import gradio as gr
from model import score_opportunity

def predict_deal(amount, stage, industry, lead_score, email_count, meeting_count, close_date_gap):
    input_data = {
        "amount": amount,
        "stage": stage,
        "industry": industry,
        "lead_score": lead_score,
        "email_count": email_count,
        "meeting_count": meeting_count,
        "close_date_gap": close_date_gap
    }
    result = score_opportunity(input_data)
    return result['score'], result['risk'], result['recommendation']

with gr.Blocks(title="AI Deal Qualification Engine") as demo:
    gr.Markdown("# 🤖 AI-Powered B2B Deal Qualification Engine")

    with gr.Row():
        amount = gr.Number(label="Amount")
        stage = gr.Dropdown(["Prospecting", "Qualified", "Proposal", "Negotiation", "Closed Won", "Closed Lost"], label="Stage")
        industry = gr.Textbox(label="Industry")
        lead_score = gr.Number(label="Lead Score")
        email_count = gr.Number(label="Email Count")
        meeting_count = gr.Number(label="Meeting Count")
        close_date_gap = gr.Number(label="Close Date Gap (days)")

    submit_btn = gr.Button("Predict Deal Quality")

    with gr.Row():
        score = gr.Number(label="Score (0–100)", interactive=False)
        risk = gr.Textbox(label="Risk Level", interactive=False)
        recommendation = gr.Textbox(label="AI Recommendation", lines=2, interactive=False)

    submit_btn.click(fn=predict_deal,
                     inputs=[amount, stage, industry, lead_score, email_count, meeting_count, close_date_gap],
                     outputs=[score, risk, recommendation])

demo.launch()