Create app.py

app.py

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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()