from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool
import datetime
import requests
import pytz
import yaml
from tools.final_answer import FinalAnswerTool

from Gradio_UI import GradioUI
from typing import Union

@tool
def unit_converter_tool(value_: int, from_unit: str, to_unit: str) -> float:
    """
    Converts a value from one unit to another.

    Args:
        value_: The numerical value to convert.
        from_unit: The unit of the input value (e.g., "cm", "inch", "kg", "celsius").
        to_unit: The unit to convert the value to (e.g., "meter", "feet", "lbs", "fahrenheit").

    Returns:
        float or int: The converted value.
        str: "Conversion not supported." if the requested conversion is not available.
        float or int: Returns the original value if from_unit and to_unit are the same.

    Raises:
        TypeError: If value is not a number (int or float).

    Supported Conversions:
        Length: cm, inch, meter, feet
        Weight: kg, lbs, ton, quintal
        Temperature: celsius, fahrenheit
        
    """
    conversions = {
        "cm_to_inch": lambda x: x * 0.393701,
        "inch_to_cm": lambda x: x / 0.393701,
        "cm_to_meter": lambda x: x / 100,
        "meter_to_cm": lambda x: x * 100,
        "cm_to_feet": lambda x: x * 0.0328084,
        "feet_to_cm": lambda x: x / 0.0328084,
        "inch_to_meter": lambda x: x * 0.0254,
        "meter_to_inch": lambda x: x / 0.0254,
        "inch_to_feet": lambda x: x * 0.0833333,
        "feet_to_inch": lambda x: x / 0.0833333,
        "meter_to_feet": lambda x: x * 3.28084,
        "feet_to_meter": lambda x: x / 3.28084,
        "kg_to_lbs": lambda x: x * 2.20462,
        "lbs_to_kg": lambda x: x / 2.20462,
        "kg_to_ton": lambda x: x * 0.001,
        "ton_to_kg": lambda x: x / 0.001,
        "kg_to_quintal": lambda x: x * 0.01,
        "quintal_to_kg": lambda x: x / 0.01,
        "ton_to_quintal": lambda x: x * 10,
        "quintal_to_ton": lambda x: x / 10,
        "celsius_to_fahrenheit": lambda x: (x * 9/5) + 32,
        "fahrenheit_to_celsius": lambda x: (x - 32) * 5/9,
    }
    
    if not isinstance(value_, (int, float)):
        raise TypeError("Value must be a number (int or float).")
    
    conversion_name = f"{from_unit}_to_{to_unit}"

    # Handle cases where units might be the same:
    if from_unit == to_unit:
        return value_

    if conversion_name in conversions:
        return conversions[conversion_name](value_)
    else:
        return "Conversion not supported."

@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)}"


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,
model_id='Qwen/Qwen2.5-Coder-32B-Instruct',# it is possible that this model may be overloaded
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, image_generation_tool, unit_converter_tool], ## 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()