Update app.py

app.py

@@ -50,7 +50,8 @@ def invoke(openai_api_key, youtube_url, process_video, prompt):
 description = """<strong>Overview:</strong> The app demonstrates how to use a Large Language Model (LLM) with Retrieval Augmented Generation (RAG) on external data 
                  (YouTube videos in this case, but it could be PDFs, URLs, or other structured/unstructured private/public 
                  <a href='https://raw.githubusercontent.com/bstraehle/ai-ml-dl/c38b224c196fc984aab6b6cc6bdc666f8f4fbcff/langchain/document-loaders.png'>data sources</a>).\n\n
-                 <strong>Instructions:</strong> Enter an OpenAI API key and perform LLM use cases on the YouTube video (semantic search, sentiment analysis, summarization, translation, etc.)
+                 <strong>Instructions:</strong> Enter an OpenAI API key and perform LLM use cases on a YouTube video (semantic search, sentiment analysis, summarization, translation, etc.) 
+                 The example is a short video about <a href='https://www.youtube.com/watch?v=--khbXchTeE'>GPT-4</a>.
                  <ul style="list-style-type:square;">
                  <li>Set "Process Video" to "False" and submit prompt "what is gpt-4". The LLM <strong>without</strong> RAG does not know the answer.</li>
                  <li>Set "Process Video" to "True" and submit prompt "what is gpt-4". The LLM <strong>with</strong> RAG knows the answer.</li>