app.py

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


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_weather(location: str) -> str:
    """A tool that fetches the current weather for a given location.
    Args:
        location: Name of the city or place (e.g., 'Bangalore').
    """
    try:
        # Using wttr.in which returns plaintext weather info
        response = requests.get(f"https://wttr.in/{location}?format=3")
        if response.status_code == 200:
            return f"Weather in {location}: {response.text.strip()}"
        else:
            return f"Failed to get weather data for {location} (status code: {response.status_code})"
    except Exception as e:
        return f"Error fetching weather for {location}: {str(e)}"



from smolagents import tool


@tool
def create_personal_schedule(tasks: list, focus_hours: str, restrictions: str, duration_scope: str = "day") -> str:
    """A tool that generates a personalized daily or weekly schedule using an LLM.
    
    Args:
        tasks: A list of tasks (e.g., ["write report", "book flight", "team meeting"])
        focus_hours: User-defined focus hours (e.g., "10:00-13:00, 16:00-18:00")
        restrictions: Any restrictions like "no meetings after 7 PM"
        duration_scope: Either "day" or "week"
    """

    prompt = f"""
    You are a smart planning assistant. Based on the following details, generate a personalized schedule:
    
    Tasks: {tasks}
    Focus Hours: {focus_hours}
    Restrictions: {restrictions}
    Scope: {duration_scope}

    Allocate realistic time durations to tasks (e.g., booking a flight = 30 min, working on project = 3 hrs). 
    Try to match important tasks with focus hours and respect user restrictions.

    Format the output as a bullet-point schedule.
    """

    # Call the LLM (you can change the model_id if needed)
    model = HfApiModel(
        model_id="mistralai/Mixtral-8x7B-Instruct-v0.1",
        temperature=0.5,
        max_tokens=1024,
    )

    output = model(prompt)
    return output


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 ,  get_current_time_in_timezone, get_weather , create_personal_schedule], ## 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()