Update app.py

app.py

@@ -73,7 +73,7 @@ def create_retriever_from_chroma(vectorstore_path="./docs/chroma/", search_type=
         )
         st.write("VectorStore is created")
     
-    retriever=vectorstore.as_retriever(search_type = search_type, search_kwargs={"k": k, "lambda_mult": lambda_mult})
+    retriever=vectorstore.as_retriever(search_type = search_type, search_kwargs={"k": k})
 
     
 
@@ -102,9 +102,11 @@ def main():
         {"role": "assistant", "content": "Hi, I'm a chatbot who is  based on respublic of Lithuania law documents. How can I help you?"}
     ]
 
-    st.markdown("Hi, I am Qwen, chat mmodel, based on respublic of Lithuania law document. Write you question and press enter to start chat.")
+    st.markdown("Hi, I am Birute, chat assistant, based on republic of Lithuania law documents. You can choose below information retrieval type and how many documents you want to be retrieved.")
+    search_type = st.radio("Choose search type. Options are [Max marginal relevance search(mmr) , Similarity search (similarity). Default value (mmr)]", options=["mmr", "similarity"], value="mmr")
+    k = st.select_slider("Select amount of documents to be retrieved. Default value(5) : ", options=[2, 15], value=5)
+    retriever = create_retriever_from_chroma(vectorstore_path="docs/chroma/", search_type=search_type, k=k, chunk_size=450, chunk_overlap=20)
     
-    retriever = create_retriever_from_chroma(vectorstore_path="docs/chroma/", search_type='similarity', k=9, chunk_size=450, chunk_overlap=20)
     if user_question := st.text_input("Ask a question about your documents:"):
         handle_userinput(user_question,retriever)