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
import yfinance as yf
from typing import Any, Optional

import logging
# Set up logging
logging.basicConfig(level=logging.INFO)

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_stock_price(ticker_symbol: str) -> Optional[dict]:
    """
    Get the latest stock price for the given ticker symbol and calculates
    the price change over the last 5 days and retrun current stock price , 
    price change and percentage change. 

    Args:
        ticker_symbol: The stock ticker symbol to fetch the price for.

    Returns:
        price -> dict: A dictionary containing the current stock price, the price change
              over the last 5 days, and the percentage change. 
              Returns None if there's an error or no data is available.
    """
    try:
        # Fetch stock data
        stock = yf.Ticker(ticker_symbol)
        stock_data = stock.history(period="5d")  # Fetch data for the last 5 days
        
        if stock_data.empty:
            return {"error": f"No historical data available for {ticker_symbol}"}
        
        # Get the current price (last close price)
        current_price = stock_data['Close'].iloc[-1]
        
        # Calculate the price change over the last 5 days
        price_change = current_price - stock_data['Close'].iloc[0]
        price_change_percent = (price_change / stock_data['Close'].iloc[0]) * 100

        # Round all values to 2 decimal places
        price =  {
            "price": round(current_price, 2),
            "price_change": round(price_change, 2),
            "price_change_percent": round(price_change_percent, 2)
        }
        return price 

    except yf.exceptions.YFinanceException as yf_err:
        logger.error(f"YFinance error for {ticker_symbol}: {str(yf_err)}")
    except Exception as e:
        logger.error(f"Unexpected error fetching price for {ticker_symbol}: {str(e)}")
    return None

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=[get_current_stock_price], ## 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()