Spaces:
Sleeping
Sleeping
File size: 10,898 Bytes
d1aea20 8f3a5d1 d82403f d1aea20 a1cfef6 8f3a5d1 d1aea20 a1cfef6 d1aea20 8f3a5d1 2fab7d3 0ec8fd1 2fab7d3 00d34d4 0ec8fd1 8f3a5d1 0ec8fd1 8f3a5d1 0ec8fd1 8f3a5d1 0ec8fd1 8f3a5d1 0ec8fd1 8f3a5d1 0ec8fd1 8f3a5d1 0ec8fd1 2fdeb17 0ec8fd1 8f3a5d1 0ec8fd1 d1aea20 0ec8fd1 0613b1a 0ec8fd1 0613b1a 0ec8fd1 00d34d4 0ec8fd1 a4315ce 0ec8fd1 c32f608 d82403f 0ec8fd1 c1d8f2a 0613b1a 0ec8fd1 0613b1a 9b40d8d 0613b1a efa0646 d82403f 0ec8fd1 0613b1a 0ec8fd1 0613b1a 0ec8fd1 0613b1a 0ec8fd1 0613b1a 0ec8fd1 0613b1a 0ec8fd1 0613b1a 0ec8fd1 0613b1a 0ec8fd1 fe14dd8 0ec8fd1 d82403f 0ec8fd1 d82403f 0ec8fd1 8f3a5d1 0ec8fd1 8f3a5d1 0ec8fd1 8f3a5d1 0ec8fd1 2fab7d3 2fdeb17 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 |
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 AutoConfig for the config object
import time
from waitress import serve
from simple_salesforce import Salesforce
import requests # Import requests for exception handling
app = Flask(__name__)
# Use whisper-small for faster processing and better speed
device = "cuda" if torch.cuda.is_available() else "cpu"
# Create config object to set timeout and other parameters
config = AutoConfig.from_pretrained("openai/whisper-small")
config.update({"timeout": 60}) # Set timeout to 60 seconds
# Salesforce credentials (Replace with actual values)
try:
print("Attempting to connect to Salesforce...")
sf = Salesforce(username='diggavalli98@gmail.com', password='Sati@1020', security_token='sSSjyhInIsUohKpG8sHzty2q')
print("Connected to Salesforce successfully!")
print("User Info:", sf.UserInfo) # Log the user info to verify the connection
except Exception as e:
print(f"Failed to connect to Salesforce: {str(e)}")
# Function for Salesforce operations
def create_salesforce_record(name, email, phone_number):
try:
# Create a new record in Salesforce's Customer_Login__c object
customer_login = sf.Customer_Login__c.create({
'Name': name,
'Email__c': email,
'Phone_Number__c': phone_number
})
return customer_login
except SalesforceResourceNotFound as e:
raise Exception(f"Salesforce resource not found: {str(e)}")
except Exception as e:
raise Exception(f"Failed to create record: {str(e)}")
def get_menu_items():
query = "SELECT Name, Price__c, Ingredients__c, Category__c FROM Menu_Item__c"
result = sf.query(query)
return result['records']
# Voice-related functions
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}")
print("Retrying after 5 seconds...")
time.sleep(5) # Wait for 5 seconds before retrying
generate_audio_prompt(text, filename)
# Utility functions
def convert_to_wav(input_path, output_path):
try:
audio = AudioSegment.from_file(input_path)
audio = audio.set_frame_rate(16000).set_channels(1) # Convert to 16kHz, mono
audio.export(output_path, format="wav")
except Exception as e:
print(f"Error: {str(e)}")
raise Exception(f"Audio conversion failed: {str(e)}")
def is_silent_audio(audio_path):
audio = AudioSegment.from_wav(audio_path)
nonsilent_parts = detect_nonsilent(audio, min_silence_len=500, silence_thresh=audio.dBFS-16) # Reduced silence duration
print(f"Detected nonsilent parts: {nonsilent_parts}")
return len(nonsilent_parts) == 0 # If no speech detected
# Routes and Views
@app.route("/")
def index():
return render_template("index.html")
@app.route("/dashboard", methods=["GET"])
def dashboard():
return render_template("dashboard.html") # Render the dashboard template
@app.route('/submit', methods=['POST'])
def submit():
try:
# Ensure JSON is being received
data = request.get_json()
print("Received Data:", data) # Debugging line
if not data:
return jsonify({"success": False, "message": "Invalid or empty JSON received"}), 400
# Get the values from the JSON data
name = data.get("name")
email = data.get("email")
phone = data.get("phone")
# Validate if all fields are present
if not name or not email or not phone:
return jsonify({"success": False, "message": "Missing required fields"}), 400
# Prepare data for Salesforce submission
salesforce_data = {
"Name": name,
"Email__c": email, # Ensure this is the correct field API name in Salesforce
"Phone_Number__c": phone # Ensure this is the correct field API name in Salesforce
}
# Insert data into Salesforce using simple_salesforce
try:
result = sf.Customer_Login__c.create(salesforce_data) # Replace `Customer_Login__c` with your Salesforce object API name
print(f"Salesforce Response: {result}") # Debugging line
return jsonify({"success": True, "message": "Data submitted successfully"})
except Exception as e:
if "STORAGE_LIMIT_EXCEEDED" in str(e):
return jsonify({"success": False, "message": "Salesforce storage limit exceeded. Please clean up or contact support."}), 500
else:
print(f"Salesforce Insertion Error: {str(e)}") # Log Salesforce errors
return jsonify({"success": False, "message": "Salesforce submission failed", "error": str(e)}), 500
except Exception as e:
print(f"Server Error: {str(e)}") # Log general errors
return jsonify({"success": False, "message": "Internal server error", "error": str(e)}), 500
@app.route('/validate-login', methods=['POST'])
def validate_login():
try:
# Ensure JSON is being received
data = request.get_json()
login_email = data.get("email")
login_mobile = data.get("mobile")
# Validate if email and mobile are present
if not login_email or not login_mobile:
return jsonify({"success": False, "message": "Missing email or mobile number"}), 400
# Query Salesforce to check if the record exists
query = f"SELECT Id, Name, Email__c, Phone_Number__c FROM Customer_Login__c WHERE Email__c = '{login_email}' AND Phone_Number__c = '{login_mobile}'"
result = sf.query(query)
if result['records']:
# If a matching record is found, return success and the name
user_name = result['records'][0]['Name'] # Assuming the 'Name' field is present in the Salesforce object
return jsonify({"success": True, "message": "Login successful", "name": user_name})
else:
# If no matching record is found
return jsonify({"success": False, "message": "Invalid email or mobile number"}), 401
except Exception as e:
print(f"Error validating login: {str(e)}")
return jsonify({"success": False, "message": "Internal server error", "error": str(e)}), 500
@app.route("/menu", methods=["GET"])
def menu_page():
menu_items = get_menu_items()
menu_data = [{"name": item['Name'], "price": item['Price__c'], "ingredients": item['Ingredients__c'], "category": item['Category__c']} for item in menu_items]
return render_template("menu_page.html", menu_items=menu_data)
# Route for handling order
@app.route("/order", methods=["POST"])
def place_order():
item_name = request.json.get('item_name')
quantity = request.json.get('quantity')
order_data = {"Item__c": item_name, "Quantity__c": quantity}
sf.Order__c.create(order_data)
return jsonify({"success": True, "message": f"Order for {item_name} placed successfully."})
# Route to handle the cart
@app.route("/cart", methods=["GET"])
def cart():
cart_items = [] # Placeholder for cart items
return render_template("cart_page.html", cart_items=cart_items)
# Route for the order summary page
@app.route("/order-summary", methods=["GET"])
def order_summary():
order_details = [] # Placeholder for order details
return render_template("order_summary.html", order_details=order_details)
@app.route("/transcribe", methods=["POST"])
def transcribe():
if "audio" not in request.files:
print("No audio file provided")
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:
# Convert to WAV
convert_to_wav(input_audio_path, output_audio_path)
# Check for silence
if is_silent_audio(output_audio_path):
return jsonify({"error": "No speech detected. Please try again."}), 400
else:
print("Audio contains speech, proceeding with transcription.")
# Use Whisper ASR model for transcription
result = None
retry_attempts = 3
for attempt in range(retry_attempts):
try:
result = pipeline("automatic-speech-recognition", model="openai/whisper-small", device=0 if torch.cuda.is_available() else -1, config=config)
print(f"Transcribed text: {result['text']}")
break
except requests.exceptions.ReadTimeout:
print(f"Timeout occurred, retrying attempt {attempt + 1}/{retry_attempts}...")
time.sleep(5)
if result is None:
return jsonify({"error": "Unable to transcribe audio after retries."}), 500
transcribed_text = result["text"].strip().capitalize()
print(f"Transcribed text: {transcribed_text}")
# Extract name, email, and phone number from the transcribed text
parts = transcribed_text.split()
name = parts[0] if len(parts) > 0 else "Unknown Name"
email = parts[1] if '@' in parts[1] else "unknown@domain.com"
phone_number = parts[2] if len(parts) > 2 else "0000000000"
print(f"Parsed data - Name: {name}, Email: {email}, Phone Number: {phone_number}")
# Confirm details before submission
confirmation = f"Is this correct? Name: {name}, Email: {email}, Phone: {phone_number}"
generate_audio_prompt(confirmation, "confirmation.mp3")
# Simulate confirmation via user action
user_confirms = True # Assuming the user confirms, you can replace this with actual user input logic
if user_confirms:
# Create record in Salesforce
salesforce_response = create_salesforce_record(name, email, phone_number)
# Log the Salesforce response
print(f"Salesforce record creation response: {salesforce_response}")
# Check if the response contains an error
if "error" in salesforce_response:
print(f"Error creating record in Salesforce: {salesforce_response['error']}")
return jsonify(salesforce_response), 500
return jsonify({"text": transcribed_text, "salesforce_record": salesforce_response})
except Exception as e:
print(f"Error in transcribing or processing: {str(e)}")
return jsonify({"error": f"Speech recognition error: {str(e)}"}), 500
# Start Production Server
if __name__ == "__main__":
serve(app, host="0.0.0.0", port=7860)
|