Las traducciones son generadas a través de traducción automática. En caso de conflicto entre la traducción y la version original de inglés, prevalecerá la version en inglés.
# CloudFormation plantillas
El archivo `cloudformation-mortgage-flow-setup.zip` que descarga contiene los siguientes archivos:
+ `deploy.sh`— Un script de shell que despliega tus recursos y prepara la CloudFormation plantilla principal que utilizarás.
+ `artifacts`: una carpeta que contiene archivos .zip con funciones para el agente y las plantillas de la base de conocimiento:
+ Funciones de Lambda para los grupos de acciones del agente
+ `agent_loan_calculator.zip`
+ `mls_lookup.zip`
+ `loader_deployment_package.zip`
+ Funciones para configurar la base de conocimiento
+ `custom-resource-lambda.zip`
+ `opensearchpy-layer.zip`
+ `provider-event-handler.zip`
+ `api-schema`; una carpeta que contiene esquemas de API para grupos de acción.
+ `knowledge-base-data-source`: una carpeta que contiene el PDF de la [Guía de ventas de Fannie Mae](https://selling-guide.fanniemae.com/).
+ `templates`: una carpeta que contiene las plantillas de los recursos de este flujo, tanto en formato JSON como YAML:
+ `main-stack-tmp`: la plantilla principal que implementa las plantillas restantes como pilas anidadas. Este archivo se convierte en `main-stack` después de ejecutar el script de implementación.
+ `guardrails-template`: la plantilla de la barrera de protección que se asociará al agente.
+ `prompts-template`: la plantilla para las peticiones que se utilizarán en el flujo.
+ `kb-role-template`— La plantilla para el rol de base de conocimientos, que se utilizará tanto en la OpenSearch plantilla como en la plantilla de base de conocimientos.
+ `oss-infra-template`— La plantilla del almacén vectorial de Amazon OpenSearch Serverless que se utilizará en la base de conocimientos.
+ `kb-infra-template`: la plantilla para la base de conocimiento sobre préstamos hipotecarios que se asociará al agente.
+ `agent-template`: la plantilla para el agente de procesamiento de hipotecas que se utilizará en el flujo.
+ `mortgage-flow-template`: la plantilla para el flujo de procesamiento de hipotecas que combina todos los recursos.
+ `README.md`: un archivo README que describe los pasos para usar la plantilla.
En los temas siguientes se muestran las CloudFormation plantillas utilizadas para cada pila. La pila principal implementa las pilas restantes como [pilas anidadas](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/using-cfn-nested-stacks.html).
**Topics**
+ [Pila principal](#getting-started-mortgage-templates-main)
+ [Pila de Barreras de protección para Amazon Bedrock](#getting-started-mortgage-guardrail-templates)
+ [Pila de administración de peticiones de Amazon Bedrock](#getting-started-mortgage-prompts-templates)
+ [Pila de Bases de conocimiento de Amazon Bedrock](#getting-started-mortgage-kb-templates)
## Pila principal
La pila principal define los parámetros que puede definir al cargar la plantilla. Estos valores se pasan a cada una de las pilas anidadas restantes. El script de despliegue sustituye el valor predeterminado del `Q01pS3BucketName` parámetro *MortgageFlowBucket* por el bucket de S3 real que contiene los recursos desplegados por el script.
------
#### [ 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"
]
}
}
}
}
}
}
```
------
## Pila de Barreras de protección para Amazon Bedrock
Esta pila crea los siguientes recursos relacionados con [barreras de protección](guardrails.md):
+ AgentGuardrail ([AWS::Bedrock::Guardrail](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide /aws-resource-bedrock-guardrail.html)): una barrera que proporciona filtrado de contenido, políticas temáticas y protección de la PII. Esta barrera de protección se asociará al agente en la pila del agente.
+ AgentGuardrailVersion ([AWS::Bedrock::GuardrailVersion](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide /aws-resource-bedrock-guardrailversion.html)): la versión del `AgentGuardrail` recurso aplicada al agente.
------
#### [ 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"
}
}
}
```
------
## Pila de administración de peticiones de Amazon Bedrock
Esta pila crea los siguientes recursos [prompt](prompt-management.md) ([AWS::IAM::Prompt](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide /aws-resource-bedrock-prompt.html)), que se añaden al flujo:
+ RejectionPrompt — Un mensaje que devuelve una carta de rechazo generada en función de la información financiera.
+ ProcessApplicationPrompt — Un aviso que envía la información financiera de un cliente a un agente y le pide que evalúe si el cliente reúne los requisitos para solicitar un préstamo.
------
#### [ 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"
}
}
}
```
------
## Pila de Bases de conocimiento de Amazon Bedrock
Esta plantilla crea la [base de conocimiento](knowledge-base.md) y su origen de datos que contiene las directrices sobre préstamos:
+ 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"
}
}
}
```
------