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delete_agent_memory async

delete_agent_memory(
    agent_id: AgentId,
    agent_alias_id: AgentAliasId,
    *,
    config_overrides: Optional[AsyncBedrockAgentRuntimeClientConfig] = None,
    memory_id: Optional[MemoryId] = None,
    session_id: Optional[SessionId] = None,
) -> DeleteAgentMemoryResponse

Deletes memory from the specified memory identifier.

Parameters:

  • agent_id (AgentId) –

    The unique identifier of the agent to which the alias belongs.

  • agent_alias_id (AgentAliasId) –

    The unique identifier of an alias of an agent.

  • memory_id (Optional[MemoryId], default: None ) –

    The unique identifier of the memory.

  • session_id (Optional[SessionId], default: None ) –

    The unique session identifier of the memory.

Raises:

  • AccessDeniedException –

    The request is denied because of missing access permissions. Check your permissions and retry your request.

  • BadGatewayException –

    There was an issue with a dependency due to a server issue. Retry your request.

  • ConflictException –

    There was a conflict performing an operation. Resolve the conflict and retry your request.

  • DependencyFailedException –

    There was an issue with a dependency. Check the resource configurations and retry the request.

  • InternalServerException –

    An internal server error occurred. Retry your request.

  • ResourceNotFoundException –

    The specified resource Amazon Resource Name (ARN) was not found. Check the Amazon Resource Name (ARN) and try your request again.

  • ServiceQuotaExceededException –

    The number of requests exceeds the service quota. Resubmit your request later.

  • ThrottlingException –

    The number of requests exceeds the limit. Resubmit your request later.

  • ValidationException –

    Input validation failed. Check your request parameters and retry the request.

  • UnknownServiceError –

    The service returned an error code this client does not model.

Source code in docs_src/capo_bedrock_agent_runtime/_services/async_bedrock_agent_runtime.py
async def delete_agent_memory(
    self,
    agent_id: "capo_bedrock_agent_runtime.types.agent_id.AgentId",
    agent_alias_id: "capo_bedrock_agent_runtime.types.agent_alias_id.AgentAliasId",
    *,
    config_overrides: Optional[AsyncBedrockAgentRuntimeClientConfig] = None,
    memory_id: Optional[
        "capo_bedrock_agent_runtime.types.memory_id.MemoryId"
    ] = None,
    session_id: Optional[
        "capo_bedrock_agent_runtime.types.session_id.SessionId"
    ] = None,
) -> "capo_bedrock_agent_runtime.types.delete_agent_memory_response.DeleteAgentMemoryResponse":
    """<p>Deletes memory from the specified memory identifier.</p>

    Args:
        agent_id: <p>The unique identifier of the agent to which the alias belongs.</p>
        agent_alias_id: <p>The unique identifier of an alias of an agent.</p>
        memory_id: <p>The unique identifier of the memory.</p>
        session_id: <p>The unique session identifier of the memory.</p>

    Raises:
        capo_bedrock_agent_runtime.errors.access_denied_exception.AccessDeniedException: <p>The request is denied because of missing access permissions. Check your permissions and retry your request.</p>
        capo_bedrock_agent_runtime.errors.bad_gateway_exception.BadGatewayException: <p>There was an issue with a dependency due to a server issue. Retry your request.</p>
        capo_bedrock_agent_runtime.errors.conflict_exception.ConflictException: <p>There was a conflict performing an operation. Resolve the conflict and retry your request.</p>
        capo_bedrock_agent_runtime.errors.dependency_failed_exception.DependencyFailedException: <p>There was an issue with a dependency. Check the resource configurations and retry the request.</p>
        capo_bedrock_agent_runtime.errors.internal_server_exception.InternalServerException: <p>An internal server error occurred. Retry your request.</p>
        capo_bedrock_agent_runtime.errors.resource_not_found_exception.ResourceNotFoundException: <p>The specified resource Amazon Resource Name (ARN) was not found. Check the Amazon Resource Name (ARN) and try your request again.</p>
        capo_bedrock_agent_runtime.errors.service_quota_exceeded_exception.ServiceQuotaExceededException: <p>The number of requests exceeds the service quota. Resubmit your request later.</p>
        capo_bedrock_agent_runtime.errors.throttling_exception.ThrottlingException: <p>The number of requests exceeds the limit. Resubmit your request later.</p>
        capo_bedrock_agent_runtime.errors.validation_exception.ValidationException: <p>Input validation failed. Check your request parameters and retry the request.</p>
        capo_bedrock_agent_runtime.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    async def _handler(
        req: "AsyncOperationRequest[capo_bedrock_agent_runtime.types.delete_agent_memory_request.DeleteAgentMemoryRequest]",
    ) -> AsyncOperationResponse[
        "capo_bedrock_agent_runtime.types.delete_agent_memory_response.DeleteAgentMemoryResponse"
    ]:
        import capo_bedrock_agent_runtime._operations.amazon_bedrock_agent_run_time_service.delete_agent_memory

        (
            output,
            http_response,
        ) = await capo_bedrock_agent_runtime._operations.amazon_bedrock_agent_run_time_service.delete_agent_memory.async_delete_agent_memory(
            req.options, req.input
        )
        return AsyncOperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("DeleteAgentMemory")
    )
    input_: capo_bedrock_agent_runtime.types.delete_agent_memory_request.DeleteAgentMemoryRequest = {
        "agent_id": agent_id,
        "agent_alias_id": agent_alias_id,
    }
    if memory_id is not None:
        input_["memory_id"] = memory_id
    if session_id is not None:
        input_["session_id"] = session_id

    response = await aexecute_pipeline(
        AsyncOperationRequest(input=input_, options=options_),
        handler=_handler,
        interceptors=list(interceptors_),
    )
    await response.response.aclose()
    return response.output