Update app.py

app.py

@@ -165,10 +165,8 @@ recommender = SemanticSearch()
 
 title = 'PDF GPT'
 description = """ What is PDF GPT ?
-1. PDF GPT allows you to chat with a PDF file using GPT functionalities. 
-2. The application intelligently breaks the document into smaller chunks and employs a powerful Deep Averaging Network Encoder to generate embeddings. 
-3. PDF GPT utilizes Open AI as its data layer to generate a summary for each chunk.
-4. PDF GPT uses a KNN algorithm to return the top-n embedding from each chunk and uses custom logic to generate a response. The application also leverages important document sections to generate precise responses, and can even provide the page number where the information is located, adding credibility to the responses and helping to locate pertinent information quickly."""
+1. The problem is that Open AI has a 4K token limit and cannot take an entire PDF file as input. Additionally, it sometimes returns irrelevant responses due to poor embeddings. ChatGPT cannot directly talk to external data. The solution is PDF GPT, which allows you to chat with an uploaded PDF file using GPT functionalities. The application breaks the document into smaller chunks and generates embeddings using a powerful Deep Averaging Network Encoder. A semantic search is performed on your query, and the top relevant chunks are used to generate a response.
+2. The returned response can even cite the page number in square brackets([]) where the information is located, adding credibility to the responses and helping to locate pertinent information quickly. The Responses are much better than the naive responses by Open AI."""
 
 with gr.Blocks() as demo: