app.py

import gradio as gr
from mock_model import predict

def run_app(amount, stage, industry, lead_score, emails, meetings, close_gap):
    input_data = {
        "amount": amount,
        "stage": stage,
        "industry": industry,
        "lead_score": lead_score,
        "emails_last_7_days": emails,
        "meetings_last_30_days": meetings,
        "close_date_gap": close_gap
    }
    result = predict(input_data, None, None, None)
    return result["score"], result["confidence"], result["risk"], result["recommendation"]

demo = gr.Interface(
    fn=run_app,
    title="AI-Powered Deal Qualification Engine (Demo)",
    inputs=[
        gr.Number(label="Amount (USD)", value=50000),
        gr.Dropdown(["Prospecting", "Proposal/Price Quote", "Negotiation", "Closed Won", "Closed Lost"], label="Stage"),
        gr.Textbox(label="Industry", value="Software"),
        gr.Number(label="Lead Score", value=85),
        gr.Number(label="Emails in Last 7 Days", value=3),
        gr.Number(label="Meetings in Last 30 Days", value=2),
        gr.Number(label="Close Date Gap (days)", value=10)
    ],
    outputs=[
        gr.Number(label="AI Score (0–100)"),
        gr.Number(label="Confidence (0–1)"),
        gr.Textbox(label="Risk Level"),
        gr.Textbox(label="Recommendation")
    ]
)

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