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

@tool
def company_logos(company_name: str, _: int) -> str:
    """A tool that retrieves the logo of a given company using the Clearbit Logo API.

    Args:
        company_name: The name of the company.
        _: A placeholder argument (not used).

    Returns:
        The URL of the company's logo or an error message if retrieval fails.
    """
    # Convert company name into a domain-friendly format
    company_domain = company_name.lower().replace(" ", "") + ".com"
    
    # Clearbit Logo API endpoint
    logo_url = f"https://logo.clearbit.com/{company_domain}?token=sk_VoU5zjclT8Ot9RoyAbAh9g"

    try:
        # Make a request to check if the logo exists
        response = requests.get(logo_url)
        if response.status_code == 200:
            return f"Logo URL for {company_name}: {logo_url}"
        else:
            return f"Could not find a logo for {company_name}."
    except Exception as e:
        return f"Error fetching logo for {company_name}: {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, company_logos], ## 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()