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 os
from huggingface_hub import InferenceClient
from Gradio_UI import GradioUI
from dotenv import load_dotenv
import random  # Added for tell_joke()

load_dotenv()

hf_token = os.getenv("HF_TOKEN")
alpha_vantage_api_key = os.getenv(
    "ALPHA_VANTAGE_API_KEY")  # Load Alpha Vantage API key

# Custom tool example


@tool
def my_custom_tool(arg1: str, arg2: int) -> str:
    """A tool that does nothing yet 
    Args:
        arg1: the first argument
        arg2: the second argument
    """
    return "What magic will you build ?"


def get_weather_report_at_coordinates(coordinates, date_time):
    # Dummy function, returns [temperature in °C, risk of rain 0-1, wave height in m]
    return [28.0, 0.35, 0.85]


def convert_location_to_coordinates(location):
    # Returns dummy coordinates
    return [3.3, -42.0]


@tool
def get_weather_api(location: str, date_time: str) -> str:
    """
    Returns the weather report.
    Args:
        location: the name of the place that you want the weather for.
        date_time: the date and time for which you want the report.
    """
    lon, lat = convert_location_to_coordinates(location)
    date_time = datetime.datetime.strptime(date_time, "%Y-%m-%d %H:%M:%S")
    return str(get_weather_report_at_coordinates((lon, lat), date_time))


user_data = {}


def update_personality(name: str, personality: str) -> str:
    """Asks the user about his personality before predicting his future"""
    user_data[name] = personality
    return f"Great! Thanks {name}, I've updated your personality traits. Now ask me about your future."


client = InferenceClient(model="Qwen/Qwen2.5-Coder-32B-Instruct")


@tool
def predict_future_with_model(name: str, personality: str) -> str:
    """
    Returns a fun and futuristic AI-generated prediction.
    Args:
        name: The user's name.
        personality: A description of the user's personality traits.
    """
    prompt = f"""
    Given the name '{name}' and personality traits '{personality}', generate a fun, futuristic prediction for their life.
    Your response should include:
    - A career path
    - A major life event
    - The number of kids they might have
    - A quirky or funny twist related to their personality
    Keep it engaging, futuristic, and a little humorous!
    """
    try:
        response = client.text_generation(prompt, max_new_tokens=100)
        return f"🔮 **Future Prediction for {name}:**\n{response}"
    except Exception as e:
        return f"Oops! I couldn't predict the future this time. Error: {str(e)}"


@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:
        tz = pytz.timezone(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_financial_price(ticker: str) -> str:
    """
    Fetches the real-time price of a stock, cryptocurrency, or financial product using Alpha Vantage API.
    Args:
        ticker: The ticker symbol (e.g., 'AAPL' for Apple stock, 'BTCUSD' for Bitcoin/USD).
    """
    if not alpha_vantage_api_key:
        return "Error: Alpha Vantage API key not found. Please set ALPHA_VANTAGE_API_KEY in your .env file."

    # Determine if it's a crypto or stock based on ticker format (simplified logic)
    is_crypto = len(ticker) > 5 and ticker.endswith(
        ("USD", "BTC", "ETH"))  # e.g., BTCUSD, ETHBTC
    if is_crypto:
        url = f"https://www.alphavantage.co/query?function=CURRENCY_EXCHANGE_RATE&from_currency={ticker[:3]}&to_currency={ticker[3:]}&apikey={alpha_vantage_api_key}"
    else:
        url = f"https://www.alphavantage.co/query?function=GLOBAL_QUOTE&symbol={ticker}&apikey={alpha_vantage_api_key}"

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

        if is_crypto:
            if "Realtime Currency Exchange Rate" in data:
                price = data["Realtime Currency Exchange Rate"]["5. Exchange Rate"]
                return f"The current price of {ticker[:3]} in {ticker[3:]} is {float(price):.2f} {ticker[3:]}."
            else:
                return f"Error: Could not fetch crypto price for {ticker}. Check the ticker symbol."
        else:
            if "Global Quote" in data and "05. price" in data["Global Quote"]:
                price = data["Global Quote"]["05. price"]
                return f"The current price of {ticker} is ${float(price):.2f} USD."
            else:
                return f"Error: Could not fetch stock price for {ticker}. Check the ticker symbol or API limits."

    except Exception as e:
        return f"Error fetching price for {ticker}: {str(e)}"


@tool
def tell_joke() -> str:
    """Returns a random stored joke."""
    jokes = [
        "Why do we tell actors to 'break a leg?' Because every play has a cast.",
        "I told my wife she should embrace her mistakes. She gave me a hug.",
        "I'm reading a book on the history of glue. I just can't seem to put it down.",
        "I would tell you a joke about an elevator, but it's an uplifting experience.",
        "I told my computer I needed a break and now it won't stop sending me vacation ads.",
        "I used to play piano by ear, but now I use my hands"
    ]
    return random.choice(jokes)


final_answer = FinalAnswerTool()

model = HfApiModel(
    max_tokens=2096,
    temperature=0.5,
    model_id='Qwen/Qwen2.5-Coder-32B-Instruct',
    custom_role_conversions=None,
)

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=[
        my_custom_tool,
        get_weather_api,
        predict_future_with_model,
        get_current_time_in_timezone,
        get_financial_price,  # New tool added here
        tell_joke,
        final_answer
    ],
    max_steps=6,
    verbosity_level=1,
    grammar=None,
    planning_interval=None,
    name=None,
    description=None,
    prompt_templates=prompt_templates
)

GradioUI(agent).launch()