Update app.py

app.py

@@ -315,11 +315,74 @@ def summarize_resume_text(resume_text):
 #####################################
 def analyze_google_fit(resume_summary):
     """
-    Analyze how well the candidate fits Google's requirements.
-    Only modifying the T5 prompt to get better expert assessments.
+    Analyze how well the candidate fits Google's requirements with detailed category breakdowns.
     """
-    # [Keep all the existing code for score calculation unchanged]
+    start_time = time.time()
+    
+    # Define Google's key skill categories with more detailed keywords
+    google_keywords = {
+        "technical_skills": ["python", "java", "c++", "javascript", "go", "sql", "algorithms", "data structures", 
+                           "coding", "software development", "git", "programming", "backend", "frontend", "full-stack"],
+        "advanced_tech": ["machine learning", "ai", "artificial intelligence", "cloud", "data science", "big data", 
+                         "tensorflow", "deep learning", "distributed systems", "kubernetes", "microservices"],
+        "problem_solving": ["problem solving", "analytical", "critical thinking", "troubleshooting", "debugging", 
+                           "optimization", "scalability", "system design", "complexity", "efficiency"],
+        "innovation": ["innovation", "creative", "creativity", "design thinking", "research", "novel solutions", 
+                      "patents", "publications", "unique approaches", "cutting-edge"],
+        "soft_skills": ["team", "leadership", "collaboration", "communication", "agile", "project management", 
+                       "mentoring", "cross-functional", "presentation", "stakeholder management"]
+    }
+    
+    # Category weights with descriptive labels
+    category_weights = {
+        "technical_skills": {"weight": 0.35, "label": "Technical Programming Skills"},
+        "advanced_tech": {"weight": 0.25, "label": "Advanced Technology Knowledge"},
+        "problem_solving": {"weight": 0.20, "label": "Problem Solving Abilities"},
+        "innovation": {"weight": 0.10, "label": "Innovation Mindset"},
+        "soft_skills": {"weight": 0.10, "label": "Collaboration & Leadership"}
+    }
+    
+    resume_lower = resume_summary.lower()
     
+    # Calculate category scores and store detailed information
+    category_scores = {}
+    category_details = {}
+    found_skills = {}
+    
+    for category, keywords in google_keywords.items():
+        # Find the specific matching keywords for feedback
+        category_matches = [keyword for keyword in keywords if keyword in resume_lower]
+        found_skills[category] = category_matches
+        
+        # Count matches but cap at a reasonable level
+        matches = len(category_matches)
+        total_keywords = len(keywords)
+        
+        # Calculate raw percentage for this category
+        raw_percentage = int((matches / total_keywords) * 100)
+        
+        # Apply logarithmic scaling for more realistic scores
+        if matches == 0:
+            adjusted_score = 0.0
+        else:
+            # Logarithmic scaling to prevent perfect scores
+            adjusted_score = min(0.95, (math.log(matches + 1) / math.log(min(total_keywords, 8) + 1)))
+        
+        # Store both raw and adjusted scores for feedback
+        category_scores[category] = adjusted_score
+        category_details[category] = {
+            "raw_percentage": raw_percentage,
+            "adjusted_score": int(adjusted_score * 100),
+            "matching_keywords": category_matches,
+            "total_keywords": total_keywords,
+            "matches": matches
+        }
+    
+    # Calculate weighted score
+    weighted_score = sum(score * category_weights[category]["weight"] for category, score in category_scores.items())
+    
+    # Apply final curve to keep scores in a realistic range
+    match_percentage = min(92, max(35, int(weighted_score * 100)))
     # Get more specific information for a better prompt
     # Get top skills across all categories (up to 5 total)
     all_matching_skills = []