create app.py

app.py

@@ -0,0 +1,38 @@
+import streamlit as st
+import llama_cpp
+
+@st.cache_resource
+def load_model(model_path):
+    return llama_cpp.Llama(model_path=model_path)
+
+st.title("CyberSecurity Assistant")
+
+model_path = "./llama-3-3b-cybersecurity-quantized.gguf"
+temperature = st.sidebar.slider('Temperature', 0.0,2.0,0.2, step=0.1)
+
+if model_path:
+    try:
+        llm = load_model(model_path)
+        st.sidebar.success('Model loaded Successfully')
+    except Exception as e:
+        st.sidebar.error(f'Error loading the model: {e}')
+        llm = None
+else:
+    st.warning("Model path not found")
+
+# SYSTEM PROMPT
+
+# GLOBAL VARIABLE INSTRUCTION
+instruction= 'You are a Cybersecurity AI Assistant, will be glad to answer your questions related to Cybersecurity, particularly LLM Security.'
+
+
+if llm:
+    user_input = st.text_input("Your message", "")
+    user_input= f'{instruction} \n\nUser: {user_input}\nAI'
+    if user_input:
+        with st.spinner("Generating response..."):
+            try:
+                response = llm(user_input, temperature=temperature, max_tokens=256)
+                st.write(f"**Cybersecurity Assistant:** {response['choices'][0]['text'].strip()}")
+            except Exception as e:
+                st.error(f"Error in Generation: {e}")