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)}"

@tool
def book_search(title: str, language: str) -> str:
    """A tool that searches for a book based on title or user query and language.
    Args:
        title: A user query or string representing the book title or query.
        language: An optional 2 char string representing the language code. e.g: en, fr, ta
    """
    try:
        # Construct the URL with the given parameters
        base_url = "https://openlibrary.org/search.json"
        params = {
            "title": title,
            "fields": "title,author_name",
            "limit": 10
        }
        if language:
            params["lang"] = language
        
        # Make the request
        response = requests.get(base_url, params=params)
        response.raise_for_status()
        
        # Parse the response
        data = response.json()
        
        # Format results
        results = []
        for book in data.get("docs", []):
            book_title = book.get("title", "Unknown Title")
            authors = ", ".join(book.get("author_name", ["Unknown Author"]))
            results.append(f"Title: *{book_title}*, Author(s): _{authors}_")
            
        return "\n".join(results) if results else "No books found."
    except Exception as e:
        return f"Error fetching books: {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
model_id='https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud',# 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, book_search, 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="Book Search Agent",
    description="An agent that searches for books based on user queries and language.",
    prompt_templates=prompt_templates,
)


GradioUI(agent).launch()