[ aws . bedrock-agent ]
update-agent
--agent-id <value>
--agent-name <value>
--agent-resource-role-arn <value>
[--customer-encryption-key-arn <value>]
[--description <value>]
--foundation-model <value>
[--guardrail-configuration <value>]
[--idle-session-ttl-in-seconds <value>]
[--instruction <value>]
[--memory-configuration <value>]
[--prompt-override-configuration <value>]
[--cli-input-json | --cli-input-yaml]
[--generate-cli-skeleton <value>]
[--debug]
[--endpoint-url <value>]
[--no-verify-ssl]
[--no-paginate]
[--output <value>]
[--query <value>]
[--profile <value>]
[--region <value>]
[--version <value>]
[--color <value>]
[--no-sign-request]
[--ca-bundle <value>]
[--cli-read-timeout <value>]
[--cli-connect-timeout <value>]
[--cli-binary-format <value>]
[--no-cli-pager]
[--cli-auto-prompt]
[--no-cli-auto-prompt]
--agent-id
(string)
The unique identifier of the agent.
--agent-name
(string)
Specifies a new name for the agent.
--agent-resource-role-arn
(string)
The Amazon Resource Name (ARN) of the IAM role with permissions to invoke API operations on the agent.
--customer-encryption-key-arn
(string)
The Amazon Resource Name (ARN) of the KMS key with which to encrypt the agent.
--description
(string)
Specifies a new description of the agent.
--foundation-model
(string)
The identifier for the model that you want to be used for orchestration by the agent you create.
The
modelId
to provide depends on the type of model or throughput that you use:
- If you use a base model, specify the model ID or its ARN. For a list of model IDs for base models, see Amazon Bedrock base model IDs (on-demand throughput) in the Amazon Bedrock User Guide.
- If you use an inference profile, specify the inference profile ID or its ARN. For a list of inference profile IDs, see Supported Regions and models for cross-region inference in the Amazon Bedrock User Guide.
- If you use a provisioned model, specify the ARN of the Provisioned Throughput. For more information, see Run inference using a Provisioned Throughput in the Amazon Bedrock User Guide.
- If you use a custom model, first purchase Provisioned Throughput for it. Then specify the ARN of the resulting provisioned model. For more information, see Use a custom model in Amazon Bedrock in the Amazon Bedrock User Guide.
- If you use an imported model , specify the ARN of the imported model. You can get the model ARN from a successful call to CreateModelImportJob or from the Imported models page in the Amazon Bedrock console.
--guardrail-configuration
(structure)
The unique Guardrail configuration assigned to the agent when it is updated.
guardrailIdentifier -> (string)
The unique identifier of the guardrail.guardrailVersion -> (string)
The version of the guardrail.
Shorthand Syntax:
guardrailIdentifier=string,guardrailVersion=string
JSON Syntax:
{
"guardrailIdentifier": "string",
"guardrailVersion": "string"
}
--idle-session-ttl-in-seconds
(integer)
The number of seconds for which Amazon Bedrock keeps information about a user’s conversation with the 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)
Specifies new instructions that tell the agent what it should do and how it should interact with users.
--memory-configuration
(structure)
Specifies the new memory configuration for the agent.
enabledMemoryTypes -> (list)
The type of memory that is stored.
(string)
storageDays -> (integer)
The number of days the agent is configured to retain the conversational context.
Shorthand Syntax:
enabledMemoryTypes=string,string,storageDays=integer
JSON Syntax:
{
"enabledMemoryTypes": ["SESSION_SUMMARY", ...],
"storageDays": integer
}
--prompt-override-configuration
(structure)
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 thepromptConfigurations
must contain aparserMode
value that is set toOVERRIDDEN
. For more information, see Parser Lambda function in Amazon Bedrock Agents .promptConfigurations -> (list)
Contains configurations to override a prompt template in one part of an agent sequence. For more information, see Advanced prompts .
(structure)
Contains configurations to override a prompt template in one part of an agent sequence. For more information, see Advanced prompts .
basePromptTemplate -> (string)
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 .inferenceConfiguration -> (structure)
Contains inference parameters to use when the agent invokes a foundation model in the part of the agent sequence defined by the
promptType
. For more information, see Inference parameters for foundation models .maximumLength -> (integer)
The maximum number of tokens to allow in the generated response.stopSequences -> (list)
A list of stop sequences. A stop sequence is a sequence of characters that causes the model to stop generating the response.
(string)
temperature -> (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 fortopK
is the number of most-likely candidates from which the model chooses the next token in the sequence. For example, if you settopK
to 50, the model selects the next token from among the top 50 most likely choices.topP -> (float)
While generating a response, the model determines the probability of the following token at each point of generation. The value that you set forTop P
determines the number of most-likely candidates from which the model chooses the next token in the sequence. For example, if you settopP
to 80, the model only selects the next token from the top 80% of the probability distribution of next tokens.parserMode -> (string)
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 thepromptType
. If you set the field asOVERRIDEN
, theoverrideLambda
field in the PromptOverrideConfiguration must be specified with the ARN of a Lambda function.promptCreationMode -> (string)
Specifies whether to override the default prompt template for thispromptType
. Set this value toOVERRIDDEN
to use the prompt that you provide in thebasePromptTemplate
. If you leave it asDEFAULT
, the agent uses a default prompt template.promptState -> (string)
Specifies whether to allow the agent to carry out the step specified in the
promptType
. If you set this value toDISABLED
, the agent skips that step. The default state for eachpromptType
is as follows.
PRE_PROCESSING
–ENABLED
ORCHESTRATION
–ENABLED
KNOWLEDGE_BASE_RESPONSE_GENERATION
–ENABLED
POST_PROCESSING
–DISABLED
promptType -> (string)
The step in the agent sequence that this prompt configuration applies to.
JSON Syntax:
{
"overrideLambda": "string",
"promptConfigurations": [
{
"basePromptTemplate": "string",
"inferenceConfiguration": {
"maximumLength": integer,
"stopSequences": ["string", ...],
"temperature": float,
"topK": integer,
"topP": float
},
"parserMode": "DEFAULT"|"OVERRIDDEN",
"promptCreationMode": "DEFAULT"|"OVERRIDDEN",
"promptState": "ENABLED"|"DISABLED",
"promptType": "PRE_PROCESSING"|"ORCHESTRATION"|"POST_PROCESSING"|"KNOWLEDGE_BASE_RESPONSE_GENERATION"
}
...
]
}
--cli-input-json
| --cli-input-yaml
(string)
Reads arguments from the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton
. If other arguments are provided on the command line, those values will override the JSON-provided values. It is not possible to pass arbitrary binary values using a JSON-provided value as the string will be taken literally. This may not be specified along with --cli-input-yaml
.
--generate-cli-skeleton
(string)
Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value input
, prints a sample input JSON that can be used as an argument for --cli-input-json
. Similarly, if provided yaml-input
it will print a sample input YAML that can be used with --cli-input-yaml
. If provided with the value output
, it validates the command inputs and returns a sample output JSON for that command. The generated JSON skeleton is not stable between versions of the AWS CLI and there are no backwards compatibility guarantees in the JSON skeleton generated.
--debug
(boolean)
Turn on debug logging.
--endpoint-url
(string)
Override command’s default URL with the given URL.
--no-verify-ssl
(boolean)
By default, the AWS CLI uses SSL when communicating with AWS services. For each SSL connection, the AWS CLI will verify SSL certificates. This option overrides the default behavior of verifying SSL certificates.
--no-paginate
(boolean)
Disable automatic pagination. If automatic pagination is disabled, the AWS CLI will only make one call, for the first page of results.
--output
(string)
The formatting style for command output.
--query
(string)
A JMESPath query to use in filtering the response data.
--profile
(string)
Use a specific profile from your credential file.
--region
(string)
The region to use. Overrides config/env settings.
--version
(string)
Display the version of this tool.
--color
(string)
Turn on/off color output.
--no-sign-request
(boolean)
Do not sign requests. Credentials will not be loaded if this argument is provided.
--ca-bundle
(string)
The CA certificate bundle to use when verifying SSL certificates. Overrides config/env settings.
--cli-read-timeout
(int)
The maximum socket read time in seconds. If the value is set to 0, the socket read will be blocking and not timeout. The default value is 60 seconds.
--cli-connect-timeout
(int)
The maximum socket connect time in seconds. If the value is set to 0, the socket connect will be blocking and not timeout. The default value is 60 seconds.
--cli-binary-format
(string)
The formatting style to be used for binary blobs. The default format is base64. The base64 format expects binary blobs to be provided as a base64 encoded string. The raw-in-base64-out format preserves compatibility with AWS CLI V1 behavior and binary values must be passed literally. When providing contents from a file that map to a binary blob fileb://
will always be treated as binary and use the file contents directly regardless of the cli-binary-format
setting. When using file://
the file contents will need to properly formatted for the configured cli-binary-format
.
--no-cli-pager
(boolean)
Disable cli pager for output.
--cli-auto-prompt
(boolean)
Automatically prompt for CLI input parameters.
--no-cli-auto-prompt
(boolean)
Disable automatically prompt for CLI input parameters.
agent -> (structure)
Contains details about the agent that was updated.
agentArn -> (string)
The Amazon Resource Name (ARN) of the agent.agentId -> (string)
The unique identifier of the agent.agentName -> (string)
The name of the agent.agentResourceRoleArn -> (string)
The Amazon Resource Name (ARN) of the IAM role with permissions to invoke API operations on the agent.agentStatus -> (string)
The status of the agent and whether it is ready for use. The following statuses are possible:
- CREATING – The agent is being created.
- PREPARING – The agent is being prepared.
- PREPARED – The agent is prepared and ready to be invoked.
- NOT_PREPARED – The agent has been created but not yet prepared.
- FAILED – The agent API operation failed.
- UPDATING – The agent is being updated.
- DELETING – The agent is being deleted.
agentVersion -> (string)
The version of the agent.clientToken -> (string)
A unique, case-sensitive identifier to ensure that the API request completes no more than one time. If this token matches a previous request, Amazon Bedrock ignores the request, but does not return an error. For more information, see Ensuring idempotency .createdAt -> (timestamp)
The time at which the agent was created.customerEncryptionKeyArn -> (string)
The Amazon Resource Name (ARN) of the KMS key that encrypts the agent.description -> (string)
The description of the agent.failureReasons -> (list)
Contains reasons that the agent-related API that you invoked failed.
(string)
foundationModel -> (string)
The foundation model used for orchestration by the agent.guardrailConfiguration -> (structure)
Details about the guardrail associated with the agent.
guardrailIdentifier -> (string)
The unique identifier of the guardrail.guardrailVersion -> (string)
The version of the guardrail.idleSessionTTLInSeconds -> (integer)
The number of seconds for which Amazon Bedrock keeps information about a user’s conversation with the 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)
Instructions that tell the agent what it should do and how it should interact with users.memoryConfiguration -> (structure)
Contains memory configuration for the agent.
enabledMemoryTypes -> (list)
The type of memory that is stored.
(string)
storageDays -> (integer)
The number of days the agent is configured to retain the conversational context.preparedAt -> (timestamp)
The time at which the agent was last prepared.promptOverrideConfiguration -> (structure)
Contains configurations to override prompt templates 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 thepromptConfigurations
must contain aparserMode
value that is set toOVERRIDDEN
. For more information, see Parser Lambda function in Amazon Bedrock Agents .promptConfigurations -> (list)
Contains configurations to override a prompt template in one part of an agent sequence. For more information, see Advanced prompts .
(structure)
Contains configurations to override a prompt template in one part of an agent sequence. For more information, see Advanced prompts .
basePromptTemplate -> (string)
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 .inferenceConfiguration -> (structure)
Contains inference parameters to use when the agent invokes a foundation model in the part of the agent sequence defined by the
promptType
. For more information, see Inference parameters for foundation models .maximumLength -> (integer)
The maximum number of tokens to allow in the generated response.stopSequences -> (list)
A list of stop sequences. A stop sequence is a sequence of characters that causes the model to stop generating the response.
(string)
temperature -> (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 fortopK
is the number of most-likely candidates from which the model chooses the next token in the sequence. For example, if you settopK
to 50, the model selects the next token from among the top 50 most likely choices.topP -> (float)
While generating a response, the model determines the probability of the following token at each point of generation. The value that you set forTop P
determines the number of most-likely candidates from which the model chooses the next token in the sequence. For example, if you settopP
to 80, the model only selects the next token from the top 80% of the probability distribution of next tokens.parserMode -> (string)
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 thepromptType
. If you set the field asOVERRIDEN
, theoverrideLambda
field in the PromptOverrideConfiguration must be specified with the ARN of a Lambda function.promptCreationMode -> (string)
Specifies whether to override the default prompt template for thispromptType
. Set this value toOVERRIDDEN
to use the prompt that you provide in thebasePromptTemplate
. If you leave it asDEFAULT
, the agent uses a default prompt template.promptState -> (string)
Specifies whether to allow the agent to carry out the step specified in the
promptType
. If you set this value toDISABLED
, the agent skips that step. The default state for eachpromptType
is as follows.
PRE_PROCESSING
–ENABLED
ORCHESTRATION
–ENABLED
KNOWLEDGE_BASE_RESPONSE_GENERATION
–ENABLED
POST_PROCESSING
–DISABLED
promptType -> (string)
The step in the agent sequence that this prompt configuration applies to.recommendedActions -> (list)
Contains recommended actions to take for the agent-related API that you invoked to succeed.
(string)
updatedAt -> (timestamp)
The time at which the agent was last updated.