import gradio as gr
from google import genai
import os

def ground_truth_engine(past_img, present_img):
    api_key = os.environ.get("GOOGLE_API_KEY")
    if not api_key:
        return "ERROR: GOOGLE_API_KEY not found in Space Secrets."

    # Initialize the new SDK client
    client = genai.Client(api_key=api_key)
    
    if past_img is None or present_img is None:
        return "Please upload both images."

    prompt = """
    Perform a high-fidelity structural audit comparing these two images.
    Focus on changes in roofing, landscaping, and exterior condition.
    Conclude with a 'Maintenance Trajectory': IMPROVING, STABLE, or DECLINING.
    """

    try:
        response = client.models.generate_content(
            model="gemini-robotics-er-1.5-preview",
            contents=[prompt, past_img, present_img]
        )
        return response.text
    except Exception as e:
        return f"Analysis Failed: {str(e)}"

# Define the UI using Gradio 4 syntax
with gr.Blocks(theme=gr.themes.Soft()) as demo:
    gr.Markdown("# 🏠 GroundTruth AI (Stable Build)")
    gr.Markdown("Temporal Property Sentinel powered by Gemini Robotics-ER 1.5")
    
    with gr.Row():
        with gr.Column():
            p_img = gr.Image(label="Past Condition", type="pil")
            c_img = gr.Image(label="Current Condition", type="pil")
            submit = gr.Button("Analyze Trajectory", variant="primary")
        
        with gr.Column():
            output = gr.Markdown(label="Audit Report")

    submit.click(fn=ground_truth_engine, inputs=[p_img, c_img], outputs=output)

if __name__ == "__main__":
    # The server_name binding is required for Docker containers on HF
    demo.launch(server_name="0.0.0.0", server_port=7860)