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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()
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