Update rag_chain.py

rag_chain.py

@@ -53,8 +53,6 @@ Your tasks:
 - If the query is intent-based, answer in **1-2 clear sentences** based on the provided policy excerpt [Detailed reason/Detailed Explanation]. 
 - If the query is decision-based, Identify both coverage clause or benefit section , Exclusion or waiting period clause (if any applies) respond in this format:
   [Yes/No] – [Procedure] is [covered/not covered] under [Coverage Clause/Section] and subject to [Exclusion/Waiting Period Clause/Section] because [Detailed reason/Detailed Explanation].
-- If the query is **general**, respond accurately using the provided policy excerpt, giving the most relevant and clear answer possible in **1-2 sentences** [Detailed reason/Detailed Explanation].
-
 
 User question: {query}
 Policy excerpt: {context}
@@ -180,12 +178,12 @@ def build_rag_chain(pdf_path: str, rebuild_index=False):
 
     # ✅ Create retrievers
     bm25_retriever = BM25Retriever.from_documents(final_chunks)
-    bm25_retriever.k = 4
+    bm25_retriever.k = 5
 
     retriever = EnsembleRetriever(
         retrievers=[
             bm25_retriever,
-            vectorstore.as_retriever(search_type="mmr", search_kwargs={"k": 10 , "lambda_mult": 0.5})
+            vectorstore.as_retriever(search_type="mmr", search_kwargs={"k": 12 , "lambda_mult": 0.5})
         ],
         weights=[0.4, 0.6]
     )