Update app.py

app.py

@@ -1,49 +1,37 @@
 import whisper
 from TTS.api import TTS
-import requests
 import gradio as gr
 from pydub import AudioSegment
-from deep_translator import GoogleTranslator
+from groq import Groq
 
 # Initialize models
-whisper_model = whisper.load_model("small")  # Faster Whisper model
+whisper_model = whisper.load_model("small")  # Use a smaller Whisper model for faster processing
 tts_model = TTS(model_name="tts_models/en/ljspeech/tacotron2-DDC", progress_bar=False, gpu=False)
 
-# Groq API Key and Base URL
+# Initialize Groq Client
 groq_api_key = "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"
-groq_base_url = "https://api.groq.com"  # Replace this with the correct base URL if needed
+client = Groq(api_key=groq_api_key)
 
 # Functions for the Chatbot
 def voice_to_text(audio_path):
-    """Convert voice input to text and detect language using Whisper."""
+    """Convert voice input to text using Whisper."""
     result = whisper_model.transcribe(audio_path)
-    detected_language = result["language"]
-    return result["text"], detected_language
+    return result["text"]
 
 def process_text_with_groq(input_text):
     """Process user text input using Groq LLM."""
-    url = f"{groq_base_url}/chat/completions"  # Replace with the correct endpoint from Groq documentation
-    headers = {"Authorization": f"Bearer {groq_api_key}"}
-    payload = {
-        "messages": [{"role": "user", "content": input_text}],
-        "model": "llama3-8b-8192",
-        "stream": False,
-    }
+    messages = [{"role": "user", "content": input_text}]
     try:
-        response = requests.post(url, json=payload, headers=headers)
-        response.raise_for_status()  # Raise an error for HTTP issues
-        return response.json().get("choices", [{}])[0].get("message", {}).get("content", "No response received.")
-    except requests.exceptions.HTTPError as http_err:
-        return f"HTTP error occurred: {http_err}"
+        chat_completion = client.chat.completions.create(
+            messages=messages,
+            model="llama3-8b-8192",
+            stream=False
+        )
+        return chat_completion.choices[0].message.content
     except Exception as e:
-        return f"An error occurred: {str(e)}"
+        return f"Error: {str(e)}"
 
-def translate_text(text, target_lang):
-    """Translate text to the target language using deep-translator."""
-    translated_text = GoogleTranslator(source="auto", target=target_lang).translate(text)
-    return translated_text
-
-def text_to_voice(output_text, language_code):
+def text_to_voice(output_text):
     """Convert text response to voice using Coqui TTS."""
     audio_path = "response.wav"
     tts_model.tts_to_file(text=output_text, file_path=audio_path)
@@ -51,19 +39,15 @@ def text_to_voice(output_text, language_code):
 
 # Gradio Interface
 def chatbot(audio_file):
-    # Step 1: Convert audio to text and detect language
-    user_input, detected_language = voice_to_text(audio_file)
-
-    # Step 2: Process the text with Groq LLM
+    # Convert audio to text
+    user_input = voice_to_text(audio_file)
+    
+    # Get Groq LLM response
     bot_response = process_text_with_groq(user_input)
-
-    # Step 3: Translate the response if the detected language is not English
-    if detected_language != "en":  # Translate only if language is not English
-        bot_response = translate_text(bot_response, detected_language)
-
-    # Step 4: Convert the response to voice
-    audio_response_path = text_to_voice(bot_response, detected_language)
-
+    
+    # Convert text response to audio
+    audio_response_path = text_to_voice(bot_response)
+    
     return bot_response, audio_response_path
 
 # Gradio UI
@@ -75,7 +59,7 @@ ui = gr.Interface(
         gr.Audio(label="Chatbot Voice Response")
     ],
     title="Zeeshan Voice-to-Voice Chatbot",
-    description="Upload an audio file to interact with Zeeshan. Zeeshan will listen, process your query, and respond in the same language with both text and voice."
+    description="Upload an audio file to interact with Zeeshan. Zeeshan will listen, process your query using Groq's LLM, and respond with both text and voice."
 )
 
 # Launch Gradio app