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import gradio as gr |
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from model import score_opportunity |
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from utils import validate_data |
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def predict_deal(amount, stage, industry, lead_score, email_count, meeting_count, close_date_gap): |
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input_data = { |
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"amount": amount, |
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"stage": stage, |
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"industry": industry, |
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"lead_score": lead_score, |
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"email_count": email_count, |
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"meeting_count": meeting_count, |
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"close_date_gap": close_date_gap |
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} |
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if not validate_data(input_data): |
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return 0, "Invalid", "⚠️ Please enter valid numeric values and select a stage." |
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result = score_opportunity(input_data) |
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return result['score'], result['risk'], result['recommendation'] |
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with gr.Blocks(title="AI Deal Qualification Engine") as demo: |
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gr.Markdown( |
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""" |
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# 🤖 AI-Powered Deal Qualification Engine |
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_Estimate the quality of your B2B opportunity using AI._ |
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Enter opportunity details below to predict: |
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✅ **Deal Score** |
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✅ **Risk Level** |
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✅ **AI Recommendation** |
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""" |
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) |
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with gr.Row(): |
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with gr.Column(): |
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amount = gr.Number(label="💰 Deal Amount (INR/USD)", scale=1) |
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stage = gr.Dropdown( |
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["Prospecting", "Qualified", "Proposal", "Negotiation", "Closed Won", "Closed Lost"], |
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label="📊 Deal Stage" |
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) |
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industry = gr.Textbox(label="🏭 Industry (e.g., IT, Healthcare)") |
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with gr.Column(): |
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lead_score = gr.Number(label="📈 Lead Score (0–100)") |
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email_count = gr.Number(label="✉️ Email Interactions") |
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meeting_count = gr.Number(label="📅 Meeting Count") |
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close_date_gap = gr.Number(label="📆 Days Until Expected Close") |
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with gr.Row(): |
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submit_btn = gr.Button("🔍 Predict Deal") |
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with gr.Row(): |
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score = gr.Number(label="🧮 Deal Score (0–100)", interactive=False) |
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risk = gr.Textbox(label="🚦 Risk Level", interactive=False) |
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recommendation = gr.Textbox(label="🧠 AI Recommendation", lines=2, interactive=False) |
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submit_btn.click(fn=predict_deal, |
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inputs=[amount, stage, industry, lead_score, email_count, meeting_count, close_date_gap], |
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outputs=[score, risk, recommendation]) |
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demo.launch() |
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