from smolagents import CodeAgent, DuckDuckGoSearchTool, HfApiModel, load_tool, tool
import datetime
import requests
import pytz
import yaml
from tools.final_answer import FinalAnswerTool
import os
from huggingface_hub import InferenceClient
from Gradio_UI import GradioUI
from dotenv import load_dotenv
load_dotenv()

hf_token = os.getenv("HF_TOKEN")

# Below is an example of a tool that does nothing. Amaze us with your creativity !


@tool
# it's import to specify the return type
def my_custom_tool(arg1: str, arg2: int) -> str:
    # Keep this format for the description / args / args description but feel free to modify the tool
    """A tool that does nothing yet 
    Args:
        arg1: the first argument
        arg2: the second argument
    """
    return "What magic will you build ?"


def get_weather_report_at_coordinates(coordinates, date_time):
    # Dummy function, returns a list of [temperature in °C, risk of rain on a scale 0-1, wave height in m]
    return [28.0, 0.35, 0.85]


def convert_location_to_coordinates(location):
    # Returns dummy coordinates
    return [3.3, -42.0]


@tool
def get_weather_api(location: str, date_time: str) -> str:
    """
    Returns the weather report.

    Args:
        location: the name of the place that you want the weather for.
        date_time: the date and time for which you want the report.
    """
    lon, lat = convert_location_to_coordinates(location)
    date_time = datetime.strptime(date_time)
    return str(get_weather_report_at_coordinates((lon, lat), date_time))


user_data = {}


def update_personality(name: str, personality: str) -> str:
    """Asks the user about his personality before predicting his future
    """
    user_data[name] = personality
    return f"Great! Thanks {name} I ve updates your personality traits, now ask me about your future."


'''
I would like to use an AI model that takes the name and personality and predicts number of kids, career etc '''

client = InferenceClient(model="Qwen/Qwen2.5-Coder-32B-Instruct")


@tool
def predict_future_with_model(name: str, personality: str) -> str:
    """

    Returns:
        str: A fun and futuristic AI-generated prediction.
    Args:
        name: The user's name.
        personality: A description of the user's personality traits.


    """

    prompt = f"""
    Given the name '{name}' and personality traits '{personality}', generate a fun, futuristic prediction for their life.

    Your response should include:
    - A career path
    - A major life event
    - The number of kids they might have
    - A quirky or funny twist related to their personality

    Keep it engaging, futuristic, and a little humorous!
    """

    try:
        response = client.text_generation(prompt, max_new_tokens=100)
        return f"🔮 **Future Prediction for {name}:**\n{response}"
    except Exception as e:
        return f"Oops! I couldn't predict the future this time. Error: {str(e)}"


@tool
def get_current_time_in_timezone(timezone: str) -> str:
    """A tool that fetches the current local time in a specified timezone.
    Args:
        timezone: A string representing a valid timezone (e.g., 'America/New_York').
    """
    try:
        # Create timezone object
        tz = pytz.timezone(timezone)
        # Get current time in that timezone
        local_time = datetime.datetime.now(tz).strftime("%Y-%m-%d %H:%M:%S")
        return f"The current local time in {timezone} is: {local_time}"
    except Exception as e:
        return f"Error fetching time for timezone '{timezone}': {str(e)}"


def tell_joke() -> str:
    """stored jokes.
    """
    jokes = ["Why do we tell actors to 'break a leg?' Because every play has a cast.",
             "I told my wife she should embrace her mistakes. She gave me a hug.",
             "I'm reading a book on the history of glue. I just can't seem to put it down.",
             "I would tell you a joke about an elevator, but it's an uplifting experience.",
             "I told my computer I needed a break and now it won't stop sending me vacation ads.",
             "I used to play piano by ear, but now I use my hands"]
    return random.choice(jokes)


final_answer = FinalAnswerTool()

# If the agent does not answer, the model is overloaded, please use another model or the following Hugging Face Endpoint that also contains qwen2.5 coder:
# model_id='https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud'

model = HfApiModel(
    max_tokens=2096,
    temperature=0.5,
    # it is possible that this model may be overloaded
    model_id='Qwen/Qwen2.5-Coder-32B-Instruct',
    custom_role_conversions=None,
)


# Import tool from Hub
image_generation_tool = load_tool(
    "agents-course/text-to-image", trust_remote_code=True)

with open("prompts.yaml", 'r') as stream:
    prompt_templates = yaml.safe_load(stream)

agent = CodeAgent(
    model=model,
    tools=[final_answer],  # add your tools here (don't remove final answer)
    max_steps=6,
    verbosity_level=1,
    grammar=None,
    planning_interval=None,
    name=None,
    description=None,
    prompt_templates=prompt_templates
)


GradioUI(agent).launch()