fix python version and requirements for streamlit cloud

.python_version

@@ -0,0 +1 @@
+3.11

.streamlit/config.toml

@@ -0,0 +1,6 @@
+[server]
+headless = true
+port = 8501
+
+[theme]
+base = "light"

app/main.py

@@ -26,6 +26,20 @@ from app.components  import render_question_card, render_result_card, render_sco
 #  PAGE CONFIG — must be first Streamlit call
 # ─────────────────────────────────────────────
 
+
+
+#cache
+
+import streamlit as st
+
+@st.cache_resource
+def load_pipeline():
+    from src.mcq_builder import build_quiz
+    return build_quiz
+
+build_quiz = load_pipeline()
+
+
 st.set_page_config(
     page_title = APP_TITLE,
     page_icon  = APP_ICON,

data/sample_passages.json

@@ -24,4 +24,4 @@
     "topic": "Water Cycle",
     "text": "The water cycle, also known as the hydrological cycle, describes the continuous movement of water on, above, and below the Earth's surface. The main processes involved are evaporation, condensation, precipitation, and collection. Evaporation occurs when water from oceans, lakes, and rivers is heated by the sun and turns into water vapour. This vapour rises into the atmosphere and cools, forming clouds through condensation. When clouds become heavy enough, water falls back to Earth as precipitation in the form of rain, snow, or hail. The water then collects in oceans, rivers, and groundwater, and the cycle begins again."
   }
-]
+]

packages.txt

@@ -0,0 +1,2 @@
+python3-dev
+build-essential

requirements.txt

@@ -1,23 +1,9 @@
-# MCQ Generator — Python dependencies
-# Install with: pip install -r requirements.txt
-
-# ── Core NLP ──────────────────────────────────
-spacy==3.7.4
-nltk==3.8.1
-
-# ── Transformers (T5 for question generation) ─
-transformers==4.38.2
-torch==2.2.1          # CPU version — change to torch==2.2.1+cu118 for GPU
-
-# ── Word Embeddings ───────────────────────────
-gensim==4.3.2         # Word2Vec / GloVe loading
-
-# ── ML utilities ─────────────────────────────
-scikit-learn==1.4.1.post1   # TF-IDF vectorizer
-numpy==1.26.4
-
-# ── UI ────────────────────────────────────────
-streamlit==1.33.0
-
-# ── Utilities ─────────────────────────────────
-pandas==2.2.1         # Useful for data inspection in notebooks
+streamlit
+torch
+transformers
+sentencepiece
+nltk
+scikit-learn
+numpy
+gensim
+https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-3.7.1/en_core_web_sm-3.7.1-py3-none-any.whl

setup.sh

@@ -0,0 +1 @@
+python -m spacy download en_core_web_sm

src/question_generator.py

@@ -17,6 +17,26 @@ print(f"[INFO] Loading QG model: {QG_MODEL_NAME} ...")
 import warnings
 warnings.filterwarnings("ignore")   # suppress HuggingFace FutureWarnings
 
+
+@st.cache_resource
+def load_model():
+    tokenizer = AutoTokenizer.from_pretrained(QG_MODEL_NAME, use_fast=False)
+    model     = T5ForConditionalGeneration.from_pretrained(QG_MODEL_NAME)
+    model.eval()
+    return tokenizer, model
+
+tokenizer, qg_model = load_model()
+
+
+
+
+
+
+
+
+
+
+
 try:
     qg_pipeline = pipeline(
         "text2text-generation",