from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool
import datetime
import requests
import pytz
import yaml
import json
from tools.final_answer import FinalAnswerTool

from Gradio_UI import GradioUI

@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 read_todo_data() -> dict:
    """A tool to read the json file which is used for storage of todo data."""
    with open('./todo.json', 'r') as f:
        data = json.load(f)
    return data

@tool
def print_out_todo_data(data: dict) -> str:
    """A tool to convert retrieved json data into a well structured string to show it to the user..
    
    Args:
        data: A dictionary representing the data read from json file by using `read_todo_data`
    """
    output = '"""\n'
    for task in data['tasks']:
        task_str = (
            f"Task ID: {task['id']}\n"
            f"Title: {task['title']}\n"
            f"Description: {task['description']}\n"
            f"Due Date: {task['due_date']}\n"
            f"Priority: {task['priority'].capitalize()}\n"
            f"Status: {task['status'].replace('_', ' ').capitalize()}\n"
            f"{'-'*40}\n\n"
        )
        output += task_str
    return output

@tool
def add_todo_task(title: str, description: str, due_date: str, priority: str) -> None:
    """A tool to add new items into todo task storage.
    
    Args:
        title: A string representing the title of task
        description: A string describing the task
        due_date: A string representing the final date to complete task
        priority: A string representing the priority of the task among whole tasks. It would take the following value: ['pending', 'in_progress', 'completed']
    """

    data = read_todo_data()

    # Create a new task
    new_task = {
        "id": max(task['id'] for task in data['tasks']) + 1 if data['tasks'] else 1,
        "title": title,
        "description": description,
        "due_date": due_date,
        "priority": priority,
        "status": "pending"
    }
    
    # Add it to tasks list
    data['tasks'].append(new_task)
    
    # Write back to JSON file
    with open(json_file_path, 'w') as f:
        json.dump(data, f, indent=4)

@tool
def update_todo_task_status(task_id: int, new_status: str) -> None:
    """A tool to update status of a particular task, determined by `task_id`. To determine the task_id given by the user,
    read the todo file and find out the particular task.
    
    Args:
        task_id: An integer representing the id of the task to update
        new_status: A string representing new status of the given task
    """
    data = read_todo_data()
    
    # Find and update the task
    found = False
    for task in data['tasks']:
        if task['id'] == task_id:
            task['status'] = new_status
            found = True
            break

    # If task was found, save it back
    if found:
        with open(json_file_path, 'w') as f:
            json.dump(data, f, indent=4)
    else:
        print(f"Task with ID {task_id} not found.")


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='meta-llama/Llama-4-Scout-17B-16E-Instruct', # it is possible that this model may be overloaded 'Qwen/Qwen2.5-Coder-32B-Instruct'
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, get_current_time_in_timezone, read_todo_data, print_out_todo_data, add_todo_task, update_todo_task_status], ## 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()