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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 creative tool that generates emojis based on mood
@tool
def my_custom_tool(mood: str) -> str: # it's important to specify the return type
"""A tool that returns a fun emoji sequence based on the given mood.
Args:
mood: A mood like 'happy', 'sad', 'angry', or 'love'.
"""
emoji_dict = {
"happy": "😊🎉🌈✨😄",
"sad": "😢🌧️💔😭🕯️",
"angry": "😠🔥💢👿⚡",
"love": "😍❤️💌💘😘",
"tired": "😴💤☕😩🛌",
"excited": "🤩🚀🎊🥳💥",
}
return f"Mood: {mood}\nEmojis: {emoji_dict.get(mood.lower(), '🤖❓ Unknown mood ❓🤖')}"
@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()
# 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, my_custom_tool, get_current_time_in_timezone, image_generation_tool], # all tools listed
max_steps=6,
verbosity_level=1,
grammar=None,
planning_interval=None,
name=None,
description=None,
prompt_templates=prompt_templates
)
GradioUI(agent).launch()
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