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| import os | |
| import tempfile | |
| from datetime import datetime | |
| from PyPDF2 import PdfReader | |
| from docx import Document | |
| import streamlit as st | |
| from transformers import pipeline | |
| # ✅ Page config MUST be first Streamlit command | |
| st.set_page_config(page_title="AI Study Plan Assistant", layout="wide") | |
| # Load models with caching | |
| def load_models(): | |
| summarizer = pipeline("summarization", model="facebook/bart-large-cnn") | |
| qa_pipeline = pipeline("question-answering", model="distilbert-base-uncased-distilled-squad") | |
| return summarizer, qa_pipeline | |
| summarizer, qa_pipeline = load_models() | |
| # Extract text from supported formats | |
| def extract_text(file): | |
| ext = os.path.splitext(file.name)[1].lower() | |
| if ext == ".txt": | |
| return file.read().decode("utf-8") | |
| elif ext == ".docx": | |
| doc = Document(file) | |
| return "\n".join([para.text for para in doc.paragraphs]) | |
| elif ext == ".pdf": | |
| pdf_reader = PdfReader(file) | |
| text = "" | |
| for page in pdf_reader.pages: | |
| text += page.extract_text() + "\n" | |
| return text | |
| else: | |
| raise ValueError("Only .txt, .docx, and .pdf files are supported.") | |
| # Generate study plan | |
| def generate_plan(file, hours_per_day, exam_date, language): | |
| try: | |
| content = extract_text(file) | |
| today = datetime.now().date() | |
| exam = datetime.strptime(exam_date.strip(), "%Y-%m-%d").date() | |
| days = (exam - today).days | |
| if days <= 0: | |
| return "❌ Exam date must be in the future." | |
| prompt = f"Create a {days}-day study plan for this syllabus:\n{content}\nDaily study time: {hours_per_day} hours." | |
| if language == "Urdu": | |
| prompt += "\nTranslate the plan into Urdu." | |
| summary = summarizer(prompt, max_length=512, min_length=150, do_sample=False) | |
| return summary[0]['summary_text'] | |
| except Exception as e: | |
| return f"⚠️ Error: {str(e)}" | |
| # Ask a question | |
| def ask_question(file, question): | |
| try: | |
| context = extract_text(file) | |
| result = qa_pipeline({"context": context, "question": question}) | |
| return result['answer'] | |
| except Exception as e: | |
| return f"⚠️ Error: {str(e)}" | |
| # Streamlit UI | |
| st.sidebar.title("📚 Study Assistant Options") | |
| uploaded_file = st.sidebar.file_uploader("Upload syllabus (.txt, .docx, .pdf)", type=["txt", "docx", "pdf"]) | |
| study_hours = st.sidebar.number_input("Study hours per day", min_value=1, max_value=12, value=3) | |
| exam_date = st.sidebar.text_input("Exam Date (YYYY-MM-DD)", value="2025-06-30") | |
| language = st.sidebar.selectbox("Select Language", ["English", "Urdu"]) | |
| st.title("🧠 AI Study Plan & QA Assistant") | |
| tab1, tab2 = st.tabs(["📅 Generate Study Plan", "❓ Ask a Question"]) | |
| with tab1: | |
| st.subheader("Generate a Personalized Study Plan") | |
| if uploaded_file and st.button("Generate Study Plan"): | |
| result = generate_plan(uploaded_file, study_hours, exam_date, language) | |
| st.text_area("Study Plan", result, height=400) | |
| with tab2: | |
| st.subheader("Ask Questions from Uploaded Material") | |
| question = st.text_input("Enter your question:") | |
| if uploaded_file and question and st.button("Get Answer"): | |
| answer = ask_question(uploaded_file, question) | |
| st.text_area("Answer", answer, height=200) | |