Update READMEs with template.

Author: rlhagerm

python/example_code/bedrock-agent-runtime/README.md

@@ -48,6 +48,13 @@ Code excerpts that show you how to call individual service functions.
 - [InvokeAgent](bedrock_agent_runtime_wrapper.py#L33)
 - [InvokeFlow](bedrock_agent_runtime_wrapper.py#L71)
 
+### Scenarios
+
+Code examples that show you how to accomplish a specific task by calling multiple
+functions within the same service.
+
+- [Create and invoke a flow](../bedrock-agent/flows/playlist_flow.py)
+
 
 <!--custom.examples.start-->
 <!--custom.examples.end-->
@@ -80,6 +87,29 @@ python flows/flow-conversation.py
 <!--custom.basics.bedrock-agent-runtime_Scenario_ConverseWithFlow.end-->
 
 
+#### Create and invoke a flow
+
+This example shows you how to do the following:
+
+- Create an execution role for the flow.
+- Create the flow.
+- Deploy the fully configured flow.
+- Invoke the flow with user-provided prompts.
+- Delete all created resources.
+
+<!--custom.scenario_prereqs.bedrock-agent_GettingStartedWithBedrockFlows.start-->
+<!--custom.scenario_prereqs.bedrock-agent_GettingStartedWithBedrockFlows.end-->
+
+Start the example by running the following at a command prompt:
+
+```
+python ../bedrock-agent/flows/playlist_flow.py
+```
+
+
+<!--custom.scenarios.bedrock-agent_GettingStartedWithBedrockFlows.start-->
+<!--custom.scenarios.bedrock-agent_GettingStartedWithBedrockFlows.end-->
+
 ### Tests
 
 ⚠ Running tests might result in charges to your AWS account.

python/example_code/bedrock-agent/README.md

@@ -11,10 +11,10 @@ _Amazon Bedrock Agents offer you the ability to build and configure autonomous a
 
 ## ⚠ Important
 
-- Running this code might result in charges to your AWS account. For more details, see [AWS Pricing](https://aws.amazon.com/pricing/) and [Free Tier](https://aws.amazon.com/free/).
-- Running the tests might result in charges to your AWS account.
-- We recommend that you grant your code least privilege. At most, grant only the minimum permissions required to perform the task. For more information, see [Grant least privilege](https://docs.aws.amazon.com/IAM/latest/UserGuide/best-practices.html#grant-least-privilege).
-- This code is not tested in every AWS Region. For more information, see [AWS Regional Services](https://aws.amazon.com/about-aws/global-infrastructure/regional-product-services).
+* Running this code might result in charges to your AWS account. For more details, see [AWS Pricing](https://aws.amazon.com/pricing/) and [Free Tier](https://aws.amazon.com/free/).
+* Running the tests might result in charges to your AWS account.
+* We recommend that you grant your code least privilege. At most, grant only the minimum permissions required to perform the task. For more information, see [Grant least privilege](https://docs.aws.amazon.com/IAM/latest/UserGuide/best-practices.html#grant-least-privilege).
+* This code is not tested in every AWS Region. For more information, see [AWS Regional Services](https://aws.amazon.com/about-aws/global-infrastructure/regional-product-services).
 
 <!--custom.important.start-->
 <!--custom.important.end-->
@@ -82,16 +82,20 @@ functions within the same service.
 - [Create and invoke a managed prompt](prompts/scenario_get_started_with_prompts.py)
 - [Create and invoke an agent](scenario_get_started_with_agents.py)
 
+
 <!--custom.examples.start-->
 <!--custom.examples.end-->
 
 ## Run the examples
 
 ### Instructions
 
+
 <!--custom.instructions.start-->
 <!--custom.instructions.end-->
 
+
+
 #### Create and invoke a flow
 
 This example shows you how to do the following:
@@ -116,6 +120,7 @@ Start the example by running the following at a command prompt:
 python flows/playlist_flow.py
 ```
 
+
 <!--custom.scenarios.bedrock-agent_GettingStartedWithBedrockFlows.start-->
 
 When prompted, enter the genre of music and the number of songs you want
@@ -142,6 +147,7 @@ Start the example by running the following at a command prompt:
 python prompts/scenario_get_started_with_prompts.py
 ```
 
+
 <!--custom.scenarios.bedrock-agent_GettingStartedWithBedrockPrompts.start-->
 
 This example shows you how to do the following:
@@ -195,16 +201,20 @@ Start the example by running the following at a command prompt:
 python scenario_get_started_with_agents.py
 ```
 
+
 <!--custom.scenarios.bedrock-agent_GettingStartedWithBedrockAgents.start-->
 <!--custom.scenarios.bedrock-agent_GettingStartedWithBedrockAgents.end-->
 
 ### Tests
 
 ⚠ Running tests might result in charges to your AWS account.
 
+
 To find instructions for running these tests, see the [README](../../README.md#Tests)
 in the `python` folder.
 
+
+
 <!--custom.tests.start-->
 <!--custom.tests.end-->
 

python/example_code/bedrock-runtime/README.md

@@ -48,6 +48,7 @@ python -m pip install -r requirements.txt
 Code examples that show you how to accomplish a specific task by calling multiple
 functions within the same service.
 
+- [Create and invoke a managed prompt](../bedrock-agent/prompts/scenario_get_started_with_prompts.py)
 - [Tool use with the Converse API](cross-model-scenarios/tool_use_demo/tool_use_demo.py)
 
 ### AI21 Labs Jurassic-2
@@ -154,6 +155,28 @@ python hello/hello_bedrock_runtime_invoke.py
 ```
 
 
+#### Create and invoke a managed prompt
+
+This example shows you how to do the following:
+
+- Create a managed prompt.
+- Create a version of the prompt.
+- Invoke the prompt using the version.
+- Clean up resources (optional).
+
+<!--custom.scenario_prereqs.bedrock-agent_GettingStartedWithBedrockPrompts.start-->
+<!--custom.scenario_prereqs.bedrock-agent_GettingStartedWithBedrockPrompts.end-->
+
+Start the example by running the following at a command prompt:
+
+```
+python ../bedrock-agent/prompts/scenario_get_started_with_prompts.py
+```
+
+
+<!--custom.scenarios.bedrock-agent_GettingStartedWithBedrockPrompts.start-->
+<!--custom.scenarios.bedrock-agent_GettingStartedWithBedrockPrompts.end-->
+
 #### Tool use with the Converse API
 
 This example shows you how to build a typical interaction between an application, a generative AI model, and connected tools or APIs to mediate interactions between the AI and the outside world. It uses the example of connecting an external weather API to the AI model so it can provide real-time weather information based on user input.