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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 find_product(num1:int, num2:int)-> int: #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 multiplies num1 and num2
# Args:
# num1: the first number
# num2: the second number
# """
# return num1*num2
@tool
def greet(name: str)-> 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 greets user when the name is specified
Args:
name: a string representing name of the user
"""
return f"Hello {name}, Have a nice day!!"
@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 get_latest_ai_agent_arxiv_papers(num_papers:int = 5) -> list:
"""
Searches arXiv for the latest research papers on AI agents and retrieves
the specified number of results.
Args:
num_papers: The number of papers to retrieve (default: 5).
Returns:
A list of dictionaries, where each dictionary represents a paper and
contains its title, authors, and URL. Returns an empty list if any errors occur.
Prints informative messages to the console during the search.
"""
import arxiv
try:
search = arxiv.Search(
query="AI agents", # Your search term
max_results=num_papers,
sort_by=arxiv.SortCriterion.SubmittedDate # Sort by submission date for latest
)
papers = []
for result in search.results():
paper_info = {
"title": result.title,
"authors": ", ".join([author.name for author in result.authors]), # Nicer author format
"url": result.pdf_url,
"date": result.published.date(), # Get the date part of the datetime object
"abstract": result.summary
}
papers.append(paper_info)
return papers
except Exception as e:
print(f"An error occurred during the arXiv search: {e}")
return []
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
model_id='https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud',
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,greet,get_latest_ai_agent_arxiv_papers], ## 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() |