Update app.py

app.py

@@ -125,7 +125,11 @@ def run_pipeline(
         "Low": -0.08,
         "Medium": 0.00,
         "High": 0.08,
-        "Peak": 0.12
+        "Peak": 0.12,
+        "Spring": 0.03,
+        "Summer": 0.08,
+        "Autumn": 0.00,
+        "Winter": -0.05
     }.get(str(season), 0.00)
 
     price_penalty = max(min(price_gap_pct / 100, 0.35), -0.35) * 0.30
@@ -151,26 +155,32 @@ def run_pipeline(
 
     if demand_score >= 70:
         demand_level = "High"
+        demand_badge = "🟢 High"
     elif demand_score >= 45:
         demand_level = "Medium"
+        demand_badge = "🟡 Medium"
     else:
         demand_level = "Low"
+        demand_badge = "🔴 Low"
 
     if price_gap_pct > 15 and demand_level != "High":
         pricing_recommendation = "Consider lowering price"
         suggested_price = round(competitor_avg_price * 1.05, 2)
         insight = "The listing appears overpriced compared with similar properties."
         next_step = f"Test a lower price around ${suggested_price} to improve occupancy."
+        recommendation_badge = "🔻 Price Reduction Suggested"
     elif price_gap_pct < -10 and demand_level in ["Medium", "High"]:
         pricing_recommendation = "Consider raising price"
         suggested_price = round(min(competitor_avg_price * 0.98, price * 1.12), 2)
         insight = "The listing appears underpriced relative to comparable demand."
         next_step = f"Consider increasing the price toward ${suggested_price}."
+        recommendation_badge = "🚀 Revenue Opportunity"
     else:
         pricing_recommendation = "Keep price stable"
         suggested_price = round(price, 2)
         insight = "The current price is aligned with comparable listings."
         next_step = "Keep price stable and focus on visibility, reviews, and conversion."
+        recommendation_badge = "✅ Stable Positioning"
 
     opportunity_score = round(
         demand_score * 0.45 +
@@ -211,38 +221,65 @@ def run_pipeline(
         }
 
     result_text = f"""
-# StayWise AI Pipeline Result
-
-## Recommendation
-**{pricing_recommendation}**
-
-## Key Metrics
+<div class="result-card">
+
+<div class="section-label">Pipeline Result</div>
+
+<h2>{recommendation_badge}</h2>
+
+<div class="kpi-grid">
+    <div class="kpi-card">
+        <div class="kpi-title">Current Price</div>
+        <div class="kpi-value">${price:,.0f}</div>
+    </div>
+    <div class="kpi-card">
+        <div class="kpi-title">Suggested Price</div>
+        <div class="kpi-value">${suggested_price:,.0f}</div>
+    </div>
+    <div class="kpi-card">
+        <div class="kpi-title">Monthly Revenue</div>
+        <div class="kpi-value">${monthly_revenue:,.0f}</div>
+    </div>
+    <div class="kpi-card">
+        <div class="kpi-title">Demand</div>
+        <div class="kpi-value">{demand_badge}</div>
+    </div>
+</div>
+
+<h3>Key Metrics</h3>
+
+<table class="metric-table">
+<tr><td>Competitor average price</td><td>${competitor_avg_price:,.2f}</td></tr>
+<tr><td>Price vs competitors</td><td>{price_gap_pct:.2f}%</td></tr>
+<tr><td>Estimated occupancy</td><td>{occupancy * 100:.1f}%</td></tr>
+<tr><td>Estimated booked nights / month</td><td>{booked_nights}</td></tr>
+<tr><td>Demand score</td><td>{demand_score}/100</td></tr>
+<tr><td>Opportunity score</td><td>{opportunity_score}/100</td></tr>
+</table>
+
+<h3>Business Insight</h3>
+<p>{insight}</p>
+
+<h3>Next Step</h3>
+<p>{next_step}</p>
+
+</div>
+"""
 
-- Current price: **${price:,.2f}**
-- Suggested price: **${suggested_price:,.2f}**
-- Competitor average price: **${competitor_avg_price:,.2f}**
-- Price vs competitors: **{price_gap_pct:.2f}%**
-- Estimated occupancy: **{occupancy * 100:.1f}%**
-- Estimated booked nights per month: **{booked_nights}**
-- Estimated monthly revenue: **${monthly_revenue:,.2f}**
-- Demand score: **{demand_score}/100**
-- Demand level: **{demand_level}**
-- Opportunity score: **{opportunity_score}/100**
+    automation_text = f"""
+<div class="automation-card">
 
-## Business Insight
-{insight}
+<div class="section-label">n8n Automation Output</div>
 
-## Next Step
-{next_step}
-"""
+<h2>Automation Status: {n8n_response.get("status", "unknown")}</h2>
 
-    automation_text = f"""
-# n8n Automation Output
+<table class="metric-table">
+<tr><td>Insight</td><td>{n8n_response.get("insight", "No insight returned.")}</td></tr>
+<tr><td>Next step</td><td>{n8n_response.get("next_step", "No next step returned.")}</td></tr>
+<tr><td>Log</td><td>{n8n_response.get("log", "No log returned.")}</td></tr>
+</table>
 
-- Status: **{n8n_response.get("status", "unknown")}**
-- Insight: {n8n_response.get("insight", "No insight returned.")}
-- Next step: {n8n_response.get("next_step", "No next step returned.")}
-- Log: {n8n_response.get("log", "No log returned.")}
+</div>
 """
 
     cols = [
@@ -267,20 +304,230 @@ def run_pipeline(
     return result_text, automation_text, comparable_table, json_output
 
 
-with gr.Blocks() as demo:
-    gr.Markdown(
-        """
-        # 🏠 StayWise AI
+custom_css = """
+/* Main background */
+body {
+    background: radial-gradient(circle at top left, #1e3a8a 0%, #0f172a 35%, #020617 100%) !important;
+    color: #f8fafc !important;
+}
+
+/* Main container */
+.gradio-container {
+    max-width: 1250px !important;
+    margin: auto !important;
+    font-family: Inter, system-ui, -apple-system, BlinkMacSystemFont, sans-serif !important;
+}
+
+/* Header */
+#hero {
+    background: linear-gradient(135deg, rgba(37, 99, 235, 0.95), rgba(14, 165, 233, 0.85));
+    border-radius: 28px;
+    padding: 38px 42px;
+    margin-bottom: 26px;
+    box-shadow: 0 25px 60px rgba(0, 0, 0, 0.35);
+    border: 1px solid rgba(255,255,255,0.16);
+}
+
+#hero h1 {
+    font-size: 48px;
+    margin: 0 0 8px 0;
+    color: white;
+    letter-spacing: -1px;
+}
+
+#hero p {
+    font-size: 18px;
+    margin: 6px 0 0 0;
+    color: #e0f2fe;
+}
+
+.hero-badge {
+    display: inline-block;
+    padding: 6px 12px;
+    background: rgba(255,255,255,0.16);
+    border: 1px solid rgba(255,255,255,0.22);
+    border-radius: 999px;
+    font-size: 13px;
+    margin-bottom: 14px;
+    color: white;
+}
+
+/* Panels */
+.gr-block, .gr-form, .gr-box, .gr-panel {
+    border-radius: 20px !important;
+}
+
+.input-panel {
+    background: rgba(15, 23, 42, 0.82);
+    border: 1px solid rgba(148, 163, 184, 0.25);
+    border-radius: 24px;
+    padding: 20px;
+    box-shadow: 0 15px 45px rgba(0,0,0,0.25);
+}
+
+/* Buttons */
+button.primary, .gr-button {
+    border-radius: 14px !important;
+    font-weight: 700 !important;
+    background: linear-gradient(90deg, #2563eb, #06b6d4) !important;
+    border: none !important;
+    color: white !important;
+    box-shadow: 0 10px 25px rgba(37, 99, 235, 0.32) !important;
+}
+
+button.primary:hover, .gr-button:hover {
+    transform: translateY(-1px);
+    filter: brightness(1.08);
+}
+
+/* Labels */
+label, .wrap label {
+    color: #dbeafe !important;
+    font-weight: 600 !important;
+}
+
+/* Inputs */
+input, textarea, select {
+    border-radius: 12px !important;
+}
+
+/* Slider */
+input[type="range"] {
+    accent-color: #38bdf8 !important;
+}
+
+/* Output cards */
+.result-card, .automation-card {
+    background: rgba(15, 23, 42, 0.88);
+    border: 1px solid rgba(148, 163, 184, 0.25);
+    border-radius: 26px;
+    padding: 26px;
+    margin-bottom: 22px;
+    box-shadow: 0 18px 50px rgba(0,0,0,0.28);
+}
+
+.result-card h2, .automation-card h2 {
+    margin-top: 8px;
+    color: #f8fafc;
+    font-size: 26px;
+}
+
+.result-card h3, .automation-card h3 {
+    margin-top: 24px;
+    color: #bae6fd;
+    font-size: 20px;
+}
+
+.result-card p, .automation-card p {
+    color: #e5e7eb;
+    line-height: 1.6;
+}
+
+.section-label {
+    display: inline-block;
+    background: rgba(56, 189, 248, 0.13);
+    border: 1px solid rgba(56, 189, 248, 0.35);
+    color: #7dd3fc;
+    padding: 7px 13px;
+    border-radius: 999px;
+    font-size: 13px;
+    font-weight: 700;
+    letter-spacing: 0.4px;
+    text-transform: uppercase;
+}
+
+/* KPI Cards */
+.kpi-grid {
+    display: grid;
+    grid-template-columns: repeat(4, minmax(120px, 1fr));
+    gap: 14px;
+    margin: 22px 0;
+}
+
+.kpi-card {
+    background: linear-gradient(180deg, rgba(30, 41, 59, 0.95), rgba(15, 23, 42, 0.95));
+    border: 1px solid rgba(148, 163, 184, 0.25);
+    border-radius: 18px;
+    padding: 18px;
+}
+
+.kpi-title {
+    color: #94a3b8;
+    font-size: 13px;
+    margin-bottom: 8px;
+}
+
+.kpi-value {
+    color: #f8fafc;
+    font-size: 22px;
+    font-weight: 800;
+}
+
+/* Tables */
+.metric-table {
+    width: 100%;
+    border-collapse: collapse;
+    overflow: hidden;
+    border-radius: 14px;
+    margin-top: 12px;
+}
+
+.metric-table td {
+    padding: 12px 14px;
+    border-bottom: 1px solid rgba(148, 163, 184, 0.18);
+    color: #e5e7eb;
+}
+
+.metric-table td:first-child {
+    color: #93c5fd;
+    font-weight: 650;
+    width: 45%;
+}
+
+.metric-table tr:last-child td {
+    border-bottom: none;
+}
+
+/* Dataframe and code areas */
+.dataframe, .wrap, .contain {
+    border-radius: 18px !important;
+}
+
+/* Footer text */
+.small-note {
+    color: #94a3b8;
+    font-size: 13px;
+    margin-top: -8px;
+    margin-bottom: 18px;
+}
+
+@media (max-width: 900px) {
+    .kpi-grid {
+        grid-template-columns: repeat(2, minmax(120px, 1fr));
+    }
+
+    #hero h1 {
+        font-size: 36px;
+    }
+}
+"""
 
-        **AI-powered pricing and performance optimization for short-term rentals.**
 
-        Enter listing details, run the full pipeline, compare with similar listings, and optionally send the result to n8n.
+with gr.Blocks(css=custom_css) as demo:
+    gr.HTML(
+        """
+        <div id="hero">
+            <div class="hero-badge">Short-Term Rental Pricing Assistant</div>
+            <h1>🏠 StayWise AI</h1>
+            <p>AI-powered pricing and performance optimization for short-term rentals.</p>
+            <p class="small-note">Run the full pipeline, benchmark a listing against comparable properties, and return automation insights from n8n.</p>
+        </div>
         """
     )
 
     with gr.Row():
-        with gr.Column():
-            gr.Markdown("## Property Inputs")
+        with gr.Column(scale=1):
+            gr.Markdown("## 📊 Property Inputs")
 
             neighbourhood_group = gr.Dropdown(
                 choices=neighbourhood_groups,
@@ -351,16 +598,16 @@ with gr.Blocks() as demo:
                 value=False
             )
 
-            run_button = gr.Button("Run Full Pipeline")
+            run_button = gr.Button("🚀 Run Full Pipeline", variant="primary")
 
-        with gr.Column():
-            result_output = gr.Markdown()
-            automation_output = gr.Markdown()
+        with gr.Column(scale=2):
+            result_output = gr.HTML()
+            automation_output = gr.HTML()
 
-    gr.Markdown("## Comparable Listings")
+    gr.Markdown("## 📈 Comparable Listings")
     comparable_output = gr.Dataframe()
 
-    gr.Markdown("## JSON Pipeline Output")
+    gr.Markdown("## 🧾 Pipeline Data Output")
     json_output = gr.Code(language="json")
 
     run_button.click(