Update app.py

app.py

@@ -88,18 +88,18 @@ st.sidebar.caption(f"Session ID: {genuuid()}")
 
 
 # Main chat interface
-st.markdown("""## Query Translation in RAG Architecture
+st.markdown("""#### Query Translation in RAG Architecture
 
 Query translation in a Retrieval-Augmented Generation (RAG) architecture is the process where an LLM acts as a translator between the user's natural language input and the retrieval system. 
 
-### Key Functions of Query Translation:
+##### Key Functions of Query Translation:
 1. **Adds Context**  
    The LLM enriches the user's input with relevant context (e.g., expanding vague questions or specifying details) to make it more precise.
    
 2. **Converts to Concise Query**  
    The LLM reformulates the input into a succinct and effective query optimized for the retrieval system's semantic search capabilities.
 
-### Purpose
+##### Purpose
 This ensures that the retrieval system receives a clear and focused query, increasing the relevance of the information it retrieves. The query translator acts as a bridge between human conversational language and the technical requirements of a semantic retrieval system.""")
 # User ID Input
 user_id = st.text_input("Experiment ID:", key="user_id")