Invoke-MetaModel¶

SYNOPSIS¶

Sends message(s) to a Meta model on the Amazon Bedrock platform and retrieves the response.

SYNTAX¶

MessageSet¶

Invoke-MetaModel -Message <String> -ModelID <String> [-ReturnFullObject] [-NoContextPersist]
 [-SystemPrompt <String>] [-MaxTokens <Int32>] [-Temperature <Single>] [-TopP <Single>] [-Tools <PSObject[]>]
 [-AccessKey <String>] [-Credential <AWSCredentials>] [-EndpointUrl <String>]
 [-NetworkCredential <PSCredential>] [-ProfileLocation <String>] [-ProfileName <String>] [-Region <Object>]
 [-SecretKey <String>] [-SessionToken <String>] [<CommonParameters>]

ImageSet¶

Invoke-MetaModel -ImagePrompt <String> -MediaPath <String[]> -ModelID <String> [-ReturnFullObject]
 [-NoContextPersist] [-MaxTokens <Int32>] [-Temperature <Single>] [-TopP <Single>] [-AccessKey <String>]
 [-Credential <AWSCredentials>] [-EndpointUrl <String>] [-NetworkCredential <PSCredential>]
 [-ProfileLocation <String>] [-ProfileName <String>] [-Region <Object>] [-SecretKey <String>]
 [-SessionToken <String>] [<CommonParameters>]

ToolsResultsSet¶

Invoke-MetaModel -ModelID <String> [-ReturnFullObject] [-NoContextPersist] [-MaxTokens <Int32>]
 [-Temperature <Single>] [-TopP <Single>] -ToolsResults <PSObject> [-AccessKey <String>]
 [-Credential <AWSCredentials>] [-EndpointUrl <String>] [-NetworkCredential <PSCredential>]
 [-ProfileLocation <String>] [-ProfileName <String>] [-Region <Object>] [-SecretKey <String>]
 [-SessionToken <String>] [<CommonParameters>]

DESCRIPTION¶

Sends a message to a Meta model on the Amazon Bedrock platform and returns the model's response. By default the conversation context history is persisted to maintain a continuous interaction with the model. You can disable this by using the NoContextPersist parameter. The cmdlet also estimates the cost of model usage based on the provided input and output tokens and adds the estimate to the models tally information.

EXAMPLES¶

EXAMPLE 1¶

Invoke-MetaModel -Message 'Explain zero-point energy.' -ModelID 'meta.llama4-scout-17b-instruct-v1:0' -Credential $awsCredential -Region 'us-west-2'

Sends a text message to the on-demand Meta model in the specified AWS region and returns the response.

EXAMPLE 2¶

Invoke-MetaModel -Message 'Explain zero-point energy.' -ModelID 'meta.llama4-scout-17b-instruct-v1:0' -Credential $awsCredential -Region 'us-west-2' -ReturnFullObject

Sends a text message to the on-demand Meta model in the specified AWS region and returns the full response object.

EXAMPLE 3¶

Invoke-MetaModel -Message 'Explain zero-point energy.' -ModelID 'meta.llama3-8b-instruct-v1:0' -Credential $awsCredential -Region 'us-west-2' -NoContextPersist

Sends a text message to the on-demand Meta model in the specified AWS region and returns the response without persisting the conversation context history.

EXAMPLE 4¶

$invokeMetaModelSplat = @{
    Message          = 'Explain zero-point energy.'
    ModelID          = 'meta.llama4-scout-17b-instruct-v1:0'
    MaxTokens        = 2000
    SystemPrompt     = 'You are a deep thinking model with a galactic perspective'
    Credential       = $awsCredential
    Region           = 'us-west-2'
    NoContextPersist = $true
    Verbose          = $false
}
Invoke-MetaModel @invokeMetaModelSplat

Sends a text message to the on-demand Meta model in the specified AWS region with a system prompt and a maximum token limit of 2000.

EXAMPLE 5¶

Invoke-MetaModel -ImagePrompt 'Describe this image in two sentences.' -ModelID 'meta.llama3-2-11b-instruct-v1:0' -MediaPath 'C:\path\to\image.jpg' -Credential $awsCredential -Region 'us-west-2'

Sends an image prompt to the Vision-Instruct Meta model in the specified AWS region and returns the response.

EXAMPLE 6¶

$invokeMetaModelSplat = @{
    ImagePrompt      = 'Compare these two images and tell me which one is more colorful.'
    ModelID          = 'meta.llama4-scout-17b-instruct-v1:0'
    MediaPath        = @('C:\path\to\image1.jpg', 'C:\path\to\image2.jpg')
    Credential       = $awsCredential
    Region           = 'us-west-2'
}
Invoke-MetaModel @invokeMetaModelSplat

Send a multiple image prompt to the Vision-Instruct Meta model in the specified AWS region and returns the response.

PARAMETERS¶

-Message¶

The message to be sent to the model.

Type: String
Parameter Sets: MessageSet
Aliases:

Required: True
Position: Named
Default value: None
Accept pipeline input: False
Accept wildcard characters: False

-ImagePrompt¶

The prompt to the Vision-Instruct model.

Type: String
Parameter Sets: ImageSet
Aliases:

Required: True
Position: Named
Default value: None
Accept pipeline input: False
Accept wildcard characters: False

-MediaPath¶

File path to local media file(s). The media files must adhere to the model's media requirements. Only large 3.2 vision models support single media files. 4.0 models support multiple media files.

Type: String[]
Parameter Sets: ImageSet
Aliases:

Required: True
Position: Named
Default value: None
Accept pipeline input: False
Accept wildcard characters: False

-ModelID¶

The unique identifier of the model.

Type: String
Parameter Sets: (All)
Aliases:

Required: True
Position: Named
Default value: None
Accept pipeline input: False
Accept wildcard characters: False

-ReturnFullObject¶

Specify if you want the full object returned instead of just the message reply.

Type: SwitchParameter
Parameter Sets: (All)
Aliases:

Required: False
Position: Named
Default value: False
Accept pipeline input: False
Accept wildcard characters: False

-NoContextPersist¶

Do not persist the conversation context history. If this parameter is specified, you will not be able to have a continuous conversation with the model. Has no effect if -PromptOnly is specified.

Type: SwitchParameter
Parameter Sets: (All)
Aliases:

Required: False
Position: Named
Default value: False
Accept pipeline input: False
Accept wildcard characters: False

-SystemPrompt¶

The system prompt for the request. If you do not provide a system prompt, the default Llama system prompt will be used.

Type: String
Parameter Sets: MessageSet
Aliases:

Required: False
Position: Named
Default value: None
Accept pipeline input: False
Accept wildcard characters: False

-MaxTokens¶

The maximum number of tokens to generate before stopping. Defaults to 2048. Ranges from 1 to 2048.

Type: Int32
Parameter Sets: (All)
Aliases:

Required: False
Position: Named
Default value: 2048
Accept pipeline input: False
Accept wildcard characters: False

-Temperature¶

The amount of randomness injected into the response. Defaults to 1.0. Ranges from 0.0 to 1.0. Use a lower value to decrease randomness in responses.

Type: Single
Parameter Sets: (All)
Aliases:

Required: False
Position: Named
Default value: 0
Accept pipeline input: False
Accept wildcard characters: False

-TopP¶

Use a lower value to ignore less probable options and decrease the diversity of responses.

Type: Single
Parameter Sets: (All)
Aliases:

Required: False
Position: Named
Default value: 0
Accept pipeline input: False
Accept wildcard characters: False

-Tools¶

A list of available tools (functions) that the model may suggest invoking before producing a text response. This must be in a properly formatted PSObject array with all required Tools properties. For more information, see the Meta documentation.

Type: PSObject[]
Parameter Sets: MessageSet
Aliases:

Required: False
Position: Named
Default value: None
Accept pipeline input: False
Accept wildcard characters: False

-ToolsResults¶

A list of results from invoking tools recommended by the model in the previous chat turn.

Type: PSObject
Parameter Sets: ToolsResultsSet
Aliases:

Required: True
Position: Named
Default value: None
Accept pipeline input: False
Accept wildcard characters: False

-AccessKey¶

The AWS access key for the user account. This can be a temporary access key if the corresponding session token is supplied to the -SessionToken parameter.

Type: String
Parameter Sets: (All)
Aliases:

Required: False
Position: Named
Default value: None
Accept pipeline input: False
Accept wildcard characters: False

-Credential¶

An AWSCredentials object instance containing access and secret key information, and optionally a token for session-based credentials.

Type: AWSCredentials
Parameter Sets: (All)
Aliases:

Required: False
Position: Named
Default value: None
Accept pipeline input: False
Accept wildcard characters: False

-EndpointUrl¶

The endpoint to make the call against. Note: This parameter is primarily for internal AWS use and is not required/should not be specified for normal usage. The cmdlets normally determine which endpoint to call based on the region specified to the -Region parameter or set as default in the shell (via Set-DefaultAWSRegion). Only specify this parameter if you must direct the call to a specific custom endpoint.

Type: String
Parameter Sets: (All)
Aliases:

Required: False
Position: Named
Default value: None
Accept pipeline input: False
Accept wildcard characters: False

-NetworkCredential¶

Used with SAML-based authentication when ProfileName references a SAML role profile. Contains the network credentials to be supplied during authentication with the configured identity provider's endpoint. This parameter is not required if the user's default network identity can or should be used during authentication.

Type: PSCredential
Parameter Sets: (All)
Aliases:

Required: False
Position: Named
Default value: None
Accept pipeline input: False
Accept wildcard characters: False

-ProfileLocation¶

Used to specify the name and location of the ini-format credential file (shared with the AWS CLI and other AWS SDKs) If this optional parameter is omitted this cmdlet will search the encrypted credential file used by the AWS SDK for .NET and AWS Toolkit for Visual Studio first. If the profile is not found then the cmdlet will search in the ini-format credential file at the default location: (user's home directory).aws\credentials. If this parameter is specified then this cmdlet will only search the ini-format credential file at the location given. As the current folder can vary in a shell or during script execution it is advised that you use specify a fully qualified path instead of a relative path.

Type: String
Parameter Sets: (All)
Aliases:

Required: False
Position: Named
Default value: None
Accept pipeline input: False
Accept wildcard characters: False

-ProfileName¶

The user-defined name of an AWS credentials or SAML-based role profile containing credential information. The profile is expected to be found in the secure credential file shared with the AWS SDK for .NET and AWS Toolkit for Visual Studio. You can also specify the name of a profile stored in the .ini-format credential file used with the AWS CLI and other AWS SDKs.

Type: String
Parameter Sets: (All)
Aliases:

Required: False
Position: Named
Default value: None
Accept pipeline input: False
Accept wildcard characters: False

-Region¶

The system name of an AWS region or an AWSRegion instance. This governs the endpoint that will be used when calling service operations. Note that the AWS resources referenced in a call are usually region-specific.

Type: Object
Parameter Sets: (All)
Aliases:

Required: False
Position: Named
Default value: None
Accept pipeline input: False
Accept wildcard characters: False

-SecretKey¶

The AWS secret key for the user account. This can be a temporary secret key if the corresponding session token is supplied to the -SessionToken parameter.

Type: String
Parameter Sets: (All)
Aliases:

Required: False
Position: Named
Default value: None
Accept pipeline input: False
Accept wildcard characters: False

-SessionToken¶

The session token if the access and secret keys are temporary session-based credentials.

Type: String
Parameter Sets: (All)
Aliases:

Required: False
Position: Named
Default value: None
Accept pipeline input: False
Accept wildcard characters: False

CommonParameters¶

This cmdlet supports the common parameters: -Debug, -ErrorAction, -ErrorVariable, -InformationAction, -InformationVariable, -OutBuffer, -OutVariable, -PipelineVariable, -Verbose, -WarningAction, -WarningVariable, and -ProgressAction. For more information, see about_CommonParameters (http://go.microsoft.com/fwlink/?LinkID=113216).

INPUTS¶

OUTPUTS¶

System.String¶

or¶

System.Management.Automation.PSCustomObject¶

NOTES¶

Author: Jake Morrison - @jakemorrison - https://www.techthoughts.info/

For a full tools example, see the advanced documentation on the pwshBedrock website.

If Tools are provided for a 3.1+ model, a new system prompt will be generated with the tools included. This means that the context will be RESET when tools are provided. This is because system prompts are created at the beginning of the conversation. Start a conversation with tools by providing them in the first message. Adding tools to a conversation after the first message will not work as a reset will occur.

Note: The Meta models require the system prompt to be set at the beginning of the conversation. When using the Format-MetaTextMessage and Invoke-MetaModel functions, the system prompt is inserted at the start of the conversation context stored in memory. If you modify the system prompt after the conversation has begun, the functions will replace the original system prompt in the in-memory context. This action does not affect previous exchanges but may influence subsequent interactions.

Be aware that changing the system prompt mid-conversation can lead to instability or confusion in the model's responses. This is particularly significant if you initially used a specialized system prompt to enable tool usage within the conversation. Overwriting the system prompt in such cases can disrupt the intended functionality and cause the model to behave unpredictably.

For consistent and reliable interactions, it is recommended to set your desired system prompt at the onset of the conversation and avoid altering it later.

https://www.pwshbedrock.dev/en/latest/Invoke-MetaModel/

https://www.pwshbedrock.dev/en/latest/pwshBedrock-Advanced/

https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-meta.html

https://huggingface.co/blog/llama2#how-to-prompt-llama-2

https://llama.meta.com/docs/model-cards-and-prompt-formats/meta-llama-2/

https://github.com/meta-llama/llama/blob/main/MODEL_CARD.md

https://llama.meta.com/docs/model-cards-and-prompt-formats/meta-llama-3/

https://github.com/meta-llama/llama3/blob/main/MODEL_CARD.md

https://www.llama.com/docs/model-cards-and-prompt-formats/llama3_1

https://github.com/meta-llama/llama-models/blob/main/models/llama3_1/MODEL_CARD.md

https://github.com/meta-llama/llama-models/blob/main/models/llama3_2/MODEL_CARD.md

https://github.com/meta-llama/llama-models/blob/main/models/llama3_2/MODEL_CARD_VISION.md