Update app.py

app.py

@@ -6,106 +6,48 @@ 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__)
 
-# Use whisper-small for faster processing and better speed
+# Check GPU availability
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
-# Create config object to set timeout and other parameters
+# Whisper ASR config
 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
-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)
-
-# 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.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
-
-# Salesforce connection details
+# Salesforce connection
 try:
-    print("Attempting to connect to Salesforce...")
+    print("Connecting 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
+    print("Connected successfully!")
 except Exception as e:
-    print(f"Failed to connect to Salesforce: {str(e)}")
+    print(f"Salesforce connection failed: {str(e)}")
+
+# API Routes
 
-# Function to create Salesforce record
-# API endpoint to receive data from voice bot
 @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:
+    if not email or not phone_number:
         return jsonify({'error': 'Missing required fields'}), 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
+        existing_customer = sf.query(f"SELECT Id, Name FROM Customer_Login__c WHERE Email__c = '{email}' AND Phone_Number__c = '{phone_number}'")
+        if existing_customer['totalSize'] > 0:
+            return jsonify({'success': True, 'message': 'Login successful!', 'customer': existing_customer['records'][0]})
+        else:
+            return jsonify({'error': 'No user found. Please register first.'}), 404
     except Exception as e:
-        return jsonify({'error': f'Failed to create record in Salesforce: {str(e)}'}), 500
+        return jsonify({'error': f'Failed to fetch user from Salesforce: {str(e)}'}), 500
 
 @app.route("/submit", methods=["POST"])
 def submit():
@@ -118,90 +60,25 @@ def submit():
         return jsonify({'error': 'Missing data'}), 400
 
     try:
-        # Create Salesforce record
+        existing_customer = sf.query(f"SELECT Id FROM Customer_Login__c WHERE Email__c = '{email}' AND Phone_Number__c = '{phone}'")
+        if existing_customer['totalSize'] > 0:
+            return jsonify({'success': False, 'message': 'User already registered. Please log in.'}), 409
+
         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
+        return jsonify({'success': True, 'message': 'Registration successful!', 'id': customer_login['id']}), 200
 
     except Exception as e:
         return jsonify({'error': str(e)}), 500
 
-
 @app.route("/")
 def index():
     return render_template("index.html")
 
-@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 "[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})
-
-    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
+# Start server
 if __name__ == "__main__":
     serve(app, host="0.0.0.0", port=7860)