Update app.py

app.py

@@ -5,7 +5,7 @@ import tempfile
 import os
 import warnings
 from groq import Groq
-from whisper_jax import FlaxWhisperPipline
+from transformers import pipeline
 
 # Suppress specific warning
 warnings.filterwarnings("ignore", message="FP16 is not supported on CPU; using FP32 instead")
@@ -13,15 +13,13 @@ warnings.filterwarnings("ignore", message="FP16 is not supported on CPU; using F
 # Set up Groq client
 client = Groq(api_key=os.environ.get("GROQ_API_KEY"))
 
-# Instantiate Whisper JAX pipeline
-pipeline = FlaxWhisperPipline("openai/whisper-large-v2")
+# Instantiate Hugging Face pipeline
+transcriber = pipeline("automatic-speech-recognition", model="openai/whisper-large-v2")
 
-# Function to transcribe audio using Whisper JAX
+# Function to transcribe audio using Hugging Face Transformers
 def transcribe_audio(file_path):
-    # JIT compile the forward call - slow, but we only do once
-    text = pipeline(file_path)
-    # Used cached function thereafter - super fast!!
-    text = pipeline(file_path)
+    result = transcriber(file_path)
+    text = result["text"]
     return text
 
 # Function to get transcript from YouTube
@@ -222,11 +220,15 @@ if st.session_state.generated_quiz:
 
     if st.button("Submit Answers"):
         if "questions" in st.session_state and st.session_state.questions:
-            with st.spinner('ProcessingIf `whisper_jax` is not found, it might not be available on PyPI or installed properly. If you need to use an alternative or similar library, ensure it's correctly installed. Let's try another approach using `whisper` from OpenAI, which should be available on PyPI and can be used similarly.
-
-### Updated `requirements.txt`
-```txt
-streamlit
-youtube_transcript_api
-groq
-whisper
+            with st.spinner('Processing your answers...'):
+                feedback = check_answers(st.session_state.questions, st.session_state.user_answers)
+                st.write("## Feedback")
+                for i, item in enumerate(feedback):
+                    with st.expander(f"Question {i+1} Feedback"):
+                        st.write(f"### {item['question']}")
+                        st.write(f"**Your answer:** {item['user_answer']}")
+                        st.write(f"**Correct answer:** {item['correct_answer']}")
+                        if item['status'] == "Incorrect":
+                            st.write(f"**Explanation:** {item['explanation']}")
+        else:
+            st.write("Please generate the quiz first.")