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 tools.generate_recipe import RecipeGeneratorTool

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 recommend_diet_brunch(diet_type: str) -> str:
    """A tool that recommends a brunch based on the type of diet.
    
    Args:
        diet_type: A description of the type of diet (e.g., vegan, keto, etc.).
        
    Returns:
        A string with a brunch recommendation.
    """
    # Normalize input to lowercase for matching.
    diet_type_lower = diet_type.lower()
    
    # Map diet types to brunch suggestions.
    diet_to_brunch = {
        "vegan": "Tofu scramble with avocado toast, fruit salad, and a green smoothie.",
        "keto": "Avocado and egg breakfast bowl with bacon and spinach.",
        "vegetarian": "Vegetable frittata with a side of roasted potatoes and fresh fruit.",
        "paleo": "Grilled chicken with roasted sweet potatoes, sautéed spinach, and avocado.",
        "gluten-free": "Gluten-free pancakes with berries and almond butter.",
        "low-carb": "Egg muffins with spinach, cheese, and bacon, served with a side of avocado.",
        "intermittent fasting": "A light salad with lean protein like grilled chicken, nuts, and avocado.",
        "mediterranean": "Greek yogurt with honey, walnuts, and a side of olives and cucumber."
    }
    
    # Default to a vegetarian brunch if diet type is unknown.
    recommended_brunch = diet_to_brunch.get(diet_type_lower, "Vegetable frittata with a side of roasted potatoes and fresh fruit.")
    
    return f"Based on your diet type ('{diet_type}'), I recommend this brunch: {recommended_brunch}"


final_answer = FinalAnswerTool()
generate_recipe = RecipeGeneratorTool()

# 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
#model_id='meta-llama/Llama-3.2-3B-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, recommend_diet_brunch], ## 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()