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 levenshtein_distance(str1:str, str2:str) -> str:
    """
    Calculate the Levenshtein distance (edit distance) between two strings.
    
    The Levenshtein distance is the minimum number of single-character operations
    (insertions, deletions, or substitutions) required to change one string into another.
    
    Args:
        str1 (str): First string
        str2 (str): Second string
    """
    # Create a matrix of size (len(str1)+1) x (len(str2)+1)
    m, n = len(str1), len(str2)
    dp = [[0 for _ in range(n + 1)] for _ in range(m + 1)]
    
    # Initialize the first row and column
    for i in range(m + 1):
        dp[i][0] = i
    for j in range(n + 1):
        dp[0][j] = j
    
    # Fill the matrix using dynamic programming
    for i in range(1, m + 1):
        for j in range(1, n + 1):
            # If characters match, no operation needed
            if str1[i-1] == str2[j-1]:
                dp[i][j] = dp[i-1][j-1]
            else:
                # Take the minimum of three operations:
                # 1. Insertion: dp[i][j-1] + 1
                # 2. Deletion: dp[i-1][j] + 1
                # 3. Substitution: dp[i-1][j-1] + 1
                dp[i][j] = 1 + min(dp[i-1][j], dp[i][j-1], dp[i-1][j-1])
    
    # The bottom-right cell contains the Levenshtein distance
    return f"The edit distance between {str1} and {str1} is {dp[m][n]} operations"


@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, image_generation_tool, levenshtein_distance, get_current_time_in_timezone], ## 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()