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fix_wikipediaTool_mst
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from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool
import datetime
import requests
import pytz
import yaml
import math
from tools.final_answer import FinalAnswerTool
from Gradio_UI import GradioUI
@tool
def calculate_mcm_mcd(num1: int, num2: int) -> dict:
"""Calcula los primeros 10 múltiplos comunes mínimos (MCM) y divisores comunes máximos (MCD) de dos números.
Args:
num1: Primer número entero.
num2: Segundo número entero.
Returns:
Un diccionario con:
- Lista de los primeros 10 MCM.
- Lista de los primeros 10 MCD.
"""
try:
gcd_value = math.gcd(num1, num2)
mcm_list = [math.lcm(num1, num2) * i for i in range(1, 11)]
mcd_list = [i for i in range(1, gcd_value + 1) if gcd_value % i == 0][:10]
return {
"MCM": mcm_list,
"MCD": mcd_list
}
except Exception as e:
return {"Error": f"Ocurrió un error: {str(e)}"}
@tool
def get_time_by_city(city: str) -> str:
"""Obtiene la hora local en una ciudad específica.
Args:
city: Nombre de la ciudad (Ejemplo: 'America/Lima')
Returns:
Hora actual en la ciudad dada.
"""
try:
tz = pytz.timezone(city)
local_time = datetime.datetime.now(tz).strftime("%Y-%m-%d %H:%M:%S")
return f"La hora en {city} es {local_time}."
except Exception as e:
return f"Error al obtener la hora para '{city}': {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=[calculate_mcm_mcd, get_time_by_city, 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()