app changes

app.py

@@ -27,10 +27,16 @@ for file in files:
 # Config
 with st.sidebar:
     st.write(f"Injected documents: \n\n {"\n".join("\n"+file for file in files)}")
-    chunk_size = st.number_input("Chunk size", value=500, step=100, placeholder=500) # Defines the chunks in amount of tokens in which the files are split. Also defines the amount of tokens that are feeded into the context. 
-    chunk_overlap = st.number_input("Chunk overlap", value=100, step=10, placeholder=100)
-    temperature = st.number_input("Temperature", value=0.0, min_value=0.0, step=0.2, max_value=1.0, placeholder=0.0)
     model = st.selectbox("Model name", ["gpt-3.5-turbo"])
+    temperature = st.number_input("Temperature", value=0.0, min_value=0.0, step=0.2, max_value=1.0, placeholder=0.0)
+    if st.toggle("Splitting"):
+        chunk_size = st.number_input("Chunk size", value=500, step=250, placeholder=500) # Defines the chunks in amount of tokens in which the files are split. Also defines the amount of tokens that are feeded into the context. 
+        chunk_overlap = st.number_input("Chunk overlap", value=100, step=10, placeholder=100)
+        text_splitter = RecursiveCharacterTextSplitter(chunk_size=chunk_size, chunk_overlap=chunk_overlap)
+        splits = text_splitter.split_documents(docs)
+        vectorstore = Chroma.from_documents(documents=splits, embedding=OpenAIEmbeddings())
+    else:
+        vectorstore = Chroma.from_documents(documents=docs, embedding=OpenAIEmbeddings())
 
 
 prompt_template ="""
@@ -38,19 +44,14 @@ You are called "Volker". You are an assistant for question-answering tasks.
 You only answer questions about Long-Covid (use Post-Covid synonymously) and the Volker-App. 
 If you don't know the answer, just say that you don't know. Say why you don't know the answer. 
 Never answer questions about other diseases (e.g. Cancer-related fatigue, Multiple Sklerose).
-Stay emphatic and positive.
+Always answer in german language. Stay emphatic and positive.
 When you use the word e.g "Arzt", "Ärzt", always write it as "Arzt".
 Only use the following pieces of retrieved context to answer the question.
-Keep your answers concise, use maximum of three sentences. 
 Question: {question} 
 Context: {context} 
 Answer:
 """ # Source: hub.pull("rlm/rag-prompt")
 
-text_splitter = RecursiveCharacterTextSplitter(chunk_size=chunk_size, chunk_overlap=chunk_overlap)
-splits = text_splitter.split_documents(docs)
-vectorstore = Chroma.from_documents(documents=splits, embedding=OpenAIEmbeddings())
-
 # (1) Retriever
 retriever = vectorstore.as_retriever()
 
@@ -84,9 +85,11 @@ def click_button(prompt):
 c = st.container()
 c.write("Beispielfragen")
 col1, col2, col3 = c.columns(3)
-col1.button("Was ist 'Lernen'?", on_click=click_button, args=["Erläutere die Säule 'Lernen' der Volker-App."])
-col2.button("Was ist 'Tracken'?", on_click=click_button, args=["Erläutere die Säule 'Tracken' der Volker-App."])
-col3.button("Was ist 'Handeln'?", on_click=click_button, args=["Erläutere die Säule 'Handeln' der Volker-App."])
+col1.button("Mehr zu 'Lernen'", on_click=click_button, args=["Was macht die Säule 'Lernen' aus?"])
+col1.button("Wie funktioniert die App?", on_click=click_button, args=["Wie funktioniert die Volker-App?"])
+col2.button("Mehr zu 'Tracken'", on_click=click_button, args=["Was macht die Säule 'Tracken' aus?"])
+col2.button("Welche Krankenkassen erstatten die App?", on_click=click_button, args=["Welche Krankenkassen erstatten die App?"])
+col3.button("Mehr zu 'Handeln'", on_click=click_button, args=["Was macht die Säule 'Handeln' aus?"])
 
 if 'clicked' not in st.session_state:
     st.session_state.clicked = False