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import gradio as gr
import pandas as pd
from utils.dataset_loader import load_dataset
# Function to safely load dataset
def load_and_validate_dataset():
df = load_dataset()
if df is not None and "prompt_text" in df.columns:
return df
else:
return None
# Load dataset with validation
df = load_and_validate_dataset()
# Function to simulate conversation with model selection
def chat_interface(user_input, selected_model, prompt_id=None):
if df is not None and prompt_id is not None:
prompt = df.iloc[prompt_id]["prompt_text"] # Replace with the actual column name
response = f"[{selected_model}] used the debugging prompt: '{prompt}'.\nUser said: '{user_input}'\nResponse: Simulated output."
else:
response = f"[{selected_model}] says: You entered '{user_input}'. This is a simulated response."
return response
# List of available models (Updated as per your request)
models = ["Canstralian/text2shellcommands", "Canstralian/RabbitRedux", "Canstralian/CySec_Known_Exploit_Analyzer"]
prompt_ids = df.index.tolist() if df is not None else []
# Gradio Interface
with gr.Blocks(css="./static/styles.css") as demo:
with gr.Row():
gr.Markdown("### Retro Hacker Chat with Debugging Prompts", elem_classes="retro-terminal")
with gr.Row():
user_input = gr.Textbox(
label="Enter your message:",
placeholder="Type your message here...",
elem_classes="retro-terminal"
)
model_selector = gr.Dropdown(
choices=models,
label="Select Model",
value=models[0],
elem_classes="retro-terminal"
)
# Conditionally display the prompt selector only if dataset is available
if df is not None:
prompt_selector = gr.Dropdown(
choices=prompt_ids,
label="Select Debugging Prompt ID",
value=prompt_ids[0] if prompt_ids else None,
elem_classes="retro-terminal"
)
else:
prompt_selector = None
with gr.Row():
response_box = gr.Textbox(
label="Model Response:",
placeholder="The model's response will appear here...",
elem_classes="retro-terminal"
)
with gr.Row():
send_button = gr.Button("Send", elem_classes="retro-terminal")
# Link input and output
if prompt_selector:
send_button.click(chat_interface, inputs=[user_input, model_selector, prompt_selector], outputs=response_box)
else:
send_button.click(chat_interface, inputs=[user_input, model_selector], outputs=response_box)
# Launch the interface
demo.launch()
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