Initial project setup with multi-URL API

app.py

@@ -8,7 +8,7 @@ import tempfile
 import gradio as gr
 from process_interview import process_interview
 from typing import Tuple, Optional, List, Dict
-from concurrent.futures import ThreadPoolExecutor  # Import ThreadPoolExecutor for parallel processing
+from concurrent.futures import ThreadPoolExecutor
 
 # Setup logging
 logging.basicConfig(
@@ -134,14 +134,15 @@ def analyze_multiple_audios(file_paths_or_urls: List[str]) -> Tuple[str, str, Li
 
     combined_summary = "\n\n---\n\n".join(all_summaries)
     # Ensure the combined_json_list is a valid JSON array string
-    combined_json_list = "[\n" + ",\n".join(all_json_data) + "\n]"
+    combined_json_list = "[\n" + ",\n".join(all_json_data) + "\n]"  # تم تصحيح خطأ الـ f-string هنا
+
     return combined_summary, combined_json_list, all_pdf_paths
 
 
 # Gradio interface
-with gr.Blocks(title="Interview Analysis System", theme=gr.themes.Soft()) as demo:
+with gr.Blocks(title="EvalBot Interview Analysis System", theme=gr.themes.Soft()) as demo:
     gr.Markdown("""
-    # 🎤 Interview Audio Analysis System
+    # 🎤 EvalBot: Automated Interview Analysis System
     Provide multiple audio file URLs or upload multiple audio files to analyze speaker performance.  
     Supported formats: WAV, MP3, M4A, FLAC (max 100MB per file).
     """)
@@ -151,14 +152,13 @@ with gr.Blocks(title="Interview Analysis System", theme=gr.themes.Soft()) as dem
             health_status = gr.Textbox(label="System Status", value=check_health(), interactive=False)
             audio_inputs = gr.File(
                 label="Provide Audio URLs or Upload Files (Multiple allowed)",
-                type="filepath",
-                file_count="multiple"  # Allow multiple files/URLs
+                type="filepath",  # هذا يسمح بـ URLs
+                file_count="multiple"  # السماح بأكثر من URL/ملف
             )
             submit_btn = gr.Button("Start Analysis", variant="primary")
 
         with gr.Column():
-            output_summary = gr.Textbox(label="Combined Analysis Summary", interactive=False,
-                                        lines=10)  # Adjusted lines
+            output_summary = gr.Textbox(label="Combined Analysis Summary", interactive=False, lines=10)
             output_json = gr.Textbox(label="Detailed Analysis (JSON Array)", interactive=False, lines=20)
             pdf_outputs = gr.File(label="Download All Reports", type="filepath", file_count="multiple")
 

process_interview.py

@@ -23,8 +23,8 @@ from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer, Table, Tabl
 from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
 from reportlab.lib.units import inch
 from reportlab.lib import colors
-import matplotlib.pyplot as plt # تم تفعيله
-from reportlab.platypus import Image # تم تفعيله
+import matplotlib.pyplot as plt # تم تفعيله للـ charts
+from reportlab.platypus import Image # تم تفعيله للـ charts
 # --- End Imports for enhanced PDF ---
 from transformers import AutoTokenizer, AutoModel
 import spacy
@@ -768,6 +768,20 @@ def create_pdf_report(analysis_data: Dict, output_path: str, gemini_report_text:
             story.append(table)
             story.append(Spacer(1, 0.2 * inch))
 
+            # --- Charts ---
+            story.append(Paragraph("Score Visualization:", h3)) # Original placeholder for charts
+            chart_path = os.path.join(OUTPUT_DIR, f"anxiety_confidence_{uuid.uuid4().hex[:8]}.png")
+            generate_anxiety_confidence_chart(voice_analysis['composite_scores'], chart_path)
+            try:
+                if os.path.exists(chart_path):
+                    img = Image(chart_path, width=3.5*inch, height=2.0*inch)
+                    story.append(img)
+                    story.append(Spacer(1, 0.1 * inch))
+                    os.remove(chart_path)
+            except Exception as img_e:
+                logger.warning(f"Could not add chart image to PDF: {img_e}")
+            # --- End Charts ---
+
             # Detailed Interpretation from Gemini (if present)
             if 'Voice Analysis Insights' in sections:
                 story.append(Paragraph("Detailed Interpretation:", h3))