# Copyright (c) Microsoft. All rights reserved.

import os
import tempfile
from copy import deepcopy
from unittest.mock import patch

import pytest

from semantic_kernel.connectors.ai.open_ai.services.open_ai_chat_completion import OpenAIChatCompletion
from semantic_kernel.connectors.ai.open_ai.services.open_ai_text_completion import OpenAITextCompletion
from semantic_kernel.connectors.ai.prompt_execution_settings import PromptExecutionSettings
from semantic_kernel.const import METADATA_EXCEPTION_KEY
from semantic_kernel.contents import AuthorRole
from semantic_kernel.contents.chat_message_content import ChatMessageContent
from semantic_kernel.contents.streaming_chat_message_content import StreamingChatMessageContent
from semantic_kernel.contents.text_content import TextContent
from semantic_kernel.exceptions import FunctionInitializationError
from semantic_kernel.filters.functions.function_invocation_context import FunctionInvocationContext
from semantic_kernel.filters.kernel_filters_extension import _rebuild_function_invocation_context
from semantic_kernel.filters.prompts.prompt_render_context import PromptRenderContext
from semantic_kernel.functions.kernel_arguments import KernelArguments
from semantic_kernel.functions.kernel_function_from_prompt import KernelFunctionFromPrompt
from semantic_kernel.kernel import Kernel
from semantic_kernel.prompt_template.input_variable import InputVariable
from semantic_kernel.prompt_template.kernel_prompt_template import KernelPromptTemplate
from semantic_kernel.prompt_template.prompt_template_config import PromptTemplateConfig


def test_init_minimal_prompt():
    function = KernelFunctionFromPrompt(
        function_name="test",
        plugin_name="test",
        prompt="test",
    )

    assert function.name == "test"
    assert function.plugin_name == "test"
    assert function.description is None
    assert function.prompt_template.prompt_template_config.template == "test"


def test_init_minimal_prompt_template():
    function = KernelFunctionFromPrompt(
        function_name="test",
        plugin_name="test",
        prompt_template=KernelPromptTemplate(prompt_template_config=PromptTemplateConfig(template="test")),
    )

    assert function.name == "test"
    assert function.plugin_name == "test"
    assert function.description is None
    assert function.prompt_template.prompt_template_config.template == "test"


def test_init_minimal_prompt_template_config():
    function = KernelFunctionFromPrompt(
        function_name="test", plugin_name="test", prompt_template_config=PromptTemplateConfig(template="test")
    )

    assert function.name == "test"
    assert function.plugin_name == "test"
    assert function.description is None
    assert function.prompt_template.prompt_template_config.template == "test"


def test_init_no_prompt():
    with pytest.raises(FunctionInitializationError):
        KernelFunctionFromPrompt(
            function_name="test",
            plugin_name="test",
        )


def test_init_invalid_name():
    with pytest.raises(FunctionInitializationError):
        KernelFunctionFromPrompt(function_name="test func", plugin_name="test", prompt="test")


def test_init_prompt_execution_settings_none():
    function = KernelFunctionFromPrompt(
        function_name="test",
        plugin_name="test",
        prompt="test",
        prompt_execution_settings=None,
    )

    assert function.name == "test"
    assert function.plugin_name == "test"
    assert function.description is None
    assert function.prompt_template.prompt_template_config.template == "test"


def test_init_prompt_execution_settings_none_with_prompt_template():
    function = KernelFunctionFromPrompt(
        function_name="test",
        plugin_name="test",
        prompt_template=KernelPromptTemplate(
            prompt_template_config=PromptTemplateConfig(template="test", execution_settings={})
        ),
        prompt_execution_settings=None,
    )

    assert function.name == "test"
    assert function.plugin_name == "test"
    assert function.description is None
    assert function.prompt_template.prompt_template_config.template == "test"


def test_init_prompt_execution_settings():
    function = KernelFunctionFromPrompt(
        function_name="test",
        plugin_name="test",
        prompt="test",
        prompt_execution_settings=PromptExecutionSettings(service_id="test"),
    )

    assert function.name == "test"
    assert function.plugin_name == "test"
    assert function.description is None
    assert function.prompt_template.prompt_template_config.template == "test"


def test_init_prompt_execution_settings_list():
    function = KernelFunctionFromPrompt(
        function_name="test",
        plugin_name="test",
        prompt="test",
        prompt_execution_settings=[PromptExecutionSettings(service_id="test")],
    )

    assert function.name == "test"
    assert function.plugin_name == "test"
    assert function.description is None
    assert function.prompt_template.prompt_template_config.template == "test"


def test_init_prompt_execution_settings_dict():
    function = KernelFunctionFromPrompt(
        function_name="test",
        plugin_name="test",
        prompt="test",
        prompt_execution_settings={"test": PromptExecutionSettings(service_id="test")},
    )

    assert function.name == "test"
    assert function.plugin_name == "test"
    assert function.description is None
    assert function.prompt_template.prompt_template_config.template == "test"


async def test_invoke_chat_stream(openai_unit_test_env):
    kernel = Kernel()
    kernel.add_service(OpenAIChatCompletion(service_id="test", ai_model_id="test"))
    function = KernelFunctionFromPrompt(
        function_name="test",
        plugin_name="test",
        prompt="test",
        prompt_execution_settings=PromptExecutionSettings(service_id="test"),
    )

    # This part remains unchanged - for synchronous mocking example
    with patch(
        "semantic_kernel.connectors.ai.open_ai.services.open_ai_chat_completion.OpenAIChatCompletion.get_chat_message_contents"
    ) as mock:
        mock.return_value = [ChatMessageContent(role=AuthorRole.ASSISTANT, content="test", metadata={})]
        result = await function.invoke(kernel=kernel)
        assert str(result) == "test"

    with patch(
        "semantic_kernel.connectors.ai.open_ai.services.open_ai_chat_completion.OpenAIChatCompletion.get_streaming_chat_message_contents"
    ) as mock:
        mock.return_value = [
            StreamingChatMessageContent(choice_index=0, role=AuthorRole.ASSISTANT, content="test", metadata={})
        ]
        async for result in function.invoke_stream(kernel=kernel):
            assert str(result) == "test"


async def test_invoke_exception(openai_unit_test_env):
    kernel = Kernel()
    kernel.add_service(OpenAIChatCompletion(service_id="test", ai_model_id="test"))
    function = KernelFunctionFromPrompt(
        function_name="test",
        plugin_name="test",
        prompt="test",
        prompt_execution_settings=PromptExecutionSettings(service_id="test"),
    )
    with patch(
        "semantic_kernel.connectors.ai.open_ai.services.open_ai_chat_completion.OpenAIChatCompletion.get_chat_message_contents",
        side_effect=Exception,
    ) as mock:
        mock.return_value = [ChatMessageContent(role=AuthorRole.ASSISTANT, content="test", metadata={})]
        with pytest.raises(Exception, match="test"):
            await function.invoke(kernel=kernel)

    with patch(
        "semantic_kernel.connectors.ai.open_ai.services.open_ai_chat_completion.OpenAIChatCompletion.get_streaming_chat_message_contents",
        side_effect=Exception,
    ) as mock:
        mock.return_value = [
            StreamingChatMessageContent(choice_index=0, role=AuthorRole.ASSISTANT, content="test", metadata={})
        ]
        with pytest.raises(Exception):
            async for result in function.invoke_stream(kernel=kernel):
                assert isinstance(result.metadata[METADATA_EXCEPTION_KEY], Exception)


async def test_invoke_text(openai_unit_test_env):
    kernel = Kernel()
    kernel.add_service(OpenAITextCompletion(service_id="test", ai_model_id="test"))
    function = KernelFunctionFromPrompt(
        function_name="test",
        plugin_name="test",
        prompt="test",
        prompt_execution_settings=PromptExecutionSettings(service_id="test"),
    )
    with patch(
        "semantic_kernel.connectors.ai.open_ai.services.open_ai_text_completion.OpenAITextCompletion.get_text_contents",
    ) as mock:
        mock.return_value = [TextContent(text="test", metadata={})]
        result = await function.invoke(kernel=kernel)
        assert str(result) == "test"

    with patch(
        "semantic_kernel.connectors.ai.open_ai.services.open_ai_text_completion.OpenAITextCompletion.get_streaming_text_contents",
    ) as mock:
        mock.return_value = [TextContent(text="test", metadata={})]
        async for result in function.invoke_stream(kernel=kernel):
            assert str(result) == "test"


async def test_invoke_exception_text(openai_unit_test_env):
    kernel = Kernel()
    kernel.add_service(OpenAITextCompletion(service_id="test", ai_model_id="test"))
    function = KernelFunctionFromPrompt(
        function_name="test",
        plugin_name="test",
        prompt="test",
        prompt_execution_settings=PromptExecutionSettings(service_id="test"),
    )
    with patch(
        "semantic_kernel.connectors.ai.open_ai.services.open_ai_text_completion.OpenAITextCompletion.get_text_contents",
        side_effect=Exception,
    ) as mock:
        mock.return_value = [TextContent(text="test", metadata={})]
        with pytest.raises(Exception, match="test"):
            await function.invoke(kernel=kernel)

    with patch(
        "semantic_kernel.connectors.ai.open_ai.services.open_ai_text_completion.OpenAITextCompletion.get_streaming_text_contents",
        side_effect=Exception,
    ) as mock:
        mock.return_value = []
        with pytest.raises(Exception):
            async for result in function.invoke_stream(kernel=kernel):
                assert isinstance(result.metadata[METADATA_EXCEPTION_KEY], Exception)


async def test_invoke_defaults(openai_unit_test_env):
    kernel = Kernel()
    kernel.add_service(OpenAIChatCompletion(service_id="test", ai_model_id="test"))
    function = KernelFunctionFromPrompt(
        function_name="test",
        plugin_name="test",
        prompt_template_config=PromptTemplateConfig(
            template="{{$input}}",
            input_variables=[InputVariable(name="input", type="str", default="test", is_required=False)],
        ),
        prompt_execution_settings=PromptExecutionSettings(service_id="test"),
    )
    with patch(
        "semantic_kernel.connectors.ai.open_ai.services.open_ai_chat_completion.OpenAIChatCompletion.get_chat_message_contents"
    ) as mock:
        mock.return_value = [ChatMessageContent(role=AuthorRole.ASSISTANT, content="test", metadata={})]
        result = await function.invoke(kernel=kernel)
        assert str(result) == "test"


def test_create_with_multiple_settings():
    function = KernelFunctionFromPrompt(
        function_name="test",
        plugin_name="test",
        prompt_template_config=PromptTemplateConfig(
            template="test",
            execution_settings=[
                PromptExecutionSettings(service_id="test", temperature=0.0),
                PromptExecutionSettings(service_id="test2", temperature=1.0),
            ],
        ),
    )
    assert (
        function.prompt_template.prompt_template_config.execution_settings["test"].extension_data["temperature"] == 0.0
    )
    assert (
        function.prompt_template.prompt_template_config.execution_settings["test2"].extension_data["temperature"] == 1.0
    )


async def test_create_with_multiple_settings_one_service_registered(openai_unit_test_env):
    kernel = Kernel()
    kernel.add_service(OpenAIChatCompletion(service_id="test2", ai_model_id="test"))
    function = KernelFunctionFromPrompt(
        function_name="test",
        plugin_name="test",
        prompt_template_config=PromptTemplateConfig(
            template="test",
            execution_settings=[
                PromptExecutionSettings(service_id="test", temperature=0.0),
                PromptExecutionSettings(service_id="test2", temperature=1.0),
            ],
        ),
    )
    with patch(
        "semantic_kernel.connectors.ai.open_ai.services.open_ai_chat_completion.OpenAIChatCompletion.get_chat_message_contents"
    ) as mock:
        mock.return_value = [ChatMessageContent(role=AuthorRole.ASSISTANT, content="test", metadata={})]
        result = await function.invoke(kernel=kernel)
        assert str(result) == "test"


def test_from_yaml_fail():
    with pytest.raises(FunctionInitializationError):
        KernelFunctionFromPrompt.from_yaml("template_format: something_else")


def test_from_directory_prompt_only():
    with pytest.raises(FunctionInitializationError):
        KernelFunctionFromPrompt.from_directory(
            path=os.path.join(
                os.path.dirname(__file__),
                "../../assets",
                "test_plugins",
                "TestPlugin",
                "TestFunctionPromptOnly",
            ),
            plugin_name="test",
        )


def test_from_directory_config_only():
    with pytest.raises(FunctionInitializationError):
        KernelFunctionFromPrompt.from_directory(
            path=os.path.join(
                os.path.dirname(__file__),
                "../../assets",
                "test_plugins",
                "TestPlugin",
                "TestFunctionConfigOnly",
            ),
            plugin_name="test",
        )


async def test_prompt_render(kernel: Kernel, openai_unit_test_env):
    kernel.add_service(OpenAIChatCompletion(service_id="default", ai_model_id="test"))
    function = KernelFunctionFromPrompt(
        function_name="test",
        plugin_name="test",
        prompt="test",
        template_format="semantic-kernel",
    )
    _rebuild_function_invocation_context()
    context = FunctionInvocationContext(function=function, kernel=kernel, arguments=KernelArguments())
    prompt_render_result = await function._render_prompt(context)
    assert prompt_render_result.rendered_prompt == "test"


async def test_prompt_render_with_filter(kernel: Kernel, openai_unit_test_env):
    kernel.add_service(OpenAIChatCompletion(service_id="default", ai_model_id="test"))

    @kernel.filter("prompt_rendering")
    async def prompt_rendering_filter(context: PromptRenderContext, next):
        await next(context)
        context.rendered_prompt = f"preface {context.rendered_prompt or ''}"

    function = KernelFunctionFromPrompt(
        function_name="test",
        plugin_name="test",
        prompt="test",
        template_format="semantic-kernel",
    )
    _rebuild_function_invocation_context()
    context = FunctionInvocationContext(function=function, kernel=kernel, arguments=KernelArguments())
    prompt_render_result = await function._render_prompt(context)
    assert prompt_render_result.rendered_prompt == "preface test"


@pytest.mark.parametrize(
    ("mode"),
    [
        ("python"),
        ("json"),
    ],
)
def test_function_model_dump(mode: str):
    function = KernelFunctionFromPrompt(
        function_name="test",
        plugin_name="test",
        prompt="test",
        template_format="semantic-kernel",
        prompt_template_config=PromptTemplateConfig(
            template="test",
            input_variables=[InputVariable(name="input", type="str", default="test", is_required=False)],
        ),
    )
    model_dump = function.model_dump(mode=mode)
    assert isinstance(model_dump, dict)
    assert "metadata" in model_dump
    assert len(model_dump["metadata"]["parameters"]) == 1


def test_function_model_dump_json():
    function = KernelFunctionFromPrompt(
        function_name="test",
        plugin_name="test",
        prompt="test",
        template_format="semantic-kernel",
    )
    model_dump_json = function.model_dump_json()
    assert isinstance(model_dump_json, str)
    assert "test" in model_dump_json


def test_from_directory_utf8_encoding_default():
    """Test loading plugin with default UTF-8 encoding."""
    with tempfile.TemporaryDirectory() as temp_dir:
        prompt_path = os.path.join(temp_dir, "skprompt.txt")
        config_path = os.path.join(temp_dir, "config.json")

        # UTF-8 content with international characters
        prompt_content = """Hello! I can help with questions in multiple languages:
        English: Hello world!
        Spanish: ¡Hola mundo!
        Chinese: 你好世界!
        Japanese: こんにちは世界!
        
        Question: {{$input}}
        """

        config_content = """{
    "schema": 1,
    "description": "A multilingual assistant function",
    "input_variables": [
        {
            "name": "input",
            "description": "User's question",
            "required": true
        }
    ]
}"""

        # Write files with UTF-8 encoding
        with open(prompt_path, "w", encoding="utf-8") as f:
            f.write(prompt_content)
        with open(config_path, "w", encoding="utf-8") as f:
            f.write(config_content)

        # Test default behavior (should use UTF-8)
        function = KernelFunctionFromPrompt.from_directory(temp_dir)
        assert function.name == os.path.basename(temp_dir)
        assert function.description == "A multilingual assistant function"
        assert "你好世界" in function.prompt_template.prompt_template_config.template
        assert "こんにちは世界" in function.prompt_template.prompt_template_config.template


def test_from_directory_explicit_utf8_encoding():
    """Test loading plugin with explicit UTF-8 encoding."""
    with tempfile.TemporaryDirectory() as temp_dir:
        prompt_path = os.path.join(temp_dir, "skprompt.txt")
        config_path = os.path.join(temp_dir, "config.json")

        prompt_content = "Hello with UTF-8 characters: ñáéíóú {{$input}}"
        config_content = '{"schema": 1, "description": "Test with UTF-8 characters"}'

        with open(prompt_path, "w", encoding="utf-8") as f:
            f.write(prompt_content)
        with open(config_path, "w", encoding="utf-8") as f:
            f.write(config_content)

        # Test explicit UTF-8 encoding
        function = KernelFunctionFromPrompt.from_directory(temp_dir, encoding="utf-8")
        assert function.description == "Test with UTF-8 characters"
        assert "ñáéíóú" in function.prompt_template.prompt_template_config.template


def test_from_directory_latin1_encoding():
    """Test loading plugin with Latin-1 encoding."""
    with tempfile.TemporaryDirectory() as temp_dir:
        prompt_path = os.path.join(temp_dir, "skprompt.txt")
        config_path = os.path.join(temp_dir, "config.json")

        # Content with Latin-1 characters (Western European)
        prompt_content = """Assistant for Western European languages:
        French: café, naïve, résumé
        German: Müller, Größe, weiß
        Spanish: niño, señora, años
        
        Question: {{$input}}
        """

        config_content = """{
    "schema": 1,
    "description": "Western European language assistant",
    "input_variables": [
        {
            "name": "input",
            "description": "User's question",
            "required": true
        }
    ]
}"""

        # Write files with Latin-1 encoding
        with open(prompt_path, "w", encoding="latin-1") as f:
            f.write(prompt_content)
        with open(config_path, "w", encoding="latin-1") as f:
            f.write(config_content)

        # Load with Latin-1 encoding
        function = KernelFunctionFromPrompt.from_directory(temp_dir, encoding="latin-1")
        assert function.description == "Western European language assistant"
        assert "café" in function.prompt_template.prompt_template_config.template
        assert "Müller" in function.prompt_template.prompt_template_config.template
        assert "niño" in function.prompt_template.prompt_template_config.template


def test_from_directory_cp1252_encoding():
    """Test loading plugin with Windows-1252 encoding."""
    with tempfile.TemporaryDirectory() as temp_dir:
        prompt_path = os.path.join(temp_dir, "skprompt.txt")
        config_path = os.path.join(temp_dir, "config.json")

        # Content with Windows-1252 specific characters
        prompt_content = """Windows text processing assistant:
        Smart quotes: "Hello" and 'world'
        Em dash: Yes—absolutely!
        Ellipsis: Wait…
        
        Question: {{$input}}
        """

        config_content = """{
    "schema": 1,
    "description": "Windows text processing assistant",
    "input_variables": [
        {
            "name": "input",
            "description": "User's question about text processing",
            "required": true
        }
    ]
}"""

        # Write files with Windows-1252 encoding
        with open(prompt_path, "w", encoding="cp1252") as f:
            f.write(prompt_content)
        with open(config_path, "w", encoding="cp1252") as f:
            f.write(config_content)

        # Load with Windows-1252 encoding
        function = KernelFunctionFromPrompt.from_directory(temp_dir, encoding="cp1252")
        assert function.description == "Windows text processing assistant"
        assert '"Hello"' in function.prompt_template.prompt_template_config.template
        assert "Yes—absolutely" in function.prompt_template.prompt_template_config.template
        assert "Wait…" in function.prompt_template.prompt_template_config.template


def test_from_directory_with_plugin_name_and_encoding():
    """Test loading plugin with both plugin name and encoding specified."""
    with tempfile.TemporaryDirectory() as temp_dir:
        prompt_path = os.path.join(temp_dir, "skprompt.txt")
        config_path = os.path.join(temp_dir, "config.json")

        prompt_content = "Simple assistant: {{$input}}"
        config_content = '{"schema": 1, "description": "Simple assistant"}'

        with open(prompt_path, "w", encoding="utf-8") as f:
            f.write(prompt_content)
        with open(config_path, "w", encoding="utf-8") as f:
            f.write(config_content)

        # Load with both plugin name and encoding specified
        function = KernelFunctionFromPrompt.from_directory(
            path=temp_dir, plugin_name="MyCustomPlugin", encoding="utf-8"
        )
        assert function.metadata.plugin_name == "MyCustomPlugin"
        assert function.description == "Simple assistant"
        assert function.prompt_template.prompt_template_config.template == "Simple assistant: {{$input}}"


def test_from_directory_encoding_error_handling():
    """Test that incorrect encoding raises appropriate error."""
    with tempfile.TemporaryDirectory() as temp_dir:
        prompt_path = os.path.join(temp_dir, "skprompt.txt")
        config_path = os.path.join(temp_dir, "config.json")

        # Write UTF-8 content
        prompt_content = "Hello with UTF-8: 你好世界 {{$input}}"
        config_content = '{"schema": 1, "description": "UTF-8 content"}'

        with open(prompt_path, "w", encoding="utf-8") as f:
            f.write(prompt_content)
        with open(config_path, "w", encoding="utf-8") as f:
            f.write(config_content)

        # Try to read with ASCII encoding - should fail
        with pytest.raises(UnicodeDecodeError):
            KernelFunctionFromPrompt.from_directory(temp_dir, encoding="ascii")


def test_from_directory_backward_compatibility():
    """Test that existing code without encoding parameter still works."""
    with tempfile.TemporaryDirectory() as temp_dir:
        prompt_path = os.path.join(temp_dir, "skprompt.txt")
        config_path = os.path.join(temp_dir, "config.json")

        prompt_content = "Basic ASCII content: {{$input}}"
        config_content = '{"schema": 1, "description": "Basic function"}'

        with open(prompt_path, "w", encoding="utf-8") as f:
            f.write(prompt_content)
        with open(config_path, "w", encoding="utf-8") as f:
            f.write(config_content)

        # Test that old calling style still works
        function = KernelFunctionFromPrompt.from_directory(temp_dir)
        assert function.description == "Basic function"
        assert function.prompt_template.prompt_template_config.template == "Basic ASCII content: {{$input}}"


def test_kernel_function_from_prompt_deepcopy():
    """Test deepcopying a KernelFunctionFromPrompt."""
    function = KernelFunctionFromPrompt(
        function_name="test_function",
        plugin_name="test_plugin",
        prompt="Hello, world!",
        description="A test function.",
    )
    copied_function = deepcopy(function)
    assert copied_function is not function
    assert copied_function.name == function.name
    assert copied_function.plugin_name == function.plugin_name
    assert copied_function.description == function.description
    assert copied_function.prompt_template.prompt_template_config.template == (
        function.prompt_template.prompt_template_config.template
    )
    assert copied_function.prompt_template is not function.prompt_template