DOCS: update rag use case images (#13615)

docs/docs/use_cases/question_answering/index.ipynb

@@ -57,11 +57,14 @@
     "1. **Load**: First we need to load our data. We'll use [DocumentLoaders](/docs/modules/data_connection/document_loaders/) for this.\n",
     "2. **Split**: [Text splitters](/docs/modules/data_connection/document_transformers/) break large `Documents` into smaller chunks. This is useful both for indexing data and for passing it in to a model, since large chunks are harder to search over and won't in a model's finite context window.\n",
     "3. **Store**: We need somewhere to store and index our splits, so that they can later be searched over. This is often done using a [VectorStore](/docs/modules/data_connection/vectorstores/) and [Embeddings](/docs/modules/data_connection/text_embedding/) model.\n",
+    "\n",
+    "![index_diagram](/img/rag_indexing.png)\n",
+    "\n",
     "#### Retrieval and generation\n",
     "4. **Retrieve**: Given a user input, relevant splits are retrieved from storage using a [Retriever](/docs/modules/data_connection/retrievers/).\n",
     "5. **Generate**: A [ChatModel](/docs/modules/model_io/chat_models) / [LLM](/docs/modules/model_io/llms/) produces an answer using a prompt that includes the question and the retrieved data\n",
     "\n",
-    "![flow.jpeg](/img/qa_flow.jpeg)"
+    "![retrieval_diagram](/img/rag_retrieval_generation.png)"
    ]
   },
   {