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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()