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agentcore_cli.models.inputs

agentcore_cli.models.inputs

Input models for AgentCore Platform CLI.

This module defines input models for CLI commands and API interactions. All models align with AWS Bedrock AgentCore API requirements.

ContainerBuildInput

Bases: BaseAgentCoreModel

Input for building and pushing a container image to ECR.

Source code in agentcore_cli/models/inputs.py
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class ContainerBuildInput(BaseAgentCoreModel):
    """Input for building and pushing a container image to ECR."""

    ecr_repository_name: str = Field(description="ECR repository name (must exist in configuration)")
    image_tag: str = Field(default="latest", description="Image tag to assign")
    dockerfile_path: str = Field(default="Dockerfile", description="Path to Dockerfile")
    build_context: str = Field(default=".", description="Docker build context directory")
    build_args: dict[str, str] = Field(default_factory=dict, description="Docker build arguments")
    platform: str = Field(default="linux/arm64", description="Target platform for the build")
    no_cache: bool = Field(default=False, description="Disable Docker build cache")

    @property
    def dockerfile(self) -> str:
        """Legacy property for backward compatibility."""
        return self.dockerfile_path

dockerfile property

Legacy property for backward compatibility.

CreateAgentRuntimeInput

Bases: BaseAgentCoreModel

Input for creating a new agent runtime.

Maps directly to AWS create_agent_runtime API parameters.

Source code in agentcore_cli/models/inputs.py
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class CreateAgentRuntimeInput(BaseAgentCoreModel):
    """Input for creating a new agent runtime.

    Maps directly to AWS create_agent_runtime API parameters.
    """

    name: str = Field(description="Agent runtime name")
    container_uri: str = Field(description="Full ECR container URI including tag")
    role_arn: str = Field(description="IAM execution role ARN for the agent runtime")

    # Optional parameters
    description: str | None = Field(default=None, description="Agent runtime description")
    network_mode: NetworkModeType = Field(default=NetworkModeType.PUBLIC, description="Network configuration mode")
    protocol: ServerProtocolType = Field(default=ServerProtocolType.HTTP, description="Server protocol type")
    environment_variables: dict[str, str] = Field(default_factory=dict, description="Runtime environment variables")
    client_token: str | None = Field(default=None, description="Client token for idempotency")

CreateEndpointInput

Bases: BaseAgentCoreModel

Input for creating an agent runtime endpoint.

Maps to AWS create_agent_runtime_endpoint API parameters.

Source code in agentcore_cli/models/inputs.py
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class CreateEndpointInput(BaseAgentCoreModel):
    """Input for creating an agent runtime endpoint.

    Maps to AWS create_agent_runtime_endpoint API parameters.
    """

    agent_runtime_id: str = Field(description="Agent runtime ID")
    name: str = Field(description="Endpoint name")
    target_version: str | None = Field(default=None, description="Specific runtime version (defaults to latest)")
    description: str | None = Field(default=None, description="Endpoint description")
    client_token: str | None = Field(default=None, description="Client token for idempotency")

EnvironmentInput

Bases: BaseAgentCoreModel

Input for environment operations.

Source code in agentcore_cli/models/inputs.py
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class EnvironmentInput(BaseAgentCoreModel):
    """Input for environment operations."""

    name: str = Field(description="Environment name")
    region: str | None = Field(default=None, description="AWS region for the environment")

InvokeAgentInput

Bases: BaseAgentCoreModel

Input for invoking an agent runtime.

Maps directly to AWS invoke_agent_runtime API requirements. The API requires a full ARN and qualifier (endpoint name).

Source code in agentcore_cli/models/inputs.py
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class InvokeAgentInput(BaseAgentCoreModel):
    """Input for invoking an agent runtime.

    Maps directly to AWS invoke_agent_runtime API requirements.
    The API requires a full ARN and qualifier (endpoint name).
    """

    agent_runtime_arn: str = Field(description="Full ARN of the agent runtime to invoke")
    qualifier: str = Field(description="Endpoint name or version qualifier (e.g., 'DEFAULT', 'production')")
    runtime_session_id: str = Field(description="Session ID for the runtime invocation")
    prompt: str = Field(description="Prompt to send to the agent")

    # Additional fields for CLI convenience
    environment: str | None = Field(default=None, description="Environment context (for CLI reference only)")
    agent_name: str | None = Field(default=None, description="Agent name (for CLI reference only)")

UpdateAgentRuntimeInput

Bases: BaseAgentCoreModel

Input for updating an agent runtime.

Updates create a new immutable version. Maps to AWS update_agent_runtime API.

Source code in agentcore_cli/models/inputs.py
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class UpdateAgentRuntimeInput(BaseAgentCoreModel):
    """Input for updating an agent runtime.

    Updates create a new immutable version. Maps to AWS update_agent_runtime API.
    """

    agent_runtime_id: str = Field(description="Agent runtime ID to update")

    # Optional update parameters - at least one must be provided
    description: str | None = Field(default=None, description="Updated description")
    container_uri: str | None = Field(default=None, description="New container URI")
    role_arn: str | None = Field(default=None, description="New IAM execution role ARN")
    network_mode: NetworkModeType | None = Field(default=None, description="New network mode")
    protocol: ServerProtocolType | None = Field(default=None, description="New protocol type")
    environment_variables: dict[str, str] | None = Field(default=None, description="Updated environment variables")
    client_token: str | None = Field(default=None, description="Client token for idempotency")

    @model_validator(mode="after")
    def validate_at_least_one_update(cls, model):
        """Ensure at least one field is being updated."""
        update_fields = [
            model.description,
            model.container_uri,
            model.role_arn,
            model.network_mode,
            model.protocol,
            model.environment_variables,
        ]
        if not any(field is not None for field in update_fields):
            raise ValueError("At least one field must be provided for update")
        return model

validate_at_least_one_update(model)

Ensure at least one field is being updated.

Source code in agentcore_cli/models/inputs.py
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@model_validator(mode="after")
def validate_at_least_one_update(cls, model):
    """Ensure at least one field is being updated."""
    update_fields = [
        model.description,
        model.container_uri,
        model.role_arn,
        model.network_mode,
        model.protocol,
        model.environment_variables,
    ]
    if not any(field is not None for field in update_fields):
        raise ValueError("At least one field must be provided for update")
    return model

UpdateEndpointInput

Bases: BaseAgentCoreModel

Input for updating an agent runtime endpoint.

Maps to AWS update_agent_runtime_endpoint API parameters.

Source code in agentcore_cli/models/inputs.py
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class UpdateEndpointInput(BaseAgentCoreModel):
    """Input for updating an agent runtime endpoint.

    Maps to AWS update_agent_runtime_endpoint API parameters.
    """

    agent_runtime_id: str = Field(description="Agent runtime ID")
    endpoint_name: str = Field(description="Endpoint name to update")
    target_version: str = Field(description="New runtime version to point endpoint to")
    description: str | None = Field(default=None, description="Updated description")
    client_token: str | None = Field(default=None, description="Client token for idempotency")