Update app.py

app.py

@@ -4,9 +4,9 @@ import re
 import tempfile
 import os
 import warnings
-from groq import Groq
 import torch
 from transformers import pipeline
+from groq.client import Client
 
 # Set up device for torch
 device = "cuda:0" if torch.cuda.is_available() else "cpu"
@@ -23,7 +23,7 @@ asr_pipeline = pipeline(
 warnings.filterwarnings("ignore", message="FP16 is not supported on CPU; using FP32 instead")
 
 # Set up Groq client
-client = Groq(api_key=os.environ.get("GROQ_API_KEY"))
+client = Client(api_key=os.environ.get("GROQ_API_KEY"))
 
 # Function to transcribe audio using ASR pipeline
 def transcribe_audio(file_path):
@@ -48,7 +48,7 @@ def get_transcript(url):
 # Function to summarize text using Groq API
 def summarize_text(text):
     try:
-        response = client.chat.completions.create(
+        response = client.chat_completions.create(
             messages=[
                 {
                     "role": "user",
@@ -57,7 +57,7 @@ def summarize_text(text):
             ],
             model="llama3-8b-8192",
         )
-        summary = response.choices[0].message.content.strip()
+        summary = response['choices'][0]['message']['content'].strip()
         return summary
     except Exception as e:
         return f"Error summarizing text: {e}"
@@ -65,7 +65,7 @@ def summarize_text(text):
 # Function to generate quiz questions using Groq API
 def generate_quiz_questions(text):
     try:
-        response = client.chat.completions.create(
+        response = client.chat_completions.create(
             messages=[
                 {
                     "role": "user",
@@ -74,7 +74,7 @@ def generate_quiz_questions(text):
             ],
             model="llama3-8b-8192",
         )
-        quiz_questions = response.choices[0].message.content.strip()
+        quiz_questions = response['choices'][0]['message']['content'].strip()
         return quiz_questions
     except Exception as e:
         return f"Error generating quiz questions: {e}"
@@ -116,7 +116,7 @@ def parse_quiz_questions(quiz_text):
 # Function to generate explanation for quiz answers using Groq API
 def generate_explanation(question, correct_answer, user_answer):
     try:
-        response = client.chat.completions.create(
+        response = client.chat_completions.create(
             messages=[
                 {
                     "role": "user",
@@ -125,7 +125,7 @@ def generate_explanation(question, correct_answer, user_answer):
             ],
             model="llama3-8b-8192",
         )
-        explanation = response.choices[0].message.content.strip()
+        explanation = response['choices'][0]['message']['content'].strip()
         return explanation
     except Exception as e:
         return f"Error generating explanation: {e}"
@@ -241,4 +241,4 @@ if st.session_state.generated_quiz:
                         if item['status'] == "Incorrect":
                             st.write(f"**Explanation:** {item['explanation']}")
         else:
-            st.write("Please generate the quiz first.")
+            st.write("Please generate the quiz first.")