Updated code

app.py

@@ -55,7 +55,7 @@ if "vector_db" not in st.session_state:
 #     st.session_state["text_chunks"] = load_text_chunks(text_chunks_pkl_dir=all_docs_pkl_directory)
 
 if "retriever" not in st.session_state:
-    st.session_state["retriever"] = load_retriver(embeddings=st.session_state["embeddings"], chroma_vectorstore=st.session_state["vector_db"] )
+    st.session_state["retriever"] = load_retriver(chroma_vectorstore=st.session_state["vector_db"])
 
 if "conversation_chain" not in st.session_state:
     st.session_state["conversation_chain"] = load_conversational_retrievel_chain(retriever=st.session_state["retriever"], llm=st.session_state["llm"])    

utils.py

@@ -269,10 +269,10 @@ def load_text_chunks(text_chunks_pkl_dir):
             pickle.dump(all_texts, file)
         print("Text chunks are created and cached")
         
-def load_retriver(text_chunks, embeddings, chroma_vectorstore):
+def load_retriver(chroma_vectorstore):
     """Load cohere rerank method for retrieval"""
-    bm25_retriever = BM25Retriever.from_documents(text_chunks)
-    bm25_retriever.k = 2
+    # bm25_retriever = BM25Retriever.from_documents(text_chunks)
+    # bm25_retriever.k = 2
     chroma_retriever = chroma_vectorstore.as_retriever(search_kwargs={"k": 3})  
     # ensemble_retriever = EnsembleRetriever(retrievers=[bm25_retriever, chroma_retriever], weights=[0.3, 0.7])
     logging.basicConfig()