import feedparser
import urllib.parse
import yaml
from tools.final_answer import FinalAnswerTool
import numpy as np
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.metrics.pairwise import cosine_similarity
import gradio as gr
from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool
import nltk

import datetime
import requests
import pytz
from tools.final_answer import FinalAnswerTool

from Gradio_UI import GradioUI

nltk.download("stopwords")
from nltk.corpus import stopwords

@tool
def convert_usd_to_eur(amount: float) -> str:
    """Converts a given amount in USD to NPR using real-time exchange rates.
    
    Args:
        amount: The amount in USD to be converted.
    
    Returns:
        A string with the converted amount in NPR.
    """
    try:
        # API Endpoint (Replace 'YOUR-API-KEY' with your actual key)
        url = "https://v6.exchangerate-api.com/v6/a0a73cc16fef27d4a2c1fd40/latest/USD"

        # Fetch data from the exchange rate API
        response = requests.get(url)
        data = response.json()

        # Check if the API response contains the exchange rate
        if "conversion_rates" not in data or "NPR" not in data["conversion_rates"]:
            return "Error: Unable to fetch exchange rate."

        # Extract USD to EUR exchange rate
        exchange_rate = data["conversion_rates"]["NPR"]

        # Convert USD to EUR
        converted_amount = amount * exchange_rate

        return f"{amount} USD is equivalent to {converted_amount:.2f} NPR"

    except Exception as e:
        return f"Error fetching exchange rate: {str(e)}"



@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()



# AI Model
model = HfApiModel(
    max_tokens=2096,
    temperature=0.5,
    model_id='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)


# Load prompt templates
with open("prompts.yaml", 'r') as stream:
    prompt_templates = yaml.safe_load(stream)

# Create the AI Agent
agent = CodeAgent(
    model=model,
    tools=[final_answer,convert_usd_to_eur],  # Add your tools here 
    max_steps=6,
    verbosity_level=1,
    grammar=None,
    planning_interval=None,
    name="CurrencyConverterAgent",
    description="An AI agent that convert USD to NPR using real-time exchange rates.",
    prompt_templates=prompt_templates
)


# Create Gradio UI
with gr.Blocks() as demo:
    gr.Markdown("# 💱 Exchange Rate Converter")

    # Textbox for user input (amount in USD)
    amount_input = gr.Number(label="Enter Amount in USD", value=1, precision=2)

    # Output display for the converted value
    output_display = gr.Markdown()

    # Button to trigger conversion
    convert_button = gr.Button("🔄 Convert to NPR")

    # Function call when button is clicked
    convert_button.click(convert_usd_to_eur, inputs=[amount_input], outputs=[output_display])

    print("DEBUG: Gradio UI is running. Waiting for user input...")

# Launch the UI
demo.launch()