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beqqrry-aws authored Jan 30, 2024
2 parents 6edd2f1 + 3015f1a commit 9ed64f7
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15 changes: 15 additions & 0 deletions .abapgit.xml
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Expand Up @@ -5,6 +5,21 @@
<MASTER_LANGUAGE>E</MASTER_LANGUAGE>
<STARTING_FOLDER>/sap-abap/</STARTING_FOLDER>
<FOLDER_LOGIC>PREFIX</FOLDER_LOGIC>
<IGNORE>
<item>/sap-abap/README.md</item>
<item>/sap-abap/services/bdr/README.md</item>
<item>/sap-abap/services/cloudwatch/README.md</item>
<item>/sap-abap/services/dyn/README.md</item>
<item>/sap-abap/services/ec2/README.md</item>
<item>/sap-abap/services/kinesis/README.md</item>
<item>/sap-abap/services/lambda/README.md</item>
<item>/sap-abap/services/s3/README.md</item>
<item>/sap-abap/services/sagemaker/README.md</item>
<item>/sap-abap/services/sns/README.md</item>
<item>/sap-abap/services/sqs/README.md</item>
<item>/sap-abap/services/textract/README.md</item>
<item>/sap-abap/services/translate/README.md</item>
</IGNORE>
</DATA>
</asx:values>
</asx:abap>
2 changes: 1 addition & 1 deletion .doc_gen/cross-content/cross_RDSDataTracker_Java_block.xml
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Expand Up @@ -10,7 +10,7 @@
<para>
For complete source code and instructions on how to set up a Spring REST API that queries Amazon Aurora Serverless data and for use by
a React application, see the full example on
<ulink url="https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/javav2/usecases/Creating_Spring_RDS_%20Rest">GitHub</ulink>.
<ulink url="https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/javav2/usecases/Creating_Spring_RDS_Rest">GitHub</ulink>.
</para>
<para>
For complete source code and instructions on how to set up and run an example that uses the JDBC API, see the full example on
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@@ -0,0 +1,50 @@
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE chapter PUBLIC "-//OASIS//DTD DocBook XML V4.5//EN" "file://zonbook/docbookx.dtd" [
<!ENTITY % phrases-shared SYSTEM "file://AWSShared/common/phrases-shared.ent">
%phrases-shared;
]>
<block>
<para>
The &BRlong; Serverless Prompt Chaining scenario demonstrates how
<ulink type="documentation" url="https://aws.amazon.com/step-functions/">&SFNlong;</ulink>,
<ulink type="documentation" url="https://aws.amazon.com/bedrock/">&BRlong;</ulink>,
and <ulink type="documentation" url="https://aws.amazon.com/bedrock/agents/">Agents for &BRlong;</ulink>
can be used to build and orchestrate complex, serverless, and highly scalable generative AI applications.
It contains the following working examples:
</para>
<itemizedlist>
<listitem>
<para>
Write an analysis of a given novel for a literature blog. This example illustrates a simple, sequential chain of prompts.
</para>
</listitem>
<listitem>
<para>
Generate a short story about a given topic. This example illustrates how the AI can iteratively process a list of items that it previously generated.
</para>
</listitem>
<listitem>
<para>
Create an itinerary for a weekend vacation to a given destination. This example illustrates how to parallelize multiple distinct prompts.
</para>
</listitem>
<listitem>
<para>
Pitch movie ideas to a human user acting as a movie producer. This example illustrates how to parallelize the same prompt with different inference parameters, how to backtrack to a previous step in the chain, and how to include human input as part of the workflow.
</para>
</listitem>
<listitem>
<para>
Plan a meal based on ingredients the user has at hand. This example illustrates how prompt chains can incorporate two distinct AI conversations, with two AI personas engaging in a debate with each other to improve the final outcome.
</para>
</listitem>
<listitem>
<para>
Find and summarize today's highest trending GitHub repository. This example illustrates chaining multiple AI agents that interact with external APIs.
</para>
</listitem>
</itemizedlist>
<para>
For complete source code and instructions to set up and run, see the full project on <ulink url="https://github.com/aws-samples/amazon-bedrock-serverless-prompt-chaining">GitHub</ulink>.
</para>
</block>
8 changes: 2 additions & 6 deletions .doc_gen/cross-content/phrases-code-examples.ent
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Expand Up @@ -82,17 +82,13 @@
<!--Elastic Load Balancing-->
<!ENTITY ELBacro 'ELB'>

<!--Bedrock-->
<!ENTITY BRlong 'Amazon Bedrock'>
<!ENTITY BR 'Amazon Bedrock'>

<!--Bedrock Runtime-->
<!ENTITY BRRUNlong '&BRlong; Runtime'>
<!ENTITY BRRUN '&BR; Runtime'>

<!--Bedrock-->
<!ENTITY BRAlong 'Agent for Amazon Bedrock'>
<!ENTITY BRA 'Amazon Bedrock Agent'>
<!ENTITY BRAlong 'Agents for Amazon Bedrock'>
<!ENTITY BRA 'Agents for Amazon Bedrock'>

<!--Bedrock Runtime-->
<!ENTITY BRARUNlong '&BRAlong; Runtime'>
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2 changes: 0 additions & 2 deletions .doc_gen/metadata/bedrock-agent_metadata.yaml
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Expand Up @@ -193,5 +193,3 @@ bedrock-agent_GettingStartedWithBedrockAgents:
ListAgentKnowledgeBases,
PrepareAgent,
}
bedrock-agent-runtime:
{InvokeAgent}
46 changes: 43 additions & 3 deletions .doc_gen/metadata/bedrock-runtime_metadata.yaml
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Expand Up @@ -60,6 +60,23 @@ bedrock-runtime_InvokeAmazonTitanImageGeneratorForImageGeneration:
services:
bedrock-runtime: {InvokeModel}

bedrock-runtime_InvokeAmazonTitanImageGeneratorForTextGeneration:
title: Invoke the Amazon Titan Text G1 model on &BR; for text generation
title_abbrev: Text generation with Amazon Titan Text G1
synopsis: invoke the Amazon Titan Text G1 model on &BR; for text generation.
category:
languages:
JavaScript:
versions:
- sdk_version: 3
github: javascriptv3/example_code/bedrock-runtime
excerpts:
- description: Invoke the Amazon Titan Text G1 foundation model to generate text.
snippet_files:
- javascriptv3/example_code/bedrock-runtime/actions/invoke-titan-text-express-v1.js
services:
bedrock-runtime: {InvokeModel}

bedrock-runtime_InvokeStableDiffusionForImageGeneration:
title: Invoke the Stability.ai Stable Diffusion XL model on &BR; for image generation
title_abbrev: Image generation with Stability.ai Stable Diffusion XL
Expand Down Expand Up @@ -108,7 +125,6 @@ bedrock-runtime_InvokeClaude:
title: Invoke the Anthropic Claude 2 model on &BR; for text generation
title_abbrev: Text generation with Anthropic Claude 2
synopsis: invoke the Anthropic Claude 2 model on &BR; for text generation.
category:
languages:
Go:
versions:
Expand All @@ -129,6 +145,14 @@ bedrock-runtime_InvokeClaude:
- description: Invoke the Anthropic Claude 2 foundation model to generate text.
snippet_tags:
- bedrock-runtime.java2.invoke_claude.main
JavaScript:
versions:
- sdk_version: 3
github: javascriptv3/example_code/bedrock-runtime
excerpts:
- description: Invoke the Anthropic Claude 2 foundation model to generate text.
snippet_files:
- javascriptv3/example_code/bedrock-runtime/actions/invoke-claude.js
PHP:
versions:
- sdk_version: 3
Expand Down Expand Up @@ -190,6 +214,14 @@ bedrock-runtime_InvokeJurassic2:
- description: Invoke the AI21 Labs Jurassic-2 foundation model to generate text.
snippet_tags:
- bedrock-runtime.java2.invoke_jurassic2.main
JavaScript:
versions:
- sdk_version: 3
github: javascriptv3/example_code/bedrock-runtime
excerpts:
- description: Invoke the AI21 Labs Jurassic-2 foundation model to generate text.
snippet_files:
- javascriptv3/example_code/bedrock-runtime/actions/invoke-jurassic2.js
PHP:
versions:
- sdk_version: 3
Expand All @@ -201,7 +233,7 @@ bedrock-runtime_InvokeJurassic2:
Python:
versions:
- sdk_version: 3
github: python/example_code/bedrockruntime
github: python/example_code/bedrock-runtime
excerpts:
- description: Invoke the AI21 Labs Jurassic-2 foundation model to generate text.
snippet_tags:
Expand Down Expand Up @@ -242,6 +274,14 @@ bedrock-runtime_InvokeLlama2:
- description: Invoke the Meta Llama 2 Chat foundation model to generate text.
snippet_tags:
- bedrock-runtime.java2.invoke_llama2.main
JavaScript:
versions:
- sdk_version: 3
github: javascriptv3/example_code/bedrock-runtime
excerpts:
- description: Invoke the Meta Llama 2 Chat foundation model to generate text.
snippet_files:
- javascriptv3/example_code/bedrock-runtime/actions/invoke-llama2.js
PHP:
versions:
- sdk_version: 3
Expand All @@ -253,7 +293,7 @@ bedrock-runtime_InvokeLlama2:
Python:
versions:
- sdk_version: 3
github: python/example_code/bedrockruntime
github: python/example_code/bedrock-runtime
excerpts:
- description: Invoke the Meta Llama 2 Chat foundation model to generate text.
snippet_tags:
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16 changes: 9 additions & 7 deletions .doc_gen/metadata/cognito-identity-provider_metadata.yaml
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Expand Up @@ -672,9 +672,9 @@ cognito-identity-provider_ConfirmDevice:
services:
cognito-identity-provider: {ConfirmDevice}
cognito-identity-provider_InitiateAuth:
title: Start authentication with a device tracked by &COG; using an &AWS; SDK
title_abbrev: Start authentication with a tracked device
synopsis: start authentication with a device tracked by &COG;.
title: Start authentication using an &AWS; SDK
title_abbrev: Start authentication
synopsis: start authentication with &COG;.
category:
languages:
.NET:
Expand All @@ -692,9 +692,8 @@ cognito-identity-provider_InitiateAuth:
github: python/example_code/cognito
sdkguide:
excerpts:
- description: Sign in with a tracked device. To complete sign-in,
the client must respond correctly to Secure Remote Password (SRP)
challenges.
- description: This example shows you how to start authentication with a tracked device. To complete
sign-in, the client must respond correctly to Secure Remote Password (SRP) challenges.
snippet_tags:
- python.example_code.cognito-idp.helper.CognitoIdentityProviderWrapper.decl
- python.example_code.cognito-idp.InitiateAuth
Expand Down Expand Up @@ -833,7 +832,10 @@ cognito-identity-provider_Scenario_SignUpUserWithMfa:
github: python/example_code/cognito
sdkguide:
excerpts:
- description: In addition to the previously listed steps, this example
- description: Create a class that wraps &COG; functions used in the scenario.
snippet_tags:
- python.example_code.cognito-idp.CognitoIdentityProviderWrapper.full
- description: Create a class that runs the scenario. This example
also registers an MFA device to be tracked by &COG; and shows you
how to sign in by using a password and information from the tracked
device. This avoids the need to enter a new MFA code.
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13 changes: 13 additions & 0 deletions .doc_gen/metadata/cross_metadata.yaml
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Expand Up @@ -779,3 +779,16 @@ cross_Testing:
- rustv1/examples/testing/src/replay.rs
services:
s3:
cross_ServerlessPromptChaining:
title: Build and orchestrate generative AI applications with &BR; and &SFN;
title_abbrev: Orchestrate generative AI applications with &SFN;
synopsis: build and orchestrate generative AI applications with &BR; and &SFN;.
category: Scenarios
languages:
Python:
versions:
- sdk_version: 3
block_content: cross_ServerlessPromptChaining_Python_block.xml
service_main: bedrock
services:
bedrock:
4 changes: 0 additions & 4 deletions .doc_gen/metadata/curated/sources.yaml

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