app.py

import datetime
import requests
import pytz
import yaml
import json

from tools.weather import WeatherForecast
from tools.final_answer import FinalAnswerTool
from smolagents import CodeAgent, HfApiModel, load_tool, tool
from Gradio_UI import GradioUI

@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_weather_forecast(city_name: str) -> str:
    """A tool that fetches the current weather/temperature of a specified city.
    Args:
        city_name: A string representing a valid city (e.g., 'Bangalore').
    """

    latitude, longitude = get_coordinates(city_name)
    
    base_url = "https://api.open-meteo.com/v1/forecast"  # No API key needed for this version
    params = {
        "latitude": latitude,
        "longitude": longitude,
        "hourly": "temperature_2m",
        "daily": "temperature_2m_max,temperature_2m_min,precipitation_sum",
        "forecast_days": 7,
        "timezone": "auto"
    }

    try:
        response = requests.get(base_url, params=params) # No headers needed
        response.raise_for_status()
        weatherJSON = response.json()
        cityName = weatherJSON.get('location').get('name')
        cityTemp = weatherJSON.get('hourly').get('temperature_2m')
        averageTemp = round(mean(cityTemp), 1)
        hourlyunits = weatherJSON.get('hourly_units').get('temperature_2m')
        return weather_data
        return f"The current Temperature in {cityName} is {averageTemp}{hourlyunits}!"
    except requests.exceptions.RequestException as e:
        print(f"Error fetching weather data: {e}")
        return None
    except json.JSONDecodeError as e:
        print(f"Error decoding JSON response: {e}")
        return None

def get_coordinates(city_name: str) -> [float, float]:
    """Gets coordinates using OpenStreetMap's Nominatim (no API key, but with limitations)."""

    # This approach is less reliable and might have rate limits.
    # It's suitable for basic use cases but not for production.
    headers = {
        'User-Agent': 'MyGeocodingApp/1.0 (youremail@example.com)'  # Replace with your actual email
    }
    geocoding_url = "https://nominatim.openstreetmap.org/search" # No API Key needed
    params = {
        "q": city_name,
        "format": "json",
        "limit": 1
    }

    try:
        response = requests.get(geocoding_url, params=params)
        response.raise_for_status()
        geocoding_data = response.json()

        if geocoding_data:  # Check if any results were found
            latitude = float(geocoding_data[0]["lat"])
            longitude = float(geocoding_data[0]["lon"])
            return latitude, longitude
        else:
            print(f"Could not find coordinates for {city_name}")
            return None, None

    except requests.exceptions.RequestException as e:
        print(f"Error during geocoding: {e}")
        return None, None
    except (KeyError, IndexError, ValueError) as e:  # Handle more potential errors
        print(f"Error parsing geocoding response: {e}")
        return None, None

final_answer = FinalAnswerTool()
weather_forecast = WeatherForecast()

# model_id='https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud' 

model_id='Qwen/Qwen2.5-Coder-32B-Instruct' # it is possible that this model may be overloaded
model = HfApiModel(
    max_tokens=2096,
    temperature=0.5,
    model_id=model_id,
    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=[weather_forecast, final_answer], ## add your tools here (don't remove final answer)
    max_steps=2,
    verbosity_level=1,
    grammar=None,
    planning_interval=None,
    name=None,
    description=None,
    prompt_templates=prompt_templates
)


GradioUI(agent).launch()