app.py

from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool
from huggingface_hub import InferenceClient
import datetime
import requests
import pytz
import yaml
import re
import os
from tools.final_answer import FinalAnswerTool
from tools.visit_webpage import VisitWebpageTool

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)}"

@tool
def summarize_text_tool(text:str)-> str:
    #Keep this format for the description / args / args description but feel free to modify the tool
    """A tool that summarizes the specified text
    Args:
        text: the text to be summaried
    """
    try:
        hf_token = os.getenv('hf_token')
        client = InferenceClient(api_key=hf_token)
        messages = [
        	{
        		"role": "user",
        		"content": f"Your are an experienced editor. Your are very skilled in summarizing texts and creating prompts from the content for LLM's to generate and image. Summarize the following text and create a prompt for an image generation: {text}"
        	}
        ]
        response = client.chat.completions.create(
            model="Qwen/Qwen2.5-Coder-32B-Instruct", 
        	messages=messages, 
        	max_tokens=500
        )
        summarized_text = response.choices[0].message.content
        return summarized_text
    except Exception as e:
        return f"OH noes, something went wrong...:-/ {str(e)}"

@tool
def helper_text_tool(text:str)-> str:
    #Keep this format for the description / args / args description but feel free to modify the tool
    """A tool that helps analyze a text including following web links
    Args:
        text: the text to be analyzed
    """
    try:
        hf_token = os.getenv('hf_token')
        client = InferenceClient(api_key=hf_token)
        messages = [
        	{
        		"role": "user",
        		"content": f"Your are an experienced requirements, tasks and process analyzer. Your are very skilled in analyzing and summarizing texts and creating prompts from the content for LLM's to generate solutions. Summarize the following text and give a meaningful answer to the question or questions: {text}"
        	}
        ]
        response = client.chat.completions.create(
            model="Qwen/Qwen2.5-Coder-32B-Instruct", 
        	messages=messages, 
        	max_tokens=500
        )
        summarized_text = response.choices[0].message.content
        return summarized_text
    except Exception as e:
        return f"OH noes, something went wrong...:-/ {str(e)}"

final_answer = FinalAnswerTool()
visit_webpage = VisitWebpageTool()

# 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, visit_webpage, summarize_text_tool, helper_text_tool], ## add your tools here (don't remove final answer)
    max_steps=10,
    verbosity_level=1,
    grammar=None,
    planning_interval=None,
    name=None,
    description=None,
    prompt_templates=prompt_templates
)


GradioUI(agent).launch()