InvokeInlineAgent response, specify RETURN_CONTROL.
- `lambda` string — The Amazon Resource Name (ARN) of the Lambda function containing the business logic that is carried out upon invoking the action.
- `actionGroupName` string, password, required — The name of the action group.
- `apiSchema` object — Contains either details about the S3 object containing the OpenAPI schema for the action group or the JSON or YAML-formatted payload defining the schema. For more information, see Action group OpenAPI schemas.
- `payload` string, password — The JSON or YAML-formatted payload defining the OpenAPI schema for the action group.
- `s3` object — Contains details about the S3 object containing the OpenAPI schema for the action group.
- `s3BucketName` string — The name of the S3 bucket.
- `s3ObjectKey` string — The S3 object key for the S3 resource.
- `description` string, password — A description of the action group.
- `functionSchema` object — Contains details about the function schema for the action group or the JSON or YAML-formatted payload defining the schema.
- `functions` FunctionDefinition[] — A list of functions that each define an action in the action group.
- `description` string — A description of the function and its purpose.
- `name` string, password, required — A name for the function.
- `parameters` object — The parameters that the agent elicits from the user to fulfill the function.
- `requireConfirmation` 'ENABLED' | 'DISABLED' — Contains information if user confirmation is required to invoke the function.
- `parentActionGroupSignature` 'AMAZON.UserInput' | 'AMAZON.CodeInterpreter' | 'ANTHROPIC.Computer' | 'ANTHROPIC.Bash' | 'ANTHROPIC.TextEditor' — Specify a built-in or computer use action for this action group. If you specify a value, you must leave the description, apiSchema, and actionGroupExecutor fields empty for this action group.
To allow your agent to request the user for additional information when trying to complete a task, set this field to AMAZON.UserInput.
To allow your agent to generate, run, and troubleshoot code when trying to complete a task, set this field to AMAZON.CodeInterpreter.
To allow your agent to use an Anthropic computer use tool, specify one of the following values.
Computer use is a new Anthropic Claude model capability (in beta) available with Anthropic Claude 3.7 Sonnet and Claude 3.5 Sonnet v2 only. When operating computer use functionality, we recommend taking additional security precautions, such as executing computer actions in virtual environments with restricted data access and limited internet connectivity. For more information, see Configure an Amazon Bedrock Agent to complete tasks with computer use tools.
ANTHROPIC.Computer - Gives the agent permission to use the mouse and keyboard and take screenshots.
ANTHROPIC.TextEditor - Gives the agent permission to view, create and edit files.
ANTHROPIC.Bash - Gives the agent permission to run commands in a bash shell.
The configuration settings for a computer use action.
Computer use is a new Anthropic Claude model capability (in beta) available with Claude 3.7 Sonnet and Claude 3.5 Sonnet v2 only. For more information, see Configure an Amazon Bedrock Agent to complete tasks with computer use tools.
optimized.
- `collaboratorConfigurations` CollaboratorConfiguration[] — Settings for an inline agent collaborator called with InvokeInlineAgent.
- `agentAliasArn` string — The Amazon Resource Name (ARN) of the inline collaborator agent.
- `collaboratorInstruction` string, password, required — Instructions that tell the inline collaborator agent what it should do and how it should interact with users.
- `collaboratorName` string, password, required — Name of the inline collaborator agent which must be the same name as specified for agentName.
- `relayConversationHistory` 'TO_COLLABORATOR' | 'DISABLED' — A relay conversation history for the inline collaborator agent.
- `collaborators` Collaborator[] — List of collaborator inline agents.
- `actionGroups` AgentActionGroup[] — List of action groups with each action group defining tasks the inline collaborator agent needs to carry out.
- `actionGroupExecutor` object — The Amazon Resource Name (ARN) of the Lambda function containing the business logic that is carried out upon invoking the action or the custom control method for handling the information elicited from the user.
- `customControl` 'RETURN_CONTROL' — To return the action group invocation results directly in the InvokeInlineAgent response, specify RETURN_CONTROL.
- `lambda` string — The Amazon Resource Name (ARN) of the Lambda function containing the business logic that is carried out upon invoking the action.
- `actionGroupName` string, password, required — The name of the action group.
- `apiSchema` object — Contains either details about the S3 object containing the OpenAPI schema for the action group or the JSON or YAML-formatted payload defining the schema. For more information, see Action group OpenAPI schemas.
- `payload` string, password — The JSON or YAML-formatted payload defining the OpenAPI schema for the action group.
- `s3` object — Contains details about the S3 object containing the OpenAPI schema for the action group.
- `s3BucketName` string — The name of the S3 bucket.
- `s3ObjectKey` string — The S3 object key for the S3 resource.
- `description` string, password — A description of the action group.
- `functionSchema` object — Contains details about the function schema for the action group or the JSON or YAML-formatted payload defining the schema.
- `functions` FunctionDefinition[] — A list of functions that each define an action in the action group.
- `description` string — A description of the function and its purpose.
- `name` string, password, required — A name for the function.
- `parameters` object — The parameters that the agent elicits from the user to fulfill the function.
- `requireConfirmation` 'ENABLED' | 'DISABLED' — Contains information if user confirmation is required to invoke the function.
- `parentActionGroupSignature` 'AMAZON.UserInput' | 'AMAZON.CodeInterpreter' | 'ANTHROPIC.Computer' | 'ANTHROPIC.Bash' | 'ANTHROPIC.TextEditor' — Specify a built-in or computer use action for this action group. If you specify a value, you must leave the description, apiSchema, and actionGroupExecutor fields empty for this action group.
To allow your agent to request the user for additional information when trying to complete a task, set this field to AMAZON.UserInput.
To allow your agent to generate, run, and troubleshoot code when trying to complete a task, set this field to AMAZON.CodeInterpreter.
To allow your agent to use an Anthropic computer use tool, specify one of the following values.
Computer use is a new Anthropic Claude model capability (in beta) available with Anthropic Claude 3.7 Sonnet and Claude 3.5 Sonnet v2 only. When operating computer use functionality, we recommend taking additional security precautions, such as executing computer actions in virtual environments with restricted data access and limited internet connectivity. For more information, see Configure an Amazon Bedrock Agent to complete tasks with computer use tools.
ANTHROPIC.Computer - Gives the agent permission to use the mouse and keyboard and take screenshots.
ANTHROPIC.TextEditor - Gives the agent permission to view, create and edit files.
ANTHROPIC.Bash - Gives the agent permission to run commands in a bash shell.
The configuration settings for a computer use action.
Computer use is a new Anthropic Claude model capability (in beta) available with Claude 3.7 Sonnet and Claude 3.5 Sonnet v2 only. For more information, see Configure an Amazon Bedrock Agent to complete tasks with computer use tools.
collaboratorName.
- `collaboratorConfigurations` CollaboratorConfiguration[] — Settings of the collaborator agent.
- `agentAliasArn` string — The Amazon Resource Name (ARN) of the inline collaborator agent.
- `collaboratorInstruction` string, password, required — Instructions that tell the inline collaborator agent what it should do and how it should interact with users.
- `collaboratorName` string, password, required — Name of the inline collaborator agent which must be the same name as specified for agentName.
- `relayConversationHistory` 'TO_COLLABORATOR' | 'DISABLED' — A relay conversation history for the inline collaborator agent.
- `customerEncryptionKeyArn` string — The Amazon Resource Name (ARN) of the AWS KMS key that encrypts the inline collaborator.
- `foundationModel` string, required — The foundation model used by the inline collaborator agent.
- `guardrailConfiguration` object — Details of the guardwrail associated with the inline collaborator.
- `guardrailIdentifier` string, required — The unique identifier for the guardrail.
- `guardrailVersion` string, required — The version of the guardrail.
- `idleSessionTTLInSeconds` integer — The number of seconds for which the Amazon Bedrock keeps information about the user's conversation with the inline collaborator agent.
A user interaction remains active for the amount of time specified. If no conversation occurs during this time, the session expires and Amazon Bedrock deletes any data provided before the timeout.
- `instruction` string, password, required — Instruction that tell the inline collaborator agent what it should do and how it should interact with users. - `knowledgeBases` KnowledgeBase[] — Knowledge base associated with the inline collaborator agent. - `description` string, password, required — The description of the knowledge base associated with the inline agent. - `knowledgeBaseId` string, required — The unique identifier for a knowledge base associated with the inline agent. - `retrievalConfiguration` object — The configurations to apply to the knowledge base during query. For more information, see Query configurations. - `managedSearchConfiguration` object — Contains configurations for managed search. For more information, see Query configurations. - `filter` RetrievalFilter —Specifies the filters to use on the metadata attributes in the knowledge base data sources before returning results. For more information, see Query configurations. See the examples below to see how to use these filters.
This data type is used in the following API operations:
Retrieve request – in the filter field
RetrieveAndGenerate request – in the filter field
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value matches the value in this object.
The following example would return data sources with an animal attribute whose value is cat:
"equals": { "key": "animal", "value": "cat" }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is greater than the value in this object.
The following example would return data sources with an year attribute whose value is greater than 1989:
"greaterThan": { "key": "year", "value": 1989 }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is greater than or equal to the value in this object.
The following example would return data sources with an year attribute whose value is greater than or equal to 1989:
"greaterThanOrEquals": { "key": "year", "value": 1989 }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is in the list specified in the value in this object.
The following example would return data sources with an animal attribute that is either cat or dog:
"in": { "key": "animal", "value": ["cat", "dog"] }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is less than the value in this object.
The following example would return data sources with an year attribute whose value is less than to 1989.
"lessThan": { "key": "year", "value": 1989 }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is less than or equal to the value in this object.
The following example would return data sources with an year attribute whose value is less than or equal to 1989.
"lessThanOrEquals": { "key": "year", "value": 1989 }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is a list that contains the value as one of its members.
The following example would return data sources with an animals attribute that is a list containing a cat member (for example ["dog", "cat"]).
"listContains": { "key": "animals", "value": "cat" }
Knowledge base data sources are returned when:
It contains a metadata attribute whose name matches the key and whose value doesn't match the value in this object.
The key is not present in the document.
The following example would return data sources that don't contain an animal attribute whose value is cat.
"notEquals": { "key": "animal", "value": "cat" }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value isn't in the list specified in the value in this object.
The following example would return data sources whose animal attribute is neither cat nor dog.
"notIn": { "key": "animal", "value": ["cat", "dog"] }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value starts with the value in this object. This filter is currently only supported for Amazon OpenSearch Serverless vector stores.
The following example would return data sources with an animal attribute starts with ca (for example, cat or camel).
"startsWith": { "key": "animal", "value": "ca" }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is one of the following:
A string that contains the value as a substring. The following example would return data sources with an animal attribute that contains the substring at (for example cat).
"stringContains": { "key": "animal", "value": "at" }
A list with a member that contains the value as a substring. The following example would return data sources with an animals attribute that is a list containing a member that contains the substring at (for example ["dog", "cat"]).
"stringContains": { "key": "animals", "value": "at" }
CUSTOM to specify a model, MANAGED to use the service default, or NONE to disable reranking.
- `vectorSearchConfiguration` object — Contains details about how the results from the vector search should be returned. For more information, see Query configurations.
- `filter` object — Specifies the filters to use on the metadata in the knowledge base data sources before returning results. For more information, see Query configurations.
- `andAll` RetrievalFilter[] — Knowledge base data sources are returned if their metadata attributes fulfill all the filter conditions inside this list.
- …
- `equals` object — Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value matches the value in this object.
The following example would return data sources with an animal attribute whose value is cat:
"equals": { "key": "animal", "value": "cat" }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is greater than the value in this object.
The following example would return data sources with an year attribute whose value is greater than 1989:
"greaterThan": { "key": "year", "value": 1989 }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is greater than or equal to the value in this object.
The following example would return data sources with an year attribute whose value is greater than or equal to 1989:
"greaterThanOrEquals": { "key": "year", "value": 1989 }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is in the list specified in the value in this object.
The following example would return data sources with an animal attribute that is either cat or dog:
"in": { "key": "animal", "value": ["cat", "dog"] }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is less than the value in this object.
The following example would return data sources with an year attribute whose value is less than to 1989.
"lessThan": { "key": "year", "value": 1989 }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is less than or equal to the value in this object.
The following example would return data sources with an year attribute whose value is less than or equal to 1989.
"lessThanOrEquals": { "key": "year", "value": 1989 }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is a list that contains the value as one of its members.
The following example would return data sources with an animals attribute that is a list containing a cat member (for example ["dog", "cat"]).
"listContains": { "key": "animals", "value": "cat" }
Knowledge base data sources are returned when:
It contains a metadata attribute whose name matches the key and whose value doesn't match the value in this object.
The key is not present in the document.
The following example would return data sources that don't contain an animal attribute whose value is cat.
"notEquals": { "key": "animal", "value": "cat" }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value isn't in the list specified in the value in this object.
The following example would return data sources whose animal attribute is neither cat nor dog.
"notIn": { "key": "animal", "value": ["cat", "dog"] }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value starts with the value in this object. This filter is currently only supported for Amazon OpenSearch Serverless vector stores.
The following example would return data sources with an animal attribute starts with ca (for example, cat or camel).
"startsWith": { "key": "animal", "value": "ca" }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is one of the following:
A string that contains the value as a substring. The following example would return data sources with an animal attribute that contains the substring at (for example cat).
"stringContains": { "key": "animal", "value": "at" }
A list with a member that contains the value as a substring. The following example would return data sources with an animals attribute that is a list containing a member that contains the substring at (for example ["dog", "cat"]).
"stringContains": { "key": "animals", "value": "at" }
HYBRID search using both vector embeddings and raw text, or SEMANTIC search using only vector embeddings. For other vector store configurations, only SEMANTIC search is available. For more information, see Test a knowledge base.
- `rerankingConfiguration` object — Contains configurations for reranking the retrieved results. For more information, see Improve the relevance of query responses with a reranker model.
- `bedrockRerankingConfiguration` object — Contains configurations for an Amazon Bedrock reranker model.
- …
- `type` 'BEDROCK_RERANKING_MODEL', required — The type of reranker model.
- `promptOverrideConfiguration` object — Contains configurations to override prompt templates in different parts of an inline collaborator sequence. For more information, see Advanced prompts.
- `overrideLambda` string — The ARN of the Lambda function to use when parsing the raw foundation model output in parts of the agent sequence. If you specify this field, at least one of the promptConfigurations must contain a parserMode value that is set to OVERRIDDEN. For more information, see Parser Lambda function in Amazon Bedrock Agents.
- `promptConfigurations` PromptConfiguration[], required — Contains configurations to override a prompt template in one part of an agent sequence. For more information, see Advanced prompts.
- `additionalModelRequestFields` object — If the Converse or ConverseStream operations support the model, additionalModelRequestFields contains additional inference parameters, beyond the base set of inference parameters in the inferenceConfiguration field.
For more information, see Inference request parameters and response fields for foundation models in the Amazon Bedrock user guide.
- `basePromptTemplate` string, password — Defines the prompt template with which to replace the default prompt template. You can use placeholder variables in the base prompt template to customize the prompt. For more information, see Prompt template placeholder variables. For more information, see Configure the prompt templates. - `foundationModel` string — The foundation model to use. - `inferenceConfiguration` object — Contains inference parameters to use when the agent invokes a foundation model in the part of the agent sequence defined by thepromptType. For more information, see Inference parameters for foundation models.
- `maximumLength` integer — The maximum number of tokens allowed in the generated response.
- `stopSequences` String[] — A list of stop sequences. A stop sequence is a sequence of characters that causes the model to stop generating the response.
- `temperature` number, float — The likelihood of the model selecting higher-probability options while generating a response. A lower value makes the model more likely to choose higher-probability options, while a higher value makes the model more likely to choose lower-probability options.
- `topK` integer — While generating a response, the model determines the probability of the following token at each point of generation. The value that you set for topK is the number of most-likely candidates from which the model chooses the next token in the sequence. For example, if you set topK to 50, the model selects the next token from among the top 50 most likely choices.
- `topP` number, float — While generating a response, the model determines the probability of the following token at each point of generation. The value that you set for Top P determines the number of most-likely candidates from which the model chooses the next token in the sequence. For example, if you set topP to 0.8, the model only selects the next token from the top 80% of the probability distribution of next tokens.
- `parserMode` 'DEFAULT' | 'OVERRIDDEN' — Specifies whether to override the default parser Lambda function when parsing the raw foundation model output in the part of the agent sequence defined by the promptType. If you set the field as OVERRIDDEN, the overrideLambda field in the PromptOverrideConfiguration must be specified with the ARN of a Lambda function.
- `promptCreationMode` 'DEFAULT' | 'OVERRIDDEN' — Specifies whether to override the default prompt template for this promptType. Set this value to OVERRIDDEN to use the prompt that you provide in the basePromptTemplate. If you leave it as DEFAULT, the agent uses a default prompt template.
- `promptState` 'ENABLED' | 'DISABLED' — Specifies whether to allow the inline agent to carry out the step specified in the promptType. If you set this value to DISABLED, the agent skips that step. The default state for each promptType is as follows.
PRE_PROCESSING – ENABLED
ORCHESTRATION – ENABLED
KNOWLEDGE_BASE_RESPONSE_GENERATION – ENABLED
POST_PROCESSING – DISABLED
meta.llama3-1-70b-instruct-v1:0.
- `guardrailConfiguration` object — The configuration details for the guardrail.
- `guardrailIdentifier` string — The unique identifier for the guardrail.
- `guardrailVersion` string — The version of the guardrail.
- `idleSessionTTLInSeconds` integer — The number of seconds for which the inline agent should maintain session information. After this time expires, the subsequent InvokeInlineAgent request begins a new session.
A user interaction remains active for the amount of time specified. If no conversation occurs during this time, the session expires and the data provided before the timeout is deleted.
- `inlineSessionState` object — Contains parameters that specify various attributes that persist across a session or prompt. You can define session state attributes as key-value pairs when writing a Lambda function for an action group or pass them when making anInvokeInlineAgent request. Use session state attributes to control and provide conversational context for your inline agent and to help customize your agent's behavior. For more information, see Control session context
- `conversationHistory` object — Contains the conversation history that persist across sessions.
- `messages` Message[] — The conversation's messages.
- `content` ContentBlock[], required — The message's content.
- `text` string — The block's text.
- `role` 'user' | 'assistant', required — The message's role.
- `files` InputFile[] — Contains information about the files used by code interpreter.
- `name` string, required — The name of the source file.
- `source` object, required — Specifies where the files are located.
- `byteContent` object — The data and the text of the attached files.
- `data` string, password, required — The raw bytes of the file to attach. The maximum size of all files that is attached is 10MB. You can attach a maximum of 5 files.
- `mediaType` string, required — The MIME type of data contained in the file used for chat.
- `s3Location` object — The s3 location of the files to attach.
- `uri` string, required — The uri of the s3 object.
- `sourceType` 'S3' | 'BYTE_CONTENT', required — The source type of the files to attach.
- `useCase` 'CODE_INTERPRETER' | 'CHAT', required — Specifies how the source files will be used by the code interpreter.
- `invocationId` string — The identifier of the invocation of an action. This value must match the invocationId returned in the InvokeInlineAgent response for the action whose results are provided in the returnControlInvocationResults field. For more information, see Return control to the agent developer.
- `promptSessionAttributes` object — Contains attributes that persist across a session and the values of those attributes.
- `returnControlInvocationResults` InvocationResultMember[] — Contains information about the results from the action group invocation. For more information, see Return control to the agent developer.
If you include this field in the sessionState field, the inputText field will be ignored.
TEXT is supported). The response may be returned directly or from the Lambda function.
- `responseState` 'FAILURE' | 'REPROMPT' — Controls the final response state returned to end user when API/Function execution failed. When this state is FAILURE, the request would fail with dependency failure exception. When this state is REPROMPT, the API/function response will be sent to model for re-prompt
- `functionResult` object — The result from the function from the action group invocation.
- `actionGroup` string, required — The action group that the function belongs to.
- `agentId` string — The agent's ID.
- `confirmationState` 'CONFIRM' | 'DENY' — Contains the user confirmation information about the function that was called.
- `function` string — The name of the function that was called.
- `responseBody` object — The response from the function call using the parameters. The response might be returned directly or from the Lambda function. Specify TEXT or IMAGES. The key of the object is the content type. You can only specify one type. If you specify IMAGES, you can specify only one image. You can specify images only when the function in the returnControlInvocationResults is a computer use action. For more information, see Configure an Amazon Bedrock Agent to complete tasks with computer use tools.
- `responseState` 'FAILURE' | 'REPROMPT' — Controls the final response state returned to end user when API/Function execution failed. When this state is FAILURE, the request would fail with dependency failure exception. When this state is REPROMPT, the API/function response will be sent to model for re-prompt
- `sessionAttributes` object — Contains attributes that persist across a session and the values of those attributes.
- `inputText` string, password — The prompt text to send to the agent.
If you include returnControlInvocationResults in the sessionState field, the inputText field will be ignored.
Specifies the filters to use on the metadata attributes in the knowledge base data sources before returning results. For more information, see Query configurations. See the examples below to see how to use these filters.
This data type is used in the following API operations:
Retrieve request – in the filter field
RetrieveAndGenerate request – in the filter field
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value matches the value in this object.
The following example would return data sources with an animal attribute whose value is cat:
"equals": { "key": "animal", "value": "cat" }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is greater than the value in this object.
The following example would return data sources with an year attribute whose value is greater than 1989:
"greaterThan": { "key": "year", "value": 1989 }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is greater than or equal to the value in this object.
The following example would return data sources with an year attribute whose value is greater than or equal to 1989:
"greaterThanOrEquals": { "key": "year", "value": 1989 }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is in the list specified in the value in this object.
The following example would return data sources with an animal attribute that is either cat or dog:
"in": { "key": "animal", "value": ["cat", "dog"] }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is less than the value in this object.
The following example would return data sources with an year attribute whose value is less than to 1989.
"lessThan": { "key": "year", "value": 1989 }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is less than or equal to the value in this object.
The following example would return data sources with an year attribute whose value is less than or equal to 1989.
"lessThanOrEquals": { "key": "year", "value": 1989 }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is a list that contains the value as one of its members.
The following example would return data sources with an animals attribute that is a list containing a cat member (for example ["dog", "cat"]).
"listContains": { "key": "animals", "value": "cat" }
Knowledge base data sources are returned when:
It contains a metadata attribute whose name matches the key and whose value doesn't match the value in this object.
The key is not present in the document.
The following example would return data sources that don't contain an animal attribute whose value is cat.
"notEquals": { "key": "animal", "value": "cat" }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value isn't in the list specified in the value in this object.
The following example would return data sources whose animal attribute is neither cat nor dog.
"notIn": { "key": "animal", "value": ["cat", "dog"] }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value starts with the value in this object. This filter is currently only supported for Amazon OpenSearch Serverless vector stores.
The following example would return data sources with an animal attribute starts with ca (for example, cat or camel).
"startsWith": { "key": "animal", "value": "ca" }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is one of the following:
A string that contains the value as a substring. The following example would return data sources with an animal attribute that contains the substring at (for example cat).
"stringContains": { "key": "animal", "value": "at" }
A list with a member that contains the value as a substring. The following example would return data sources with an animals attribute that is a list containing a member that contains the substring at (for example ["dog", "cat"]).
"stringContains": { "key": "animals", "value": "at" }
CUSTOM to specify a model, MANAGED to use the service default, or NONE to disable reranking.
- `vectorSearchConfiguration` object — Contains details about how the results from the vector search should be returned. For more information, see Query configurations.
- `filter` object — Specifies the filters to use on the metadata in the knowledge base data sources before returning results. For more information, see Query configurations.
- `andAll` RetrievalFilter[] — Knowledge base data sources are returned if their metadata attributes fulfill all the filter conditions inside this list.
- `andAll` RetrievalFilter[] — Knowledge base data sources are returned if their metadata attributes fulfill all the filter conditions inside this list.
- `equals` object — Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value matches the value in this object.
The following example would return data sources with an animal attribute whose value is cat:
"equals": { "key": "animal", "value": "cat" }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is greater than the value in this object.
The following example would return data sources with an year attribute whose value is greater than 1989:
"greaterThan": { "key": "year", "value": 1989 }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is greater than or equal to the value in this object.
The following example would return data sources with an year attribute whose value is greater than or equal to 1989:
"greaterThanOrEquals": { "key": "year", "value": 1989 }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is in the list specified in the value in this object.
The following example would return data sources with an animal attribute that is either cat or dog:
"in": { "key": "animal", "value": ["cat", "dog"] }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is less than the value in this object.
The following example would return data sources with an year attribute whose value is less than to 1989.
"lessThan": { "key": "year", "value": 1989 }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is less than or equal to the value in this object.
The following example would return data sources with an year attribute whose value is less than or equal to 1989.
"lessThanOrEquals": { "key": "year", "value": 1989 }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is a list that contains the value as one of its members.
The following example would return data sources with an animals attribute that is a list containing a cat member (for example ["dog", "cat"]).
"listContains": { "key": "animals", "value": "cat" }
Knowledge base data sources are returned when:
It contains a metadata attribute whose name matches the key and whose value doesn't match the value in this object.
The key is not present in the document.
The following example would return data sources that don't contain an animal attribute whose value is cat.
"notEquals": { "key": "animal", "value": "cat" }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value isn't in the list specified in the value in this object.
The following example would return data sources whose animal attribute is neither cat nor dog.
"notIn": { "key": "animal", "value": ["cat", "dog"] }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value starts with the value in this object. This filter is currently only supported for Amazon OpenSearch Serverless vector stores.
The following example would return data sources with an animal attribute starts with ca (for example, cat or camel).
"startsWith": { "key": "animal", "value": "ca" }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is one of the following:
A string that contains the value as a substring. The following example would return data sources with an animal attribute that contains the substring at (for example cat).
"stringContains": { "key": "animal", "value": "at" }
A list with a member that contains the value as a substring. The following example would return data sources with an animals attribute that is a list containing a member that contains the substring at (for example ["dog", "cat"]).
"stringContains": { "key": "animals", "value": "at" }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value matches the value in this object.
The following example would return data sources with an animal attribute whose value is cat:
"equals": { "key": "animal", "value": "cat" }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is greater than the value in this object.
The following example would return data sources with an year attribute whose value is greater than 1989:
"greaterThan": { "key": "year", "value": 1989 }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is greater than or equal to the value in this object.
The following example would return data sources with an year attribute whose value is greater than or equal to 1989:
"greaterThanOrEquals": { "key": "year", "value": 1989 }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is in the list specified in the value in this object.
The following example would return data sources with an animal attribute that is either cat or dog:
"in": { "key": "animal", "value": ["cat", "dog"] }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is less than the value in this object.
The following example would return data sources with an year attribute whose value is less than to 1989.
"lessThan": { "key": "year", "value": 1989 }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is less than or equal to the value in this object.
The following example would return data sources with an year attribute whose value is less than or equal to 1989.
"lessThanOrEquals": { "key": "year", "value": 1989 }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is a list that contains the value as one of its members.
The following example would return data sources with an animals attribute that is a list containing a cat member (for example ["dog", "cat"]).
"listContains": { "key": "animals", "value": "cat" }
Knowledge base data sources are returned when:
It contains a metadata attribute whose name matches the key and whose value doesn't match the value in this object.
The key is not present in the document.
The following example would return data sources that don't contain an animal attribute whose value is cat.
"notEquals": { "key": "animal", "value": "cat" }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value isn't in the list specified in the value in this object.
The following example would return data sources whose animal attribute is neither cat nor dog.
"notIn": { "key": "animal", "value": ["cat", "dog"] }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value matches the value in this object.
The following example would return data sources with an animal attribute whose value is cat:
"equals": { "key": "animal", "value": "cat" }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is greater than the value in this object.
The following example would return data sources with an year attribute whose value is greater than 1989:
"greaterThan": { "key": "year", "value": 1989 }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is greater than or equal to the value in this object.
The following example would return data sources with an year attribute whose value is greater than or equal to 1989:
"greaterThanOrEquals": { "key": "year", "value": 1989 }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is in the list specified in the value in this object.
The following example would return data sources with an animal attribute that is either cat or dog:
"in": { "key": "animal", "value": ["cat", "dog"] }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is less than the value in this object.
The following example would return data sources with an year attribute whose value is less than to 1989.
"lessThan": { "key": "year", "value": 1989 }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is less than or equal to the value in this object.
The following example would return data sources with an year attribute whose value is less than or equal to 1989.
"lessThanOrEquals": { "key": "year", "value": 1989 }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is a list that contains the value as one of its members.
The following example would return data sources with an animals attribute that is a list containing a cat member (for example ["dog", "cat"]).
"listContains": { "key": "animals", "value": "cat" }
Knowledge base data sources are returned when:
It contains a metadata attribute whose name matches the key and whose value doesn't match the value in this object.
The key is not present in the document.
The following example would return data sources that don't contain an animal attribute whose value is cat.
"notEquals": { "key": "animal", "value": "cat" }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value isn't in the list specified in the value in this object.
The following example would return data sources whose animal attribute is neither cat nor dog.
"notIn": { "key": "animal", "value": ["cat", "dog"] }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value starts with the value in this object. This filter is currently only supported for Amazon OpenSearch Serverless vector stores.
The following example would return data sources with an animal attribute starts with ca (for example, cat or camel).
"startsWith": { "key": "animal", "value": "ca" }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is one of the following:
A string that contains the value as a substring. The following example would return data sources with an animal attribute that contains the substring at (for example cat).
"stringContains": { "key": "animal", "value": "at" }
A list with a member that contains the value as a substring. The following example would return data sources with an animals attribute that is a list containing a member that contains the substring at (for example ["dog", "cat"]).
"stringContains": { "key": "animals", "value": "at" }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value starts with the value in this object. This filter is currently only supported for Amazon OpenSearch Serverless vector stores.
The following example would return data sources with an animal attribute starts with ca (for example, cat or camel).
"startsWith": { "key": "animal", "value": "ca" }
Knowledge base data sources are returned if they contain a metadata attribute whose name matches the key and whose value is one of the following:
A string that contains the value as a substring. The following example would return data sources with an animal attribute that contains the substring at (for example cat).
"stringContains": { "key": "animal", "value": "at" }
A list with a member that contains the value as a substring. The following example would return data sources with an animals attribute that is a list containing a member that contains the substring at (for example ["dog", "cat"]).
"stringContains": { "key": "animals", "value": "at" }
HYBRID search using both vector embeddings and raw text, or SEMANTIC search using only vector embeddings. For other vector store configurations, only SEMANTIC search is available. For more information, see Test a knowledge base.
- `rerankingConfiguration` object — Contains configurations for reranking the retrieved results. For more information, see Improve the relevance of query responses with a reranker model.
- `bedrockRerankingConfiguration` object — Contains configurations for an Amazon Bedrock reranker model.
- `metadataConfiguration` object — Contains configurations for the metadata to use in reranking.
- …
- `modelConfiguration` object, required — Contains configurations for the reranker model.
- …
- `numberOfRerankedResults` integer — The number of results to return after reranking.
- `type` 'BEDROCK_RERANKING_MODEL', required — The type of reranker model.
- `orchestrationType` 'DEFAULT' | 'CUSTOM_ORCHESTRATION' — Specifies the type of orchestration strategy for the agent. This is set to DEFAULT orchestration type, by default.
- `promptCreationConfigurations` object — Specifies parameters that control how the service populates the agent prompt for an InvokeAgent or InvokeInlineAgent request. You can control which aspects of previous invocations in the same agent session the service uses to populate the agent prompt. This gives you more granular control over the contextual history that is used to process the current request.
- `excludePreviousThinkingSteps` boolean — If true, the service removes any content between <thinking> tags from previous conversations in an agent session. The service will only remove content from already processed turns. This helps you remove content which might not be useful for current and subsequent invocations. This can reduce the input token count and potentially save costs. The default value is false.
- `previousConversationTurnsToInclude` integer — The number of previous conversations from the ongoing agent session to include in the conversation history of the agent prompt, during the current invocation. This gives you more granular control over the context that the model is made aware of, and helps the model remove older context which is no longer useful during the ongoing agent session.
- `promptOverrideConfiguration` object — Contains configurations to override prompts in different parts of an agent sequence. For more information, see Advanced prompts.
- `overrideLambda` string — The ARN of the Lambda function to use when parsing the raw foundation model output in parts of the agent sequence. If you specify this field, at least one of the promptConfigurations must contain a parserMode value that is set to OVERRIDDEN. For more information, see Parser Lambda function in Amazon Bedrock Agents.
- `promptConfigurations` PromptConfiguration[] — Contains configurations to override a prompt template in one part of an agent sequence. For more information, see Advanced prompts.
- `additionalModelRequestFields` object — If the Converse or ConverseStream operations support the model, additionalModelRequestFields contains additional inference parameters, beyond the base set of inference parameters in the inferenceConfiguration field.
For more information, see Inference request parameters and response fields for foundation models in the Amazon Bedrock user guide.
- `basePromptTemplate` string, password — Defines the prompt template with which to replace the default prompt template. You can use placeholder variables in the base prompt template to customize the prompt. For more information, see Prompt template placeholder variables. For more information, see Configure the prompt templates. - `foundationModel` string — The foundation model to use. - `inferenceConfiguration` object — Contains inference parameters to use when the agent invokes a foundation model in the part of the agent sequence defined by thepromptType. For more information, see Inference parameters for foundation models.
- `maximumLength` integer — The maximum number of tokens allowed in the generated response.
- `stopSequences` String[] — A list of stop sequences. A stop sequence is a sequence of characters that causes the model to stop generating the response.
- `temperature` number, float — The likelihood of the model selecting higher-probability options while generating a response. A lower value makes the model more likely to choose higher-probability options, while a higher value makes the model more likely to choose lower-probability options.
- `topK` integer — While generating a response, the model determines the probability of the following token at each point of generation. The value that you set for topK is the number of most-likely candidates from which the model chooses the next token in the sequence. For example, if you set topK to 50, the model selects the next token from among the top 50 most likely choices.
- `topP` number, float — While generating a response, the model determines the probability of the following token at each point of generation. The value that you set for Top P determines the number of most-likely candidates from which the model chooses the next token in the sequence. For example, if you set topP to 0.8, the model only selects the next token from the top 80% of the probability distribution of next tokens.
- `parserMode` 'DEFAULT' | 'OVERRIDDEN' — Specifies whether to override the default parser Lambda function when parsing the raw foundation model output in the part of the agent sequence defined by the promptType. If you set the field as OVERRIDDEN, the overrideLambda field in the PromptOverrideConfiguration must be specified with the ARN of a Lambda function.
- `promptCreationMode` 'DEFAULT' | 'OVERRIDDEN' — Specifies whether to override the default prompt template for this promptType. Set this value to OVERRIDDEN to use the prompt that you provide in the basePromptTemplate. If you leave it as DEFAULT, the agent uses a default prompt template.
- `promptState` 'ENABLED' | 'DISABLED' — Specifies whether to allow the inline agent to carry out the step specified in the promptType. If you set this value to DISABLED, the agent skips that step. The default state for each promptType is as follows.
PRE_PROCESSING – ENABLED
ORCHESTRATION – ENABLED
KNOWLEDGE_BASE_RESPONSE_GENERATION – ENABLED
POST_PROCESSING – DISABLED
The guardrail interval to apply as response is generated. By default, the guardrail interval is set to 50 characters. If a larger interval is specified, the response will be generated in larger chunks with fewer ApplyGuardrail calls. The following examples show the response generated for Hello, I am an agent input string.
Example response in chunks: Interval set to 3 characters
'Hel', 'lo, ','I am', ' an', ' Age', 'nt'
Each chunk has at least 3 characters except for the last chunk
Example response in chunks: Interval set to 20 or more characters
Hello, I am an Agent
false by default.
## Response `200`
Success
- InvokeInlineAgentResponse
- `completion` object, required — The inline agent's response to the user prompt.
- `accessDeniedException` object — The request is denied because of missing access permissions. Check your permissions and retry your request.
- `message` string
- `badGatewayException` object — There was an issue with a dependency due to a server issue. Retry your request.
- `message` string
- `resourceName` string — The name of the dependency that caused the issue, such as Amazon Bedrock, Lambda, or STS.
- `chunk` object — Contains a part of an agent response and citations for it.
- `attribution` object — Contains citations for a part of an agent response.
- `citations` Citation[] — A list of citations and related information for a part of an agent response.
- `generatedResponsePart` object — Contains the generated response and metadata
- `textResponsePart` object — Contains metadata about a textual part of the generated response that is accompanied by a citation.
- …
- `retrievedReferences` RetrievedReference[] — Contains metadata about the sources cited for the generated response.
- `content` object — Contains the cited text from the data source.
- …
- `location` object — Contains information about the location of the data source.
- …
- `metadata` object — Contains metadata attributes and their values for the file in the data source. For more information, see Metadata and filtering.
- `bytes` string, password — A part of the agent response in bytes.
- `conflictException` object — There was a conflict performing an operation. Resolve the conflict and retry your request.
- `message` string
- `dependencyFailedException` object — There was an issue with a dependency. Check the resource configurations and retry the request.
- `message` string
- `resourceName` string — The name of the dependency that caused the issue, such as Amazon Bedrock, Lambda, or STS.
- `files` object — Contains intermediate response for code interpreter if any files have been generated.
- `files` OutputFile[] — Files containing intermediate response for the user.
- `bytes` string, password — The byte count of files that contains response from code interpreter.
- `name` string — The name of the file containing response from code interpreter.
- `type` string — The type of file that contains response from the code interpreter.
- `internalServerException` object — An internal server error occurred. Retry your request.
- `message` string
- `reason` string — The reason for the exception. If the reason is BEDROCK_MODEL_INVOCATION_SERVICE_UNAVAILABLE, the model invocation service is unavailable. Retry your request.
- `resourceNotFoundException` object — The specified resource Amazon Resource Name (ARN) was not found. Check the Amazon Resource Name (ARN) and try your request again.
- `message` string
- `returnControl` object — Contains the parameters and information that the agent elicited from the customer to carry out an action. This information is returned to the system and can be used in your own setup for fulfilling the action.
- `invocationId` string — The identifier of the action group invocation.
- `invocationInputs` InvocationInputMember[] — A list of objects that contain information about the parameters and inputs that need to be sent into the API operation or function, based on what the agent determines from its session with the user.
- `apiInvocationInput` object — Contains information about the API operation that the agent predicts should be called.
- `actionGroup` string, required — The action group that the API operation belongs to.
- `actionInvocationType` 'RESULT' | 'USER_CONFIRMATION' | 'USER_CONFIRMATION_AND_RESULT' — Contains information about the API operation to invoke.
- `agentId` string — The agent's ID.
- `apiPath` string, password — The path to the API operation.
- `collaboratorName` string, password — The agent collaborator's name.
- `httpMethod` string — The HTTP method of the API operation.
- `parameters` ApiParameter[] — The parameters to provide for the API request, as the agent elicited from the user.
- `name` string — The name of the parameter.
- `type` string — The data type for the parameter.
- `value` string — The value of the parameter.
- `requestBody` object — The request body to provide for the API request, as the agent elicited from the user.
- `content` object — The content of the request body. The key of the object in this field is a media type defining the format of the request body.
- `functionInvocationInput` object — Contains information about the function that the agent predicts should be called.
- `actionGroup` string, required — The action group that the function belongs to.
- `actionInvocationType` 'RESULT' | 'USER_CONFIRMATION' | 'USER_CONFIRMATION_AND_RESULT' — Contains information about the function to invoke,
- `agentId` string — The agent's ID.
- `collaboratorName` string, password — The collaborator's name.
- `function` string — The name of the function.
- `parameters` FunctionParameter[] — A list of parameters of the function.
- `name` string — The name of the parameter.
- `type` string — The data type of the parameter.
- `value` string — The value of the parameter.
- `serviceQuotaExceededException` object — The number of requests exceeds the service quota. Resubmit your request later.
- `message` string
- `throttlingException` object — The number of requests exceeds the limit. Resubmit your request later.
- `message` string
- `trace` object — Contains information about the agent and session, alongside the agent's reasoning process and results from calling actions and querying knowledge bases and metadata about the trace. You can use the trace to understand how the agent arrived at the response it provided the customer. For more information, see Trace events.
- `callerChain` Caller[] — The caller chain for the trace part.
- `agentAliasArn` string — The caller's agent alias ARN.
- `collaboratorName` string, password — The collaborator name for the trace part.
- `eventTime` string, date-time — The time that trace occurred.
- `sessionId` string — The unique identifier of the session with the agent.
- `trace` object — Contains one part of the agent's reasoning process and results from calling API actions and querying knowledge bases. You can use the trace to understand how the agent arrived at the response it provided the customer. For more information, see Trace enablement.
- `customOrchestrationTrace` object — Details about the custom orchestration step in which the agent determines the order in which actions are executed.
- `event` object — The event details used with the custom orchestration.
- `text` string — The text that prompted the event at this step.
- `traceId` string — The unique identifier of the trace.
- `failureTrace` object — Contains information about the failure of the interaction.
- `failureCode` integer — The failure code for the trace.
- `failureReason` string, password — The reason the interaction failed.
- `metadata` object — Information about the failure that occurred.
- `clientRequestId` string — A unique identifier associated with the downstream invocation. This ID can be used for tracing, debugging, and identifying specific invocations in customer logs or systems.
- `endTime` string, date-time — In the final response, endTime is the end time of the agent invocation operation.
- `operationTotalTimeMs` integer — The total time it took for the agent to complete execution. This field is only set for the final response.
- `startTime` string, date-time — In the final response, startTime is the start time of the agent invocation operation.
- `totalTimeMs` integer — The total execution time for the specific invocation being processed (model, knowledge base, guardrail, agent collaborator, or code interpreter). It represents how long the individual invocation took.
- `usage` object — Specific to model invocation and contains details about the usage of a foundation model.
- …
- `traceId` string — The unique identifier of the trace.
- `guardrailTrace` object — The trace details for a trace defined in the Guardrail filter.
- `action` 'INTERVENED' | 'NONE' — The trace action details used with the Guardrail.
- `inputAssessments` GuardrailAssessment[] — The details of the input assessments used in the Guardrail Trace.
- `contentPolicy` object — Content policy details of the Guardrail.
- …
- `sensitiveInformationPolicy` object — Sensitive Information policy details of Guardrail.
- …
- `topicPolicy` object — Topic policy details of the Guardrail.
- …
- `wordPolicy` object — Word policy details of the Guardrail.
- …
- `metadata` object — Contains information about the Guardrail output.
- `clientRequestId` string — A unique identifier associated with the downstream invocation. This ID can be used for tracing, debugging, and identifying specific invocations in customer logs or systems.
- `endTime` string, date-time — In the final response, endTime is the end time of the agent invocation operation.
- `operationTotalTimeMs` integer — The total time it took for the agent to complete execution. This field is only set for the final response.
- `startTime` string, date-time — In the final response, startTime is the start time of the agent invocation operation.
- `totalTimeMs` integer — The total execution time for the specific invocation being processed (model, knowledge base, guardrail, agent collaborator, or code interpreter). It represents how long the individual invocation took.
- `usage` object — Specific to model invocation and contains details about the usage of a foundation model.
- …
- `outputAssessments` GuardrailAssessment[] — The details of the output assessments used in the Guardrail Trace.
- `contentPolicy` object — Content policy details of the Guardrail.
- …
- `sensitiveInformationPolicy` object — Sensitive Information policy details of Guardrail.
- …
- `topicPolicy` object — Topic policy details of the Guardrail.
- …
- `wordPolicy` object — Word policy details of the Guardrail.
- …
- `traceId` string — The details of the trace Id used in the Guardrail Trace.
- `orchestrationTrace` object — Details about the orchestration step, in which the agent determines the order in which actions are executed and which knowledge bases are retrieved.
- `invocationInput` object — Contains information pertaining to the action group or knowledge base that is being invoked.
- `actionGroupInvocationInput` object — Contains information about the action group to be invoked.
- …
- `agentCollaboratorInvocationInput` object — The collaborator's invocation input.
- …
- `codeInterpreterInvocationInput` object — Contains information about the code interpreter to be invoked.
- …
- `invocationType` 'ACTION_GROUP' | 'KNOWLEDGE_BASE' | 'FINISH' | 'ACTION_GROUP_CODE_INTERPRETER' | 'AGENT_COLLABORATOR' — Specifies whether the agent is invoking an action group or a knowledge base.
- `knowledgeBaseLookupInput` object — Contains details about the knowledge base to look up and the query to be made.
- …
- `traceId` string — The unique identifier of the trace.
- `modelInvocationInput` object — The input for the orchestration step.
The type is ORCHESTRATION.
The text contains the prompt.
The inferenceConfiguration, parserMode, and overrideLambda values are set in the PromptOverrideConfiguration object that was set when the agent was created or updated.
promptType.
- `promptCreationMode` 'DEFAULT' | 'OVERRIDDEN' — Specifies whether the default prompt template was OVERRIDDEN. If it was, the basePromptTemplate that was set in the PromptOverrideConfiguration object when the agent was created or updated is used instead.
- `text` string, password — The text that prompted the agent at this step.
- `traceId` string — The unique identifier of the trace.
- `type` 'PRE_PROCESSING' | 'ORCHESTRATION' | 'KNOWLEDGE_BASE_RESPONSE_GENERATION' | 'POST_PROCESSING' | 'ROUTING_CLASSIFIER' — The step in the agent sequence.
- `modelInvocationOutput` object — Contains information pertaining to the output from the foundation model that is being invoked.
- `metadata` object — Contains information about the foundation model output from the orchestration step.
- …
- `rawResponse` object — Contains details of the raw response from the foundation model output.
- …
- `reasoningContent` object — Contains content about the reasoning that the model made during the orchestration step.
- …
- `traceId` string — The unique identifier of the trace.
- `observation` object — Details about the observation (the output of the action group Lambda or knowledge base) made by the agent.
- `actionGroupInvocationOutput` object — Contains the JSON-formatted string returned by the API invoked by the action group.
- …
- `agentCollaboratorInvocationOutput` object — A collaborator's invocation output.
- …
- `codeInterpreterInvocationOutput` object — Contains the JSON-formatted string returned by the API invoked by the code interpreter.
- …
- `finalResponse` object — Contains details about the response to the user.
- …
- `knowledgeBaseLookupOutput` object — Contains details about the results from looking up the knowledge base.
- …
- `repromptResponse` object — Contains details about the response to reprompt the input.
- …
- `traceId` string — The unique identifier of the trace.
- `type` 'ACTION_GROUP' | 'AGENT_COLLABORATOR' | 'KNOWLEDGE_BASE' | 'FINISH' | 'ASK_USER' | 'REPROMPT' — Specifies what kind of information the agent returns in the observation. The following values are possible.
ACTION_GROUP – The agent returns the result of an action group.
KNOWLEDGE_BASE – The agent returns information from a knowledge base.
FINISH – The agent returns a final response to the user with no follow-up.
ASK_USER – The agent asks the user a question.
REPROMPT – The agent prompts the user again for the same information.
The input for the post-processing step.
The type is POST_PROCESSING.
The text contains the prompt.
The inferenceConfiguration, parserMode, and overrideLambda values are set in the PromptOverrideConfiguration object that was set when the agent was created or updated.
promptType.
- `promptCreationMode` 'DEFAULT' | 'OVERRIDDEN' — Specifies whether the default prompt template was OVERRIDDEN. If it was, the basePromptTemplate that was set in the PromptOverrideConfiguration object when the agent was created or updated is used instead.
- `text` string, password — The text that prompted the agent at this step.
- `traceId` string — The unique identifier of the trace.
- `type` 'PRE_PROCESSING' | 'ORCHESTRATION' | 'KNOWLEDGE_BASE_RESPONSE_GENERATION' | 'POST_PROCESSING' | 'ROUTING_CLASSIFIER' — The step in the agent sequence.
- `modelInvocationOutput` object — The foundation model output from the post-processing step.
- `metadata` object — Contains information about the foundation model output from the post-processing step.
- …
- `parsedResponse` object — Details about the response from the Lambda parsing of the output of the post-processing step.
- …
- `rawResponse` object — Details of the raw response from the foundation model output.
- …
- `reasoningContent` object — Contains content about the reasoning that the model made during the post-processing step.
- …
- `traceId` string — The unique identifier of the trace.
- `preProcessingTrace` object — Details about the pre-processing step, in which the agent contextualizes and categorizes user inputs.
- `modelInvocationInput` object — The input for the pre-processing step.
The type is PRE_PROCESSING.
The text contains the prompt.
The inferenceConfiguration, parserMode, and overrideLambda values are set in the PromptOverrideConfiguration object that was set when the agent was created or updated.
promptType.
- `promptCreationMode` 'DEFAULT' | 'OVERRIDDEN' — Specifies whether the default prompt template was OVERRIDDEN. If it was, the basePromptTemplate that was set in the PromptOverrideConfiguration object when the agent was created or updated is used instead.
- `text` string, password — The text that prompted the agent at this step.
- `traceId` string — The unique identifier of the trace.
- `type` 'PRE_PROCESSING' | 'ORCHESTRATION' | 'KNOWLEDGE_BASE_RESPONSE_GENERATION' | 'POST_PROCESSING' | 'ROUTING_CLASSIFIER' — The step in the agent sequence.
- `modelInvocationOutput` object — The foundation model output from the pre-processing step.
- `metadata` object — Contains information about the foundation model output from the pre-processing step.
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- `parsedResponse` object — Details about the response from the Lambda parsing of the output of the pre-processing step.
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- `rawResponse` object — Details of the raw response from the foundation model output.
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- `reasoningContent` object — Contains content about the reasoning that the model made during the pre-processing step.
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- `traceId` string — The unique identifier of the trace.
- `routingClassifierTrace` object — A routing classifier's trace.
- `invocationInput` object — The classifier's invocation input.
- `actionGroupInvocationInput` object — Contains information about the action group to be invoked.
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- `agentCollaboratorInvocationInput` object — The collaborator's invocation input.
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- `codeInterpreterInvocationInput` object — Contains information about the code interpreter to be invoked.
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- `invocationType` 'ACTION_GROUP' | 'KNOWLEDGE_BASE' | 'FINISH' | 'ACTION_GROUP_CODE_INTERPRETER' | 'AGENT_COLLABORATOR' — Specifies whether the agent is invoking an action group or a knowledge base.
- `knowledgeBaseLookupInput` object — Contains details about the knowledge base to look up and the query to be made.
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- `traceId` string — The unique identifier of the trace.
- `modelInvocationInput` object — The classifier's model invocation input.
- `foundationModel` string — The identifier of a foundation model.
- `inferenceConfiguration` object — Specifications about the inference parameters that were provided alongside the prompt. These are specified in the PromptOverrideConfiguration object that was set when the agent was created or updated. For more information, see Inference parameters for foundation models.
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- `overrideLambda` string — The ARN of the Lambda function to use when parsing the raw foundation model output in parts of the agent sequence.
- `parserMode` 'DEFAULT' | 'OVERRIDDEN' — Specifies whether to override the default parser Lambda function when parsing the raw foundation model output in the part of the agent sequence defined by the promptType.
- `promptCreationMode` 'DEFAULT' | 'OVERRIDDEN' — Specifies whether the default prompt template was OVERRIDDEN. If it was, the basePromptTemplate that was set in the PromptOverrideConfiguration object when the agent was created or updated is used instead.
- `text` string, password — The text that prompted the agent at this step.
- `traceId` string — The unique identifier of the trace.
- `type` 'PRE_PROCESSING' | 'ORCHESTRATION' | 'KNOWLEDGE_BASE_RESPONSE_GENERATION' | 'POST_PROCESSING' | 'ROUTING_CLASSIFIER' — The step in the agent sequence.
- `modelInvocationOutput` object — The classifier's model invocation output.
- `metadata` object — The invocation's metadata.
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- `rawResponse` object — The invocation's raw response.
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- `traceId` string — The invocation's trace ID.
- `observation` object — The classifier's observation.
- `actionGroupInvocationOutput` object — Contains the JSON-formatted string returned by the API invoked by the action group.
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- `agentCollaboratorInvocationOutput` object — A collaborator's invocation output.
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- `codeInterpreterInvocationOutput` object — Contains the JSON-formatted string returned by the API invoked by the code interpreter.
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- `finalResponse` object — Contains details about the response to the user.
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- `knowledgeBaseLookupOutput` object — Contains details about the results from looking up the knowledge base.
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- `repromptResponse` object — Contains details about the response to reprompt the input.
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- `traceId` string — The unique identifier of the trace.
- `type` 'ACTION_GROUP' | 'AGENT_COLLABORATOR' | 'KNOWLEDGE_BASE' | 'FINISH' | 'ASK_USER' | 'REPROMPT' — Specifies what kind of information the agent returns in the observation. The following values are possible.
ACTION_GROUP – The agent returns the result of an action group.
KNOWLEDGE_BASE – The agent returns information from a knowledge base.
FINISH – The agent returns a final response to the user with no follow-up.
ASK_USER – The agent asks the user a question.
REPROMPT – The agent prompts the user again for the same information.