Update app.py

app.py

@@ -58,39 +58,28 @@ def load_csv(file):
 
 # ---------- Main Analysis ----------
 def analyze(df, selected_kpis):
+    print("✅ Analyze function triggered")
 
-    print("Analyze function triggered")
     if df is None or not selected_kpis:
         return "❌ Upload CSV and select KPI columns"
 
-    progress(0, desc="Starting analysis...")
-
     results = []
     explanations = []
 
-    total = len(selected_kpis)
-
-    for i, kpi in enumerate(selected_kpis):
-        progress((i + 1) / total, desc=f"Analyzing {kpi}...")
-
+    for kpi in selected_kpis:
         vals = df[kpi].dropna().values.tolist()
         trend = detect_trend(vals)
         score = change_score(vals)
-
         results.append((kpi, trend, score, vals))
 
     ranked = sorted(results, key=lambda x: x[2], reverse=True)
 
-    progress(0.85, desc="Generating LLM explanations...")
-
-    # Explain only top 5
+    # LLM explanation for top 5
     for kpi, trend, score, vals in ranked[:5]:
         exp = explain(kpi, vals, trend)
         explanations.append(f"**{kpi}** → {exp}")
 
-    progress(1.0, desc="Done ✅")
-
-    # ----- Output -----
+    # Output
     text = "## 🔥 Top 5 KPIs with Biggest Change\n"
     for kpi, trend, score, _ in ranked[:5]:
         text += f"**{kpi}** → {trend} (Score: {score})\n\n"
@@ -105,7 +94,6 @@ def analyze(df, selected_kpis):
 
     return text
 
-
 # ---------- UI ----------
 with gr.Blocks() as demo:
     gr.Markdown("# 🤖 KPI Trend Analyzer with LLM Explanation")