import torch
from flask import Flask, render_template, request, jsonify
import json
import os
from transformers import pipeline
from gtts import gTTS
from pydub import AudioSegment
from pydub.silence import detect_nonsilent
from transformers import AutoConfig
import time
from waitress import serve
from simple_salesforce import Salesforce
import requests

app = Flask(__name__)

device = "cuda" if torch.cuda.is_available() else "cpu"
config = AutoConfig.from_pretrained("openai/whisper-small")
config.update({"timeout": 60})

def generate_audio_prompt(text, filename):
    try:
        tts = gTTS(text)
        tts.save(os.path.join("static", filename))
    except gtts.tts.gTTSError as e:
        print(f"Error: {e}")
        time.sleep(5)
        generate_audio_prompt(text, filename)

prompts = {
    "welcome": "Welcome to Biryani Hub.",
    "ask_name": "Tell me your name.",
    "ask_email": "Please provide your email address.",
    "thank_you": "Thank you for registration."
}

for key, text in prompts.items():
    generate_audio_prompt(text, f"{key}.mp3")

try:
    print("Attempting to connect to Salesforce...")
    sf = Salesforce(username='diggavalli98@gmail.com', password='Sati@1020', security_token='sSSjyhInIsUohKpG8sHzty2q')
    print("Connected to Salesforce successfully!")
except Exception as e:
    print(f"Failed to connect to Salesforce: {str(e)}")

@app.route("/")
def index():
    return render_template("index.html")

@app.route("/dashboard")
def dashboard():
    return render_template("dashboard.html")

@app.route("/menu")
def menu():
    return render_template("menu.html")

@app.route("/cart")
def cart():
    return render_template("cart.html")

@app.route("/order")
def order():
    return render_template("order.html")

@app.route("/final")
def final():
    return render_template("final.html")

@app.route("/submit", methods=["POST"])
def submit():
    data = request.json
    name = data.get('name')
    email = data.get('email')
    phone = data.get('phone')

    if not name or not email or not phone:
        return jsonify({'error': 'Missing data'}), 400

    try:
        customer_login = sf.Customer_Login__c.create({
            'Name': name,
            'Email__c': email,
            'Phone_Number__c': phone
        })

        if customer_login.get('id'):
            return jsonify({'success': True})
        else:
            return jsonify({'error': 'Failed to create record'}), 500

    except Exception as e:
        return jsonify({'error': str(e)}), 500

@app.route("/login", methods=["POST"])
def login():
    data = request.json
    name = data.get('name')
    email = data.get('email')
    phone_number = data.get('phone_number')

    if not name or not email or not phone_number:
        return jsonify({'error': 'Missing required fields'}), 400

    try:
        customer_login = sf.Customer_Login__c.create({
            'Name': name,
            'Email__c': email,
            'Phone_Number__c': phone_number
        })
        return jsonify({'success': True, 'id': customer_login['id']}), 200
    except Exception as e:
        return jsonify({'error': f'Failed to create record in Salesforce: {str(e)}'}), 500

@app.route("/transcribe", methods=["POST"])
def transcribe():
    if "audio" not in request.files:
        return jsonify({"error": "No audio file provided"}), 400

    audio_file = request.files["audio"]
    input_audio_path = os.path.join("static", "temp_input.wav")
    output_audio_path = os.path.join("static", "temp.wav")
    audio_file.save(input_audio_path)

    try:
        audio = AudioSegment.from_file(input_audio_path)
        audio = audio.set_frame_rate(16000).set_channels(1)
        audio.export(output_audio_path, format="wav")
        
        nonsilent_parts = detect_nonsilent(audio, min_silence_len=500, silence_thresh=audio.dBFS-16)
        if len(nonsilent_parts) == 0:
            return jsonify({"error": "No speech detected. Please try again."}), 400
        
        result = pipeline("automatic-speech-recognition", model="openai/whisper-small", device=0 if torch.cuda.is_available() else -1, config=config)
        transcribed_text = result["text"].strip().capitalize()
        
        return jsonify({"text": transcribed_text})
    except Exception as e:
        return jsonify({"error": f"Speech recognition error: {str(e)}"}), 500

if __name__ == "__main__":
    serve(app, host="0.0.0.0", port=7860)