Update readme

README.md

@@ -5,21 +5,3 @@ NOTE: This repository is a work-in-progress. Currently, the AWS integrations are
 This repository contains 1 package with AWS integrations with LangChain:
 
 - [langchain-aws](https://pypi.org/project/langchain-aws/) integrates [AWS](https://aws.amazon.com).
-
-## Initial Repo Checklist (Remove this section after completing)
-
-This setup assumes that the partner package is already split. For those instructions,
-see [these docs](https://python.langchain.com/docs/contributing/integrations#partner-packages).
-
-- [ ] Copy package into /libs folder
-- [ ] Update these fields in /libs/*/pyproject.toml
-
-    - `tool.poetry.repository`
-    - `tool.poetry.urls["Source Code"]`
-
-- [ ] Add integration testing secrets in Github (ask Erick for help)
-- [ ] Add secrets as env vars in .github/workflows/_release.yml
-- [ ] Configure `LIB_DIRS` in .github/scripts/check_diff.py
-- [ ] Add partner collaborators in Github (ask Erick for help)
-- [ ] Add new repo to test-pypi and pypi trusted publishing (ask Erick for help)
-- [ ] Populate .github/workflows/_release.yml with `on.workflow_dispatch.inputs.working-directory.default`

libs/aws/README.md

@@ -1,16 +1,13 @@
 # langchain-aws
 
-This package contains the LangChain integration with Bedrock
+This package contains the LangChain integrations with AWS.
 
 ## Installation
 
 ```bash
 pip install -U langchain-aws
 ```
-
-And you should configure credentials by setting the following environment variables:
-
-* TODO: fill this out
+All integrations in this package assume that you have the credentials setup to connect with AWS services.
 
 ## Chat Models
 
@@ -43,3 +40,29 @@ from langchain_aws import BedrockLLM
 llm = BedrockLLM()
 llm.invoke("The meaning of life is")
 ```
+
+## Retrievers
+`AmazonKendraRetriever` class provides a retriever to connect with Amazon Kendra.
+
+```python
+from langchain_aws import AmazonKendraRetriever
+
+retriever = AmazonKendraRetriever(
+    index_id="561be2b6d-9804c7e7-f6a0fbb8-5ccd350"
+)
+
+retriever.get_relevant_documents(query="What is the meaning of life?")
+```
+
+`AmazonKnowlegeBasesRetriever` class provides a retriever to connect with Amazon Knowlege Bases.
+
+```python
+from langchain_aws import AmazonKnowledgeBasesRetriever
+
+retriever = AmazonKnowledgeBasesRetriever(
+    knowledge_base_id="IAPJ4QPUEU",
+    retrieval_config={"vectorSearchConfiguration": {"numberOfResults": 4}},
+)
+
+retriever.get_relevant_documents(query="What is the meaning of life?")
+```