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app.py

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+
+import streamlit as st
+import pickle
+from sklearn.feature_extraction.text import TfidfVectorizer
+from sklearn.metrics.pairwise import cosine_similarity
+
+# Must match the class used in Colab for unpickling
+class CodePaulLite:
+    def __init__(self, dataset):
+        self.dataset = dataset
+        self.keys = list(dataset.keys())
+        self.vectorizer = TfidfVectorizer(stop_words='english')
+        self.matrix = self.vectorizer.fit_transform(self.keys)
+
+    def ask(self, query, threshold=0.1):
+        query_vec = self.vectorizer.transform([query])
+        similarities = cosine_similarity(query_vec, self.matrix).flatten()
+        best_idx = similarities.argsort()[-1]
+        if similarities[best_idx] < threshold:
+            return "I don't have enough context for that."
+        return self.dataset[self.keys[best_idx]]
+
+@st.cache_resource
+def load_model():
+    with open('codepaul_lite_100k.pkl', 'rb') as f:
+        return pickle.load(f)
+
+st.set_page_config(page_title="CodePaul Lite Ultra", page_icon="🚀")
+st.title("🚀 CodePaul Lite Ultra")
+st.markdown("### 100,000 Algorithmic Knowledge Nodes")
+
+try:
+    model = load_model()
+    query = st.text_input("Ask a coding or logic question:", "Write a Python function for binary search")
+
+    if st.button("Generate Solution"):
+        with st.spinner('Searching knowledge nodes...'):
+            response = model.ask(query)
+            st.code(response)
+except FileNotFoundError:
+    st.error("Model file 'codepaul_lite_100k.pkl' not found. Please upload it to the Space.")

requirements.txt

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+scikit-learn
+streamlit