app.py

from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool, VisitWebpageTool
import datetime
import requests
import pytz
import yaml
from tools.final_answer import FinalAnswerTool
from datetime import date
from collections import namedtuple
from typing import Tuple
import re


from Gradio_UI import GradioUI


web_search = DuckDuckGoSearchTool()
visit_webpage = VisitWebpageTool()

final_answer = FinalAnswerTool()

SearchResult = namedtuple("SearchResult", ["title", "url", "description"])



# 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 todays_date() -> str:
    """ Returns the current date in the format of 'Month Day, Year' 
    
    Returns:
        str: The current date in the format of 'Month Day
    """
    today = date.today()
    return today.strftime("%b %d, %Y")

def parse_md_link(md_link: str) -> Tuple[str, str]:
    """ parse markdown link to the title and link"""
    pattern = r'\[([^\]]+)\]\(([^)]+)\)'
    matches = re.findall(pattern, md_link)
    if len(matches) > 0:
        return matches[0]
    return None

def search_specific_website(topic: str, url: str, num_results: int):
    query = f"{url} {topic}"

    query_result =  web_search(query).split("\n\n")[1:num_results]
    output = []
    for result in query_result:
        link, description = result.split("\n")
        title_url = parse_md_link(link)
        if title_url is None:
            continue
        title, url = title_url
        output.append(SearchResult(title=title, url=url, description=description))
    return output
    

def get_arxiv_paper_abstract(url):
    result = visit_webpage(url)
    for line in result.split("\n"):
        if line.startswith("> Abstract:"):
            return line.strip("> Abstract:")
    return ""


@tool
def search_arxiv(topic: str, year: str = None, num_results: int = 10) -> str:
    """
    Search arxiv.org for a given topic. It will return the title and abstract of the top results

    Args:
        topic: The topic to search for.
        year: Specic year to search for. Default is None
        num_results: Indicating how many top search results should be included in the output

    Returns:
        A list of query result of title and abstract contcatenated by "\n\n".
    """
    if year is None:
        year = ""
    query_results =  search_specific_website(topic + " " + year, "site:arxiv.org", num_results)

    output = []
    for result in query_results:
        output.append("Title: {}\nAbstract: {}".format(result.title, get_arxiv_paper_abstract(result.url)))
    return "\n\n".join(output)

    

@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)}"


# 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, todays_date, search_arxiv], ## 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()