Update app.py

app.py

@@ -82,7 +82,7 @@ if __name__ == "__main__":
     description = """
     <img src="https://superagi.com/wp-content/uploads/2023/10/Introduction-to-RAGA-Retrieval-Augmented-Generation-and-Actions-1200x600.png.webp" width=100%>
     <br>
-    Demo using Vector store-backed retriever. This space demonstrate application of RAG on a small model and its effectiveness, I used small model because of the space constraint. The current space runs on mere <b>2v CPU and 16GB of RAM</b>, hence there is some delay in generating output. Test this to your hearts content and let me know your thoughts, I will keep updating this space with tiny improvements on architecture and design
+    Demo using Vector store-backed retriever. This space demonstrate application of RAG on a small model and its effectiveness, I used small model because of the space constraint. The current space runs on meer <b>2v CPU and 16GB of RAM</b>, hence there is some delay in generating output. Test this to your hearts content and let me know your thoughts, I will keep updating this space with tiny improvements on architecture and design
     <ul>
         <li>model: TinyLlama/TinyLlama-1.1B-Chat-v1.0</li>
         <li>update1: This space now does not create a faiss index on build, it uses a locally saved faiss index</li>
@@ -96,8 +96,8 @@ if __name__ == "__main__":
         <li>What are forms of memory implementation in langchain</li>
         <li>What is question answering from documents</li>
     </ul>
-    Go through this paper here to find more about langchain and then test how this solution performs. <a href='https://www.researchgate.net/publication/372669736_Creating_Large_Language_Model_Applications_Utilizing_LangChain_A_Primer_on_Developing_LLM_Apps_Fast' target='_blank'>This paper is the data source for this solution</a>
-    Have you already used RAG? feel free to suggest improvements
+    Go through this paper here to find more about langchain and then test how this solution performs. <a href='https://www.researchgate.net/publication/372669736_Creating_Large_Language_Model_Applications_Utilizing_LangChain_A_Primer_on_Developing_LLM_Apps_Fast' target='_blank'> This paper is the data source for this solution.</a>
+    Have you already used RAG? feel free to suggest improvements.
     Feel excited about the implementation? You know where to find me!
     I would love to connect and have a chat.
     </p>"""