Update app.py

app.py

@@ -155,6 +155,9 @@ qa_prompt = ChatPromptTemplate.from_messages(messages)
 # Define the temperature value in a variable
 ai_temp = 0.1
 
+# Define the K Value
+k_value = 14
+
 
 chat_history = []
 user_query = ""
@@ -271,6 +274,11 @@ def chat_page():
     st.sidebar.header("Select AI Temperature:")
     ai_temp = st.sidebar.slider(label="Temperature", min_value=0.0, max_value=1.0, value=0.0, step=0.1)
 
+
+    # Streamlit slider for selecting the value of k
+    st.sidebar.header("Select a K Value for Retrieval:")
+    k_value = st.slider('K Value', min_value=0, max_value=16, value=14)
+
  
 
 
@@ -350,7 +358,7 @@ def chat_page():
 
     pdf_qa = ConversationalRetrievalChain.from_llm(
         ChatOpenAI(temperature=ai_temp, model_name=selected_model),
-        retriever=vectordb.as_retriever(search_kwargs={'k': 14}),
+        retriever=vectordb.as_retriever(search_kwargs={'k': k_value}),
         chain_type='stuff',
         return_source_documents=True, 
         verbose=False, 
@@ -582,7 +590,7 @@ def chat_page():
     date_string_clean = date_string_clean[:max_length]
 
     # Append the cleaned data to the worksheet
-    data_to_append = [message_clean, answer_clean, date_string, str(ai_temp), st.session_state['session_id'], st.session_state['selected_model']]
+    data_to_append = [message_clean, answer_clean, date_string, str(ai_temp), st.session_state['session_id'], st.session_state['selected_model'], str(k_value)]