app.py

from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool
import datetime
import requests
import pytz
import yaml
from urllib.parse import quote_plus
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_food_nutritional_facts(food_item: str) -> str:
    """A tool that fetches nutritional facts for an input food item.
    Args:
        food_item: A string that represents the input food item (e.g., 'Chicken Breast').
    """
    api_key = "qCdPkedVRtvwvaQiNqq8khx15Rj8GG7ukexEn9nk"
    encoded_food_item = quote_plus(food_item)
    url = f"https://api.nal.usda.gov/fdc/v1/foods/search?query={encoded_food_item}&api_key={api_key}&pageSize=1"

    try:
        response = requests.get(url)
        data = response.json()

        if not data.get("foods"):
            return f"No results found for '{food_item}'"

        food = data["foods"][0]
        description = food.get("description", "Unknown")

        nutrient_ids = {1008: "Calories", 1003: "Protein", 1004: "Fat", 1005: "Carbs"}
        results = {}

        for nutrient in food.get("foodNutrients", []):
            nid = nutrient.get("nutrientId")
            if nid in nutrient_ids:
                results[nutrient_ids[nid]] = f"{nutrient.get('value', 'N/A')} {nutrient.get('unitName', '')}"

        output = f"Nutritional facts for: {description} (per 100g)\n"
        for name, value in results.items():
            output += f"  {name}: {value}\n"

        return output

    except Exception as e:
        return f"Error fetching nutritional facts for '{food_item}': {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, get_food_nutritional_facts], ## 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()