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| 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 | |
| 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)}" | |
| 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 | |
| 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 | |
| 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) | |
| 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() |