Update app.py

app.py

@@ -43,11 +43,13 @@ def invoke(openai_api_key, youtube_url, process_video, prompt):
     result = qa_chain({"query": prompt})
     return result["result"]
 
-description = """The app demonstrates how to use a <strong>Large Language Model</strong> (LLM) with <strong>Retrieval Augmented Generation</strong> (RAG) on external data.\n\n
-                 Usage: Enter an OpenAI API key, YouTube URL (external data), and prompt to perform semantic search, sentiment analysis, summarization, translation, etc. 
-                 "Process Video" specifies whether or not to perform speech to text processing. To ask multiple question related to the same video, typically set it to "True" 
-                 the first time, and then set it to "False". Note that persistence is not guaranteed in the Hugging Face free tier (I plan to migrate to AWS S3).\n\n
-                 Implementation: <a href='https://www.gradio.app/'>Gradio</a> UI using <a href='https://platform.openai.com/'>OpenAI</a> API 
+description = """<strong>Overview:</strong> The app demonstrates how to use a <strong>Large Language Model</strong> (LLM) with <strong>Retrieval Augmented Generation</strong> (RAG) 
+                 on external data.\n\n
+                 <strong>Usage:</strong> Enter an OpenAI API key, YouTube URL (external data), and prompt to perform semantic search, sentiment analysis, summarization, 
+                 translation, etc. "Process Video" specifies whether or not to perform speech-to-text processing. To ask multiple questions related to the same video, 
+                 typically set it to "True" the first time, and then set it to "False". Note that persistence is not guaranteed in the Hugging Face free tier 
+                 (the plan is to migrate to AWS S3).\n\n
+                 <strong>Implementation:</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 use cases) foundation models as well as AI-native 
                  <a href='https://www.trychroma.com/'>Chroma</a> embedding database."""