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

# Below is an example of a tool that does nothing. Amaze us with your creativity !
@tool
def my_custom_tool(arg1:str, arg2:int)-> str: #it's import to specify the return type
    #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 ?"

@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)}"

@tool
def get_current_weather(city) -> str:
    """
    Retrieve the current weather for a given city.
    """

    # 1. Retrieve the city's coordinates
    api_url = "https://geocoding-api.open-meteo.com/v1/search"

    params = {
        "name": city,
        "count": 1,
        "language": "fr",
        "format": "json",
        "countryCode": "FR"
    }

    response = requests.get(api_url, params=params, timeout=10)
    response.raise_for_status()
    data = response.json()

    # Check whether the city was found
    if not data.get("results"):
        return f"No city found for: {city}"

    city_data = data["results"][0]
    latitude = city_data["latitude"]
    longitude = city_data["longitude"]

    # 2. Retrieve the current weather
    weather_url = "https://api.open-meteo.com/v1/forecast"

    weather_params = {
        "latitude": latitude,
        "longitude": longitude,
        "current": "temperature_2m,relative_humidity_2m,weather_code",
        "timezone": "auto"
    }

    response = requests.get(
        weather_url,
        params=weather_params,
        timeout=10
    )
    response.raise_for_status()
    weather_data = response.json()

    # 3. Extract the current weather information
    current = weather_data["current"]

    temperature = current["temperature_2m"]
    humidity = current["relative_humidity_2m"]
    weather_code = current["weather_code"]

    # 4. Convert the weather code into a description
    weather_descriptions = {
        0: "Clear sky",
        1: "Mainly clear",
        2: "Partly cloudy",
        3: "Overcast",
        45: "Fog",
        48: "Depositing rime fog",
        51: "Light drizzle",
        53: "Moderate drizzle",
        55: "Dense drizzle",
        61: "Slight rain",
        63: "Moderate rain",
        65: "Heavy rain",
        71: "Slight snowfall",
        73: "Moderate snowfall",
        75: "Heavy snowfall",
        80: "Slight rain showers",
        81: "Moderate rain showers",
        82: "Violent rain showers",
        95: "Thunderstorm"
    }

    description = weather_descriptions.get(
        weather_code,
        "Unknown weather conditions"
    )

    # 5. Return the weather report
    return (
        f"In {city}, the temperature is {temperature} °C, "
        f"with a relative humidity of {humidity}%. "
        f"Conditions: {description}."
    )


print(get_current_weather("Paris"))

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], ## 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()