Update app.py

app.py

@@ -3,28 +3,28 @@ from youtube_transcript_api import YouTubeTranscriptApi
 import re
 import tempfile
 import os
-import openai
+import warnings
+from groq import Groq
 
-# Set up OpenAI API key
-openai.api_key = os.getenv("OPENAI_API_KEY")
+# Set up Groq client
+client = Groq(api_key=os.environ.get("GROQ_API_KEY"))
 
-# Supported file types for OpenAI API
+# Supported file types for Groq API
 SUPPORTED_FILE_TYPES = ["mp3", "mp4", "mpeg", "mpga", "m4a", "wav", "webm"]
 
-# Function to transcribe audio using OpenAI Whisper API
+# Function to transcribe audio using Groq Whisper API
 def transcribe_audio(file_path):
     file_extension = os.path.splitext(file_path)[1][1:]
     if file_extension not in SUPPORTED_FILE_TYPES:
         return f"Error: Unsupported file type '{file_extension}'. Please upload a valid file."
-
+    
     try:
         with open(file_path, "rb") as file:
-            response = openai.Audio.transcribe(
-                model="whisper-1",
-                file=file,
-                response_format="json"
+            transcription = client.audio.transcriptions.create(
+                file=(file_path, file.read()),
+                model="whisper-large-v3",
             )
-        return response['text']
+        return transcription.text
     except Exception as e:
         return f"Error during transcription: {e}"
 
@@ -41,34 +41,36 @@ def get_transcript(url):
     except Exception as e:
         return str(e)
 
-# Function to summarize text using OpenAI API
+# Function to summarize text using Groq API
 def summarize_text(text):
     try:
-        response = openai.ChatCompletion.create(
-            model="gpt-3.5-turbo",
+        response = client.chat.completions.create(
             messages=[
-                {"role": "system", "content": "You are a helpful assistant."},
-                {"role": "user", "content": f"Summarize the following text:\n\n{text}"}
+                {
+                    "role": "user",
+                    "content": f"Summarize the following text:\n\n{text}"
+                }
             ],
-            max_tokens=100,
+            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}"
 
-# Function to generate quiz questions using OpenAI API
+# Function to generate quiz questions using Groq API
 def generate_quiz_questions(text):
     try:
-        response = openai.ChatCompletion.create(
-            model="gpt-3.5-turbo",
+        response = client.chat.completions.create(
             messages=[
-                {"role": "system", "content": "You are a helpful assistant."},
-                {"role": "user", "content": f"Generate 10 quiz questions from the following text. Make sure the questions cover all key points and are varied in type (e.g., multiple choice, short answer). Number each question and provide the correct answer after the question number:\n\n{text}"}
+                {
+                    "role": "user",
+                    "content": f"Generate quiz questions for the following text:\n\n{text}"
+                }
             ],
-            max_tokens=1000,
+            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}"
@@ -76,50 +78,50 @@ def generate_quiz_questions(text):
 # Function to parse quiz questions from generated text
 def parse_quiz_questions(quiz_text):
     questions = []
+    question_blocks = quiz_text.split("\n\n")
     current_question = None
     current_choices = []
     correct_answer = None
-
-    lines = quiz_text.split("\n")
-    for line in lines:
-        line = line.strip()
-        if re.match(r'^\d+\.', line):  # This line is a question number
-            if current_question:
-                questions.append({
-                    "question": current_question,
-                    "choices": current_choices,
-                    "correct_answer": correct_answer
-                })
-            current_question = line
-            current_choices = []
-            correct_answer = None
-        elif line.startswith("Answer:"):
-            correct_answer = line.split(":", 1)[1].strip()
-        elif line:
-            current_choices.append(line)
+    
+    for block in question_blocks:
+        lines = block.strip().split("\n")
+        if lines:
+            if re.match(r'^\d+\.', lines[0]):  # This line is a question number
+                if current_question and current_choices and correct_answer:
+                    questions.append({
+                        "question": current_question,
+                        "choices": current_choices,
+                        "correct_answer": correct_answer
+                    })
+                current_question = lines[0]
+                current_choices = lines[1:5]
+                correct_answer = lines[-1].split(": ")[-1].strip() if len(lines) > 5 else None
+            else:  # This line is an answer
+                correct_answer = lines[-1].split(": ")[-1].strip()
 
     # Add the last question if it exists
-    if current_question:
+    if current_question and current_choices and correct_answer:
         questions.append({
             "question": current_question,
             "choices": current_choices,
             "correct_answer": correct_answer
         })
-
+    
     return questions
 
-# Function to generate explanation for quiz answers using OpenAI API
+# Function to generate explanation for quiz answers using Groq API
 def generate_explanation(question, correct_answer, user_answer):
     try:
-        response = openai.ChatCompletion.create(
-            model="gpt-3.5-turbo",
+        response = client.chat.completions.create(
             messages=[
-                {"role": "system", "content": "You are a helpful assistant."},
-                {"role": "user", "content": f"Explain why the correct answer to the following question is '{correct_answer}' and not '{user_answer}':\n\n{question}"}
+                {
+                    "role": "user",
+                    "content": f"Explain why the correct answer to the following question is '{correct_answer}' and not '{user_answer}':\n\n{question}"
+                }
             ],
-            max_tokens=100,
+            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}"
@@ -129,7 +131,7 @@ def check_answers(questions, user_answers):
     feedback = []
     correct_count = 0
     for i, question in enumerate(questions):
-        correct_answer = question.get('correct_answer')
+        correct_answer = question['correct_answer']
         user_answer = user_answers.get(f"question_{i+1}", "")
         if user_answer == correct_answer:
             feedback.append({
@@ -176,11 +178,11 @@ if option == "YouTube URL":
                 quiz_text = generate_quiz_questions(transcript_text)
                 questions = parse_quiz_questions(quiz_text)
 
-                if len(questions) < 10:
+                if not questions:
                     st.error("No valid quiz questions could be generated.")
                 else:
                     st.session_state.summary = summary
-                    st.session_state.questions = questions[:10]  # Ensure only 10 questions are taken
+                    st.session_state.questions = questions
                     st.session_state.user_answers = {}
                     st.session_state.generated_quiz = True
             else:
@@ -198,11 +200,11 @@ if option == "Upload audio/video file":
                 quiz_text = generate_quiz_questions(transcript_text)
                 questions = parse_quiz_questions(quiz_text)
 
-                if len(questions) < 10:
+                if not questions:
                     st.error("No valid quiz questions could be generated.")
                 else:
                     st.session_state.summary = summary
-                    st.session_state.questions = questions[:10]  # Ensure only 10 questions are taken
+                    st.session_state.questions = questions
                     st.session_state.user_answers = {}
                     st.session_state.generated_quiz = True
             else: