app.py

# app.py - SIMPLEST WORKING VERSION
import gradio as gr
import subprocess
import time

print("🚀 Starting Foundation-Sec-8B Space...")

def generate(prompt):
    """Generate text using transformers CLI (avoids loading issues)"""
    python_code = f"""
import torch
from transformers import pipeline

print("Loading model...")
model = pipeline(
    "text-generation",
    model="fdtn-ai/Foundation-Sec-8B",
    device=0,
    torch_dtype=torch.float16,
    trust_remote_code=True
)

result = model("{prompt}", max_new_tokens=200, temperature=0.7)
print(result[0]['generated_text'])
"""
    
    # Save to temp file
    with open("/tmp/generate.py", "w") as f:
        f.write(python_code)
    
    try:
        # Run in subprocess
        result = subprocess.run(
            ["python", "/tmp/generate.py"],
            capture_output=True,
            text=True,
            timeout=180
        )
        
        if result.returncode == 0:
            return result.stdout.strip().split('\n')[-1]  # Get last line
        else:
            return f"Error: {result.stderr}"
            
    except subprocess.TimeoutExpired:
        return "Timeout - Model taking too long to load"
    except Exception as e:
        return f"Exception: {str(e)}"

# Create interface
iface = gr.Interface(
    fn=generate,
    inputs=gr.Textbox(label="Ask about cybersecurity:", lines=3),
    outputs=gr.Textbox(label="Response", lines=10),
    title="🔒 Foundation-Sec-8B",
    description="Cybersecurity AI Assistant",
    examples=[
        ["What is a firewall?"],
        ["Explain encryption:"],
        ["How to create strong passwords?"]
    ]
)

if __name__ == "__main__":
    iface.launch(server_name="0.0.0.0")