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import gradio as gr
from transformers import pipeline
import subprocess
# Load your Hugging Face model
model_name = "Canstralian/RedTeamAI" # Replace with your Hugging Face model path
chatbot = pipeline("text-generation", model=model_name)
def generate_response(prompt):
"""Generate a response using the Hugging Face model."""
try:
response = chatbot(prompt, max_length=150, num_return_sequences=1)
return response[0]["generated_text"]
except Exception as e:
return f"Model Error: {str(e)}"
def execute_bash(command):
"""Execute a Bash command and return the output."""
try:
result = subprocess.run(command, shell=True, capture_output=True, text=True)
return result.stdout or result.stderr
except Exception as e:
return f"Execution Error: {str(e)}"
def execute_python(script):
"""Execute a Python script dynamically."""
try:
exec_globals = {}
exec(script, exec_globals)
return "Script executed successfully!"
except Exception as e:
return f"Python Execution Error: {str(e)}"
def chatbot_interface(user_input, execution_mode, code=None):
"""Main interface logic for guiding and executing scripts."""
if execution_mode == "Guide":
return generate_response(user_input)
elif execution_mode == "Execute Bash":
return execute_bash(user_input)
elif execution_mode == "Execute Python":
return execute_python(code)
else:
return "Invalid mode selected!"
# Gradio Interface
interface = gr.Interface(
fn=chatbot_interface,
inputs=[
gr.Textbox(label="Enter your query or script"),
gr.Radio(["Guide", "Execute Bash", "Execute Python"], label="Mode"),
gr.Textbox(label="Python Script (if applicable)", lines=10, optional=True)
],
outputs="text",
title="RedTeamAI Script Assistant",
description="A GPT-powered chatbot to guide through and execute Bash and Python scripts."
)
if __name__ == "__main__":
interface.launch() |