from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool import datetime import requests import pytz import yaml import os from dotenv import load_dotenv from tools.final_answer import FinalAnswerTool from pytrends.request import TrendReq from Gradio_UI import GradioUI load_dotenv() HF_TOKEN = os.getenv("HF_U1APP_TOKEN") @tool def get_trending_searches(region:str="united states") -> list: """ A tool to fetch the current top trending searches from Google Trends. Args: region: Country code (e.g., 'united states') """ try: pytrends = TrendReq() trending = pytrends.trending_searches(pn=region) return trending[0].tolist() except Exception as e: return f"Error fetching trends:{str(e)}" @tool def add_numbers(a:int, b:int)-> int: """A tool that adds two integers. Args: a: the first integer b: the second integer """ return a+b @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 duckduckgo_search(query: str) -> str: """Searches DuckDuckGo for a given query and returns the top result. Args: query: The search query string. Returns: A short summary with the top DuckDuckGo result. """ search_tool = DuckDuckGoSearchTool() results = search_tool.run(query) if results: return f"Top search result: {results[0]['title']} - {results[0]['link']}" else: return "No results found." @tool def get_sentiment(text: str) -> str: """Analyze the sentiment of the given text (Positive/Negative/Neutral) Args: text: The input text to analyze. (e.g., 'I am so happy today!') Returns: A string indicating the sentiment (Positive, Negative, or Neutral). """ text_lower = text.lower() if any(word in text_lower for word in ["good", "great", "awesome", "fantastic", "love", "happy"]): return "Sentiment: Positive" elif any(word in text_lower for word in ["bad", "terrible", "awful", "hate", "angry", "sad"]): return "Sentiment: Negative" else: return "Sentiment: Neutral" final_answer = FinalAnswerTool() model = HfApiModel( max_tokens=2096, temperature=0.5, model_id="Qwen/Qwen2.5-Coder-32B-Instruct", custom_role_conversions=None, token=HF_TOKEN ) # 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=[get_trending_searches, image_generation_tool, add_numbers, duckduckgo_search, get_current_time_in_timezone,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()