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plugin_name="test_plugin",
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prompt="Hello, world!",
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description="A test function.",
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)
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copied_function = deepcopy(function)
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assert copied_function is not function
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assert copied_function.name == function.name
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assert copied_function.plugin_name == function.plugin_name
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assert copied_function.description == function.description
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assert copied_function.prompt_template.prompt_template_config.template == (
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function.prompt_template.prompt_template_config.template
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)
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assert copied_function.prompt_template is not function.prompt_template
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