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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. | |
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?" | |
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}" | |
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() | |