# app.py

import gradio as gr
from model import score_opportunity
from utils import validate_data

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
    }

    if not validate_data(input_data):
        return 0, "Invalid", "⚠️ Please enter valid numeric values and select a stage."

    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 Deal Qualification Engine
        _Estimate the quality of your B2B opportunity using AI._  
        Enter opportunity details below to predict:  
        ✅ **Deal Score**  
        ✅ **Risk Level**  
        ✅ **AI Recommendation**
        """
    )

    with gr.Row():
        with gr.Column():
            amount = gr.Number(label="💰 Deal Amount (INR/USD)", scale=1)
            stage = gr.Dropdown(
                ["Prospecting", "Qualified", "Proposal", "Negotiation", "Closed Won", "Closed Lost"],
                label="📊 Deal Stage"
            )
            industry = gr.Textbox(label="🏭 Industry (e.g., IT, Healthcare)")

        with gr.Column():
            lead_score = gr.Number(label="📈 Lead Score (0–100)")
            email_count = gr.Number(label="✉️ Email Interactions")
            meeting_count = gr.Number(label="📅 Meeting Count")
            close_date_gap = gr.Number(label="📆 Days Until Expected Close")

    with gr.Row():
        submit_btn = gr.Button("🔍 Predict Deal")

    with gr.Row():
        score = gr.Number(label="🧮 Deal 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()