本文為英文版的機器翻譯版本，如內容有任何歧義或不一致之處，概以英文版為準。
CloudFormation 範本
您下載cloudformation-mortgage-flow-setup.zip的檔案包含下列檔案：
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deploy.sh– 殼層指令碼，可部署您的資源並準備您將使用的主要 CloudFormation 範本。 -
artifacts– 包含 .zip 檔案的資料夾，其中包含代理程式和知識庫範本的 函數：-
客服人員動作群組的 Lambda 函數
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agent_loan_calculator.zip -
mls_lookup.zip -
loader_deployment_package.zip
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用於設定知識庫的函數
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custom-resource-lambda.zip -
opensearchpy-layer.zip -
provider-event-handler.zip
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api-schema– 包含動作群組 API 結構描述的資料夾。 -
knowledge-base-data-source– 包含 Fannie Mae 銷售指南 PDF 的資料夾。 -
templates– 包含此流程中資源範本的資料夾，包括 JSON 和 YAML 格式：-
main-stack-tmp– 將其餘範本部署為巢狀堆疊的主要範本。部署指令碼執行main-stack後，此檔案會變成 。 -
guardrails-template– 要與代理程式建立關聯的護欄範本。 -
prompts-template– 要在流程中使用的提示範本。 -
kb-role-template– 知識庫角色的範本，供 OpenSearch 範本和知識庫範本使用。 -
oss-infra-template– 用於知識庫的 Amazon OpenSearch Serverless 向量存放區的範本。 -
kb-infra-template– 要與代理程式建立關聯的抵押貸款知識庫範本。 -
agent-template– 要在流程中使用的抵押貸款處理代理程式範本。 -
mortgage-flow-template– 合併所有資源的抵押貸款處理流程範本。
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README.md– README 檔案，描述使用範本的步驟。
下列主題顯示用於每個堆疊的 AWS CloudFormation 範本。主要堆疊會將剩餘的堆疊部署為巢狀堆疊。
主要堆疊
主要堆疊會定義您可以在上傳範本時定義的參數。這些值會傳遞至每個剩餘的巢狀堆疊。部署指令碼會將Q01pS3BucketName參數預設值的 MortgageFlowBucket 取代為您實際的 S3 儲存貯體，其中包含指令碼部署的資源。
- YAML
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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
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{ "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 Guardrails 堆疊
此堆疊會建立下列與護欄相關的資源：
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AgentGuardrail (AWS::Bedrock::Guardrail) – 提供內容篩選、主題政策和 PII 保護的護欄。此護欄將連接到代理程式堆疊中的代理程式。
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AgentGuardrailVersion (AWS::Bedrock::GuardrailVersion) – 套用至代理
AgentGuardrail程式的資源版本。
- YAML
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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
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{ "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 提示詞管理堆疊
此堆疊會建立下列提示 (AWS::IAM::Prompt) 資源，這些資源會新增至流程：
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RejectionPrompt – 根據財務資訊傳回產生的拒絕信件的提示。
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ProcessApplicationPrompt – 將客戶財務資訊傳送給客服人員的提示，並提示客服人員評估客戶是否符合貸款資格。
- YAML
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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
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{ "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 知識庫堆疊
此範本會建立知識庫及其資料來源，其中包含貸款準則：
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KnowledgeBase (AWS::Bedrock::KnowledgeBase)
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KnowledgeBaseDataSource (AWS::Bedrock::DataSource)
- YAML
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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
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{ "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" } } }
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