# Copyright (c) Microsoft. All rights reserved.

import asyncio
import os
from typing import Tuple

import semantic_kernel as sk
import semantic_kernel.connectors.ai.open_ai as sk_oai
from semantic_kernel.connectors.ai.open_ai.semantic_functions.open_ai_chat_prompt_template import (
    OpenAIChatPromptTemplate,
)
from semantic_kernel.connectors.ai.open_ai.utils import (
    chat_completion_with_function_call,
    get_function_calling_object,
)
from semantic_kernel.core_skills import MathSkill

system_message = """
You are a chat bot. Your name is Mosscap and
you have one goal: figure out what people need.
Your full name, should you need to know it, is
Splendid Speckled Mosscap. You communicate
effectively, but you tend to answer with long
flowery prose. You are also a math wizard, 
especially for adding and subtracting.
You also excel at joke telling, where your tone is often sarcastic.
Once you have the answer I am looking for, 
you will return a full answer to me as soon as possible.
"""

kernel = sk.Kernel()

deployment_name, api_key, endpoint = sk.azure_openai_settings_from_dot_env()
api_version = "2023-07-01-preview"
kernel.add_chat_service(
    "chat-gpt",
    sk_oai.AzureChatCompletion(
        deployment_name,
        endpoint,
        api_key=api_key,
        api_version=api_version,
    ),
)

skills_directory = os.path.join(__file__, "../../../../samples/skills")
# adding skills to the kernel
# the joke skill in the FunSkills is a semantic skill and has the function calling disabled.
kernel.import_semantic_skill_from_directory(skills_directory, "FunSkill")
# the math skill is a core skill and has the function calling enabled.
kernel.import_skill(MathSkill(), skill_name="math")

# enabling or disabling function calling is done by setting the function_call parameter for the completion.
# when the function_call parameter is set to "auto" the model will decide which function to use, if any.
# if you only want to use a specific function, set the name of that function in this parameter,
# the format for that is 'SkillName-FunctionName', (i.e. 'math-Add').
# if the model or api version do not support this you will get an error.
prompt_config = sk.PromptTemplateConfig(
    completion=sk_oai.AzureChatRequestSettings(
        service_id="chat-gpt",
        ai_model_id=deployment_name,
        max_tokens=2000,
        temperature=0.7,
        top_p=0.8,
        function_call="auto",
        functions=get_function_calling_object(kernel, {"exclude_skill": ["ChatBot"]}),
    )
)
prompt_template = OpenAIChatPromptTemplate("{{$user_input}}", kernel.prompt_template_engine, prompt_config)
prompt_template.add_system_message(system_message)
prompt_template.add_user_message("Hi there, who are you?")
prompt_template.add_assistant_message("I am Mosscap, a chat bot. I'm trying to figure out what people need.")

function_config = sk.SemanticFunctionConfig(prompt_config, prompt_template)
chat_function = kernel.register_semantic_function("ChatBot", "Chat", function_config)


async def chat(context: sk.SKContext) -> Tuple[bool, sk.SKContext]:
    try:
        user_input = input("User:> ")
        context.variables["user_input"] = user_input
    except KeyboardInterrupt:
        print("\n\nExiting chat...")
        return False, None
    except EOFError:
        print("\n\nExiting chat...")
        return False, None

    if user_input == "exit":
        print("\n\nExiting chat...")
        return False, None

    context = await chat_completion_with_function_call(
        kernel,
        chat_skill_name="ChatBot",
        chat_function_name="Chat",
        context=context,
    )
    print(f"Mosscap:> {context.result}")
    return True, context


async def main() -> None:
    chatting = True
    context = kernel.create_new_context()
    print(
        "Welcome to the chat bot!\
\n  Type 'exit' to exit.\
\n  Try a math question to see the function calling in action (i.e. what is 3+3?)."
    )
    while chatting:
        chatting, context = await chat(context)


if __name__ == "__main__":
    asyncio.run(main())
