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app.py

@@ -420,93 +420,115 @@ def analyze_job(job_title):
             empty, "", ""
         )
 
-    row = df_jobs[df_jobs["title"] == job_title]
-    if row.empty:
+    try:
+        row = df_jobs[df_jobs["title"] == job_title]
+        if row.empty:
+            empty = go.Figure()
+            apply_layout(empty, height=100)
+            return (
+                "<p style='color:#999;'>Job not found</p>",
+                empty, "", ""
+            )
+
+        row = row.iloc[0]
+        score = float(row["observed_exposure"])
+        rank = int(row["rank"])
+        occ_code = str(row["occ_code"])
+
+        # Percentile
+        percentile = (total_jobs - rank) / total_jobs * 100
+
+        # Find similar jobs (same 2-digit SOC code)
+        soc_prefix = occ_code[:2]
+        similar = df_jobs[
+            (df_jobs["occ_code"].str.startswith(soc_prefix))
+            & (df_jobs["title"] != job_title)
+        ].head(5)
+
+        # Risk color
+        if score >= 0.5:
+            score_color = COLORS["danger"]
+        elif score >= 0.3:
+            score_color = COLORS["warning"]
+        elif score >= 0.15:
+            score_color = COLORS["info"]
+        else:
+            score_color = COLORS["success"]
+
+        # Build cards HTML
+        badge = risk_badge(score)
+        card1 = styled_card("AI Exposure Score", f"{score*100:.1f}%", f"Rank #{rank} of {total_jobs}", score_color)
+        card2 = styled_card("Percentile", f"{percentile:.0f}th", "Higher = more exposed than other jobs", COLORS["primary"])
+        card3 = styled_card("Risk Level", badge, "", COLORS["text"])
+
+        cards_html = f"""
+        <div style="display:grid;grid-template-columns:repeat(3,1fr);gap:16px;margin:16px 0;">
+            {card1}
+            {card2}
+            {card3}
+        </div>
+        <div style="background:white;border-radius:16px;padding:24px;margin-top:16px;
+                    box-shadow:0 2px 12px rgba(0,0,0,0.06);border:1px solid #f0ece8;">
+            <h3 style="margin:0 0 4px 0;color:{COLORS['secondary']};">{job_title}</h3>
+            <p style="margin:0;color:{COLORS['muted']};">O*NET Code: {occ_code}</p>
+        </div>
+        """
+
+        # Gauge chart
+        gauge = make_gauge(score)
+
+        # Similar jobs comparison
+        if not similar.empty:
+            similar_html = "<div style='margin-top:16px;'><h4>Related Occupations</h4><table style='width:100%;border-collapse:collapse;'>"
+            similar_html += "<tr style='border-bottom:2px solid #f0ece8;'><th style='text-align:left;padding:8px;'>Occupation</th><th style='text-align:right;padding:8px;'>Exposure</th></tr>"
+            for _, s in similar.iterrows():
+                bar_width = float(s["observed_exposure"]) * 100
+                similar_html += f"""
+                <tr style='border-bottom:1px solid #f5f0eb;'>
+                    <td style='padding:10px 8px;'>{s['title']}</td>
+                    <td style='padding:10px 8px;text-align:right;'>
+                        <div style='display:flex;align-items:center;justify-content:flex-end;gap:8px;'>
+                            <div style='width:80px;height:8px;background:#f0ece8;border-radius:4px;overflow:hidden;'>
+                                <div style='width:{bar_width:.1f}%;height:100%;background:{COLORS["primary"]};border-radius:4px;'></div>
+                            </div>
+                            <span style='font-weight:600;min-width:45px;'>{bar_width:.1f}%</span>
+                        </div>
+                    </td>
+                </tr>"""
+            similar_html += "</table></div>"
+        else:
+            similar_html = ""
+
+        # Interpretation
+        if score >= 0.5:
+            interp = "This occupation has <b>very high</b> AI exposure. A significant portion of its tasks are already being performed with AI assistance. Workers in this field should actively develop AI collaboration skills."
+        elif score >= 0.3:
+            interp = "This occupation has <b>high</b> AI exposure. Many of its tasks intersect with AI capabilities. Embracing AI tools can significantly boost productivity."
+        elif score >= 0.15:
+            interp = "This occupation has <b>moderate</b> AI exposure. Some tasks are being augmented by AI, but core functions still require substantial human expertise."
+        else:
+            interp = "This occupation has <b>low</b> AI exposure. Most of its tasks are not significantly impacted by current AI capabilities, though this may change over time."
+
+        interp_html = f"""
+        <div style="background:#fef9f5;border-left:4px solid {COLORS['primary']};padding:16px 20px;
+                    border-radius:0 12px 12px 0;margin-top:16px;">
+            <strong>Interpretation:</strong> {interp}
+        </div>
+        """
+
+        return cards_html, gauge, similar_html, interp_html
+
+    except Exception as e:
+        import traceback
+        err = traceback.format_exc()
+        print(f"Error in analyze_job: {err}")
         empty = go.Figure()
         apply_layout(empty, height=100)
         return (
-            "<p style='color:#999;'>Job not found</p>",
+            f"<p style='color:red;'>Error analyzing job: {str(e)}</p>",
             empty, "", ""
         )
 
-    row = row.iloc[0]
-    score = row["observed_exposure"]
-    rank = row["rank"]
-    occ_code = row["occ_code"]
-
-    # Percentile
-    percentile = ((total_jobs - rank) / total_jobs * 100)
-
-    # Find similar jobs (same 2-digit SOC code)
-    soc_prefix = occ_code[:2]
-    similar = df_jobs[
-        (df_jobs["occ_code"].str.startswith(soc_prefix))
-        & (df_jobs["title"] != job_title)
-    ].head(5)
-
-    # Build cards HTML
-    cards_html = f"""
-    <div style="display:grid;grid-template-columns:repeat(auto-fit,minmax(200px,1fr));gap:16px;margin:16px 0;">
-        {styled_card("AI Exposure Score", f"{score*100:.1f}%", f"Rank #{rank} of {total_jobs}",
-                      COLORS['danger'] if score >= 0.5 else COLORS['warning'] if score >= 0.3
-                      else COLORS['info'] if score >= 0.15 else COLORS['success'])}
-        {styled_card("Percentile", f"{percentile:.0f}th",
-                      "Higher = more exposed than other jobs",
-                      COLORS['primary'])}
-        {styled_card("Risk Level", risk_badge(score), "", COLORS['text'])}
-    </div>
-    <div style="background:white;border-radius:16px;padding:24px;margin-top:16px;
-                box-shadow:0 2px 12px rgba(0,0,0,0.06);border:1px solid #f0ece8;">
-        <h3 style="margin:0 0 4px 0;color:{COLORS['secondary']};">{job_title}</h3>
-        <p style="margin:0;color:{COLORS['muted']};">O*NET Code: {occ_code}</p>
-    </div>
-    """
-
-    # Gauge chart
-    gauge = make_gauge(score)
-
-    # Similar jobs comparison
-    if not similar.empty:
-        compare_data = pd.concat([row.to_frame().T, similar])
-        similar_html = "<div style='margin-top:16px;'><h4>Related Occupations</h4><table style='width:100%;border-collapse:collapse;'>"
-        similar_html += "<tr style='border-bottom:2px solid #f0ece8;'><th style='text-align:left;padding:8px;'>Occupation</th><th style='text-align:right;padding:8px;'>Exposure</th></tr>"
-        for _, s in similar.iterrows():
-            bar_width = s["observed_exposure"] * 100
-            similar_html += f"""
-            <tr style='border-bottom:1px solid #f5f0eb;'>
-                <td style='padding:10px 8px;'>{s['title']}</td>
-                <td style='padding:10px 8px;text-align:right;'>
-                    <div style='display:flex;align-items:center;justify-content:flex-end;gap:8px;'>
-                        <div style='width:80px;height:8px;background:#f0ece8;border-radius:4px;overflow:hidden;'>
-                            <div style='width:{bar_width}%;height:100%;background:{COLORS["primary"]};border-radius:4px;'></div>
-                        </div>
-                        <span style='font-weight:600;min-width:45px;'>{s['observed_exposure']*100:.1f}%</span>
-                    </div>
-                </td>
-            </tr>"""
-        similar_html += "</table></div>"
-    else:
-        similar_html = ""
-
-    # Interpretation
-    if score >= 0.5:
-        interp = "This occupation has **very high** AI exposure. A significant portion of its tasks are already being performed with AI assistance. Workers in this field should actively develop AI collaboration skills."
-    elif score >= 0.3:
-        interp = "This occupation has **high** AI exposure. Many of its tasks intersect with AI capabilities. Embracing AI tools can significantly boost productivity."
-    elif score >= 0.15:
-        interp = "This occupation has **moderate** AI exposure. Some tasks are being augmented by AI, but core functions still require substantial human expertise."
-    else:
-        interp = "This occupation has **low** AI exposure. Most of its tasks are not significantly impacted by current AI capabilities, though this may change over time."
-
-    interp_html = f"""
-    <div style="background:#fef9f5;border-left:4px solid {COLORS['primary']};padding:16px 20px;
-                border-radius:0 12px 12px 0;margin-top:16px;">
-        <strong>Interpretation:</strong> {interp}
-    </div>
-    """
-
-    return cards_html, gauge, similar_html, interp_html
-
 
 # ============================================================================
 # KEY METRICS