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 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_nba_matches() -> str:
    """
    A tool that retrieves upcoming NBA matches using TheRundown API.
    
    Returns:
        A human-readable string listing the upcoming NBA matches.
    """
    import requests
    # Replace the endpoint below with the correct NBA events endpoint if available.
    # Here we assume sport_id 4 corresponds to NBA and that the '/events' endpoint returns the matches.
    url = "https://api.apilayer.com/therundown/sports/4/events"
    headers = {
        "apikey": "7k4hKSUeWkbigKxZiNV5CQ8RSlEd72Cj"
    }
    
    response = requests.get(url, headers=headers)
    if response.status_code == 200:
        data = response.json()
        matches = []
        # Parse the JSON based on the API's structure.
        # (Adjust the keys below according to the actual response format.)
        for event in data.get("events", []):
            start_time = event.get("start_time", "Unknown time")
            home_team = event.get("home_team", "Home team not available")
            away_team = event.get("away_team", "Away team not available")
            matches.append(f"{start_time}: {home_team} vs {away_team}")
        if matches:
            return "\n".join(matches)
        else:
            return "No NBA matches found."
    else:
        return f"Error retrieving NBA matches: {response.status_code}"

@tool
def predict_nba_match(match_info: str) -> str:
    """
    A tool that generates a prediction for an NBA match.
    
    Args:
        match_info: A string containing match details in the format "TeamA vs TeamB".
    
    Returns:
        A string with the prediction, e.g. "The prediction is that TeamA will win.".
    """
    import random
    teams = match_info.split(" vs ")
    if len(teams) == 2:
        prediction = random.choice(teams)
        return f"The prediction is that {prediction} will win."
    else:
        return "Invalid match format. Please provide match details in the format 'TeamA vs TeamB'."


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()