from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool, LiteLLMModel from transformers import pipeline import datetime import requests import pytz import yaml import os 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 to classify text into politeness categories @tool def ask_polite_guard(input_text: str) -> dict: """Tool that classifies text into four categories: polite, somewhat polite, neutral, and impolite. Args: input_text: The text to classify. """ try: classifier = pipeline("text-classification", "Intel/polite-guard") return { "label": result['label'], "score": result['score'] } except Exception as e: return f"Error fetching classification for text '{input_text}': {str(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() # 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, # ) model = LiteLLMModel( model_id="gemini/gemini-2.0-flash-exp", max_tokens=2096, temperature=0.6, api_key=os.getenv("LITELLM_API_KEY") ) # 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, ask_polite_guard, get_current_time_in_timezone ], ## 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()