Update 1-rag.md

Typo

Author: madeline-underwood

content/learning-paths/servers-and-cloud-computing/copilot-extension/1-rag.md

@@ -28,6 +28,6 @@ While RAG systems improve AI-generated content, they also introduce several chal
 * Context Length Limitations: all models, including the GitHub Copilot API, have limitations on the amount of information they can process at once, requiring careful selection and ranking of retrieved data.
 * Handling Conflicting Information: if your knowledge base has contradictory information, the system may struggle to reconcile them and generate a coherent response.
 * Scalability and Latency: querying large knowledge bases and integrating retrieval with generation can increase response time. This is another place where the choice of similarity search algorithm has an impact.
-* Data Freshness and Maintenance: The knowledge base must be regularly updated to ensure the system remains accurate and relevant.
+* Data Freshness and Maintenance: the knowledge base must be regularly updated to ensure the system remains accurate and relevant.
 
 For an example of a production RAG GitHub Copilot Extension, you can check out [Arm for GitHub Copilot](https://github.com/marketplace/arm-for-github-copilot) in the GitHub Marketplace.