import os
import torch
import argparse
import gradio as gr
from mailersend import emails
from dotenv import load_dotenv
import base64
import psycopg2
from urllib.parse import urlparse, parse_qs
import shutil
import boto3
from botocore.exceptions import NoCredentialsError
import json
from elevenlabs import ElevenLabs

# Load environment variables
load_dotenv()

# Argument parsing
parser = argparse.ArgumentParser()
parser.add_argument("--share", action='store_true', default=False, help="make link public")
args = parser.parse_args()

device = 'cuda' if torch.cuda.is_available() else 'cpu'
output_dir = 'outputs'
samples_dir = 'samples'
os.makedirs(output_dir, exist_ok=True)
os.makedirs(samples_dir, exist_ok=True)

supported_languages = ['zh', 'en']

MAILERSEND_API_KEY = os.getenv("MAILERSEND_API_KEY")
MAILERSEND_DOMAIN = os.getenv("MAILERSEND_DOMAIN")
MAILERSEND_SENDER_EMAIL = f"noreply@{MAILERSEND_DOMAIN}"
MAILERSEND_SENDER_NAME = "Voice Clone App"

ELEVENLABS_API_KEY = os.getenv("ELEVENLABS_API_KEY")
elevenlabs_client = ElevenLabs(api_key=ELEVENLABS_API_KEY)

AWS_ACCESS_KEY_ID = os.getenv('AWS_ACCESS_KEY_ID')
AWS_SECRET_ACCESS_KEY = os.getenv('AWS_SECRET_ACCESS_KEY')
AWS_REGION_NAME = os.getenv('AWS_REGION_NAME')
S3_BUCKET_NAME = os.getenv('S3_BUCKET_NAME')

# List of blocked words
BLOCKED_WORDS = ['Kill','hurt','shoot','gun','rifle','AR','semi automatic','knife','blade','sword','punch harm','disrupt','blackmail','steal','bitch','cunt','fuck','freaking','nigger','nigga','niggas','cracker','jew','oriental','fag','faggot','account','money','transfer','urgent','help','scared','policy','frightened','accident','fear','scam','address','social security number','assault','injure','maim','destroy','damage','threaten','intimidate','bully','menace','blackmail','extort','exploit','defame','steal','rob','embezzle','defraud Harass','jerk','idiot','stupid','moron','asshole','con','trick','swindle','defraud','payment','credit card','bank account','urgent','immediate','afraid','phone number','email','password']

# Function to check for blocked words
def contains_blocked_words(text):
    return any(word.lower() in text.lower() for word in BLOCKED_WORDS)

# Function to send email with downloadable file using MailerSend
def send_email_with_file(recipient_email, file_path, subject, body):
    try:
        mailer = emails.NewEmail(MAILERSEND_API_KEY)

        mail_body = {}
        mail_from = {
            "name": MAILERSEND_SENDER_NAME,
            "email": MAILERSEND_SENDER_EMAIL,
        }
        recipients = [
            {
                "name": "Recipient",
                "email": recipient_email,
            }
        ]

        mailer.set_mail_from(mail_from, mail_body)
        mailer.set_mail_to(recipients, mail_body)
        mailer.set_subject(subject, mail_body)
        mailer.set_html_content(f"<p>{body}</p>", mail_body)
        mailer.set_plaintext_content(body, mail_body)

        with open(file_path, "rb") as file:
            attachment_content = base64.b64encode(file.read()).decode('utf-8')
        
        attachments = [
            {
                "filename": os.path.basename(file_path),
                "content": attachment_content,
                "disposition": "attachment"
            }
        ]
        mailer.set_attachments(attachments, mail_body)

        response = mailer.send(mail_body)

        if response[0] == 202:
            print("Email sent successfully")
            return True
        else:
            print(f"Failed to send email. Status code: {response[0]}")
            print(f"Response: {response[1]}")
            return False
    except Exception as e:
        print(f"An error occurred while sending email: {e}")
        return False

# Database connection details
connection_string = os.environ.get("DATABASE_URL")
result = urlparse(connection_string)
user = result.username
password = result.password
host = result.hostname
port = result.port
database = result.path[1:]
sslmode = parse_qs(result.query)['sslmode'][0]

# Function to add user information to the database
def add_user_info_to_db(email, order_name, sample_audio_path, name):
    connection = psycopg2.connect(
        dbname=database,
        user=user,
        password=password,
        host=host,
        port=port,
        sslmode=sslmode
    )
    cursor = connection.cursor()
    
    insert_query = """
    INSERT INTO main (email, order_name, sample_audio, name)
    VALUES (%s, %s, %s, %s);
    """
    try:
        cursor.execute(insert_query, (email, order_name, sample_audio_path, name))
        connection.commit()
        print("User information added to the database successfully")
    except Exception as error:
        print(f"Error occurred during data insertion: {error}")
        connection.rollback()
    finally:
        cursor.close()
        connection.close()

# S3 upload functions
def upload_to_s3(local_file, bucket, s3_file):
    s3 = boto3.client('s3', 
                      aws_access_key_id=AWS_ACCESS_KEY_ID,
                      aws_secret_access_key=AWS_SECRET_ACCESS_KEY,
                      region_name=AWS_REGION_NAME)

    try:
        s3.upload_file(local_file, bucket, s3_file, ExtraArgs={'ACL': 'public-read'})
        print(f"Upload Successful: {s3_file}")
        return True
    except FileNotFoundError:
        print(f"The file was not found: {local_file}")
        return False
    except NoCredentialsError:
        print("Credentials not available")
        return False

def upload_voice_sample_and_metadata(sample_path, metadata, bucket):
    # Upload the voice sample
    sample_filename = os.path.basename(sample_path)
    s3_sample_path = f'voice_samples/{sample_filename}'
    if not upload_to_s3(sample_path, bucket, s3_sample_path):
        return False

    # Create and upload metadata file
    metadata['sample_s3_path'] = s3_sample_path
    metadata_filename = f"{os.path.splitext(sample_filename)[0]}_metadata.json"
    s3_metadata_path = f'voice_metadata/{metadata_filename}'
    
    # Save metadata to a temporary file
    temp_metadata_path = '/tmp/temp_metadata.json'
    with open(temp_metadata_path, 'w') as f:
        json.dump(metadata, f)
    
    # Upload metadata file
    if not upload_to_s3(temp_metadata_path, bucket, s3_metadata_path):
        return False
    
    # Clean up temporary file
    os.remove(temp_metadata_path)

    return True

# Predict function with ElevenLabs API usage
def predict(prompt, style, audio_file_pth, voice_name, customer_email, order_name):
    text_hint = 'Your file will only be saved for 24 hours.\n'
    if len(prompt) < 2:
        text_hint += "[ERROR] Please provide a longer prompt text.\n"
        return text_hint, None, None
    if len(prompt) > 200:
        text_hint += "[ERROR] Text length limited to 200 characters. Please try shorter text.\n"
        return text_hint, None, None
    if contains_blocked_words(prompt):
        text_hint += "[ERROR] Your text contains blocked words. Please remove them and try again.\n"
        return text_hint, None, None

    # Copy the sample audio to the samples directory
    sample_filename = f"{voice_name}_{customer_email}_sample.mp3"
    sample_path = os.path.join(samples_dir, sample_filename)
    shutil.copy2(audio_file_pth, sample_path)
    
    # Prepare metadata
    metadata = {
        'name': voice_name,
        'email': customer_email,
        'order_name': order_name
    }

    # Upload voice sample and metadata to S3
    if upload_voice_sample_and_metadata(sample_path, metadata, S3_BUCKET_NAME):
        text_hint += "Voice sample and metadata uploaded to S3 successfully.\n"
    else:
        text_hint += "Failed to upload voice sample and metadata to S3.\n"

    # Add user information to the database
    add_user_info_to_db(customer_email, order_name, sample_path, voice_name)

    # Use ElevenLabs API to generate the cloned voice audio
    try:
        response = elevenlabs_client.text_to_speech(prompt, voice_name=voice_name, style=style)
        output_audio_path = os.path.join(output_dir, f"{voice_name}_output.mp3")
        with open(output_audio_path, 'wb') as f:
            f.write(response['audio'])
        text_hint += "Audio generated successfully using ElevenLabs.\n"
    except Exception as e:
        text_hint += f"[ERROR] ElevenLabs API error: {e}\n"
        return text_hint, None, None

    # Send email with the generated audio file
    email_subject = "Your Voice Clone Audio is Ready"
    email_body = f"Hi {voice_name},\n\nYour voice clone audio file is ready. Please find the attached file.\n\nBest regards,\nVoice Clone App"
    if send_email_with_file(customer_email, output_audio_path, email_subject, email_body):
        text_hint += "Email sent successfully with the generated audio file.\n"
    else:
        text_hint += "Failed to send email with the generated audio file.\n"

    return text_hint, output_audio_path, audio_file_pth

# Gradio interface setup
with gr.Blocks(gr.themes.Glass()) as demo:
    with gr.Row():
        with gr.Column():
            input_text_gr = gr.Textbox(
                label="Create This",
                info="One or two sentences at a time is better. Up to 200 text characters.",
                value="He hoped there would be stew for dinner, turnips and carrots and bruised potatoes and fat mutton pieces to be ladled out in thick, peppered, flour-fattened sauce.",
            )
            style_gr = gr.Dropdown(
                label="Style",
                choices=['default', 'whispering', 'cheerful', 'terrified', 'angry', 'sad', 'friendly'],
                info="Please upload a reference audio file that is at least 1 minute long. For best results, ensure the audio is clear.",
                max_choices=1,
                value="default",
            )
            ref_gr = gr.Audio(
                label="Original Audio",
                type="filepath",
                sources=["upload"],
            )
            voice_name_gr = gr.Textbox(
                label="Your name",
                value="Sam"
            )
            order_gr = gr.Textbox(
                label="Your order",
                value="Sample Order",
            )
            customer_email_gr = gr.Textbox(
                label="Your Email",
                info="We'll send you a downloadable file to this email address."
            )
            tts_button = gr.Button("Start", elem_id="send-btn", visible=True)

        with gr.Column():
            out_text_gr = gr.Text(label="Info")
            audio_gr = gr.Audio(label="Generated Audio", autoplay=True)
            ref_audio_gr = gr.Audio(label="Original Audio Used")

            tts_button.click(predict, [input_text_gr, style_gr, ref_gr, voice_name_gr, customer_email_gr, order_gr], outputs=[out_text_gr, audio_gr, ref_audio_gr])

    demo.queue()
    demo.launch(debug=True, show_api=False, share=args.share)

css = """
footer {visibility: hidden}
audio .btn-container {display: none}
"""

demo.add_css(css)