fix(docs): update RAG tutorials link to point to correct path (#32169)

## **Description:** 
This PR updates the internal documentation link for the RAG tutorials to
reflect the updated path. Previously, the link pointed to the root
`/docs/tutorials/`, which was generic. It now correctly routes to the
RAG-specific tutorial page for the following text-embedding models.

1. DatabricksEmbeddings
2. IBM watsonx.ai
3. OpenAIEmbeddings
4. NomicEmbeddings
5. CohereEmbeddings
6. MistralAIEmbeddings
7. FireworksEmbeddings
8. TogetherEmbeddings
9. LindormAIEmbeddings
10. ModelScopeEmbeddings
11. ClovaXEmbeddings
12. NetmindEmbeddings
13. SambaNovaCloudEmbeddings
14. SambaStudioEmbeddings
15. ZhipuAIEmbeddings

## **Issue:** N/A
## **Dependencies:** None
## **Twitter handle:** N/A

Author: bansalkanav

docs/docs/integrations/text_embedding/cohere.ipynb

@@ -125,7 +125,7 @@
    "source": [
     "## Indexing and Retrieval\n",
     "\n",
-    "Embedding models are often used in retrieval-augmented generation (RAG) flows, both as part of indexing data as well as later retrieving it. For more detailed instructions, please see our [RAG tutorials](/docs/tutorials/).\n",
+    "Embedding models are often used in retrieval-augmented generation (RAG) flows, both as part of indexing data as well as later retrieving it. For more detailed instructions, please see our [RAG tutorials](/docs/tutorials/rag).\n",
     "\n",
     "Below, see how to index and retrieve data using the `embeddings` object we initialized above. In this example, we will index and retrieve a sample document in the `InMemoryVectorStore`."
    ]
@@ -264,7 +264,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.5"
+   "version": "3.9.6"
   }
  },
  "nbformat": 4,