Update process_interview.py

process_interview.py

@@ -354,17 +354,25 @@ def generate_gemini_report_text(analysis_data: Dict) -> str:
     interviewee_text = "\n".join([f"- {u['text']}" for u in analysis_data['transcript_with_roles'] if u.get('role') == 'Interviewee'])
     acceptance_prob = analysis_data.get('acceptance_probability', 50.0)
 
+    # Format numbers only if they are not 'N/A' or strings
+    def format_value(val):
+        return f"{val:.2f}" if isinstance(val, (int, float)) else val
+
+    confidence = voice.get('composite_scores', {}).get('confidence', 'N/A')
+    anxiety = voice.get('composite_scores', {}).get('anxiety', 'N/A')
+    speaking_rate = voice.get('speaking_rate', 'N/A')
+
     prompt = f"""
     You are EvalBot, a highly experienced senior HR analyst generating a comprehensive interview evaluation report.
     Analyze deeply based on actual responses provided below. Avoid generic analysis.
     Maintain professional, HR-standard language with clear structure and bullet points.
-    **Suitability Score: {acceptance_prob:.2f}%**
+    **Suitability Score: {format_value(acceptance_prob)}%**
     ### Interviewee Full Responses:
     {interviewee_text if interviewee_text else "No responses recorded."}
     ### Key Metrics:
-    - Confidence Score: {voice.get('composite_scores', {}).get('confidence', 'N/A'):.2f}
-    - Anxiety Score: {voice.get('composite_scores', {}).get('anxiety', 'N/A'):.2f}
-    - Speaking Rate: {voice.get('speaking_rate', 'N/A')} words/sec
+    - Confidence Score: {format_value(confidence)}
+    - Anxiety Score: {format_value(anxiety)}
+    - Speaking Rate: {format_value(speaking_rate)} words/sec
     ### Report Sections to Generate (Follow this structure exactly):
     **1. Executive Summary:**
     - 3 bullets summarizing performance, key strengths, and hiring recommendation.