from smolagents import CodeAgent, HfApiModel, load_tool, tool
import datetime
import pytz
import yaml
from tools.final_answer import FinalAnswerTool
from Gradio_UI import GradioUI


# A simple example tool that currently does nothing but shows how to define a tool.
@tool
def my_custom_tool(arg1: str, arg2: int) -> str:
    """
    A placeholder tool that returns a fun message.
    
    Args:
        arg1: The first argument as a string.
        arg2: The second argument as an integer.
    
    Returns:
        A string message.
    """
    return "What magic will you build with this tool?"


@tool
def get_current_time_in_timezone(timezone: str) -> str:
    """
    Returns the current local time in the specified timezone.
    
    Args:
        timezone: A valid timezone string (e.g., 'America/New_York').
    
    Returns:
        A formatted string with the current local time or an error message.
    """
    try:
        tz = pytz.timezone(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: could not fetch time for timezone '{timezone}'. Details: {e}"


@tool
def emoji_summarizer(text: str) -> str:
    """
    Summarizes the input text using emojis representing key ideas.
    
    Args:
        text: Input text string.
    
    Returns:
        A string of emojis or a default emoji if no matches are found.
    """
    mapping = {
        "happy": "😊",
        "sad": "😢",
        "fire": "🔥",
        "love": "❤️",
        "party": "🎉",
        "work": "💼",
        "sleep": "😴",
        "money": "💰",
        "music": "🎵",
        "food": "🍔",
        "travel": "✈️",
        "error": "❌",
        "question": "❓",
    }

    # Basic tokenization: lowercase and split on whitespace
    words = text.lower().split()
    emojis = [mapping[word] for word in words if word in mapping]

    if not emojis:
        return "🤔 (no matching emojis found)"
    return "".join(emojis)


# Initialize the final answer tool
final_answer = FinalAnswerTool()

# Initialize the language model (make sure model_id is correct and accessible)
model = HfApiModel(
    max_tokens=2096,
    temperature=0.5,
    model_id='Qwen/Qwen2.5-Coder-32B-Instruct',
    custom_role_conversions=None,
)

# Load the text-to-image generation tool from the Hugging Face hub
image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True)

# Load prompt templates from YAML file (make sure 'prompts.yaml' is present and valid)
with open("prompts.yaml", "r") as stream:
    prompt_templates = yaml.safe_load(stream)

# Initialize the code agent with all desired tools
agent = CodeAgent(
    model=model,
    tools=[
        final_answer,
        emoji_summarizer,
        image_generation_tool,
        my_custom_tool,
        get_current_time_in_timezone,
    ],
    max_steps=6,
    verbosity_level=1,
    grammar=None,
    planning_interval=None,
    name=None,
    description=None,
    prompt_templates=prompt_templates,
)

# Launch the Gradio UI to interact with the agent
GradioUI(agent).launch()