Update app.py

app.py

@@ -6,11 +6,11 @@ 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
+from transformers import AutoConfig
 import time
 from waitress import serve
 from simple_salesforce import Salesforce
-import requests  # Import requests for exception handling
+import requests
 
 app = Flask(__name__)
 
@@ -19,9 +19,17 @@ 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
+config.update({"timeout": 60})
 
-# Your function where you generate and save the audio
+# 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."
+}
+
+# Function to generate and save audio prompts
 def generate_audio_prompt(text, filename):
     try:
         tts = gTTS(text)
@@ -29,17 +37,9 @@ 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")
 
@@ -60,52 +60,50 @@ SYMBOL_MAPPING = {
 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)}")
 
-# Function to create Salesforce record
-# API endpoint to receive data from voice bot
+# Function to handle login & registration in Salesforce
 @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')
+    data = request.json
     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
+    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
+        # Check if user already exists
+        query = f"SELECT Id, Name FROM Customer_Login__c WHERE Email__c = '{email}' AND Phone_Number__c = '{phone_number}' LIMIT 1"
+        result = sf.query(query)
+
+        if result['totalSize'] > 0:
+            user_data = result['records'][0]
+            return jsonify({'success': True, 'message': 'Login successful', 'user_id': user_data['Id'], 'name': user_data['Name']}), 200
+        else:
+            return jsonify({'error': 'Invalid email or phone number. User not found'}), 401
+
+    except requests.exceptions.RequestException as 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
+        return jsonify({'error': f'Unexpected error: {str(e)}'}), 500
 
 @app.route("/submit", methods=["POST"])
 def submit():
@@ -118,7 +116,14 @@ def submit():
         return jsonify({'error': 'Missing data'}), 400
 
     try:
-        # Create Salesforce record
+        # Check if user already exists
+        query = f"SELECT Id FROM Customer_Login__c WHERE 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  # Conflict
+
+        # Create new user
         customer_login = sf.Customer_Login__c.create({
             'Name': name,
             'Email__c': email,
@@ -126,14 +131,13 @@ 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")
@@ -141,7 +145,6 @@ def index():
 @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"]
@@ -156,50 +159,14 @@ def transcribe():
         # 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