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app.py

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+import os
+import gradio as gr
+from openai import OpenAI
+from langchain_community.document_loaders import PyPDFDirectoryLoader
+from langchain_text_splitters import RecursiveCharacterTextSplitter
+from langchain_community.vectorstores import Chroma
+from langchain_community.embeddings import HuggingFaceEmbeddings
+
+HF_TOKEN = os.environ.get("HF_TOKEN", "")
+
+print("🌙 Initializing your PQC Tutor...")
+embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-L6-v2")
+vectordb = Chroma(persist_directory="database/", embedding_function=embeddings)
+client = OpenAI(base_url="https://router.huggingface.co/v1", api_key=HF_TOKEN)
+print("✨ Ready!")
+
+def ask(question, history):
+    docs = vectordb.similarity_search(question, k=3)
+    context = "\n\n".join([doc.page_content for doc in docs])
+    sources = []
+    for doc in docs:
+        filename = doc.metadata.get("source", "Unknown").split("\\")[-1]
+        page = doc.metadata.get("page", "?")
+        sources.append(f"📄 **{filename}** — Page {int(page)+1}")
+
+    prompt = f"""You are a PQC expert teacher. Use the context below to answer clearly and kindly.
+
+Context:
+{context}
+
+Question: {question}
+
+Answer:"""
+
+    response = client.chat.completions.create(
+        model="Qwen/Qwen2.5-7B-Instruct",
+        messages=[{"role": "user", "content": prompt}],
+        max_tokens=512,
+        temperature=0.5
+    )
+    answer = response.choices[0].message.content
+    sources_text = "\n\n---\n🔍 **References from PQC papers:**\n" + "\n".join(set(sources))
+    return answer + sources_text
+
+css = """
+* { box-sizing: border-box; }
+
+body, .gradio-container {
+    background: #ffffff !important;
+    max-width: 100% !important;
+    padding: 0 40px !important;
+}
+
+#title {
+    text-align: center;
+    color: #222;
+    font-size: 2.2em;
+    font-family: 'Georgia', serif;
+    padding: 20px 0 5px 0;
+}
+
+#subtitle {
+    text-align: center;
+    color: #666;
+    font-size: 0.95em;
+    margin-bottom: 15px;
+}
+
+.chatbot {
+    background: #ffffff !important;
+    border: 1px solid #e0e0e0 !important;
+    border-radius: 16px !important;
+    box-shadow: 0 2px 12px rgba(0,0,0,0.08) !important;
+}
+
+.user .message {
+    background: #f5f5f5 !important;
+    color: #111111 !important;
+    border-radius: 18px 18px 4px 18px !important;
+    border: none !important;
+    padding: 12px 16px !important;
+}
+
+.bot .message {
+    background: #f5f5f5 !important;
+    color: #111111 !important;
+    border-radius: 18px 18px 18px 4px !important;
+    border: 1px solid #e0e0e0 !important;
+    padding: 12px 16px !important;
+}
+
+.textbox textarea {
+    background: #ffffff !important;
+    border: 1.5px solid #4f46e5 !important;
+    border-radius: 12px !important;
+    color: #111 !important;
+    font-size: 1em !important;
+}
+
+button.primary {
+    background: #222222 !important;
+    border: none !important;
+    border-radius: 10px !important;
+    color: white !important;
+}
+
+button.primary:hover {
+    background: #4338ca !important;
+}
+
+footer { display: none !important; }
+"""
+
+with gr.Blocks(title="🌙 PQC Bot") as demo:
+    gr.HTML("""
+        <div id='title'>🐱✨ PQC Bot ✨🐱</div>
+        <div id='subtitle'>🌙 The Cat Guide to Post-Quantum Cryptography 🌙</div>
+        <div style='text-align:center; font-size:2em;'>🌟 ⭐ 💫 ✨ 🌟 ⭐ 💫 ✨ 🌟</div>
+    """)
+
+    gr.ChatInterface(
+        fn=ask,
+        chatbot=gr.Chatbot(
+            height=450,
+            avatar_images=("👤", "🐱"),
+            show_label=False,
+        ),
+        textbox=gr.Textbox(
+            placeholder="🌙 Ask me PQC Queries...",
+            container=False,
+        ),
+        examples=[
+            "What is post quantum cryptography?",
+            "How does CRYSTALS-Kyber work?",
+            "What is lattice based cryptography?",
+            "Why does quantum computing break RSA?",
+            "What are NIST PQC standards?",
+        ],
+        submit_btn="✨ Ask",
+    )
+
+print("🌙 Ask Your PQC Queries...")
+demo.launch(css=css)

requirements.txt

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+gradio
+langchain
+langchain-community
+langchain-text-splitters
+langchain-huggingface
+chromadb
+sentence-transformers
+pypdf
+openai
+huggingface_hub