Update app.py

app.py

@@ -51,13 +51,14 @@ description = """<strong>Overview:</strong> The app demonstrates how to use a La
                  (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 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>.
+                 The example is a short video about GPT-4.
                  <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>
                  <li>Set "Process Video" to "False" and experiment with different prompts, for example "what is gpt-4, answer in german" or "write a haiku about gpt-4".</li>
                  </ul>
-                 In a production system processing external data would be done in a batch process, while prompting is done in a user interaction.\n\n
+                 In a production system processing external data would be done in a batch process, while prompting is done in a user interaction. 
+                 An idea for a production system would be to perform LLM use cases on the <a href='https://www.youtube.com/playlist?list=PL2yQDdvlhXf_hIzmfHCdbcXj2hS52oP9r'>AWS re:Invent</a> playlist.\n\n
                  <strong>Technology:</strong> <a href='https://www.gradio.app/'>Gradio</a> UI using <a href='https://platform.openai.com/'>OpenAI</a> API 
                  via AI-first <a href='https://www.langchain.com/'>LangChain</a> toolkit with <a href='https://openai.com/research/whisper'>Whisper</a> (speech-to-text) 
                  and <a href='https://openai.com/research/gpt-4'>GPT-4</a> (LLM) foundation models as well as AI-native