Merge pull request #1475 from zc277584121/master

fix dynamiq url

bootcamp/tutorials/integration/milvus_rag_with_dynamiq.ipynb

@@ -22,9 +22,9 @@
     "\n",
     "\n",
     "\n",
-    "[Dynamiq](https://dynamiq.ai/) is a powerful Gen AI framework that streamlines the development of AI-powered applications. With robust support for retrieval-augmented generation (RAG) and large language model (LLM) agents, Dynamiq empowers developers to create intelligent, dynamic systems with ease and efficiency.\n",
+    "[Dynamiq](https://www.getdynamiq.ai/) is a powerful Gen AI framework that streamlines the development of AI-powered applications. With robust support for retrieval-augmented generation (RAG) and large language model (LLM) agents, Dynamiq empowers developers to create intelligent, dynamic systems with ease and efficiency.\n",
     "\n",
-    "In this tutorial, we’ll explore how to seamlessly use Dynamiq with [Milvus](https://milvus.io/), a high-performance, open-source vector database purpose-built for RAG workflows. Milvus excels at efficient storage, indexing, and retrieval of vector embeddings, making it an indispensable component for AI systems that demand fast and precise contextual data access.\n",
+    "In this tutorial, we’ll explore how to seamlessly use Dynamiq with [Milvus](https://milvus.io/), the high-performance vector database purpose-built for RAG workflows. Milvus excels at efficient storage, indexing, and retrieval of vector embeddings, making it an indispensable component for AI systems that demand fast and precise contextual data access.\n",
     "\n",
     "This step-by-step guide will cover two core RAG workflows:\n",
     "\n",
@@ -732,4 +732,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 5
-}
+}