Update process_interview.py

process_interview.py

@@ -491,29 +491,26 @@ def generate_voice_interpretation(analysis: Dict) -> str:
     return "\n".join(interpretation_lines)
 
 
-# --- Chart Generation Function ---
-def generate_anxiety_confidence_chart(composite_scores: Dict, chart_path: str):
+def generate_anxiety_confidence_chart(composite_scores: Dict, chart_path_or_buffer):
     try:
         labels = ['Anxiety', 'Confidence']
         scores = [composite_scores.get('anxiety', 0), composite_scores.get('confidence', 0)]
-
-        fig, ax = plt.subplots(figsize=(4, 2.5))  # Smaller size for embedding in PDF
-        ax.bar(labels, scores, color=['lightcoral', 'lightskyblue'])
-        ax.set_ylabel('Score')
-        ax.set_title('Anxiety vs. Confidence Scores')
-        ax.set_ylim(0, 1.0)  # Assuming scores are normalized 0-1
-
-        for i, v in enumerate(scores):
-            ax.text(i, v + 0.05, f"{v:.2f}", color='black', ha='center', fontweight='bold')
-
-        # هذه الأوامر يجب أن تكون خارج الـ loop عشان يتم تنفيذها مرة واحدة بعد رسم كل العناصر
+        fig, ax = plt.subplots(figsize=(5, 3))
+        bars = ax.bar(labels, scores, color=['#FF6B6B', '#4ECDC4'], edgecolor='black', width=0.6)
+        ax.set_ylabel('Score (Normalized)', fontsize=12)
+        ax.set_title('Vocal Dynamics: Anxiety vs. Confidence', fontsize=14, pad=15)
+        ax.set_ylim(0, 1.2)
+        for bar in bars:
+            height = bar.get_height()
+            ax.text(bar.get_x() + bar.get_width()/2, height + 0.05, f"{height:.2f}",
+                    ha='center', color='black', fontweight='bold', fontsize=11)
+        ax.grid(True, axis='y', linestyle='--', alpha=0.7)
         plt.tight_layout()
-        plt.savefig(chart_path)
-        plt.close(fig)  # Close the figure to free up memory
+        plt.savefig(chart_path_or_buffer, format='png', bbox_inches='tight', dpi=200)
+        plt.close(fig)
     except Exception as e:
         logger.error(f"Error generating chart: {str(e)}")
 
-
 # --- Acceptance Probability Calculation ---
 def calculate_acceptance_probability(analysis_data: Dict) -> float:
     """