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
import logging
from typing import Optional, Dict, Any

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)}"


final_answer = FinalAnswerTool()


@tool
def get_current_stock_price(ticker_symbol: str) -> Optional[Dict[str, Any]]:
    logger = logging.getLogger(__name__)
    logger.setLevel(logging.DEBUG)
    
    """
    Get the latest stock price for the given ticker symbol by querying Yahoo Finance directly,
    then calculate the price change over the last 5 days (percentage and absolute).

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

    Returns:
        A dictionary containing:
            - "price"                : current closing price (float)
            - "price_change"         : absolute change over 5 days (float)
            - "price_change_percent" : percent change over 5 days (float)

        If there's an error or no data is available, returns a dict with an "error" key, e.g.
            {"error": "No historical data available for TSLA"}
        Or returns None for unexpected issues.
    """
    try:
        # Build the Yahoo Finance “chart” API URL for the last 5 calendar days.
        url = f"https://query1.finance.yahoo.com/v8/finance/chart/{ticker_symbol}"
        params = {
            "range": "5d",
            "interval": "1d",
            # We only need daily closes, so the default interval=1d is fine.
        }

        resp = requests.get(url, params=params, timeout=10)
        resp.raise_for_status()
        data = resp.json()

        # Drill into the JSON structure:
        #   data["chart"]["result"][0]["indicators"]["quote"][0]["close"]
        chart = data.get("chart", {})
        if not chart or chart.get("error"):
            return {"error": f"Yahoo Finance returned an error for {ticker_symbol}."}

        result_list = chart.get("result", [])
        if not result_list:
            return {"error": f"No chart result found for {ticker_symbol}."}

        quote_section = result_list[0].get("indicators", {}).get("quote", [])
        if not quote_section:
            return {"error": f"No quote information in chart for {ticker_symbol}."}

        closes = quote_section[0].get("close", [])
        # The “close” array may contain nulls if the market was closed on a given day.
        # Filter out any None values:
        closes = [c for c in closes if (c is not None)]

        if len(closes) < 2:
            return {"error": f"Not enough close‐price data (need at least 2 days) for {ticker_symbol}."}

        # The “closes” list is chronological; last element is the most recent closing price:
        first_price = closes[0]
        current_price = closes[-1]

        # Calculate changes:
        price_change = current_price - first_price
        price_change_percent = (price_change / first_price) * 100 if first_price != 0 else 0.0

        # Round everything to two decimals:
        return {
            "price": round(current_price, 2),
            "price_change": round(price_change, 2),
            "price_change_percent": round(price_change_percent, 2),
        }

    except requests.HTTPError as http_err:
        logger.error(f"HTTP error while fetching {ticker_symbol} data: {http_err}")
        return {"error": f"HTTPError fetching data for {ticker_symbol}: {http_err}"}
    except requests.RequestException as req_err:
        logger.error(f"Request exception for {ticker_symbol}: {req_err}")
        return {"error": f"RequestException fetching data for {ticker_symbol}: {req_err}"}
    except (KeyError, IndexError, ValueError) as parse_err:
        logger.error(f"Parsing error for {ticker_symbol}: {parse_err}")
        return {"error": f"Parsing error for {ticker_symbol}: {parse_err}"}
    except Exception as e:
        logger.error(f"Unexpected error fetching price for {ticker_symbol}: {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=[final_answer], ## 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()