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# 教程：创建处理抵押贷款申请的流
为了熟悉 Amazon Bedrock 资源及其功能，我们将使用 CloudFormation 模板来设置一个[流程](flows.md)，通过组合各种 Amazon Bedrock 和其他资源，自动执行抵押贷款申请流程。 AWS
**注意**
在本教程中，我们将使用*us-east-1*区域。您可以使用任何支持代理、流、护栏、知识库和提示管理器的区域。有关按区域的功能支持表，请参阅[Amazon Bedroc AWS 区域 k 中的功能支持](features-regions.md)。确保您有权在所使用的区域中创建 Amazon S3、Amazon Bedrock、Lambda 和 DynamoDB 资源。
此流并不用于部署目的，而是用作了解 Amazon Bedrock 资源的教程。下图直观地展示了 AWS 管理控制台中的流：
![\[抵押贷款处理流\]](http://docs.aws.amazon.com/zh_cn/bedrock/latest/userguide/images/cloudformation/mortgage-processing-flow.png)
该流结合使用 Amazon Bedrock [代理](agents.md)、[提示](prompt-management.md)和 [Lambda](https://docs.aws.amazon.com/lambda/latest/dg/welcome.html) 函数，来创建一个抵押贷款处理流，该流会收集客户的财务信息并处理客户是否符合贷款资格。Amazon Bedrock [知识库](knowledge-base.md)和[护栏](guardrails.md)也附加到流的代理，以增强响应并提供安全保障。有关流组件的更详细信息，请参阅[有关抵押贷款处理流的详细信息](getting-started-mortgage-flow-details.md)。
**Topics**
+ [先决条件](#getting-started-mortgage-flow-prereqs)
+ [使用创建抵押贷款处理流程 CloudFormation](#getting-started-mortgage-flow-create)
+ [测试抵押贷款处理流](#getting-started-mortgage-flow-test)
+ [清理：删除资源](#getting-started-mortgage-flow-delete)
+ [CloudFormation 模板](getting-started-mortgage-flow-template.md)
+ [有关抵押贷款处理流的详细信息](getting-started-mortgage-flow-details.md)
## 先决条件
要创建此流，您需要下载一个 .zip 文件，并按照说明运行脚本，该脚本将为您设置资源和模板。
**重要**
您创建的 Amazon 资源将会收费，直到您删除它们。
然后，完成以下先决任务：
1. 下载 [cloudformation-mortgage-flow-setup.zip](samples/cloudformation-mortgage-flow-setup.zip) 文件。
1. 解压缩该文件。您可以在 [CloudFormation 模板](getting-started-mortgage-flow-template.md)中了解有关内容的更多信息。
1. 通过执行以下操作，请求访问 Amazon Bedrock 基础模型：
1. 使用有权使用 Amazon Bedrock 控制台的 IAM 身份登录。 AWS 管理控制台 然后，在 [https://console.aws.amazon.com/](https://console.aws.amazon.com/bedrock)bedrock 上打开 Amazon Bedrock 控制台。
1. 检查右上角的区域，确保您使用的是**美国东部（弗吉尼亚州北部）**区域。如果不是，请切换区域。
1. 选择左侧导航窗格底部的**模型访问权限**。
1. 选择**修改模型访问权限**。
1. 请执行以下操作之一：
+ 要请求访问所有模型，请选择**启用所有模型**。在您转到的页面上，所有模型旁边的复选框都将处于选中状态。
+ 要请求访问特定模型，请选择**启用特定模型**。在您转到的页面上，您有以下选项：
+ 要请求访问提供商的所有模型，请选中提供商名称旁边的复选框。
+ 要请求访问某一模型，请选中模型名称旁边的复选框。
1. 就以下教程而言，您应尽量减少请求访问 **Titan Embeddings G1 - Text** 和 **Claude 3 Haiku** 模型的次数。然后选择**下一步**。
1. 查看您请求访问的模型和相应**条款**。准备好之后，选择**提交**以请求访问权限。
## 使用创建抵押贷款处理流程 CloudFormation
为了创建抵押贷款处理流程及其相关资源，我们将创建一个 CloudFormation 模板并使用它来创建包含 Amazon Bedrock 资源的堆栈。
**重要**
您创建的 Amazon 资源将会收费，直到您删除它们。
### 创建资源和 CloudFormation 模板文件
首先，使用.zip 文件中的脚本将资源上传到 S3 存储桶并创建 CloudFormation 模板。
1. 在终端中运行以下命令，将资源复制到 Amazon S3 存储桶，并将 `main-stack.yaml` 和 `main-stack.json` 文件填充为 S3 存储桶名称，作为存储桶名称参数的默认值。
```
bash deploy.sh
```
**注意**
脚本的用法是`bash deploy.sh `，其中**和**是可选参数。如果您不提供这些参数，将使用以下默认值：
**— 在您的 AWS 凭证设置中指定的默认 AWS 区域。
**— 存储桶将被命名*mortgage-flow-deployment--*，其中**是您的 AWS 账户 ID，与您提供的值或 AWS 证书设置中指定的默认 AWS 区域**相匹配。
1. 确认提示。部署完成后，您应该有一个完整的 `main-stack.json` 和 `main-stack.yaml` 模板供下一步使用。
**注意**
如果脚本失败，您可以通过执行以下操作，手动准备资源：
在 Amazon S3 控制台中将解压缩文件夹的*内容*（不包括`cloudformation-mortgage-flow-setup`文件夹本身）上传到美国东部（弗吉尼亚北部）的 S3 存储桶，网址为。[https://console.aws.amazon.com/s3/](https://console.aws.amazon.com/s3/)
查找 `templates/json/main-stack-tmp.yaml` 或 `templates/json/main-stack-tmp.json` 文件并执行以下操作：
将`Q01pS3BucketName`参数的`Default`值从更改为您*MortgageFlowBucket*的 S3 存储桶名称。
从文件名中删除 `-tmp`，使其变为 `templates/json/main-stack.yaml` 或 `templates/json/main-stack.json`。
### 使用 CloudFormation 控制台创建堆栈
接下来，使用您保存的模板来配置堆 CloudFormation 栈。
1. 在 [https://console.aws.amazon.com/cloudformat](https://console.aws.amazon.com/cloudformation/) ion 上打开 CloudFormation 控制台。检查右上角的区域，确保您使用的是**美国东部（弗吉尼亚州北部）**区域。如果不是，请切换区域。
1. 在**堆栈**页面中，从**创建堆栈**菜单中选择**使用新资源（标准）**。
1. 指定模板：
1. 在**先决条件**下，选择**选择现有模板**。
1. 在**指定模板**下，选择**上传模板文件**。
1. 选择**选择文件**，导航到 `main-stack.yaml` 或 `main-stack.json` 模板，并选择该模板。
1. 选择**下一步**。
1. 指定堆栈详细信息：
1. 在**堆栈名称**字段中，为堆栈输入名称。
1. 在**参数**字段中，保留默认值。
**注意**
`Q01pS3BucketName` 值应与您为此模板上传资源的 S3 存储桶名称匹配。其余的参数与知识库的配置有关；如果您修改其中任何一个，请确保各配置之间是兼容的。有关更多信息，请参阅 [将您创建的向量存储用于知识库的先决条件](knowledge-base-setup.md)。
1. 选择**下一步**。
1. 配置堆栈选项：
1. 在**堆栈故障选项**下，选择**删除所有新创建的资源**。
**注意**
如果选择此选项，即使堆栈创建失败，您可能也不会因为删除策略规定保留资源而向资源付费。有关更多信息，请参阅《CloudFormation 用户指南》**中的 [`DeletionPolicy` 属性](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-attribute-deletionpolicy.html)。
1. 在 “**能力**” 下，选中复选框以确认 CloudFormation 可能会在您的账户中创建 IAM 资源。
1. 选择**下一步**。
1. 查看堆栈详细信息并选择**提交**。 CloudFormation 创建堆栈。创建过程需要几分钟时间。在堆栈创建完成后，可以使用堆栈详细信息页面上的**资源**选项卡来查看账户中预置的资源。
1. 在堆栈创建完成后，执行以下操作以同步知识库的数据来源，从而可以查询知识库：
1. 使用有权使用 Amazon Bedrock 控制台的 IAM 身份登录。 AWS 管理控制台 然后，在 [https://console.aws.amazon.com/](https://console.aws.amazon.com/bedrock)bedrock 上打开 Amazon Bedrock 控制台。
1. 在左侧导航窗格中，选择**知识库**，然后选择已创建的名为 `AWSDocsTutorial-MortgageKB` 的知识库。
1. 在**数据来源**部分中，选中已创建的名为 `AWSDocsTutorial-MortgageKB-DS` 的数据来源旁边的复选框。
1. 选择**同步**。同步完成后，您可以测试该流。
## 测试抵押贷款处理流
创建抵押贷款处理流后，您可以使用 Amazon Bedrock 控制台来检查、测试和修改流。您还可以检查、测试和修改流中的各个资源。
**测试流**
1. 使用有权使用 Amazon Bedrock 控制台的 IAM 身份登录。 AWS 管理控制台 然后，在 [https://console.aws.amazon.com/](https://console.aws.amazon.com/bedrock)bedrock 上打开 Amazon Bedrock 控制台。
1. 从左侧导航窗格中选择**流**。检查右上角的区域，确保您使用的是**美国东部（弗吉尼亚州北部）**区域。如果不是，请切换区域。
1. 在 “**流程**” 部分中，选择根据 CloudFormation 模板创建的流程。它应该是 `AWSDocsTutorial-MortgageFlow`。
1. 选择**在流生成器中编辑**。您可以拖动流中的各个节点来修改流的可视化表示。
1. 在**测试流**窗格中，在文本字段中输入以下内容，然后选择**运行**。
```
{
"income": 80000,
"totalDebt": 5000,
"loanTerm": 30,
"loanAmount": 600000,
"creditScore": 750,
"mlsId": "MLS-5678"
}
```
由于贷款金额大于计算得到的最大可承受贷款额度，因此会触发 **incomeDebt** 提示并且流会生成拒绝函。您可以选择**显示跟踪**来查看流中运行的节点。
1. 同样，在**测试流**窗格中，在文本字段中输入以下内容，然后选择**运行**。
```
{
"income": 120000,
"totalDebt": 5000,
"loanTerm": 30,
"loanAmount": 200000,
"creditScore": 650,
"mlsId": "MLS-3456"
}
```
由于贷款金额低于计算出的最高可负担贷款，因此会触发 P **roces** sApplication 提示并将其发送到 **mortgageProcessingAgent**，后者会查找附带的知识库并生成响应，根据输入值评估客户是否有资格获得贷款。
1. （可选）尝试通过为 JSON 对象中的字段使用不同的值来运行流。这些 `mlsId` 值对应于多重挂牌服务上列出的房产。您可以执行以下操作来查找有效的 `mlsId` 值：
1. 登录 AWS 管理控制台 并打开 DynamoDB 控制台，网址为。[https://console.aws.amazon.com/dynamodb/](https://console.aws.amazon.com/dynamodb/)
1. 在左侧导航窗格中，选择**表**。
1. 选择上面写着的表格**AWSDocsTutorial-PropertyListing**。
1. 选择**浏览表项目**。
1. 您可以在流输入中使用 **mls\$1id** 列中的任何值。
您还可以导航到中的**代理**、**知识库**、**防护栏**和**提示管理**页面， AWS 管理控制台 以独立检查流程中使用的每个 Amazon Bedrock 资源。要了解有关流的更多信息并更详细地了解各个组件，请参阅[有关抵押贷款处理流的详细信息](getting-started-mortgage-flow-details.md)。
## 清理：删除资源
在您探索这些资源并更好地了解不同 Amazon Bedrock 资源的功能后，我们将删除该堆栈及其包含的资源。
**重要**
您创建的 Amazon 资源将会收费，直到您删除它们。
1. 打开 [https://console.aws.amazon.com/cloudformation](https://console.aws.amazon.com/cloudformation/)。
1. 从左侧导航窗格中选择**堆栈**。
1. 选择您根据此模板创建的堆栈。然后，选择**删除**，再确认**删除**。
CloudFormation 启动删除主堆栈、其所有嵌套堆栈以及堆栈中包含的所有资源。
# CloudFormation 模板
您下载的 `cloudformation-mortgage-flow-setup.zip` 文件中包含以下文件：
+ `deploy.sh`— 一个 shell 脚本，用于部署您的资源并准备您将使用的主 CloudFormation 模板。
+ `artifacts` – 这是一个包含 .zip 文件的文件夹，这些文件包含用于代理和知识库模板的函数：
+ 代理操作组的 Lambda 函数
+ `agent_loan_calculator.zip`
+ `mls_lookup.zip`
+ `loader_deployment_package.zip`
+ 用于设置知识库的函数
+ `custom-resource-lambda.zip`
+ `opensearchpy-layer.zip`
+ `provider-event-handler.zip`
+ `api-schema` – 一个包含操作组的 API 架构的文件夹。
+ `knowledge-base-data-source` – 一个包含[房利美销售指南](https://selling-guide.fanniemae.com/) PDF 文件的文件夹。
+ `templates` – 一个包含此流中的资源模板的文件夹，采用 JSON 和 YAML 格式：
+ `main-stack-tmp` – 将剩余模板部署为嵌套堆栈的主模板。此文件将在运行部署脚本后变成 `main-stack`。
+ `guardrails-template` – 要与代理关联的护栏的模板。
+ `prompts-template` – 流中要使用的提示的模板。
+ `kb-role-template`— 知识库角色的模板，供 OpenSearch 模板和知识库模板使用。
+ `oss-infra-template`— 用于知识库的 Amazon OpenSearch Serverless 矢量存储的模板。
+ `kb-infra-template` – 要与代理关联的抵押贷款知识库的模板。
+ `agent-template` – 流中要使用的抵押贷款处理代理的模板。
+ `mortgage-flow-template` – 组合所有资源的抵押贷款处理流的模板。
+ `README.md` – 一个描述模板使用步骤的 README 文件。
以下主题显示了用于每个堆栈的 CloudFormation 模板。主堆栈将其余堆栈部署为[嵌套堆栈](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/using-cfn-nested-stacks.html)。
**Topics**
+ [主堆栈](#getting-started-mortgage-templates-main)
+ [Amazon Bedrock 护栏堆栈](#getting-started-mortgage-guardrail-templates)
+ [Amazon Bedrock 提示管理器堆栈](#getting-started-mortgage-prompts-templates)
+ [Amazon Bedrock 知识库堆栈](#getting-started-mortgage-kb-templates)
## 主堆栈
主堆栈定义了您在上传模板时可定义的参数。这些值将传递到其余的每个嵌套堆栈。部署脚本将`Q01pS3BucketName`参数的默认值替换*MortgageFlowBucket*为包含该脚本部署的资源的实际 S3 存储桶。
------
#### [ YAML ]
```
AWSTemplateFormatVersion: '2010-09-09'
Description: "[AWSDocs] AmazonBedrockDocs: getting-started-mortgage-flow"
Parameters:
Q01pS3BucketName:
Type: String
Description: Provide existing S3 bucket name where data is already stored
Default: MortgageFlowBucket
Q02pFlowName:
Type: String
Description: Name for the flow
Default: MortgageFlow
Q03pGuardrailName:
Type: String
Description: Name for guardrail to attach to agent
Default: MortgageGR
Q04pKnowledgeBaseName:
Type: String
Description: Name for knowledge base to associate with agent
Default: MortgageKB
Q05pAgentName:
Type: String
Description: Name for agent to create
Default: MortgageAgent
Q06pKBEmbedModel:
Type: String
Description: Select Embedding model
Default: amazon.titan-embed-text-v1
Q07pKBChunkingStrategy:
Type: String
Description: Select Chunking strategy
AllowedValues:
- Default chunking
- Fixed-size chunking
- No chunking
Default: Default chunking
Q08pKBMaxTokens:
Type: Number
Description: Maximum number of tokens in a chunk
Default: 300
Q09pKBOverlapPercentage:
Type: Number
Description: Percent overlap in each chunk
Default: 20
Q10pKBVectorStore:
Type: String
Description: Select vector store
AllowedValues:
- Open-Search-Serverless
Default: Open-Search-Serverless
Q11pOSSCollectionName:
Type: String
Description: Name of the Collection
MinLength: 1
MaxLength: 63
Default: mortgage-kb-collection
AllowedPattern: ^[a-z0-9](-*[a-z0-9])*
ConstraintDescription: Must be lowercase or numbers with a length of 1-32 characters
Q12pOSSIndexName:
Type: String
Description: Index name to be created in vector store
MinLength: 1
MaxLength: 63
Default: mortgage-kb-index
AllowedPattern: ^[a-z0-9](-*[a-z0-9])*
ConstraintDescription: Must be lowercase or numbers with a length of 1-63 characters
# Q13pVectorFieldName:
# Type: String
# Description: Vector field name
# Default: bedrock-knowledge-base-default-vector
# Q14pMetaDataFieldName:
# Type: String
# Description: Metadata field name
# Default: AMAZON_BEDROCK_METADATA
# Q15pTextFieldName:
# Type: String
# Description: Text field name
# Default: AMAZON_BEDROCK_TEXT_CHUNK
Resources:
KBRoleStack:
Type: AWS::CloudFormation::Stack
Properties:
TemplateURL: !Sub https://${Q01pS3BucketName}.s3.amazonaws.com/templates/yaml/kb-role-template.yaml
TimeoutInMinutes: 15
Parameters:
Q01pS3BucketName:
Ref: Q01pS3BucketName
OSSStack:
Type: AWS::CloudFormation::Stack
DependsOn: KBRoleStack
Properties:
TemplateURL: !Sub https://${Q01pS3BucketName}.s3.amazonaws.com/templates/yaml/oss-infra-template.yaml
TimeoutInMinutes: 15
Parameters:
Q01pS3BucketName:
Ref: Q01pS3BucketName
Q06pKBEmbedModel:
Ref: Q06pKBEmbedModel
Q11pOSSCollectionName:
Ref: Q11pOSSCollectionName
Q12pOSSIndexName:
Ref: Q12pOSSIndexName
pKBRole:
Fn::GetAtt:
- KBRoleStack
- Outputs.KBRole
pKBRoleArn:
Fn::GetAtt:
- KBRoleStack
- Outputs.KBRoleArn
KBStack:
Type: AWS::CloudFormation::Stack
DependsOn: OSSStack
Properties:
TemplateURL: !Sub https://${Q01pS3BucketName}.s3.amazonaws.com/templates/yaml/kb-infra-template.yaml
TimeoutInMinutes: 15
Parameters:
KnowledgeBaseName:
Ref: Q04pKnowledgeBaseName
Q01pS3BucketName:
Ref: Q01pS3BucketName
Q06pKBEmbedModel:
Ref: Q06pKBEmbedModel
Q07pKBChunkingStrategy:
Ref: Q07pKBChunkingStrategy
Q08pKBMaxTokens:
Ref: Q08pKBMaxTokens
Q09pKBOverlapPercentage:
Ref: Q09pKBOverlapPercentage
Q11pOSSCollectionName:
Ref: Q11pOSSCollectionName
Q12pOSSIndexName:
Ref: Q12pOSSIndexName
# Q13pVectorFieldName:
# Ref: Q13pVectorFieldName
# Q14pMetaDataFieldName:
# Ref: Q14pMetaDataFieldName
# Q15pTextFieldName:
# Ref: Q15pTextFieldName
pCollectionArn:
Fn::GetAtt:
- OSSStack
- Outputs.CollectionArn
pKBRoleArn:
Fn::GetAtt:
- KBRoleStack
- Outputs.KBRoleArn
pKBRole:
Fn::GetAtt:
- KBRoleStack
- Outputs.KBRole
GRStack:
Type: AWS::CloudFormation::Stack
Properties:
TemplateURL: !Sub https://${Q01pS3BucketName}.s3.amazonaws.com/templates/yaml/guardrails-template.yaml
TimeoutInMinutes: 15
Parameters:
GuardrailName:
Ref: Q03pGuardrailName
AgentStack:
Type: AWS::CloudFormation::Stack
DependsOn:
- KBStack
- GRStack
Properties:
TemplateURL: !Sub https://${Q01pS3BucketName}.s3.amazonaws.com/templates/yaml/agent-template.yaml
TimeoutInMinutes: 15
Parameters:
Q01pS3BucketName:
Ref: Q01pS3BucketName
KnowledgeBaseId:
Fn::GetAtt:
- KBStack
- Outputs.KBId
GuardrailArn:
Fn::GetAtt:
- GRStack
- Outputs.GuardrailArn
GuardrailVersion:
Fn::GetAtt:
- GRStack
- Outputs.GuardrailVersion
PromptsStack:
Type: AWS::CloudFormation::Stack
Properties:
TemplateURL: !Sub https://${Q01pS3BucketName}.s3.amazonaws.com/templates/yaml/prompts-template.yaml
TimeoutInMinutes: 15
FlowStack:
Type: AWS::CloudFormation::Stack
DependsOn:
- AgentStack
- PromptsStack
Properties:
TemplateURL: !Sub https://${Q01pS3BucketName}.s3.amazonaws.com/templates/yaml/mortgage-flow-template.yaml
TimeoutInMinutes: 15
Parameters:
FlowName:
Ref: Q02pFlowName
Q01pS3BucketName:
Ref: Q01pS3BucketName
ProcessApplicationPromptArn:
Fn::GetAtt:
- PromptsStack
- Outputs.ProcessApplicationPromptArn
RejectionPromptArn:
Fn::GetAtt:
- PromptsStack
- Outputs.RejectionPromptArn
AgentId:
Fn::GetAtt:
- AgentStack
- Outputs.AgentId
```
------
#### [ JSON ]
```
{
"AWSTemplateFormatVersion": "2010-09-09",
"Description": "[AWSDocs] AmazonBedrockDocs: getting-started-mortgage-flow",
"Parameters": {
"Q01pS3BucketName": {
"Type": "String",
"Description": "Provide existing S3 bucket name where data is already stored",
"Default": "MortgageFlowBucket"
},
"Q02pFlowName": {
"Type": "String",
"Description": "Name for the flow",
"Default": "MortgageFlow"
},
"Q03pGuardrailName": {
"Type": "String",
"Description": "Name for guardrail to attach to agent",
"Default": "MortgageGR"
},
"Q04pKnowledgeBaseName": {
"Type": "String",
"Description": "Name for knowledge base to associate with agent",
"Default": "MortgageKB"
},
"Q05pAgentName": {
"Type": "String",
"Description": "Name for agent to create",
"Default": "MortgageAgent"
},
"Q06pKBEmbedModel": {
"Type": "String",
"Description": "Select Embedding model",
"Default": "amazon.titan-embed-text-v1"
},
"Q07pKBChunkingStrategy": {
"Type": "String",
"Description": "Select Chunking strategy",
"AllowedValues": [
"Default chunking",
"Fixed-size chunking",
"No chunking"
],
"Default": "Default chunking"
},
"Q08pKBMaxTokens": {
"Type": "Number",
"Description": "Maximum number of tokens in a chunk",
"Default": 300
},
"Q09pKBOverlapPercentage": {
"Type": "Number",
"Description": "Percent overlap in each chunk",
"Default": 20
},
"Q10pKBVectorStore": {
"Type": "String",
"Description": "Select vector store",
"AllowedValues": [
"Open-Search-Serverless"
],
"Default": "Open-Search-Serverless"
},
"Q11pOSSCollectionName": {
"Type": "String",
"Description": "Name of the Collection",
"MinLength": 1,
"MaxLength": 63,
"Default": "mortgage-kb-collection",
"AllowedPattern": "^[a-z0-9](-*[a-z0-9])*",
"ConstraintDescription": "Must be lowercase or numbers with a length of 1-32 characters"
},
"Q12pOSSIndexName": {
"Type": "String",
"Description": "Index name to be created in vector store",
"MinLength": 1,
"MaxLength": 63,
"Default": "mortgage-kb-index",
"AllowedPattern": "^[a-z0-9](-*[a-z0-9])*",
"ConstraintDescription": "Must be lowercase or numbers with a length of 1-63 characters"
}
},
"Resources": {
"KBRoleStack": {
"Type": "AWS::CloudFormation::Stack",
"Properties": {
"TemplateURL": {
"Fn::Sub": "https://${Q01pS3BucketName}.s3.amazonaws.com/templates/json/kb-role-template.json"
},
"TimeoutInMinutes": 15,
"Parameters": {
"Q01pS3BucketName": {
"Ref": "Q01pS3BucketName"
}
}
}
},
"OSSStack": {
"Type": "AWS::CloudFormation::Stack",
"DependsOn": "KBRoleStack",
"Properties": {
"TemplateURL": {
"Fn::Sub": "https://${Q01pS3BucketName}.s3.amazonaws.com/templates/json/oss-infra-template.json"
},
"TimeoutInMinutes": 15,
"Parameters": {
"Q01pS3BucketName": {
"Ref": "Q01pS3BucketName"
},
"Q06pKBEmbedModel": {
"Ref": "Q06pKBEmbedModel"
},
"Q11pOSSCollectionName": {
"Ref": "Q11pOSSCollectionName"
},
"Q12pOSSIndexName": {
"Ref": "Q12pOSSIndexName"
},
"pKBRole": {
"Fn::GetAtt": [
"KBRoleStack",
"Outputs.KBRole"
]
},
"pKBRoleArn": {
"Fn::GetAtt": [
"KBRoleStack",
"Outputs.KBRoleArn"
]
}
}
}
},
"KBStack": {
"Type": "AWS::CloudFormation::Stack",
"DependsOn": "OSSStack",
"Properties": {
"TemplateURL": {
"Fn::Sub": "https://${Q01pS3BucketName}.s3.amazonaws.com/templates/json/kb-infra-template.json"
},
"TimeoutInMinutes": 15,
"Parameters": {
"KnowledgeBaseName": {
"Ref": "Q04pKnowledgeBaseName"
},
"Q01pS3BucketName": {
"Ref": "Q01pS3BucketName"
},
"Q06pKBEmbedModel": {
"Ref": "Q06pKBEmbedModel"
},
"Q07pKBChunkingStrategy": {
"Ref": "Q07pKBChunkingStrategy"
},
"Q08pKBMaxTokens": {
"Ref": "Q08pKBMaxTokens"
},
"Q09pKBOverlapPercentage": {
"Ref": "Q09pKBOverlapPercentage"
},
"Q11pOSSCollectionName": {
"Ref": "Q11pOSSCollectionName"
},
"Q12pOSSIndexName": {
"Ref": "Q12pOSSIndexName"
},
"pCollectionArn": {
"Fn::GetAtt": [
"OSSStack",
"Outputs.CollectionArn"
]
},
"pKBRoleArn": {
"Fn::GetAtt": [
"KBRoleStack",
"Outputs.KBRoleArn"
]
},
"pKBRole": {
"Fn::GetAtt": [
"KBRoleStack",
"Outputs.KBRole"
]
}
}
}
},
"GRStack": {
"Type": "AWS::CloudFormation::Stack",
"Properties": {
"TemplateURL": {
"Fn::Sub": "https://${Q01pS3BucketName}.s3.amazonaws.com/templates/json/guardrails-template.json"
},
"TimeoutInMinutes": 15,
"Parameters": {
"GuardrailName": {
"Ref": "Q03pGuardrailName"
}
}
}
},
"AgentStack": {
"Type": "AWS::CloudFormation::Stack",
"DependsOn": [
"KBStack",
"GRStack"
],
"Properties": {
"TemplateURL": {
"Fn::Sub": "https://${Q01pS3BucketName}.s3.amazonaws.com/templates/json/agent-template.json"
},
"TimeoutInMinutes": 15,
"Parameters": {
"Q01pS3BucketName": {
"Ref": "Q01pS3BucketName"
},
"KnowledgeBaseId": {
"Fn::GetAtt": [
"KBStack",
"Outputs.KBId"
]
},
"GuardrailArn": {
"Fn::GetAtt": [
"GRStack",
"Outputs.GuardrailArn"
]
},
"GuardrailVersion": {
"Fn::GetAtt": [
"GRStack",
"Outputs.GuardrailVersion"
]
}
}
}
},
"PromptsStack": {
"Type": "AWS::CloudFormation::Stack",
"Properties": {
"TemplateURL": {
"Fn::Sub": "https://${Q01pS3BucketName}.s3.amazonaws.com/templates/json/prompts-template.json"
},
"TimeoutInMinutes": 15
}
},
"FlowStack": {
"Type": "AWS::CloudFormation::Stack",
"DependsOn": [
"AgentStack",
"PromptsStack"
],
"Properties": {
"TemplateURL": {
"Fn::Sub": "https://${Q01pS3BucketName}.s3.amazonaws.com/templates/json/mortgage-flow-template.json"
},
"TimeoutInMinutes": 15,
"Parameters": {
"FlowName": {
"Ref": "Q02pFlowName"
},
"Q01pS3BucketName": {
"Ref": "Q01pS3BucketName"
},
"ProcessApplicationPromptArn": {
"Fn::GetAtt": [
"PromptsStack",
"Outputs.ProcessApplicationPromptArn"
]
},
"RejectionPromptArn": {
"Fn::GetAtt": [
"PromptsStack",
"Outputs.RejectionPromptArn"
]
},
"AgentId": {
"Fn::GetAtt": [
"AgentStack",
"Outputs.AgentId"
]
}
}
}
}
}
}
```
------
## Amazon Bedrock 护栏堆栈
此堆栈创建了以下与[护栏](guardrails.md)相关的资源：
+ AgentGuardrail ([AWS::Bedrock::Guardrail](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide /aws-resource-bedrock-guardrail.html)) — 提供内容筛选、主题策略和 PII 保护的护栏。该护栏将附加到代理堆栈中的代理。
+ AgentGuardrailVersion ([AWS::Bedrock::GuardrailVersion](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide /aws-resource-bedrock-guardrailversion.html))-应用于代理的`AgentGuardrail`资源版本。
------
#### [ YAML ]
```
AWSTemplateFormatVersion: "2010-09-09"
Description: "[AWSDocs] AmazonBedrockDocs: getting-started-mortgage-flow"
Parameters:
GuardrailName:
Type: String
Description: Name for guardrail
Default: MortgageGuardrail
Resources:
AgentGuardrail:
Type: AWS::Bedrock::Guardrail
Properties:
Name: !Sub AWSDocsTutorial-${GuardrailName}
Description: Guardrail for mortgage processing with investment advice blocking, content filtering, and PII protection
BlockedInputMessaging: "Sorry, the model cannot answer this question."
BlockedOutputsMessaging: "Sorry, the model cannot answer this question."
TopicPolicyConfig:
TopicsConfig:
- Name: InvestmentAdvice
Definition: "Investment advice refers to inquires, guidance or recommendations regarding the management or allocation of fund or asset with the goal of generating returns or achieving specific financial objectives"
Examples:
- "Is investing in the stocks better than bonds?"
- "Should I invest in gold?"
Type: DENY
ContentPolicyConfig:
FiltersConfig:
- Type: VIOLENCE
InputStrength: HIGH
OutputStrength: HIGH
- Type: PROMPT_ATTACK
InputStrength: HIGH
OutputStrength: NONE
- Type: MISCONDUCT
InputStrength: HIGH
OutputStrength: HIGH
- Type: HATE
InputStrength: HIGH
OutputStrength: HIGH
- Type: SEXUAL
InputStrength: HIGH
OutputStrength: HIGH
- Type: INSULTS
InputStrength: HIGH
OutputStrength: HIGH
WordPolicyConfig:
WordsConfig:
- Text: "crypto currency"
- Text: "bitcoin"
ManagedWordListsConfig:
- Type: PROFANITY
SensitiveInformationPolicyConfig:
PiiEntitiesConfig:
- Type: EMAIL
Action: ANONYMIZE
- Type: CREDIT_DEBIT_CARD_NUMBER
Action: BLOCK
ContextualGroundingPolicyConfig:
FiltersConfig:
- Type: GROUNDING
Threshold: 0.85
- Type: RELEVANCE
Threshold: 0.5
AgentGuardrailVersion:
Type: AWS::Bedrock::GuardrailVersion
Properties:
GuardrailIdentifier: !Ref AgentGuardrail
Description: Version 1 of the mortgage agent guardrail
Outputs:
GuardrailArn:
Value:
Ref: AgentGuardrail
Description: ARN of guardrail to associate with agent
GuardrailVersion:
Value:
Fn::GetAtt:
- AgentGuardrailVersion
- Version
Description: Version of guardrail to associate with agent
```
------
#### [ JSON ]
```
{
"AWSTemplateFormatVersion": "2010-09-09",
"Description": "[AWSDocs] AmazonBedrockDocs: getting-started-mortgage-flow",
"Parameters": {
"GuardrailName": {
"Type": "String",
"Description": "Name for guardrail",
"Default": "MortgageGuardrail"
}
},
"Resources": {
"AgentGuardrail": {
"Type": "AWS::Bedrock::Guardrail",
"Properties": {
"Name": {
"Fn::Sub": "AWSDocsTutorial-${GuardrailName}"
},
"Description": "Guardrail for mortgage processing with investment advice blocking, content filtering, and PII protection",
"BlockedInputMessaging": "Sorry, the model cannot answer this question.",
"BlockedOutputsMessaging": "Sorry, the model cannot answer this question.",
"TopicPolicyConfig": {
"TopicsConfig": [
{
"Name": "InvestmentAdvice",
"Definition": "Investment advice refers to inquires, guidance or recommendations regarding the management or allocation of fund or asset with the goal of generating returns or achieving specific financial objectives",
"Examples": [
"Is investing in the stocks better than bonds?",
"Should I invest in gold?"
],
"Type": "DENY"
}
]
},
"ContentPolicyConfig": {
"FiltersConfig": [
{
"Type": "VIOLENCE",
"InputStrength": "HIGH",
"OutputStrength": "HIGH"
},
{
"Type": "PROMPT_ATTACK",
"InputStrength": "HIGH",
"OutputStrength": "NONE"
},
{
"Type": "MISCONDUCT",
"InputStrength": "HIGH",
"OutputStrength": "HIGH"
},
{
"Type": "HATE",
"InputStrength": "HIGH",
"OutputStrength": "HIGH"
},
{
"Type": "SEXUAL",
"InputStrength": "HIGH",
"OutputStrength": "HIGH"
},
{
"Type": "INSULTS",
"InputStrength": "HIGH",
"OutputStrength": "HIGH"
}
]
},
"WordPolicyConfig": {
"WordsConfig": [
{
"Text": "crypto currency"
},
{
"Text": "bitcoin"
}
],
"ManagedWordListsConfig": [
{
"Type": "PROFANITY"
}
]
},
"SensitiveInformationPolicyConfig": {
"PiiEntitiesConfig": [
{
"Type": "EMAIL",
"Action": "ANONYMIZE"
},
{
"Type": "CREDIT_DEBIT_CARD_NUMBER",
"Action": "BLOCK"
}
]
},
"ContextualGroundingPolicyConfig": {
"FiltersConfig": [
{
"Type": "GROUNDING",
"Threshold": 0.85
},
{
"Type": "RELEVANCE",
"Threshold": 0.5
}
]
}
}
},
"AgentGuardrailVersion": {
"Type": "AWS::Bedrock::GuardrailVersion",
"Properties": {
"GuardrailIdentifier": {
"Ref": "AgentGuardrail"
},
"Description": "Version 1 of the mortgage agent guardrail"
}
}
},
"Outputs": {
"GuardrailArn": {
"Value": {
"Ref": "AgentGuardrail"
},
"Description": "ARN of guardrail to associate with agent"
},
"GuardrailVersion": {
"Value": {
"Fn::GetAtt": [
"AgentGuardrailVersion",
"Version"
]
},
"Description": "Version of guardrail to associate with agent"
}
}
}
```
------
## Amazon Bedrock 提示管理器堆栈
此堆栈创建以下 [promp [AWS::IAM::Prompt](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide /aws-resource-bedrock-prompt.html)](prompt-management.md)t () 资源，这些资源已添加到流程中：
+ RejectionPrompt — 根据财务信息返回生成的拒绝信的提示。
+ ProcessApplicationPrompt — 一种提示，它会将客户的财务信息发送给代理人，并提示代理评估客户是否有资格获得贷款。
------
#### [ YAML ]
```
AWSTemplateFormatVersion: "2010-09-09"
Description: "[AWSDocs] AmazonBedrockDocs: getting-started-mortgage-flow"
Resources:
RejectionPrompt:
Type: AWS::Bedrock::Prompt
Properties:
Name: !Sub AWSDocsTutorial-RejectionPrompt
Description: "Use this prompt to generate a rejection letter triggered by an unsatisfactory income to debt ratio"
DefaultVariant: variantOne
Variants:
- Name: variantOne
TemplateType: TEXT
ModelId: anthropic.claude-3-haiku-20240307-v1:0
TemplateConfiguration:
Text:
Text: |
Write a mortgage loan rejection letter for a candiate with income {{income}}, totalDebt {{totalDebt}}, loanAmount {{loanAmount}}.
The reason for rejection is their income to debt ratio.
Do not mention any other reason.
Make the letter as concise as possible.
Treat all numeric inputs as whole numbers.
Let the general structure be like the below:
Dear [Applicant's Name],
We appreciate your interest in obtaining a mortgage loan with our institution...
The primary reason for this decision is that ...
While we understand that this news may be disappointing, ...
Thank you again for your interest, and we wish you the best in your future endeavors...
Sincerely,
[Your Institution's Name]
InputVariables:
- Name: income
- Name: totalDebt
- Name: loanAmount
InferenceConfiguration:
Text:
MaxTokens: 2000
Temperature: 0.0
TopP: 0.999
StopSequences:
- "\n\nHuman:"
AdditionalModelRequestFields:
top_k: 250
ProcessApplicationPrompt:
Type: AWS::Bedrock::Prompt
Properties:
Name: !Sub AWSDocsTutorial-ProcessApplicationPrompt
Description: "Use this prompt to generate a question for an agent to process the mortgage application"
DefaultVariant: variantOne
Variants:
- Name: variantOne
TemplateType: TEXT
ModelId: anthropic.claude-3-haiku-20240307-v1:0
TemplateConfiguration:
Text:
Text: |
Generate a question asking if the user will qualify for a loan for the specified criteria.
Include instruction to base the answer on key features of the property retrieved from MLS listing.
Start with "will an applicant...".
{ "income": {{income}}, "creditScore": {{creditScore}}, "totalDebt": {{totalDebt}}, "loanAmount": {{loanAmount}}, "mlsId": {{mlsId}} }
Include a second question on loan requirements an applicant with the below attributes should consider for a Fannie Mae backed loan (other than debt to income).
InputVariables:
- Name: income
- Name: creditScore
- Name: totalDebt
- Name: loanAmount
- Name: mlsId
InferenceConfiguration:
Text:
MaxTokens: 2000
Temperature: 0.0
TopP: 0.999
StopSequences:
- "\n\nHuman:"
AdditionalModelRequestFields:
top_k: 250
Outputs:
ProcessApplicationPromptArn:
Value:
Ref: ProcessApplicationPrompt
Description: ARN of the prompt to process a mortgage application
RejectionPromptArn:
Value:
Ref: RejectionPrompt
Description: ARN of the prompt to reject a mortgage application
```
------
#### [ JSON ]
```
{
"AWSTemplateFormatVersion": "2010-09-09",
"Description": "[AWSDocs] AmazonBedrockDocs: getting-started-mortgage-flow",
"Resources": {
"RejectionPrompt": {
"Type": "AWS::Bedrock::Prompt",
"Properties": {
"Name": {
"Fn::Sub": "AWSDocsTutorial-RejectionPrompt"
},
"Description": "Use this prompt to generate a rejection letter triggered by an unsatisfactory income to debt ratio",
"DefaultVariant": "variantOne",
"Variants": [
{
"Name": "variantOne",
"TemplateType": "TEXT",
"ModelId": "anthropic.claude-3-haiku-20240307-v1:0",
"TemplateConfiguration": {
"Text": {
"Text": "Write a mortgage loan rejection letter for a candiate with income {{income}}, totalDebt {{totalDebt}}, loanAmount {{loanAmount}}. \nThe reason for rejection is their income to debt ratio. \nDo not mention any other reason. \nMake the letter as concise as possible. \nTreat all numeric inputs as whole numbers.\nLet the general structure be like the below:\n\nDear [Applicant's Name],\nWe appreciate your interest in obtaining a mortgage loan with our institution...\nThe primary reason for this decision is that ...\nWhile we understand that this news may be disappointing, ...\nThank you again for your interest, and we wish you the best in your future endeavors...\n\nSincerely,\n[Your Institution's Name]\n",
"InputVariables": [
{
"Name": "income"
},
{
"Name": "totalDebt"
},
{
"Name": "loanAmount"
}
]
}
},
"InferenceConfiguration": {
"Text": {
"MaxTokens": 2000,
"Temperature": 0.0,
"TopP": 0.999,
"StopSequences": [
"\n\nHuman:"
]
}
},
"AdditionalModelRequestFields": {
"top_k": 250
}
}
]
}
},
"ProcessApplicationPrompt": {
"Type": "AWS::Bedrock::Prompt",
"Properties": {
"Name": {
"Fn::Sub": "AWSDocsTutorial-ProcessApplicationPrompt"
},
"Description": "Use this prompt to generate a question for an agent to process the mortgage application",
"DefaultVariant": "variantOne",
"Variants": [
{
"Name": "variantOne",
"TemplateType": "TEXT",
"ModelId": "anthropic.claude-3-haiku-20240307-v1:0",
"TemplateConfiguration": {
"Text": {
"Text": "Generate a question asking if the user will qualify for a loan for the specified criteria. \n\nInclude instruction to base the answer on key features of the property retrieved from MLS listing. \n\nStart with \"will an applicant...\".\n\n{ \"income\": {{income}}, \"creditScore\": {{creditScore}}, \"totalDebt\": {{totalDebt}}, \"loanAmount\": {{loanAmount}}, \"mlsId\": {{mlsId}} }\n\nInclude a second question on loan requirements an applicant with the below attributes should consider for a Fannie Mae backed loan (other than debt to income).\n",
"InputVariables": [
{
"Name": "income"
},
{
"Name": "creditScore"
},
{
"Name": "totalDebt"
},
{
"Name": "loanAmount"
},
{
"Name": "mlsId"
}
]
}
},
"InferenceConfiguration": {
"Text": {
"MaxTokens": 2000,
"Temperature": 0.0,
"TopP": 0.999,
"StopSequences": [
"\n\nHuman:"
]
}
},
"AdditionalModelRequestFields": {
"top_k": 250
}
}
]
}
}
},
"Outputs": {
"ProcessApplicationPromptArn": {
"Value": {
"Ref": "ProcessApplicationPrompt"
},
"Description": "ARN of the prompt to process a mortgage application"
},
"RejectionPromptArn": {
"Value": {
"Ref": "RejectionPrompt"
},
"Description": "ARN of the prompt to reject a mortgage application"
}
}
}
```
------
## Amazon Bedrock 知识库堆栈
此模板创建包含贷款指南的[知识库](knowledge-base.md)及其数据来源：
+ KnowledgeBase ([AWS::Bedrock::KnowledgeBase](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide /aws-resource-bedrock-knowledgebase.html))
+ KnowledgeBaseDataSource ([AWS::Bedrock::DataSource](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide /aws-resource-bedrock-datasource.html))
------
#### [ YAML ]
```
AWSTemplateFormatVersion: '2010-09-09'
Description: "[AWSDocs] AmazonBedrockDocs: getting-started-mortgage-flow"
Parameters:
KnowledgeBaseName:
Type: String
Description: Name of knowledge base
Default: MortgageKB
Q01pS3BucketName:
Type: String
Description: Name of S3 bucket where knowledge base data is stored
Q06pKBEmbedModel:
Type: String
Description: Selected Embedding model
Q07pKBChunkingStrategy:
Type: String
Description: Selected Chunking strategy
Q08pKBMaxTokens:
Type: Number
Description: Maximum number of tokens in a chunk
Q09pKBOverlapPercentage:
Type: Number
Description: Percent overlap in each chunk
Q11pOSSCollectionName:
Type: String
Description: Name of the Collection
Q12pOSSIndexName:
Type: String
Description: Index name to be created in vector store
Q13pVectorFieldName:
Type: String
Description: Vector field name
Default: bedrock-knowledge-base-default-vector
Q14pMetaDataFieldName:
Type: String
Description: Metadata field name
Default: AMAZON_BEDROCK_METADATA
Q15pTextFieldName:
Type: String
Description: Text field name
Default: AMAZON_BEDROCK_TEXT_CHUNK
pCollectionArn:
Type: String
Description: Name of the Collection Arn
pKBRole:
Type: String
Description: KB role for e2e RAG
pKBRoleArn:
Type: String
Description: KB role Arn for e2e RAG
Conditions:
IsChunkingStrategyFixed:
Fn::Equals:
- Ref: Q07pKBChunkingStrategy
- Fixed-size chunking
IsChunkingStrategyDefault:
Fn::Equals:
- Ref: Q07pKBChunkingStrategy
- Default chunking
IsChunkingStrategyNoChunking:
Fn::Equals:
- Ref: Q07pKBChunkingStrategy
- No chunking
IsChunkingStrategyFixedOrDefault:
Fn::Or:
- Condition: IsChunkingStrategyFixed
- Condition: IsChunkingStrategyDefault
Resources:
KnowledgeBase:
Type: AWS::Bedrock::KnowledgeBase
Properties:
Description: Test KB Deployment
KnowledgeBaseConfiguration:
Type: VECTOR
VectorKnowledgeBaseConfiguration:
EmbeddingModelArn:
Fn::Sub: arn:aws:bedrock:${AWS::Region}::foundation-model/${Q06pKBEmbedModel}
Name: !Sub AWSDocsTutorial-${KnowledgeBaseName}
RoleArn:
Ref: pKBRoleArn
StorageConfiguration:
OpensearchServerlessConfiguration:
CollectionArn:
Ref: pCollectionArn
FieldMapping:
MetadataField:
Ref: Q14pMetaDataFieldName
TextField:
Ref: Q15pTextFieldName
VectorField:
Ref: Q13pVectorFieldName
VectorIndexName:
Ref: Q12pOSSIndexName
Type: OPENSEARCH_SERVERLESS
KnowledgeBaseDataSource:
Type: AWS::Bedrock::DataSource
DependsOn:
- KnowledgeBase
Properties:
DataSourceConfiguration:
Type: S3
S3Configuration:
BucketArn:
Fn::Sub: arn:aws:s3:::${Q01pS3BucketName}
InclusionPrefixes:
- knowledge-base-data-source/
Description: Knowledge base data source
KnowledgeBaseId:
Ref: KnowledgeBase
Name: !Sub AWSDocsTutorial-${KnowledgeBaseName}-DS
VectorIngestionConfiguration:
ChunkingConfiguration:
Fn::If:
- IsChunkingStrategyFixed
- ChunkingStrategy: FIXED_SIZE
FixedSizeChunkingConfiguration:
MaxTokens: !Ref Q08pKBMaxTokens
OverlapPercentage: !Ref Q09pKBOverlapPercentage
- Fn::If:
- IsChunkingStrategyDefault
- ChunkingStrategy: FIXED_SIZE
FixedSizeChunkingConfiguration:
MaxTokens: 300
OverlapPercentage: 20
- Fn::If:
- IsChunkingStrategyNoChunking
- ChunkingStrategy: NONE
- !Ref AWS::NoValue
Outputs:
KBId:
Value:
Ref: KnowledgeBase
Description: KnowledgeBase ID
DS:
Value:
Ref: KnowledgeBaseDataSource
Description: KnowledgeBase Datasource
```
------
#### [ JSON ]
```
{
"AWSTemplateFormatVersion": "2010-09-09",
"Description": "[AWSDocs] AmazonBedrockDocs: getting-started-mortgage-flow",
"Parameters": {
"KnowledgeBaseName": {
"Type": "String",
"Description": "Name of knowledge base",
"Default": "MortgageKB"
},
"Q01pS3BucketName": {
"Type": "String",
"Description": "Name of S3 bucket where knowledge base data is stored"
},
"Q06pKBEmbedModel": {
"Type": "String",
"Description": "Selected Embedding model"
},
"Q07pKBChunkingStrategy": {
"Type": "String",
"Description": "Selected Chunking strategy"
},
"Q08pKBMaxTokens": {
"Type": "Number",
"Description": "Maximum number of tokens in a chunk"
},
"Q09pKBOverlapPercentage": {
"Type": "Number",
"Description": "Percent overlap in each chunk"
},
"Q11pOSSCollectionName": {
"Type": "String",
"Description": "Name of the Collection"
},
"Q12pOSSIndexName": {
"Type": "String",
"Description": "Index name to be created in vector store"
},
"Q13pVectorFieldName": {
"Type": "String",
"Description": "Vector field name",
"Default": "bedrock-knowledge-base-default-vector"
},
"Q14pMetaDataFieldName": {
"Type": "String",
"Description": "Metadata field name",
"Default": "AMAZON_BEDROCK_METADATA"
},
"Q15pTextFieldName": {
"Type": "String",
"Description": "Text field name",
"Default": "AMAZON_BEDROCK_TEXT_CHUNK"
},
"pCollectionArn": {
"Type": "String",
"Description": "Name of the Collection Arn"
},
"pKBRole": {
"Type": "String",
"Description": "KB role for e2e RAG"
},
"pKBRoleArn": {
"Type": "String",
"Description": "KB role Arn for e2e RAG"
}
},
"Conditions": {
"IsChunkingStrategyFixed": {
"Fn::Equals": [
{
"Ref": "Q07pKBChunkingStrategy"
},
"Fixed-size chunking"
]
},
"IsChunkingStrategyDefault": {
"Fn::Equals": [
{
"Ref": "Q07pKBChunkingStrategy"
},
"Default chunking"
]
},
"IsChunkingStrategyNoChunking": {
"Fn::Equals": [
{
"Ref": "Q07pKBChunkingStrategy"
},
"No chunking"
]
},
"IsChunkingStrategyFixedOrDefault": {
"Fn::Or": [
{
"Condition": "IsChunkingStrategyFixed"
},
{
"Condition": "IsChunkingStrategyDefault"
}
]
}
},
"Resources": {
"KnowledgeBase": {
"Type": "AWS::Bedrock::KnowledgeBase",
"Properties": {
"Description": "Test KB Deployment",
"KnowledgeBaseConfiguration": {
"Type": "VECTOR",
"VectorKnowledgeBaseConfiguration": {
"EmbeddingModelArn": {
"Fn::Sub": "arn:aws:bedrock:${AWS::Region}::foundation-model/${Q06pKBEmbedModel}"
}
}
},
"Name": {
"Fn::Sub": "AWSDocsTutorial-${KnowledgeBaseName}"
},
"RoleArn": {
"Ref": "pKBRoleArn"
},
"StorageConfiguration": {
"OpensearchServerlessConfiguration": {
"CollectionArn": {
"Ref": "pCollectionArn"
},
"FieldMapping": {
"MetadataField": {
"Ref": "Q14pMetaDataFieldName"
},
"TextField": {
"Ref": "Q15pTextFieldName"
},
"VectorField": {
"Ref": "Q13pVectorFieldName"
}
},
"VectorIndexName": {
"Ref": "Q12pOSSIndexName"
}
},
"Type": "OPENSEARCH_SERVERLESS"
}
}
},
"KnowledgeBaseDataSource": {
"Type": "AWS::Bedrock::DataSource",
"DependsOn": [
"KnowledgeBase"
],
"Properties": {
"DataSourceConfiguration": {
"Type": "S3",
"S3Configuration": {
"BucketArn": {
"Fn::Sub": "arn:aws:s3:::${Q01pS3BucketName}"
},
"InclusionPrefixes": [
"knowledge-base-data-source/"
]
}
},
"Description": "Knowledge base data source",
"KnowledgeBaseId": {
"Ref": "KnowledgeBase"
},
"Name": {
"Fn::Sub": "AWSDocsTutorial-${KnowledgeBaseName}-DS"
},
"VectorIngestionConfiguration": {
"ChunkingConfiguration": {
"Fn::If": [
"IsChunkingStrategyFixed",
{
"ChunkingStrategy": "FIXED_SIZE",
"FixedSizeChunkingConfiguration": {
"MaxTokens": {
"Ref": "Q08pKBMaxTokens"
},
"OverlapPercentage": {
"Ref": "Q09pKBOverlapPercentage"
}
}
},
{
"Fn::If": [
"IsChunkingStrategyDefault",
{
"ChunkingStrategy": "FIXED_SIZE",
"FixedSizeChunkingConfiguration": {
"MaxTokens": 300,
"OverlapPercentage": 20
}
},
{
"Fn::If": [
"IsChunkingStrategyNoChunking",
{
"ChunkingStrategy": "NONE"
},
{
"Ref": "AWS::NoValue"
}
]
}
]
}
]
}
}
}
}
},
"Outputs": {
"KBId": {
"Value": {
"Ref": "KnowledgeBase"
},
"Description": "KnowledgeBase ID"
},
"DS": {
"Value": {
"Ref": "KnowledgeBaseDataSource"
},
"Description": "KnowledgeBase Datasource"
}
}
}
```
------
# 有关抵押贷款处理流的详细信息
中抵押贷款处理流程的直观表示 AWS 管理控制台 如下：
![\[抵押贷款处理流\]](http://docs.aws.amazon.com/zh_cn/bedrock/latest/userguide/images/cloudformation/mortgage-processing-flow.png)
## 流中的步骤
流中会发生以下步骤：
1. 从输入中获取的客户财务信息将发送到 `loanCalculator` Lambda 函数，该函数会计算客户能够承受的最高贷款额度。
1. `loanCalculator` 函数（`maximumAffordableLoan`）的输出以及来自输入的 `loanAmount` 值会发送到条件节点，然后按如下方式进行评估：
+ 如果 `loanAmount` 大于 `maximumAffordableLoan`，则会触发 `incomeDebt` 提示并生成贷款拒绝函。
+ 否则，客户的财务信息将通过 `processApplication` 提示发送给 `mortgageProcessingAgent`。该代理使用贷款计算器功能以及多重挂牌服务（MLS）查询功能，来查找 DynamoDB 表，并根据输入中指定的 MLS 房产评测客户的信息。此外，该代理会从包含房利美销售指南的知识库中查找信息。该代理使用所有这些信息来生成一个响应，分析客户是否符合所请求贷款金额的资格。