app.py

import gradio as gr
from inference import generate_response
from logger import log_user_feedback
from dashboard import update_dashboard_plot
from watchdog import retrain_model

evo_output = gr.Textbox(label="🧠 EvoTransformer Suggestion")
gpt_output = gr.Textbox(label="💬 GPT-3.5 Suggestion")
feedback_output = gr.Textbox(visible=False)

def evo_chat(goal, sol1, sol2):
    response = generate_response(goal, sol1, sol2)
    evo = response.get("evo_suggestion", "Error")
    gpt = response.get("gpt_suggestion", "Error")
    return evo, gpt

def handle_feedback(goal, sol1, sol2, winner):
    try:
        log_user_feedback(goal, sol1, sol2, winner)
        return "✅ Feedback logged. Thank you!"
    except Exception as e:
        return f"❌ Failed to log: {e}"

with gr.Blocks(title="EvoTransformer v2.1 – Compare Options and Learn") as demo:
    gr.Markdown("## 🧠 EvoTransformer v2.1 – Compare Options and Learn")

    with gr.Row():
        goal_input = gr.Textbox(label="Goal", placeholder="e.g. Escape from house on fire")
    with gr.Row():
        option1_input = gr.Textbox(label="Option 1", placeholder="e.g. Exit house through main door")
        option2_input = gr.Textbox(label="Option 2", placeholder="e.g. Hide under bed")

    compare_btn = gr.Button("🔍 Compare")

    with gr.Row():
        evo_output.render()
        gpt_output.render()

    with gr.Row():
        winner_dropdown = gr.Radio(["Solution 1", "Solution 2"], label="Which was better?")
        feedback_btn = gr.Button("✅ Log Feedback")

    feedback_output.render()

    compare_btn.click(
        fn=evo_chat,
        inputs=[goal_input, option1_input, option2_input],
        outputs=[evo_output, gpt_output]
    )

    feedback_btn.click(
        fn=handle_feedback,
        inputs=[goal_input, option1_input, option2_input, winner_dropdown],
        outputs=[feedback_output]
    )

    with gr.Row():
        gr.Markdown("### 📊 Dashboard")
        dashboard_plot = gr.Plot()
        update_dashboard_plot(dashboard_plot)

    with gr.Row():
        retrain_button = gr.Button("♻️ Retrain Evo")
        retrain_status = gr.Textbox(label="Retrain Status")

    retrain_button.click(fn=retrain_model, inputs=[], outputs=[retrain_status])

if __name__ == "__main__":
    demo.launch(share=True)