Update app.py

app.py

@@ -100,7 +100,6 @@ def filter_by_roles(category_name):
 def llm_recommendations(category_name):
     job_titles = CATEGORIES[category_name]
 
-    # Read filtered candidates from CSV
     if not os.path.exists(FILTERED_CSV):
         return pd.DataFrame(), None
 
@@ -116,16 +115,22 @@ def llm_recommendations(category_name):
     for i in range(0, len(filtered_candidates), BATCH_SIZE):
         batch = filtered_candidates[i:i+BATCH_SIZE]
         for person in batch:
-            candidate_str = json.dumps(person)
+            # Only send necessary info
+            candidate_info = {
+                "Name": person.get("Name"),
+                "Roles": person.get("Roles"),
+                "Skills": person.get("Skills")
+            }
+            candidate_str = json.dumps(candidate_info)
             response = call_llm(candidate_str, category_name, tuple(job_titles))
-            if "Yes" in response:
+            if response.strip().lower().startswith("yes"):
                 recommended.append(person)
 
     if not recommended:
         return pd.DataFrame(), None
 
     df_rec = pd.DataFrame(recommended)
-    # Sort by Salary (numeric)
+    # Sort by numeric salary
     def parse_salary(s):
         try:
             return float(s.replace("$","").replace(",",""))