Add visuals to the tutorial

qdrant-landing/content/documentation/tutorials/faq-oci-cohere-langchain.md

@@ -27,7 +27,7 @@ Our application will consist of two main processes: indexing and searching. Lang
 as we will use a few components, including Cohere and Qdrant, as well as some OCI services. Here is a high-level
 overview of the architecture:
 
-TODO: add a diagram of the architecture
+![Architecture diagram of the target system](/documentation/tutorials/faq-oci-cohere-langchain/architecture-diagram.png)
 
 ### Prerequisites
 
@@ -120,9 +120,13 @@ models to convert the text into vectors, and then store them in Qdrant. Langchai
 Service, so we can easily access the models. 
 
 Our dataset will be fairly simple, as it will consist of the questions and answers from the [Oracle Cloud Free Tier
-FAQ page](https://www.oracle.com/cloud/free/faq/). Questions and answers are presented in an HTML format, but we don't
-want to manually extract the text and adapt it for each subpage. Instead, we will use the `WebBaseLoader` that just 
-loads the HTML content from given URL and converts it to text. 
+FAQ page](https://www.oracle.com/cloud/free/faq/). 
+
+![Some examples of the Oracle Cloud FAQ](/documentation/tutorials/faq-oci-cohere-langchain/oracle-faq.png)
+
+Questions and answers are presented in an HTML format, but we don't want to manually extract the text and adapt it for 
+each subpage. Instead, we will use the `WebBaseLoader` that just loads the HTML content from given URL and converts it 
+to text. 
 
 ```python
 from langchain_community.document_loaders.web_base import WebBaseLoader