experimental[minor]: Amazon Personalize support (#17436)

## Amazon Personalize support on Langchain

This PR is a successor to this PR -
https://github.com/langchain-ai/langchain/pull/13216

This PR introduces an integration with [Amazon
Personalize](https://aws.amazon.com/personalize/) to help you to
retrieve recommendations and use them in your natural language
applications. This integration provides two new components:

1. An `AmazonPersonalize` client, that provides a wrapper around the
Amazon Personalize API.
2. An `AmazonPersonalizeChain`, that provides a chain to pull in
recommendations using the client, and then generating the response in
natural language.

We have added this to langchain_experimental since there was feedback
from the previous PR about having this support in experimental rather
than the core or community extensions.

Here is some sample code to explain the usage.

```python

from langchain_experimental.recommenders import AmazonPersonalize
from langchain_experimental.recommenders import AmazonPersonalizeChain
from langchain.llms.bedrock import Bedrock

recommender_arn = "<insert_arn>"

client=AmazonPersonalize(
    credentials_profile_name="default",
    region_name="us-west-2",
    recommender_arn=recommender_arn
)
bedrock_llm = Bedrock(
    model_id="anthropic.claude-v2", 
    region_name="us-west-2"
)

chain = AmazonPersonalizeChain.from_llm(
    llm=bedrock_llm, 
    client=client
)
response = chain({'user_id': '1'})
```


Reviewer: @3coins

libs/experimental/langchain_experimental/recommenders/__init__.py

@@ -0,0 +1,7 @@
+"""Amazon Personalize primitives."""
+from langchain_experimental.recommenders.amazon_personalize import AmazonPersonalize
+from langchain_experimental.recommenders.amazon_personalize_chain import (
+    AmazonPersonalizeChain,
+)
+
+__all__ = ["AmazonPersonalize", "AmazonPersonalizeChain"]