Update app.py

app.py

@@ -575,8 +575,15 @@ def summarize_resume_text(resume_text, models):
     job_position = extract_job_position(resume_text)
     skills = extract_skills(resume_text)
     
-    # Extract work experience
-    work_experience = extract_work_experience(resume_text)
+    # Extract work experience section
+    work_experience_text = extract_work_experience_section(resume_text)
+    
+    # Use the summarization model to summarize the work experience
+    if work_experience_text:
+        # Summarize work experience using the model
+        work_summary = summarize_text(work_experience_text, models, max_length=150)
+    else:
+        work_summary = "No detailed work experience found in the resume."
     
     # Format the structured summary with different paragraphs for each critical piece
     formatted_summary = f"Name: {name}\n\n"
@@ -584,15 +591,15 @@ def summarize_resume_text(resume_text, models):
     formatted_summary += f"Expected Industry: {industry}\n\n"
     formatted_summary += f"Expected Job Position: {job_position}\n\n"
     formatted_summary += f"Skills: {', '.join(skills)}\n\n"
-    formatted_summary += f"Previous Work Experience: {work_experience}"
+    formatted_summary += f"Previous Work Experience: {work_summary}"
     
     execution_time = time.time() - start_time
     
     return formatted_summary, execution_time
 
-# Extract work experience
-def extract_work_experience(text):
-    """Extract work experience from resume text"""
+# Extract work experience section
+def extract_work_experience_section(text):
+    """Extract work experience section from resume for summarization"""
     # Work experience extraction
     work_headers = [
         "work experience", "professional experience", "employment history", 
@@ -607,7 +614,7 @@ def extract_work_experience(text):
     lines = text.split('\n')
     text_lower = text.lower()
     
-    # Work experience extraction - simplified approach
+    # Work experience extraction
     work_section = []
     in_work_section = False
     
@@ -627,49 +634,31 @@ def extract_work_experience(text):
             if line.strip():
                 work_section.append(line.strip())
     
-    # Simplified work formatting
-    if not work_section:
-        # If no explicit work section found, try to extract key employment information
-        experience_found = False
-        company_patterns = [
-            r'(\d{4}(?:\s*-\s*\d{4}|\s*-\s*present|\s*-\s*current))\s*([^,.\n]+)',
-            r'(?:at|with|for)\s+([A-Z][A-Za-z\s]+)(?:\s*|\.|,|\()'
-        ]
-        
-        experience_lines = []
-        for pattern in company_patterns:
-            matches = re.findall(pattern, text, re.IGNORECASE)
-            if matches:
-                experience_found = True
-                for match in matches[:3]: # Limit to top 3 matches
-                    if isinstance(match, tuple):
-                        experience_lines.append(f"• {match[0]} {match[1]}")
-                    else:
-                        experience_lines.append(f"• {match}")
-        
-        if experience_found:
-            return "\n".join(experience_lines)
-        return "No detailed work experience provided in resume"
-    else:
-        # Just take the first 5-7 lines of the work section as a summary
-        work_lines = []
-        company_count = 0
-        
-        for line in work_section:
-            # New company entry often has a date
-            if re.search(r'(19|20)\d{2}', line):
-                company_count += 1
-                if company_count <= 3:  # Limit to 3 most recent positions
-                    work_lines.append(f"• {line}")
-                else:
-                    break
-            elif company_count <= 3 and len(work_lines) < 10:  # Limit total lines
-                if line.strip() and len(line) > 5:
-                    work_lines.append(f"  {line}")
-        
-        if work_lines:
-            return "\n".join(work_lines)
-        return "Work experience mentioned but details unclear"
+    # If we found a work section, join it back into text for summarization
+    if work_section:
+        return "\n".join(work_section)
+    
+    # If no explicit work section found, try to extract paragraphs that might contain work experience
+    # Look for company names, dates, job titles
+    work_related_paragraphs = []
+    paragraphs = text.split('\n\n')
+    
+    for paragraph in paragraphs:
+        # Check if paragraph has dates that look like work experience
+        if re.search(r'(19|20)\d{2}\s*-\s*(19|20)\d{2}|present|current', paragraph, re.IGNORECASE):
+            work_related_paragraphs.append(paragraph)
+        # Check for common job titles
+        elif re.search(r'\b(engineer|developer|manager|analyst|director|consultant|specialist)\b', 
+                      paragraph, re.IGNORECASE):
+            work_related_paragraphs.append(paragraph)
+        # Check for company indicators
+        elif re.search(r'\b(company|corporation|inc\.|corp\.|ltd\.)\b', paragraph, re.IGNORECASE):
+            work_related_paragraphs.append(paragraph)
+    
+    if work_related_paragraphs:
+        return "\n\n".join(work_related_paragraphs)
+    
+    return ""  # Return empty string if no work experience found
 
 #####################################
 # Function: Extract Job Requirements