Update app.py

app.py

@@ -1,27 +1,52 @@
-import torch
-from flask import Flask, render_template, request, jsonify
-import json
 import os
-from transformers import pipeline
+import time
+import logging
+import json
+import requests
+import torch
+from flask import Flask, render_template, request, jsonify, session
+from flask_session import Session
+from simple_salesforce import Salesforce
+from transformers import pipeline, AutoConfig
 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"
+# Configure Flask session
+app.secret_key = os.getenv("SECRET_KEY", "sSSjyhInIsUohKpG8sHzty2q")
+app.config["SESSION_TYPE"] = "filesystem"
+app.config["SESSION_COOKIE_NAME"] = "my_session"
+app.config["SESSION_COOKIE_SECURE"] = True
+app.config["SESSION_COOKIE_SAMESITE"] = "None"
+Session(app)
+
+# Set up logging
+logging.basicConfig(level=logging.INFO)
+
+# Connect to Salesforce
+try:
+    print("Attempting to connect to Salesforce...")
+    sf = Salesforce(username='[email protected]', password='Sati@1020', security_token='sSSjyhInIsUohKpG8sHzty2q')
+    print("Connected to Salesforce successfully!")
+except Exception as e:
+    print(f"Failed to connect to Salesforce: {str(e)}")
 
-# Create config object to set timeout and other parameters
+# Whisper ASR Configuration
+device = "cuda" if torch.cuda.is_available() else "cpu"
 config = AutoConfig.from_pretrained("openai/whisper-small")
-config.update({"timeout": 60})  # Set timeout to 60 seconds
+config.update({"timeout": 60})
+
+# Voice prompts for registration
+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."
+}
 
-# Your function where you generate and save the audio
 def generate_audio_prompt(text, filename):
     try:
         tts = gTTS(text)
@@ -29,96 +54,83 @@ def generate_audio_prompt(text, 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
+        time.sleep(5)
         generate_audio_prompt(text, filename)
 
-# Generate required voice prompts
-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")
 
-# Symbol mapping for proper recognition
-SYMBOL_MAPPING = {
-    "at the rate": "@",
-    "at": "@",
-    "dot": ".",
-    "underscore": "_",
-    "hash": "#",
-    "plus": "+",
-    "dash": "-",
-    "comma": ",",
-    "space": " "
-}
-
 # Function to convert audio to WAV format
 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 = audio.set_frame_rate(16000).set_channels(1)
         audio.export(output_path, format="wav")
     except Exception as e:
-        print(f"Error: {str(e)}")
         raise Exception(f"Audio conversion failed: {str(e)}")
 
 # Function to check if audio contains actual speech
 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
+    nonsilent_parts = detect_nonsilent(audio, min_silence_len=500, silence_thresh=audio.dBFS-16)
+    return len(nonsilent_parts) == 0
 
-# Salesforce connection details
-try:
-    print("Attempting to connect to Salesforce...")
-    sf = Salesforce(username='[email protected]', 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)}")
+@app.route("/")
+def index():
+    return render_template("index.html")
 
-# Function to create Salesforce record
-# API endpoint to receive data from voice bot
+# ✅ LOGIN ENDPOINT (Validates Existing Users)
 @app.route('/login', methods=['POST'])
 def login():
-    # Get data from voice bot (name, email, phone number)
-    data = request.json  # Assuming voice bot sends JSON data
-    
-    name = data.get('name')
-    email = data.get('email')
-    phone_number = data.get('phone_number')
+    data = request.json
+    email = data.get('email').strip().lower()
+    phone_number = data.get('phone_number').strip()
 
-    if not name or not email or not phone_number:
-        return jsonify({'error': 'Missing required fields'}), 400
+    if not email or not phone_number:
+        return jsonify({'error': 'Missing email or phone number'}), 400
 
-    # Create a record in Salesforce
     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
+        print(f"🔍 Checking login for Email: {email}, Phone: {phone_number}")
+
+        query = f"SELECT Id, Name FROM Customer_Login__c WHERE LOWER(Email__c) = '{email}' AND Phone_Number__c = '{phone_number}' LIMIT 1"
+        result = sf.query(query)
+
+        if result['totalSize'] == 0:
+            print("❌ No matching records found!")
+            return jsonify({'error': 'Invalid email or phone number. User not found'}), 401
+
+        user_data = result['records'][0]
+        session['user_id'] = user_data['Id']
+        session['name'] = user_data['Name']
+        print("✅ User found:", user_data)
+
+        return jsonify({'success': True, 'message': 'Login successful', 'user_id': user_data['Id'], 'name': user_data['Name']}), 200
+
+    except requests.exceptions.RequestException as req_error:
+        print("🔴 Salesforce Connection Error:", req_error)
+        return jsonify({'error': f'Salesforce connection error: {str(req_error)}'}), 500
     except Exception as e:
-        return jsonify({'error': f'Failed to create record in Salesforce: {str(e)}'}), 500
+        print("🚨 Unexpected Error:", e)
+        return jsonify({'error': f'Unexpected error: {str(e)}'}), 500
 
-@app.route("/submit", methods=["POST"])
-def submit():
+# ✅ REGISTRATION ENDPOINT (Creates New User)
+@app.route("/register", methods=["POST"])
+def register():
     data = request.json
     name = data.get('name')
-    email = data.get('email')
-    phone = data.get('phone')
+    email = data.get('email').strip().lower()
+    phone = data.get('phone').strip()
 
     if not name or not email or not phone:
         return jsonify({'error': 'Missing data'}), 400
 
     try:
-        # Create Salesforce record
+        query = f"SELECT Id FROM Customer_Login__c WHERE LOWER(Email__c) = '{email}' AND Phone_Number__c = '{phone}' LIMIT 1"
+        existing_user = sf.query(query)
+
+        if existing_user['totalSize'] > 0:
+            return jsonify({'error': 'User already exists'}), 409
+
         customer_login = sf.Customer_Login__c.create({
             'Name': name,
             'Email__c': email,
@@ -126,22 +138,17 @@ def submit():
         })
 
         if customer_login.get('id'):
-            return jsonify({'success': True})
+            return jsonify({'success': True, 'user_id': customer_login['id']}), 200
         else:
             return jsonify({'error': 'Failed to create record'}), 500
 
     except Exception as e:
         return jsonify({'error': str(e)}), 500
 
-
-@app.route("/")
-def index():
-    return render_template("index.html")
-
+# ✅ TRANSCRIPTION ENDPOINT (Converts Speech to Text)
 @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"]
@@ -150,56 +157,17 @@ def transcribe():
     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 "[email protected]"
-        phone_number = parts[2] if len(parts) > 2 else "0000000000"
-        print(f"Parsed data - Name: {name}, Email: {email}, Phone Number: {phone_number}")
-
-        # 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
-
-        # If creation was successful, return the details
-        return jsonify({"text": transcribed_text, "salesforce_record": salesforce_response})
+
+        result = pipeline("automatic-speech-recognition", model="openai/whisper-small", device=0 if torch.cuda.is_available() else -1, config=config)
+        transcribed_text = result(output_audio_path)["text"].strip().capitalize()
+
+        return jsonify({"text": transcribed_text})
 
     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