Update app.py

app.py

@@ -1,29 +1,24 @@
 import gradio as gr
-from huggingface_hub import InferenceClient
 import speech_recognition as sr
 import pyttsx3
-import os
 import requests
 
-# Load API Key securely
-API_KEY = "AIzaSyD7Xm52Snz28g5Ddpd3d4SXgxLWE0K7Ong"  # Replace with your actual API key
-MODEL_NAME = "mistralai/mistral-7b-instruct"  # Ensure this model is accessible
+# Load Groq API Key securely
+API_KEY = "your_groq_api_key_here"  # Replace with your actual Groq API key
+MODEL_NAME = "groq-model-id"  # Ensure this model is accessible on Groq Cloud
 
 # Check if API key is set
 if not API_KEY:
-    raise ValueError("Error: Hugging Face API key is missing. Set HF_API_KEY as an environment variable.")
+    raise ValueError("Error: Groq API key is missing. Set the API key.")
 
-# Verify API Key
-headers = {"Authorization": f"Bearer {API_KEY}"}
-response = requests.get("https://huggingface.co/api/whoami-v2", headers=headers)
+# Headers for authorization
+headers = {
+    "Authorization": f"Bearer {API_KEY}",
+    "Content-Type": "application/json"
+}
 
-if response.status_code != 200:
-    raise ValueError(f"Invalid API Key! Error: {response.json()}")
-
-print("API Key is valid!")
-
-# Initialize the InferenceClient
-client = InferenceClient(model=MODEL_NAME, token=API_KEY)
+# URL for Groq Cloud model endpoint (example URL, replace with actual Groq Cloud endpoint)
+url = f"https://api.groq.ai/v1/models/{MODEL_NAME}/predict"
 
 # System message for the chatbot
 system_message = "You are a friendly and helpful chatbot."
@@ -52,32 +47,34 @@ def respond(message, history=None, audio_input=None):
                 messages.append({"role": "assistant", "content": bot_msg})
         messages.append({"role": "user", "content": message})
 
-        # Log input messages for debugging
-        print("Sending messages:", messages)
-
-        # Get response from Hugging Face API using the correct method
-        chat_response = client.chat(messages=messages)
+        # Prepare the payload for Groq Cloud
+        payload = {
+            "inputs": message,
+            "parameters": {"max_new_tokens": 512}  # Optional parameters like max tokens
+        }
 
-        # Log API response for debugging
-        print("Raw API Response:", chat_response)
+        # Send the request to Groq Cloud API
+        response = requests.post(url, json=payload, headers=headers)
 
         # Validate API Response
-        if chat_response is None or "error" in chat_response:
-            return "Error: No response from API. Check API key and model permissions.", None
+        if response.status_code != 200:
+            return f"Error: No response from API. Check API key and model permissions. Status: {response.status_code}", None
 
         # Extract chatbot response
-        response = chat_response.get("choices", [{}])[0].get("message", {}).get("content", "").strip()
+        chat_response = response.json()
 
-        if not response:
-            response = "Error: Model returned an empty response."
+        if "generated_text" in chat_response:
+            response_text = chat_response["generated_text"].strip()
+        else:
+            response_text = "Error: Model returned an empty response."
 
     except Exception as e:
-        response = f"Error: {str(e)}"
+        response_text = f"Error: {str(e)}"
         print("Exception Occurred:", e)
 
     # Convert response to speech
-    audio_output = text_to_voice(response)
-    return response, audio_output
+    audio_output = text_to_voice(response_text)
+    return response_text, audio_output
 
 
 # Convert audio to text