udpate text (#6)

rag_semantic_chunking/experiment_rag_semantic_chunking.ipynb

@@ -6,8 +6,6 @@
    "source": [
     "# L&L Blog Series - RAG Semantic Chunking Experiment\n",
     "\n",
-    "Did the lunch & learn blog series bring you here? If not, you should definitely check it out [here]().\n",
-    "\n",
     "In this experiment, we'll compare the simplest chunking method, fixed-size chunking, with the improvements offered by semantic chunking.\n",
     "\n",
     "The goal of semantic chunking is to create meaningful and context-aware chunks.\n",
@@ -309,7 +307,9 @@
     "\n",
     "This step is crucial because it transforms our text data into a format that allows us to measure how similar or different the sentences are from one another.\n",
     "\n",
-    "We will use Cohere's embedding API for to generate our embeddings."
+    "We will use Cohere's embedding API for to generate our embeddings which you can get an API key [here](https://dashboard.cohere.com/api-keys).\n",
+    "\n",
+    "> NOTE: It will prompt you for an API key when you run the below block of code."
    ]
   },
   {