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from smolagents import CodeAgent, HfApiModel, load_tool, tool
import datetime
import pytz
import yaml
from tools.final_answer import FinalAnswerTool
from Gradio_UI import GradioUI
# A simple example tool that currently does nothing but shows how to define a tool.
@tool
def my_custom_tool(arg1: str, arg2: int) -> str:
"""
A placeholder tool that returns a fun message.
Args:
arg1: The first argument as a string.
arg2: The second argument as an integer.
Returns:
A string message.
"""
return "What magic will you build with this tool?"
@tool
def get_current_time_in_timezone(timezone: str) -> str:
"""
Returns the current local time in the specified timezone.
Args:
timezone: A valid timezone string (e.g., 'America/New_York').
Returns:
A formatted string with the current local time or an error message.
"""
try:
tz = pytz.timezone(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: could not fetch time for timezone '{timezone}'. Details: {e}"
@tool
def emoji_summarizer(text: str) -> str:
"""
Summarizes the input text using emojis representing key ideas.
Args:
text: Input text string.
Returns:
A string of emojis or a default emoji if no matches are found.
"""
mapping = {
"happy": "😊",
"sad": "😢",
"fire": "🔥",
"love": "❤️",
"party": "🎉",
"work": "💼",
"sleep": "😴",
"money": "💰",
"music": "🎵",
"food": "🍔",
"travel": "✈️",
"error": "❌",
"question": "❓",
}
# Basic tokenization: lowercase and split on whitespace
words = text.lower().split()
emojis = [mapping[word] for word in words if word in mapping]
if not emojis:
return "🤔 (no matching emojis found)"
return "".join(emojis)
# Initialize the final answer tool
final_answer = FinalAnswerTool()
# Initialize the language model (make sure model_id is correct and accessible)
model = HfApiModel(
max_tokens=2096,
temperature=0.5,
model_id='Qwen/Qwen2.5-Coder-32B-Instruct',
custom_role_conversions=None,
)
# Load the text-to-image generation tool from the Hugging Face hub
image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True)
# Load prompt templates from YAML file (make sure 'prompts.yaml' is present and valid)
with open("prompts.yaml", "r") as stream:
prompt_templates = yaml.safe_load(stream)
# Initialize the code agent with all desired tools
agent = CodeAgent(
model=model,
tools=[
final_answer,
emoji_summarizer,
image_generation_tool,
my_custom_tool,
get_current_time_in_timezone,
],
max_steps=6,
verbosity_level=1,
grammar=None,
planning_interval=None,
name=None,
description=None,
prompt_templates=prompt_templates,
)
# Launch the Gradio UI to interact with the agent
GradioUI(agent).launch()