Update app.py

app.py

@@ -51,63 +51,21 @@ def analyze_book(title, reviews_text, avg_units_sold):
 
     payload = {
         "title": title,
-        "reviews": reviews_text
+        "reviews": reviews_text,
+        "avg_units_sold": avg_units_sold
     }
 
     try:
         response = requests.post(url, json=payload)
-        result = response.json()
 
         summary = f"""
 📚 **{title}**
 
-💡 **Pricing Decision : {result.get("pricing_decision", "Error")}**
-📊 Sentiment : {result.get("sentiment", "N/A")}
-"""
+Status code: {response.status_code}
 
-        return summary, "Processed via n8n", None
-
-    except Exception as e:
-        return f"Error: {str(e)}", "N/A", None
-
-    # Analyse sentiment de chaque review
-    lines = [r.strip() for r in reviews_text.strip().split("\n") if r.strip()]
-    labels = [get_sentiment_label(line) for line in lines]
-
-    total         = len(labels)
-    positive_ratio = labels.count("positive") / total
-    negative_ratio = labels.count("negative") / total
-    neutral_ratio  = labels.count("neutral")  / total
-
-    decision = pricing_decision(avg_units_sold, positive_ratio, negative_ratio)
-
-    # Résumé texte
-    summary = f"""
-📚 **{title}**
-
-🔢 Reviews analysées : {total}
-😊 Positive : {positive_ratio:.0%}
-😐 Neutral  : {neutral_ratio:.0%}
-😞 Negative : {negative_ratio:.0%}
-📦 Avg units sold : {avg_units_sold}
-
-💡 **Pricing Decision : {decision}**
-"""
-
-    # Graphique en camembert
-    fig, ax = plt.subplots(figsize=(4, 4))
-    colors = ["#4CAF50", "#FFC107", "#F44336"]
-    ax.pie(
-        [positive_ratio, neutral_ratio, negative_ratio],
-        labels=["Positive", "Neutral", "Negative"],
-        autopct="%1.0f%%",
-        colors=colors,
-        startangle=90
-    )
-    ax.set_title(f"Sentiment — {title}")
-    plt.tight_layout()
-
-    return summary, "\n".join(f"{l} → {s}" for l, s in zip(lines, labels)), fig
+Raw response:
+```text
+{response.text}
 
 # ─────────────────────────────────────────
 # SECTION 3 — Interface Gradio