quiz2.py

quiz2.py

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+import streamlit as st
+import PyPDF2
+import nltk
+import re
+import networkx as nx
+import matplotlib.pyplot as plt
+from io import BytesIO
+import random
+
+nltk.download("punkt", quiet=True)
+
+def extract_text_from_pdf(pdf_file):
+    """Extract text from uploaded PDF"""
+    reader = PyPDF2.PdfReader(pdf_file)
+    text = ""
+    for page in reader.pages:
+        text += page.extract_text() + " "
+    return text
+
+def summarize_text(text, num_sentences=5):
+    """Simple bullet point summary (frequency-based)"""
+    sentences = nltk.sent_tokenize(text)
+    words = nltk.word_tokenize(text.lower())
+    freq = nltk.FreqDist(words)
+    ranked_sentences = sorted(
+        sentences, key=lambda s: sum(freq[w] for w in nltk.word_tokenize(s.lower()) if w in freq), reverse=True
+    )
+    return ranked_sentences[:num_sentences]
+
+def generate_mindmap(text):
+    """Generate a simple mindmap graph of keywords"""
+    words = re.findall(r'\b[a-zA-Z]{4,}\b', text.lower())
+    freq = nltk.FreqDist(words)
+    common_words = [w for w, _ in freq.most_common(10)]
+
+    G = nx.Graph()
+    for word in common_words:
+        G.add_node(word)
+    for i in range(len(common_words)):
+        for j in range(i+1, len(common_words)):
+            if random.random() > 0.5:  # Random connections for visualization
+                G.add_edge(common_words[i], common_words[j])
+
+    # Plot the mindmap
+    fig, ax = plt.subplots(figsize=(6, 6))
+    nx.draw(G, with_labels=True, node_color="lightblue", node_size=2000, font_size=10, ax=ax)
+    return fig
+
+def generate_quiz(text, num_q=5):
+    """Generate quiz questions from text"""
+    sentences = nltk.sent_tokenize(text)
+    quiz = []
+    for _ in range(min(num_q, len(sentences))):
+        sent = random.choice(sentences)
+        words = sent.split()
+        if len(words) > 5:
+            blank_idx = random.randint(0, len(words)-1)
+            answer = words[blank_idx]
+            words[blank_idx] = "____"
+            quiz.append((" ".join(words), answer))
+    return quiz
+
+
+st.title("📘 StudyMate: AI-Powered Study Assistant")
+st.write("Upload a PDF to get **summaries, mindmaps, and quiz questions** 🎯")
+
+pdf_file = st.file_uploader("Upload PDF", type=["pdf"])
+
+if pdf_file:
+    text = extract_text_from_pdf(pdf_file)
+
+    st.subheader("📌 Summary (Bullet Points)")
+    summary = summarize_text(text)
+    for s in summary:
+        st.markdown(f"- {s}")
+
+    st.subheader("🧠 Mindmap")
+    fig = generate_mindmap(text)
+    st.pyplot(fig)
+
+    st.subheader("❓ Quiz Questions")
+    quiz = generate_quiz(text)
+    for idx, (q, ans) in enumerate(quiz, 1):
+        st.markdown(f"**Q{idx}.** {q}")
+        with st.expander("Show Answer"):
+            st.write(ans)