Update app.py

app.py

@@ -134,10 +134,10 @@ def invoke(openai_api_key, rag_option, prompt):
         raise gr.Error(e)
     return result
 
-description = """<strong>Overview:</strong> Reasoning application that demonstrates a <strong>Large Language Model (LLM)</strong> with 
-                 <strong>Retrieval Augmented Generation (RAG)</strong> on <strong>external data</strong>.\n\n
+description = """<strong>Overview:</strong> Reasoning application that demonstrates a <strong>large language model (LLM)</strong> with 
+                 <strong>retrieval augmented generation (RAG)</strong> on <strong>external data</strong>.\n\n
                  <strong>Instructions:</strong> Enter an OpenAI API key and perform text generation use cases on <a href='""" + YOUTUBE_URL_1 + """'>YouTube</a>, 
-                 <a href='""" + PDF_URL + """'>PDF</a>, and <a href='""" + WEB_URL + """'>Web</a> data published after LLM knowledge cutoff (example: GPT-4 data).
+                 <a href='""" + PDF_URL + """'>PDF</a>, and <a href='""" + WEB_URL + """'>web</a> data published after LLM knowledge cutoff (example: GPT-4 data).
                  <ul style="list-style-type:square;">
                  <li>Set "Retrieval Augmented Generation" to "<strong>Off</strong>" and submit prompt "What is GPT-4?" The <strong>LLM without RAG</strong> does not know the answer.</li>
                  <li>Set "Retrieval Augmented Generation" to "<strong>Chroma</strong>" or "<strong>MongoDB</strong>" and experiment with prompts. The <strong>LLM with RAG</strong> knows the answer:</li>