Added a rag template for Kendra (#12470)

## Description
Adds a rag template for Amazon Kendra with Bedrock.

---------

Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>

templates/rag-aws-kendra/rag_aws_kendra/chain.py

@@ -0,0 +1,49 @@
+import os
+
+from langchain.llms.bedrock import Bedrock
+from langchain.prompts import ChatPromptTemplate
+from langchain.retrievers import AmazonKendraRetriever
+from langchain.schema.output_parser import StrOutputParser
+from langchain.schema.runnable import RunnableParallel, RunnablePassthrough
+
+# Get region and profile from env
+region = os.environ.get("AWS_DEFAULT_REGION", "us-east-1")
+profile = os.environ.get("AWS_PROFILE", "default")
+kendra_index = os.environ.get("KENDRA_INDEX_ID", None)
+
+if not kendra_index:
+    raise ValueError(
+        "No value provided in env variable 'KENDRA_INDEX_ID'. "
+        "A Kendra index is required to run this application."
+    )
+
+# Set LLM and embeddings
+model = Bedrock(
+    model_id="anthropic.claude-v2",
+    region_name=region,
+    credentials_profile_name=profile,
+    model_kwargs={'max_tokens_to_sample': 200}
+)
+
+# Create Kendra retriever
+retriever = AmazonKendraRetriever(
+    index_id=kendra_index, 
+    top_k=5, 
+    region_name=region
+)
+
+# RAG prompt
+template = """Answer the question based only on the following context:
+{context}
+Question: {question}
+"""
+prompt = ChatPromptTemplate.from_template(template)
+
+
+# RAG
+chain = (
+    RunnableParallel({"context": retriever, "question": RunnablePassthrough()})
+    | prompt
+    | model
+    | StrOutputParser()
+)