Update app.py

app.py

@@ -3,11 +3,13 @@ import pandas as pd
 from transformers import pipeline
 
 # ------------------------------------------------
-# Load SLM (polishing only)
+# Load Qwen-3B (polishing only)
 # ------------------------------------------------
 generator = pipeline(
-    "text2text-generation",
-    model="google/flan-t5-small"
+    task="text-generation",
+    model="Qwen/Qwen2.5-3B-Instruct",
+    device_map="auto",
+    trust_remote_code=True
 )
 
 # ------------------------------------------------
@@ -31,7 +33,6 @@ def summarize_secondary(diffs):
     avg_change = diffs.abs().mean()
     inc_ratio = (diffs > 0).mean()
 
-    # Magnitude descriptor
     if avg_change < 0.05:
         magnitude = "minor variation"
     elif avg_change < 0.2:
@@ -39,7 +40,6 @@ def summarize_secondary(diffs):
     else:
         magnitude = "notable movement"
 
-    # Direction descriptor
     if inc_ratio > 0.7:
         direction = "mostly increased"
     elif inc_ratio < 0.3:
@@ -79,22 +79,22 @@ def analyze_kpi(csv_file, top_n):
     )
 
     # -------------------------------
-    # Secondary KPIs sentence (DATA-DRIVEN)
+    # Secondary KPI sentence
     # -------------------------------
     secondary_diffs = top_kpis.iloc[1:]["Diff"]
     secondary_sentence = summarize_secondary(secondary_diffs)
 
-    # Combined input
+    # Model input (already well-formed)
     model_input = primary_sentence + ". " + secondary_sentence + "."
 
-    # Light smoothing only
-    summary = generator(
+    # Qwen generation (polishing only)
+    output = generator(
         model_input,
-        max_new_tokens=45,
+        max_new_tokens=60,
         do_sample=False
     )[0]["generated_text"]
 
-    return top_kpis[["Kpi", "Change"]], summary
+    return top_kpis[["Kpi", "Change"]], output
 
 # ------------------------------------------------
 # Gradio UI (HF Space)