Update app.py

app.py

@@ -1,32 +1,23 @@
-import openai
 import streamlit as st
+from openai import OpenAI
 from youtube_transcript_api import YouTubeTranscriptApi
 import re
 import tempfile
 import os
-from transformers import WhisperProcessor, WhisperForConditionalGeneration
-import torch
-import librosa
+from transformers import pipeline
+import soundfile as sf
 
-# Load the Whisper model and processor from Hugging Face
-processor = WhisperProcessor.from_pretrained("openai/whisper-large-v2")
-model = WhisperForConditionalGeneration.from_pretrained("openai/whisper-large-v2")
+# Initialize the pipeline with the model
+pipe = pipeline("automatic-speech-recognition", model="openai/whisper-small")
 
+# Function to transcribe audio using Hugging Face Whisper
 def transcribe_audio(file_path):
-    # Load audio file
-    audio, _ = librosa.load(file_path, sr=16000)
-
-    # Tokenize the audio
-    inputs = processor(audio, return_tensors="pt", sampling_rate=16000)
-
-    # Perform the transcription
-    with torch.no_grad():
-        generated_ids = model.generate(inputs["input_features"])
-
-    # Decode the transcription
-    transcription = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
+    # Load audio file into NumPy array
+    audio_input, _ = sf.read(file_path)
+    transcription = pipe(audio_input)["text"]
     return transcription
 
+# Function to get YouTube transcript
 def get_transcript(url):
     try:
         video_id_match = re.search(r"(?:v=|\/)([0-9A-Za-z_-]{11}).*", url)
@@ -41,32 +32,31 @@ def get_transcript(url):
     except Exception as e:
         return str(e)
 
-def summarize_text(api_key, text):
-    openai.api_key = api_key
-    response = openai.ChatCompletion.create(
+# Function to summarize text using OpenAI API
+def summarize_text(client, text):
+    response = client.chat.completions.create(
         model="gpt-3.5-turbo",
         messages=[
             {"role": "system", "content": "You are a helpful assistant."},
             {"role": "user", "content": f"Summarize the following text:\n\n{text}"}
-        ],
-        max_tokens=150
+        ]
     )
-    summary = response.choices[0]['message']['content'].strip()
+    summary = response.choices[0].message.content.strip()
     return summary
 
-def generate_quiz_questions(api_key, text):
-    openai.api_key = api_key
-    response = openai.ChatCompletion.create(
+# Function to generate quiz questions using OpenAI API
+def generate_quiz_questions(client, text):
+    response = client.chat.completions.create(
         model="gpt-3.5-turbo",
         messages=[
             {"role": "system", "content": "You are a helpful assistant."},
             {"role": "user", "content": f"Generate ten quiz questions and four multiple choice answers for each question from the following text. Mark the correct answer with an asterisk (*) at the beginning:\n\n{text}"}
-        ],
-        max_tokens=300
+        ]
     )
-    quiz_questions = response.choices[0]['message']['content'].strip()
+    quiz_questions = response.choices[0].message.content.strip()
     return quiz_questions
 
+# Function to parse quiz questions
 def parse_quiz_questions(quiz_text):
     questions = []
     question_blocks = quiz_text.split("\n\n")
@@ -83,21 +73,21 @@ def parse_quiz_questions(quiz_text):
             questions.append({"question": question, "choices": choices, "correct_answer": correct_answer})
     return questions
 
-def generate_explanation(api_key, question, correct_answer, user_answer):
-    openai.api_key = api_key
+# Function to generate explanation using OpenAI API
+def generate_explanation(client, question, correct_answer, user_answer):
     prompt = f"Explain why the correct answer to the following question is '{correct_answer}' and not '{user_answer}':\n\n{question}"
-    response = openai.ChatCompletion.create(
+    response = client.chat.completions.create(
         model="gpt-3.5-turbo",
         messages=[
             {"role": "system", "content": "You are a helpful assistant."},
             {"role": "user", "content": prompt}
-        ],
-        max_tokens=150
+        ]
     )
-    explanation = response.choices[0]['message']['content'].strip()
+    explanation = response.choices[0].message.content.strip()
     return explanation
 
-def check_answers(api_key, questions, user_answers):
+# Function to check answers and provide feedback
+def check_answers(client, questions, user_answers):
     feedback = []
     correct_count = 0
     for i, question in enumerate(questions):
@@ -112,7 +102,7 @@ def check_answers(api_key, questions, user_answers):
             })
             correct_count += 1
         else:
-            explanation = generate_explanation(api_key, question['question'], correct_answer, user_answer)
+            explanation = generate_explanation(client, question['question'], correct_answer, user_answer)
             feedback.append({
                 "question": question['question'],
                 "user_answer": user_answer,
@@ -122,17 +112,23 @@ def check_answers(api_key, questions, user_answers):
             })
     return feedback
 
+# Function to handle uploaded file
 def handle_uploaded_file(uploaded_file):
     with tempfile.NamedTemporaryFile(delete=False) as tmp_file:
         tmp_file.write(uploaded_file.read())
         tmp_file_path = tmp_file.name
     return tmp_file_path
 
+# Streamlit UI
 st.title("YouTube Transcript Quiz Generator")
 
 st.markdown("**Instructions:** Enter your OpenAI API key and paste a YouTube link or upload a media file to generate a quiz.")
 
 api_key = st.text_input("Enter your OpenAI API Key", type="password")
+
+if api_key:
+    client = OpenAI(api_key=api_key)
+
 option = st.selectbox("Choose input type", ("YouTube URL", "Upload audio/video file"))
 
 if "generated_quiz" not in st.session_state:
@@ -144,60 +140,51 @@ if option == "YouTube URL":
         if st.button("Generate Quiz"):
             transcript_text = get_transcript(url)
             if "Error" not in transcript_text:
-                summary = summarize_text(api_key, transcript_text)
-                quiz_text = generate_quiz_questions(api_key, transcript_text)
+                summary = summarize_text(client, transcript_text)
+                quiz_text = generate_quiz_questions(client, transcript_text)
                 questions = parse_quiz_questions(quiz_text)
 
-                st.write("## Summary")
-                st.write(summary)
-
-                st.write("## Quiz Questions")
+                st.session_state.summary = summary
                 st.session_state.questions = questions
                 st.session_state.user_answers = {}
                 st.session_state.generated_quiz = True
 
-                for i, question in enumerate(questions):
-                    st.write(f"### Question {i+1}")
-                    st.write(question['question'])
-                    st.session_state.user_answers[f"question_{i+1}"] = st.radio(
-                        label="",
-                        options=question['choices'],
-                        key=f"question_{i+1}"
-                    )
-
-elif option == "Upload audio/video file":
+if option == "Upload audio/video file":
     uploaded_file = st.file_uploader("Choose an audio or video file", type=["mp3", "wav", "mp4", "mov"])
     if uploaded_file and api_key:
-        tmp_file_path = handle_uploaded_file(uploaded_file)
-        transcript_text = transcribe_audio(tmp_file_path)
-        os.remove(tmp_file_path)
-        if "Error" not in transcript_text:
-            summary = summarize_text(api_key, transcript_text)
-            quiz_text = generate_quiz_questions(api_key, transcript_text)
-            questions = parse_quiz_questions(quiz_text)
-
-            st.write("## Summary")
-            st.write(summary)
-
-            st.write("## Quiz Questions")
-            st.session_state.questions = questions
-            st.session_state.user_answers = {}
-            st.session_state.generated_quiz = True
-
-            for i, question in enumerate(questions):
-                st.write(f"### Question {i+1}")
-                st.write(question['question'])
-                st.session_state.user_answers[f"question_{i+1}"] = st.radio(
-                    label="",
-                    options=question['choices'],
-                    key=f"question_{i+1}"
-                )
+        if st.button("Generate Quiz"):
+            tmp_file_path = handle_uploaded_file(uploaded_file)
+            with st.spinner('Transcribing audio...'):
+                transcript_text = transcribe_audio(tmp_file_path)
+            os.remove(tmp_file_path)
+            if "Error" not in transcript_text:
+                summary = summarize_text(client, transcript_text)
+                quiz_text = generate_quiz_questions(client, transcript_text)
+                questions = parse_quiz_questions(quiz_text)
+
+                st.session_state.summary = summary
+                st.session_state.questions = questions
+                st.session_state.user_answers = {}
+                st.session_state.generated_quiz = True
 
 if st.session_state.generated_quiz:
+    st.write("## Summary")
+    st.write(st.session_state.summary)
+
+    st.write("## Quiz Questions")
+    for i, question in enumerate(st.session_state.questions):
+        st.write(f"### Question {i+1}")
+        st.write(question['question'])
+        st.session_state.user_answers[f"question_{i+1}"] = st.radio(
+            label="",
+            options=question['choices'],
+            key=f"question_{i+1}"
+        )
+
     if st.button("Submit Answers"):
         if "questions" in st.session_state and st.session_state.questions:
             with st.spinner('Processing your answers...'):
-                feedback = check_answers(api_key, st.session_state.questions, st.session_state.user_answers)
+                feedback = check_answers(client, 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"):