app1.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

# Tool: Fetch current time in a given timezone
@tool
def get_current_time_in_timezone(timezone: str) -> str:
    """
    Fetches the current local time in a specified timezone.

    Args:
        timezone (str): The timezone string (e.g., 'America/New_York').
    
    Returns:
        str: The current local time in the specified timezone.
    """
    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: Fetch real-time weather for a given location
@tool
def get_weather(city: str) -> str:
    """
    Fetches the current weather for a given city.

    Args:
        city (str): The name of the city.
    
    Returns:
        str: Weather description and temperature.
    """
    api_url = f"https://wttr.in/{city}?format=%C+%t"
    response = requests.get(api_url)
    if response.status_code == 200:
        return response.text
    return "Unable to retrieve weather information."

# Tool: Fetch currency exchange rate
@tool
def get_exchange_rate(base_currency: str, target_currency: str) -> str:
    """
    Fetches the exchange rate between two currencies.

    Args:
        base_currency (str): The currency to convert from.
        target_currency (str): The currency to convert to.
    
    Returns:
        str: Exchange rate information.
    """
    url = f"https://api.exchangerate-api.com/v4/latest/{base_currency}"
    response = requests.get(url)
    if response.status_code == 200:
        data = response.json()
        rate = data['rates'].get(target_currency, "N/A")
        return f"1 {base_currency} = {rate} {target_currency}"
    return "Exchange rate information not available."

# Tool: Fetch Wikipedia summary
@tool
def get_wikipedia_summary(query: str) -> str:
    """
    Fetches a short summary from Wikipedia.

    Args:
        query (str): The topic to search on Wikipedia.
    
    Returns:
        str: Summary of the topic.
    """
    url = f"https://en.wikipedia.org/api/rest_v1/page/summary/{query}"
    response = requests.get(url)
    if response.status_code == 200:
        return response.json().get("extract", "No summary available.")
    return "Wikipedia summary not found."

# Tool: Fetch latest news headlines
@tool
def get_latest_news() -> str:
    """
    Fetches the latest news headlines.
    
    Returns:
        str: Top 5 latest news headlines.
    """
    url = "https://newsapi.org/v2/top-headlines?country=us&apiKey=YOUR_NEWSAPI_KEY"
    response = requests.get(url)
    if response.status_code == 200:
        articles = response.json().get("articles", [])[:5]
        return "\n".join([f"{i+1}. {article['title']}" for i, article in enumerate(articles)])
    return "Unable to retrieve news."

# Tool: Fetch stock price for a given company symbol
@tool
def get_stock_price(symbol: str) -> str:
    """
    Fetches the latest stock price for a given company symbol.

    Args:
        symbol (str): The stock ticker symbol.
    
    Returns:
        str: The latest stock price.
    """
    url = f"https://finnhub.io/api/v1/quote?symbol={symbol}&token=YOUR_FINNHUB_API_KEY"
    response = requests.get(url)
    if response.status_code == 200:
        data = response.json()
        return f"Stock price of {symbol}: ${data.get('c', 'N/A')}"
    return "Stock information not available."

final_answer = FinalAnswerTool()

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

# Load image generation tool from Hugging Face
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)
    
# Creating the AI agent
agent = CodeAgent(
    model=model,
    tools=[
        final_answer,
        get_current_time_in_timezone,
        get_weather,
        get_exchange_rate,
        get_wikipedia_summary,
        get_latest_news,
        get_stock_price,
        image_generation_tool,
    ],
    max_steps=6,
    verbosity_level=1,
    grammar=None,
    planning_interval=None,
    name=None,
    description=None,
    prompt_templates=prompt_templates
)

# Launch Gradio UI for interaction
GradioUI(agent).launch()