Spaces:
Running
Running
File size: 2,445 Bytes
44feadc 43350c0 44feadc 43350c0 44feadc 43350c0 44feadc 43350c0 44feadc 43350c0 44feadc 43350c0 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 |
import streamlit as st
from llama_cpp import Llama
st.set_page_config(page_title="Cybertron Chat Interface", layout="wide")
st.title("🧠 Cybertron Chat: Generalist vs Specialist Mode")
st.markdown("""
Welcome to the Cybertron Chat Interface. Choose between:
- 🤖 **Generalist Mode** for creative, imaginative, multi-purpose reasoning
- 🛡️ **Specialist Mode** for precise, tactical cyber security and pentesting insights
""")
# Sidebar toggle for mode
model_choice = st.sidebar.radio("Choose Mode:", ["Generalist 🤖", "Specialist 🛡️"], help="Switch between general reasoning and focused cybersec models")
# Display model tips
if model_choice == "Generalist 🤖":
st.sidebar.markdown("""
**Best for:**
- Creative writing
- Brainstorming tools or strategies
- Simulating conversations
""")
llm = Llama.from_pretrained(
repo_id="bartowski/cybertron-v4-qw7B-MGS-GGUF",
filename="cybertron-v4-qw7B-MGS-IQ2_M.gguf",
)
example_prompts = [
"Simulate a hacker group planning a phishing campaign",
"Explain how to exploit a misconfigured NGINX server",
"Write a Python script that scrapes threat intel feeds"
]
else:
st.sidebar.markdown("""
**Best for:**
- Penetration testing guidance
- Red/blue team planning
- Shell scripting and command-line tasks
""")
llm = Llama.from_pretrained(
repo_id="TheBloke/una-cybertron-7B-v2-GGUF",
filename="una-cybertron-7b-v2-bf16.Q2_K.gguf",
)
example_prompts = [
"List enumeration commands for Active Directory",
"Simulate a post-exploitation persistence technique",
"Generate a Bash reverse shell with obfuscation"
]
# Prompt input and example selector
col1, col2 = st.columns([2, 1])
with col1:
user_input = st.text_area("\U0001F4AC Enter your query below:", height=150)
with col2:
st.markdown("**\U0001F4D6 Prompt Examples:**")
selected_example = st.selectbox("Try an example:", ["-- Select an example --"] + example_prompts)
if selected_example != "-- Select an example --":
user_input = selected_example
# Run inference
if st.button("Submit", use_container_width=True):
with st.spinner("Generating response..."):
output = llm(user_input, max_tokens=512, echo=True)
st.markdown("---")
st.markdown("**\U0001F4C4 Response:**")
st.code(output["choices"][0]["text"].strip())
|