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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 convert_currency(amount: float, from_currency: str, to_currency: str) -> str:
"""Converts an amount from one currency to another.
Args:
amount: Amount to convert (must be a positive number)
from_currency: Source currency code (e.g., 'USD', 'EUR', 'JPY')
to_currency: Target currency code (e.g., 'USD', 'EUR', 'JPY')
"""
# Validate input parameters
if amount <= 0:
return "Error: Amount must be a positive number."
# Convert currency codes to uppercase
from_currency = from_currency.upper()
to_currency = to_currency.upper()
# List of valid currency codes (abbreviated)
valid_currencies = ["USD", "EUR", "JPY", "GBP", "AUD", "CAD", "CHF", "CNY", "INR"]
# Validate currency codes
if from_currency not in valid_currencies:
return f"Error: '{from_currency}' is not a recognized currency code."
if to_currency not in valid_currencies:
return f"Error: '{to_currency}' is not a recognized currency code."
try:
# For a real application, you would use an API like:
# api_url = f"https://api.exchangerate-api.com/v4/latest/{from_currency}"
# response = requests.get(api_url)
# data = response.json()
# rate = data["rates"][to_currency]
# For demonstration, using a simplified mock conversion
# This is a very simplified approach, would use real API in production
exchange_rates = {
"USD": {"EUR": 0.92, "JPY": 150.2, "GBP": 0.79, "AUD": 1.53, "CAD": 1.36, "CHF": 0.89, "CNY": 7.2, "INR": 83.5},
"EUR": {"USD": 1.09, "JPY": 163.3, "GBP": 0.86, "AUD": 1.66, "CAD": 1.48, "CHF": 0.97, "CNY": 7.84, "INR": 90.8},
# Add other currency pairs as needed
}
# Get conversion rate
if from_currency == to_currency:
rate = 1.0
elif from_currency in exchange_rates and to_currency in exchange_rates[from_currency]:
rate = exchange_rates[from_currency][to_currency]
else:
# For missing pairs, return a message about using a real API
return f"Demo mode: Would use real API to convert {from_currency} to {to_currency}."
# Calculate converted amount
converted_amount = amount * rate
# Format result
return f"{amount:.2f} {from_currency} = {converted_amount:.2f} {to_currency}"
except Exception as e:
return f"Error during currency conversion: {str(e)}"
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, convert_currency, DuckDuckGoSearchTool(), image_generation_tool], ## 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()