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 calculate_bandwidth(users: int, usage: dict) -> float:
    """
    Calculate the recommended internet speed based on user inputs.
    
    :param users: The total number of users requiring internet access.
    :param usage: A dictionary with usage categories as keys and the number of users per category as values.
    :return: Recommended bandwidth in Mbps to ensure smooth performance.
    """
    usage_requirements = {
        "browsing": 1,        # Mbps per user
        "video_call": 2,      # Mbps per user
        "hd_streaming": 5,    # Mbps per user
        "4k_streaming": 25,   # Mbps per user
        "gaming": 10,         # Mbps per user
        "remote_work": 3      # Mbps per user
    }
    
    total_bandwidth = sum(usage_requirements[activity] * count for activity, count in usage.items())
    
    overhead = 1.2  # 20% overhead for seamless experience
    return round(total_bandwidth * overhead, 2)


final_answer = FinalAnswerTool()
duck_duck_go_search = DuckDuckGoSearchTool()

# 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,calculate_bandwidth], ## 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()