max marginal retreval

app.py

@@ -230,6 +230,7 @@ def handle_userinput(query):
     except Exception as e:
         # logger.error(f"Answer retrieval failed with {e}")
         st.error(f"Error Occured! see log info for more details.")#, icon=":books:")
+        print(f"> Error Occured! {e}.")#, icon=":books:")
         return
 
 

qaPipeline.py

@@ -216,7 +216,7 @@ class QAPipeline:
                 """
                 You are the AI of company boardpac which provide services to company board members.
                 please answer the question based on the chat history and context information provided below related to central bank acts published in various years.
-                The published year may indicated in the source of metadata of each source document annd in the content itself. 
+                The published year may indicated in the source of metadata of each source document. 
 
                 The content of a bank act of a past year can updated by a bank act from a latest year.
                 Always try to answer with latest information and mention the year which information extracted if possible.
@@ -236,8 +236,14 @@ class QAPipeline:
             bank_regulations_qa = ConversationalRetrievalChain.from_llm(
                 llm=self.llm,
                 chain_type="stuff",
-                retriever = self.vectorstore.as_retriever(), 
-                # retriever = self.vectorstore.as_retriever(search_kwargs={"k": target_source_chunks}
+                # retriever = self.vectorstore.as_retriever(), 
+                retriever = self.vectorstore.as_retriever(
+                    search_type="mmr",
+                    search_kwargs={
+                        'k': 4, 
+                        # 'lambda_mult': 0.1, 
+                        'fetch_k': 40}
+                ),
                 return_source_documents= True,
                 get_chat_history=lambda h : h,
                 combine_docs_chain_kwargs={"prompt": retrieval_qa_chain_prompt},