Update src/rag_engine.py

expanded the number of retrieved documents from 10 to 25 and output documents from 3-6

src/rag_engine.py

@@ -101,7 +101,7 @@ def process_and_add_document(file_path, username, strategy="paragraph"):
         return False, str(e)
 
 # --- RETRIEVAL ENGINE ---
-def search_knowledge_base(query, username, k=3):
+def search_knowledge_base(query, username, k=6):
     """
     Two-Stage Retrieval System (RAG):
     1. Retrieval: Get 10 candidates via fast Vector Search.
@@ -120,7 +120,7 @@ def search_knowledge_base(query, username, k=3):
         reranker = get_reranker_model()
         
         # 1. Broad Search
-        results = db.similarity_search(query, k=10)
+        results = db.similarity_search(query, k=25)
         
         if not results:
             return []
@@ -131,7 +131,8 @@ def search_knowledge_base(query, username, k=3):
         
         top_results = []
         sorted_ranks = sorted(ranks, key=lambda x: x['score'], reverse=True)
-        
+
+        # Return the top k results
         for rank in sorted_ranks[:k]:
             doc_index = rank['corpus_id']
             doc = results[doc_index]