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 buscar_duckduckgo(termo: str, num_resultados: int = 5) -> str:
    """Busca real na web usando DuckDuckGo (gratuito, sem API key).
    
    Args:
        termo: Termo para buscar
        num_resultados: Quantidade de resultados (máximo 10)
    """
    if not termo.strip():
        return "❌ Termo de busca não pode estar vazio!"
    
    if num_resultados > 10:
        num_resultados = 10
    
    try:
        # DuckDuckGo Instant Answer API (gratuita)
        url = "https://api.duckduckgo.com/"
        params = {
            'q': termo,
            'format': 'json',
            'no_html': '1',
            'skip_disambig': '1'
        }
        
        response = requests.get(url, params=params, timeout=10)
        
        if response.status_code == 200:
            data = response.json()
            
            resultado = f"🔍 **Busca: '{termo}'**\n\n"
            
            # Abstract (resumo principal)
            if data.get('Abstract'):
                resultado += f"📄 **Resumo:**\n{data['Abstract']}\n\n"
            
            # Definition (definição)
            if data.get('Definition'):
                resultado += f"📚 **Definição:**\n{data['Definition']}\n\n"
            
            # Related Topics
            if data.get('RelatedTopics'):
                resultado += "🔗 **Tópicos Relacionados:**\n"
                for i, topic in enumerate(data['RelatedTopics'][:num_resultados], 1):
                    if isinstance(topic, dict) and topic.get('Text'):
                        resultado += f"{i}. {topic['Text'][:100]}...\n"
                resultado += "\n"
            
            # Answer (resposta direta)
            if data.get('Answer'):
                resultado += f"💡 **Resposta Direta:**\n{data['Answer']}\n\n"
            
            if not any([data.get('Abstract'), data.get('Definition'), 
                       data.get('RelatedTopics'), data.get('Answer')]):
                resultado += "ℹ️ Nenhum resultado específico encontrado para este termo.\n"
                resultado += "💡 Tente termos mais específicos ou diferentes."
            
            return resultado
            
        else:
            return f"❌ Erro na busca: Status {response.status_code}"
            
    except requests.RequestException as e:
        return f"❌ Erro de conexão: {e}"
    except Exception as e:
        return f"❌ Erro inesperado: {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:
        # 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)}"


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()