app.py

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 tool that does nothing. Amaze us with your creativity !
@tool
def my_custom_tool(arg1:str, arg2:int)-> str: #it's import to specify the return type
    #Keep this format for the description / args / args description but feel free to modify the tool
    """A tool that does nothing yet 
    Args:
        arg1: the first argument
        arg2: the second argument
    """
    return "What magic will you build ?"

@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)}"

# ==============================================
# YOUR TEXT COUNTER TOOL - ADD THIS WHOLE BLOCK
# ==============================================
@tool
def count_text_stats(text: str) -> str:
    """Count characters, words, and sentences in a text.
    
    Args:
        text: The text you want to analyze
    """
    # Count characters (including spaces)
    char_count = len(text)
    
    # Count words (split by spaces)
    words = text.split()
    word_count = len(words)
    
    # Handle empty text to avoid division by zero
    if word_count == 0:
        return f"""📊 Text Statistics:
- Characters: {char_count}
- Words: 0
- Sentences: 0
- Average word length: 0 characters"""
    
    # Count sentences (split by ., !, ?)
    sentence_endings = ['.', '!', '?']
    sentence_count = 0
    for char in text:
        if char in sentence_endings:
            sentence_count += 1
    
    return f"""📊 Text Statistics:
- Characters: {char_count}
- Words: {word_count}
- Sentences: {sentence_count}
- Average word length: {char_count / word_count:.1f} characters"""
# ==============================================

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, count_text_stats],  # <-- ADDED count_text_stats HERE!
    max_steps=6,
    verbosity_level=1,
    grammar=None,
    planning_interval=None,
    name=None,
    description=None,
    prompt_templates=prompt_templates
)


GradioUI(agent).launch()