Update app.py

app.py

@@ -4,14 +4,14 @@ import re
 import tempfile
 import os
 import warnings
-from groq import Groq
+from groq import GroqClient
 from transformers import pipeline
 
 # Suppress specific warning
 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 = GroqClient(api_key=os.environ.get("GROQ_API_KEY"))
 
 # Instantiate Hugging Face pipeline
 transcriber = pipeline("automatic-speech-recognition", model="openai/whisper-large-v2")
@@ -38,16 +38,16 @@ def get_transcript(url):
 # Function to summarize text using Groq API
 def summarize_text(text):
     try:
-        response = client.chat.completions.create(
+        response = client.completions.create(
+            model="llama3-8b-8192",
             messages=[
                 {
                     "role": "user",
                     "content": f"Summarize the following text:\n\n{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}"
@@ -55,16 +55,16 @@ 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.completions.create(
+            model="llama3-8b-8192",
             messages=[
                 {
                     "role": "user",
                     "content": f"Generate quiz questions for the following text:\n\n{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}"
@@ -106,16 +106,16 @@ 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.completions.create(
+            model="llama3-8b-8192",
             messages=[
                 {
                     "role": "user",
                     "content": f"Explain why the correct answer to the following question is '{correct_answer}' and not '{user_answer}':\n\n{question}"
                 }
-            ],
-            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}"