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 !

import random

@tool
def get_daily_strength_training() -> str:
    """A tool that provides 5 daily strength training exercises for a full-body workout.
    These exercises can be completed in 20 minutes.
    """
    # Define a pool of exercises targeting different muscle groups
    exercises = {
        "Upper Body": [
            {"name": "Push-Ups", "instructions": "Perform 3 sets of 10-15 reps.", "target": "Chest, Shoulders, Triceps"},
            {"name": "Dumbbell Shoulder Press", "instructions": "Perform 3 sets of 12 reps per arm.", "target": "Shoulders, Triceps"},
            {"name": "Bent-Over Rows", "instructions": "Perform 3 sets of 12 reps per arm.", "target": "Back, Biceps"},
        ],
        "Lower Body": [
            {"name": "Squats", "instructions": "Perform 3 sets of 15 reps.", "target": "Quads, Glutes, Hamstrings"},
            {"name": "Lunges", "instructions": "Perform 3 sets of 10 reps per leg.", "target": "Quads, Glutes, Hamstrings"},
            {"name": "Glute Bridges", "instructions": "Perform 3 sets of 15 reps.", "target": "Glutes, Hamstrings"},
        ],
        "Core": [
            {"name": "Plank", "instructions": "Hold for 30-60 seconds, repeat 3 times.", "target": "Abs, Core Stability"},
            {"name": "Russian Twists", "instructions": "Perform 3 sets of 20 twists.", "target": "Obliques, Abs"},
            {"name": "Leg Raises", "instructions": "Perform 3 sets of 15 reps.", "target": "Lower Abs"},
        ],
    }

    # Randomly select exercises to ensure variety
    upper_body_exercise = random.choice(exercises["Upper Body"])
    lower_body_exercise = random.choice(exercises["Lower Body"])
    core_exercise = random.choice(exercises["Core"])

    # Include two additional exercises from any category
    additional_exercises = random.sample(
        [item for category in exercises.values() for item in category], 2
    )

    # Combine all selected exercises
    selected_exercises = [
        upper_body_exercise,
        lower_body_exercise,
        core_exercise,
        *additional_exercises,
    ]

    # Format the output
    workout_plan = "Here's your 20-minute full-body workout:\n"
    for i, exercise in enumerate(selected_exercises, start=1):
        workout_plan += (
            f"{i}. {exercise['name']} ({exercise['target']}) - {exercise['instructions']}\n"
        )

    return workout_plan
@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)}"


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], ## 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()