Update app.py

app.py

@@ -25,7 +25,7 @@ QA_CHAIN_PROMPT = PromptTemplate(input_variables = ["context", "question"], temp
 CHROMA_DIR  = "docs/chroma"
 YOUTUBE_DIR = "docs/youtube"
 
-YOUTUBE_URL = " playlist"
+YOUTUBE_URL = "https://www.youtube.com/watch?v=--khbXchTeE"
 
 MODEL_NAME  = "gpt-4"
 
@@ -52,7 +52,7 @@ description = """<strong>Overview:</strong> The app demonstrates how to use a La
                  (in this case YouTube videos, 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 <a href='c'>short video about GPT-4</a>.
+                 translation, etc.) The example is a <a href='https://www.youtube.com/watch?v=--khbXchTeE'>short video about 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>