import os
import requests
import random
import yaml
import datetime
import pytz
import gradio as gr
from gtts import gTTS  # Use Google TTS instead of pyttsx3
from smolagents import CodeAgent, DuckDuckGoSearchTool, HfApiModel, load_tool, tool
from tools.final_answer import FinalAnswerTool
from Gradio_UI import GradioUI
from tools.web_search import DuckDuckGoSearchTool
from tools.visit_webpage import VisitWebpageTool



# Define the audio output path
AUDIO_OUTPUT_PATH = "/tmp/response.mp3"

def speak_text(text):
    """Convert text to speech using gTTS and save as an MP3 file."""
    tts = gTTS(text=text, lang='en')
    tts.save(AUDIO_OUTPUT_PATH)
    return AUDIO_OUTPUT_PATH  # Return the file path for Gradio Audio component



@tool
def search_dad_jokes(term: str) -> str:
    """A tool that searches for dad jokes containing a specific term.
    Args:
        term: The keyword to search for in dad jokes.
    """
    try:
        headers = {
            "Accept": "application/json",
            "User-Agent": "YourAppName (https://yourappurl.com)"
        }
        response = requests.get(f"https://icanhazdadjoke.com/search?term={term}", headers=headers)
        data = response.json()
        if data['results']:
            jokes = [joke['joke'] for joke in data['results']]
            response_text = f"Found {len(jokes)} jokes:\n" + "\n\n".join(jokes)
        else:
            response_text = f"No jokes found for the term '{term}'."
    except Exception as e:
        response_text = f"Error searching for jokes: {str(e)}"

    # Generate audio using gTTS
    audio_file = speak_text(response_text)

    return response_text, audio_file  # Return text and audio file path


final_answer = FinalAnswerTool()
web_search_tool = DuckDuckGoSearchTool()
visit_webpage_tool = VisitWebpageTool()



# 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=[visit_webpage_tool, web_search_tool, final_answer, image_generation_tool, search_dad_jokes], ## 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
)

Gradio interface with text and audio output
def gradio_search_jokes(word):
    """Wrapper function for Gradio to call search_dad_jokes and generate audio."""
    response_text, audio_file = search_dad_jokes(word)  # Ensure search_dad_jokes returns (text, file path)
    return response_text, audio_file



Define the Gradio UI
with gr.Blocks() as demo:
   gr.Markdown("### Dad Jokes Finder with AI & Text-to-Speech 🎙️")
   
   with gr.Row():
       input_box = gr.Textbox(label="Enter a word")
       output_text = gr.Textbox(label="Jokes Found")
       output_audio = gr.Audio(label="Audio Pronunciation", type="filepath")
   
   btn = gr.Button("Get Jokes")
   btn.click(gradio_search_jokes, inputs=input_box, outputs=[output_text, output_audio])

demo.launch()


# GradioUI(agent).launch()