Update Docs (#3520)

docs/examples/aws_example.mdx

@@ -36,7 +36,7 @@ This sets up Mem0 with:
 - [AWS Bedrock for LLM](https://docs.mem0.ai/components/llms/models/aws_bedrock)
 - [AWS Bedrock for embeddings](https://docs.mem0.ai/components/embedders/models/aws_bedrock#aws-bedrock)
 - [OpenSearch as the vector store](https://docs.mem0.ai/components/vectordbs/dbs/opensearch)
-- [Neptune Analytics as your graph store](https://docs.mem0.ai/open-source/graph_memory/overview#initialize-neptune-analytics).
+- [Neptune Analytics as your graph store](https://docs.mem0.ai/open-source/graph_memory/overview#initialize-neptune-analytics)
 
 ```python
 import boto3
@@ -93,12 +93,12 @@ m = Memory.from_config(config)
 
 Reference [Notebook example](https://github.com/mem0ai/mem0/blob/main/examples/graph-db-demo/neptune-example.ipynb)
 
-#### Add a memory:
+### Add a memory
 
 ```python
 messages = [
     {"role": "user", "content": "I'm planning to watch a movie tonight. Any recommendations?"},
-    {"role": "assistant", "content": "How about a thriller movies? They can be quite engaging."},
+    {"role": "assistant", "content": "How about thriller movies? They can be quite engaging."},
     {"role": "user", "content": "I'm not a big fan of thriller movies but I love sci-fi movies."},
     {"role": "assistant", "content": "Got it! I'll avoid thriller recommendations and suggest sci-fi movies in the future."}
 ]
@@ -107,24 +107,24 @@ messages = [
 result = m.add(messages, user_id="alice", metadata={"category": "movie_recommendations"})
 ```
 
-#### Search a memory:
+### Search a memory
+
 ```python
 relevant_memories = m.search(query, user_id="alice")
 ```
 
-#### Get all memories:
+### Get all memories
+
 ```python
 all_memories = m.get_all(user_id="alice")
 ```
 
-#### Get a specific memory:
+### Get a specific memory
+
 ```python
 memory = m.get(memory_id)
 ```
 
-
----
-
 ## Conclusion
 
 With Mem0 and AWS services like Bedrock, OpenSearch, and Neptune Analytics, you can build intelligent AI companions that remember, adapt, and personalize their responses over time. This makes them ideal for long-term assistants, tutors, or support bots with persistent memory and natural conversation abilities.