%% WARNING: DO NOT EDIT, AUTO-GENERATED CODE! %% See https://github.com/aws-beam/aws-codegen for more details. %% @doc The Amazon SageMaker AI runtime API. -module(aws_sagemaker_runtime). -export([invoke_endpoint/3, invoke_endpoint/4, invoke_endpoint_async/3, invoke_endpoint_async/4, invoke_endpoint_with_response_stream/3, invoke_endpoint_with_response_stream/4]). -include_lib("hackney/include/hackney_lib.hrl"). %% Example: %% internal_dependency_exception() :: #{ %% <<"Message">> => string() %% } -type internal_dependency_exception() :: #{binary() => any()}. %% Example: %% internal_failure() :: #{ %% <<"Message">> => string() %% } -type internal_failure() :: #{binary() => any()}. %% Example: %% internal_stream_failure() :: #{ %% <<"Message">> => string() %% } -type internal_stream_failure() :: #{binary() => any()}. %% Example: %% invoke_endpoint_async_input() :: #{ %% <<"Accept">> => string(), %% <<"ContentType">> => string(), %% <<"CustomAttributes">> => string(), %% <<"Filename">> => string(), %% <<"InferenceId">> => string(), %% <<"InputLocation">> := string(), %% <<"InvocationTimeoutSeconds">> => integer(), %% <<"RequestTTLSeconds">> => integer(), %% <<"S3OutputPathExtension">> => string() %% } -type invoke_endpoint_async_input() :: #{binary() => any()}. %% Example: %% invoke_endpoint_async_output() :: #{ %% <<"FailureLocation">> => string(), %% <<"InferenceId">> => string(), %% <<"OutputLocation">> => string() %% } -type invoke_endpoint_async_output() :: #{binary() => any()}. %% Example: %% invoke_endpoint_input() :: #{ %% <<"Accept">> => string(), %% <<"Body">> := binary(), %% <<"ContentType">> => string(), %% <<"CustomAttributes">> => string(), %% <<"EnableExplanations">> => string(), %% <<"InferenceComponentName">> => string(), %% <<"InferenceId">> => string(), %% <<"SessionId">> => string(), %% <<"TargetContainerHostname">> => string(), %% <<"TargetModel">> => string(), %% <<"TargetVariant">> => string() %% } -type invoke_endpoint_input() :: #{binary() => any()}. %% Example: %% invoke_endpoint_output() :: #{ %% <<"Body">> => binary(), %% <<"ClosedSessionId">> => string(), %% <<"ContentType">> => string(), %% <<"CustomAttributes">> => string(), %% <<"InvokedProductionVariant">> => string(), %% <<"NewSessionId">> => string() %% } -type invoke_endpoint_output() :: #{binary() => any()}. %% Example: %% invoke_endpoint_with_response_stream_input() :: #{ %% <<"Accept">> => string(), %% <<"Body">> := binary(), %% <<"ContentType">> => string(), %% <<"CustomAttributes">> => string(), %% <<"InferenceComponentName">> => string(), %% <<"InferenceId">> => string(), %% <<"SessionId">> => string(), %% <<"TargetContainerHostname">> => string(), %% <<"TargetVariant">> => string() %% } -type invoke_endpoint_with_response_stream_input() :: #{binary() => any()}. %% Example: %% invoke_endpoint_with_response_stream_output() :: #{ %% <<"Body">> => list(), %% <<"ContentType">> => string(), %% <<"CustomAttributes">> => string(), %% <<"InvokedProductionVariant">> => string() %% } -type invoke_endpoint_with_response_stream_output() :: #{binary() => any()}. %% Example: %% model_error() :: #{ %% <<"LogStreamArn">> => string(), %% <<"Message">> => string(), %% <<"OriginalMessage">> => string(), %% <<"OriginalStatusCode">> => integer() %% } -type model_error() :: #{binary() => any()}. %% Example: %% model_not_ready_exception() :: #{ %% <<"Message">> => string() %% } -type model_not_ready_exception() :: #{binary() => any()}. %% Example: %% model_stream_error() :: #{ %% <<"ErrorCode">> => string(), %% <<"Message">> => string() %% } -type model_stream_error() :: #{binary() => any()}. %% Example: %% payload_part() :: #{ %% <<"Bytes">> => binary() %% } -type payload_part() :: #{binary() => any()}. %% Example: %% service_unavailable() :: #{ %% <<"Message">> => string() %% } -type service_unavailable() :: #{binary() => any()}. %% Example: %% validation_error() :: #{ %% <<"Message">> => string() %% } -type validation_error() :: #{binary() => any()}. -type invoke_endpoint_errors() :: validation_error() | service_unavailable() | model_not_ready_exception() | model_error() | internal_failure() | internal_dependency_exception(). -type invoke_endpoint_async_errors() :: validation_error() | service_unavailable() | internal_failure(). -type invoke_endpoint_with_response_stream_errors() :: validation_error() | service_unavailable() | model_stream_error() | model_error() | internal_stream_failure() | internal_failure(). %%==================================================================== %% API %%==================================================================== %% @doc After you deploy a model into production using Amazon SageMaker AI %% hosting services, %% your client applications use this API to get inferences from the model %% hosted at the %% specified endpoint. %% %% For an overview of Amazon SageMaker AI, see How It Works: %% https://docs.aws.amazon.com/sagemaker/latest/dg/how-it-works.html. %% %% Amazon SageMaker AI strips all POST headers except those supported by the %% API. Amazon SageMaker AI might add %% additional headers. You should not rely on the behavior of headers outside %% those %% enumerated in the request syntax. %% %% Calls to `InvokeEndpoint' are authenticated by using Amazon Web %% Services %% Signature Version 4. For information, see Authenticating %% Requests (Amazon Web Services Signature Version 4): %% https://docs.aws.amazon.com/AmazonS3/latest/API/sig-v4-authenticating-requests.html %% in the Amazon S3 API Reference. %% %% A customer's model containers must respond to requests within 60 %% seconds. The model %% itself can have a maximum processing time of 60 seconds before responding %% to %% invocations. If your model is going to take 50-60 seconds of processing %% time, the SDK %% socket timeout should be set to be 70 seconds. %% %% Endpoints are scoped to an individual account, and are not public. The URL %% does %% not contain the account ID, but Amazon SageMaker AI determines the account %% ID from %% the authentication token that is supplied by the caller. -spec invoke_endpoint(aws_client:aws_client(), binary() | list(), invoke_endpoint_input()) -> {ok, invoke_endpoint_output(), tuple()} | {error, any()} | {error, invoke_endpoint_errors(), tuple()}. invoke_endpoint(Client, EndpointName, Input) -> invoke_endpoint(Client, EndpointName, Input, []). -spec invoke_endpoint(aws_client:aws_client(), binary() | list(), invoke_endpoint_input(), proplists:proplist()) -> {ok, invoke_endpoint_output(), tuple()} | {error, any()} | {error, invoke_endpoint_errors(), tuple()}. invoke_endpoint(Client, EndpointName, Input0, Options0) -> Method = post, Path = ["/endpoints/", aws_util:encode_uri(EndpointName), "/invocations"], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, true), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, true), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary}, {append_sha256_content_hash, false} | Options2], HeadersMapping = [ {<<"Accept">>, <<"Accept">>}, {<<"Content-Type">>, <<"ContentType">>}, {<<"X-Amzn-SageMaker-Custom-Attributes">>, <<"CustomAttributes">>}, {<<"X-Amzn-SageMaker-Enable-Explanations">>, <<"EnableExplanations">>}, {<<"X-Amzn-SageMaker-Inference-Component">>, <<"InferenceComponentName">>}, {<<"X-Amzn-SageMaker-Inference-Id">>, <<"InferenceId">>}, {<<"X-Amzn-SageMaker-Session-Id">>, <<"SessionId">>}, {<<"X-Amzn-SageMaker-Target-Container-Hostname">>, <<"TargetContainerHostname">>}, {<<"X-Amzn-SageMaker-Target-Model">>, <<"TargetModel">>}, {<<"X-Amzn-SageMaker-Target-Variant">>, <<"TargetVariant">>} ], {Headers, Input1} = aws_request:build_headers(HeadersMapping, Input0), CustomHeaders = [], Input2 = Input1, Query_ = [], Input = Input2, case request(Client, Method, Path, Query_, CustomHeaders ++ Headers, Input, Options, SuccessStatusCode) of {ok, Body0, {_, ResponseHeaders, _} = Response} -> ResponseHeadersParams = [ {<<"X-Amzn-SageMaker-Closed-Session-Id">>, <<"ClosedSessionId">>}, {<<"Content-Type">>, <<"ContentType">>}, {<<"X-Amzn-SageMaker-Custom-Attributes">>, <<"CustomAttributes">>}, {<<"x-Amzn-Invoked-Production-Variant">>, <<"InvokedProductionVariant">>}, {<<"X-Amzn-SageMaker-New-Session-Id">>, <<"NewSessionId">>} ], FoldFun = fun({Name_, Key_}, Acc_) -> case lists:keyfind(Name_, 1, ResponseHeaders) of false -> Acc_; {_, Value_} -> Acc_#{Key_ => Value_} end end, Body = lists:foldl(FoldFun, Body0, ResponseHeadersParams), {ok, Body, Response}; Result -> Result end. %% @doc After you deploy a model into production using Amazon SageMaker AI %% hosting services, %% your client applications use this API to get inferences from the model %% hosted at the %% specified endpoint in an asynchronous manner. %% %% Inference requests sent to this API are enqueued for asynchronous %% processing. The %% processing of the inference request may or may not complete before you %% receive a %% response from this API. The response from this API will not contain the %% result of the %% inference request but contain information about where you can locate it. %% %% Amazon SageMaker AI strips all POST headers except those supported by the %% API. Amazon SageMaker AI might add %% additional headers. You should not rely on the behavior of headers outside %% those %% enumerated in the request syntax. %% %% Calls to `InvokeEndpointAsync' are authenticated by using Amazon Web %% Services Signature Version 4. For information, see Authenticating %% Requests (Amazon Web Services Signature Version 4): %% https://docs.aws.amazon.com/AmazonS3/latest/API/sig-v4-authenticating-requests.html %% in the Amazon S3 API Reference. -spec invoke_endpoint_async(aws_client:aws_client(), binary() | list(), invoke_endpoint_async_input()) -> {ok, invoke_endpoint_async_output(), tuple()} | {error, any()} | {error, invoke_endpoint_async_errors(), tuple()}. invoke_endpoint_async(Client, EndpointName, Input) -> invoke_endpoint_async(Client, EndpointName, Input, []). -spec invoke_endpoint_async(aws_client:aws_client(), binary() | list(), invoke_endpoint_async_input(), proplists:proplist()) -> {ok, invoke_endpoint_async_output(), tuple()} | {error, any()} | {error, invoke_endpoint_async_errors(), tuple()}. invoke_endpoint_async(Client, EndpointName, Input0, Options0) -> Method = post, Path = ["/endpoints/", aws_util:encode_uri(EndpointName), "/async-invocations"], SuccessStatusCode = 202, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary}, {append_sha256_content_hash, false} | Options2], HeadersMapping = [ {<<"X-Amzn-SageMaker-Accept">>, <<"Accept">>}, {<<"X-Amzn-SageMaker-Content-Type">>, <<"ContentType">>}, {<<"X-Amzn-SageMaker-Custom-Attributes">>, <<"CustomAttributes">>}, {<<"X-Amzn-SageMaker-Filename">>, <<"Filename">>}, {<<"X-Amzn-SageMaker-Inference-Id">>, <<"InferenceId">>}, {<<"X-Amzn-SageMaker-InputLocation">>, <<"InputLocation">>}, {<<"X-Amzn-SageMaker-InvocationTimeoutSeconds">>, <<"InvocationTimeoutSeconds">>}, {<<"X-Amzn-SageMaker-RequestTTLSeconds">>, <<"RequestTTLSeconds">>}, {<<"X-Amzn-SageMaker-S3OutputPathExtension">>, <<"S3OutputPathExtension">>} ], {Headers, Input1} = aws_request:build_headers(HeadersMapping, Input0), CustomHeaders = [], Input2 = Input1, Query_ = [], Input = Input2, case request(Client, Method, Path, Query_, CustomHeaders ++ Headers, Input, Options, SuccessStatusCode) of {ok, Body0, {_, ResponseHeaders, _} = Response} -> ResponseHeadersParams = [ {<<"X-Amzn-SageMaker-FailureLocation">>, <<"FailureLocation">>}, {<<"X-Amzn-SageMaker-OutputLocation">>, <<"OutputLocation">>} ], FoldFun = fun({Name_, Key_}, Acc_) -> case lists:keyfind(Name_, 1, ResponseHeaders) of false -> Acc_; {_, Value_} -> Acc_#{Key_ => Value_} end end, Body = lists:foldl(FoldFun, Body0, ResponseHeadersParams), {ok, Body, Response}; Result -> Result end. %% @doc Invokes a model at the specified endpoint to return the inference %% response as a %% stream. %% %% The inference stream provides the response payload incrementally as a %% series of %% parts. Before you can get an inference stream, you must have access to a %% model that's %% deployed using Amazon SageMaker AI hosting services, and the container for %% that model %% must support inference streaming. %% %% For more information that can help you use this API, see the following %% sections in the %% Amazon SageMaker AI Developer Guide: %% %% For information about how to add streaming support to a model, see How %% Containers Serve Requests: %% https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms-inference-code.html#your-algorithms-inference-code-how-containe-serves-requests. %% %% For information about how to process the streaming response, see Invoke %% real-time endpoints: %% https://docs.aws.amazon.com/sagemaker/latest/dg/realtime-endpoints-test-endpoints.html. %% %% Before you can use this operation, your IAM permissions must allow the %% `sagemaker:InvokeEndpoint' action. For more information about Amazon %% SageMaker AI actions for IAM policies, see Actions, resources, and %% condition keys for Amazon SageMaker AI: %% https://docs.aws.amazon.com/service-authorization/latest/reference/list_amazonsagemaker.html %% in the IAM Service Authorization %% Reference. %% %% Amazon SageMaker AI strips all POST headers except those supported by the %% API. Amazon SageMaker AI might add %% additional headers. You should not rely on the behavior of headers outside %% those %% enumerated in the request syntax. %% %% Calls to `InvokeEndpointWithResponseStream' are authenticated by using %% Amazon Web Services Signature Version 4. For information, see %% Authenticating Requests (Amazon Web Services Signature Version 4): %% https://docs.aws.amazon.com/AmazonS3/latest/API/sig-v4-authenticating-requests.html %% in the %% Amazon S3 API Reference. -spec invoke_endpoint_with_response_stream(aws_client:aws_client(), binary() | list(), invoke_endpoint_with_response_stream_input()) -> {ok, invoke_endpoint_with_response_stream_output(), tuple()} | {error, any()} | {error, invoke_endpoint_with_response_stream_errors(), tuple()}. invoke_endpoint_with_response_stream(Client, EndpointName, Input) -> invoke_endpoint_with_response_stream(Client, EndpointName, Input, []). -spec invoke_endpoint_with_response_stream(aws_client:aws_client(), binary() | list(), invoke_endpoint_with_response_stream_input(), proplists:proplist()) -> {ok, invoke_endpoint_with_response_stream_output(), tuple()} | {error, any()} | {error, invoke_endpoint_with_response_stream_errors(), tuple()}. invoke_endpoint_with_response_stream(Client, EndpointName, Input0, Options0) -> Method = post, Path = ["/endpoints/", aws_util:encode_uri(EndpointName), "/invocations-response-stream"], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, true), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary}, {append_sha256_content_hash, false} | Options2], HeadersMapping = [ {<<"X-Amzn-SageMaker-Accept">>, <<"Accept">>}, {<<"Content-Type">>, <<"ContentType">>}, {<<"X-Amzn-SageMaker-Custom-Attributes">>, <<"CustomAttributes">>}, {<<"X-Amzn-SageMaker-Inference-Component">>, <<"InferenceComponentName">>}, {<<"X-Amzn-SageMaker-Inference-Id">>, <<"InferenceId">>}, {<<"X-Amzn-SageMaker-Session-Id">>, <<"SessionId">>}, {<<"X-Amzn-SageMaker-Target-Container-Hostname">>, <<"TargetContainerHostname">>}, {<<"X-Amzn-SageMaker-Target-Variant">>, <<"TargetVariant">>} ], {Headers, Input1} = aws_request:build_headers(HeadersMapping, Input0), CustomHeaders = [], Input2 = Input1, Query_ = [], Input = Input2, case request(Client, Method, Path, Query_, CustomHeaders ++ Headers, Input, Options, SuccessStatusCode) of {ok, Body0, {_, ResponseHeaders, _} = Response} -> ResponseHeadersParams = [ {<<"X-Amzn-SageMaker-Content-Type">>, <<"ContentType">>}, {<<"X-Amzn-SageMaker-Custom-Attributes">>, <<"CustomAttributes">>}, {<<"x-Amzn-Invoked-Production-Variant">>, <<"InvokedProductionVariant">>} ], FoldFun = fun({Name_, Key_}, Acc_) -> case lists:keyfind(Name_, 1, ResponseHeaders) of false -> Acc_; {_, Value_} -> Acc_#{Key_ => Value_} end end, Body = lists:foldl(FoldFun, Body0, ResponseHeadersParams), {ok, Body, Response}; Result -> Result end. %%==================================================================== %% Internal functions %%==================================================================== -spec proplists_take(any(), proplists:proplist(), any()) -> {any(), proplists:proplist()}. proplists_take(Key, Proplist, Default) -> Value = proplists:get_value(Key, Proplist, Default), {Value, proplists:delete(Key, Proplist)}. -spec request(aws_client:aws_client(), atom(), iolist(), list(), list(), map() | undefined, list(), pos_integer() | undefined) -> {ok, {integer(), list()}} | {ok, Result, {integer(), list(), hackney:client()}} | {error, Error, {integer(), list(), hackney:client()}} | {error, term()} when Result :: map(), Error :: map(). request(Client, Method, Path, Query, Headers0, Input, Options, SuccessStatusCode) -> RequestFun = fun() -> do_request(Client, Method, Path, Query, Headers0, Input, Options, SuccessStatusCode) end, aws_request:request(RequestFun, Options). do_request(Client, Method, Path, Query, Headers0, Input, Options, SuccessStatusCode) -> Client1 = Client#{service => <<"sagemaker">>}, DefaultHost = build_host(<<"runtime.sagemaker">>, Client1), URL0 = build_url(DefaultHost, Path, Client1), PathBin = erlang:iolist_to_binary(Path), {URL1, Host} = aws_util:apply_endpoint_url_override(URL0, DefaultHost, PathBin, <<"AWS_ENDPOINT_URL_AWS_SAGEMAKER_RUNTIME">>), URL = aws_request:add_query(URL1, Query), AdditionalHeaders1 = [ {<<"Host">>, Host} , {<<"Content-Type">>, <<"application/x-amz-json-1.1">>} ], Payload = case proplists:get_value(send_body_as_binary, Options) of true -> maps:get(<<"Body">>, Input, <<"">>); false -> encode_payload(Input) end, AdditionalHeaders = case proplists:get_value(append_sha256_content_hash, Options, false) of true -> add_checksum_hash_header(AdditionalHeaders1, Payload); false -> AdditionalHeaders1 end, Headers1 = aws_request:add_headers(AdditionalHeaders, Headers0), MethodBin = aws_request:method_to_binary(Method), SignedHeaders = aws_request:sign_request(Client1, MethodBin, URL, Headers1, Payload), Response = hackney:request(Method, URL, SignedHeaders, Payload, Options), DecodeBody = not proplists:get_value(receive_body_as_binary, Options), handle_response(Response, SuccessStatusCode, DecodeBody). add_checksum_hash_header(Headers, Body) -> [ {<<"X-Amz-CheckSum-SHA256">>, base64:encode(crypto:hash(sha256, Body))} | Headers ]. handle_response({ok, StatusCode, ResponseHeaders}, SuccessStatusCode, _DecodeBody) when StatusCode =:= 200; StatusCode =:= 202; StatusCode =:= 204; StatusCode =:= 206; StatusCode =:= SuccessStatusCode -> {ok, {StatusCode, ResponseHeaders}}; handle_response({ok, StatusCode, ResponseHeaders}, _, _DecodeBody) -> {error, {StatusCode, ResponseHeaders}}; handle_response({ok, StatusCode, ResponseHeaders, Client}, SuccessStatusCode, DecodeBody) when StatusCode =:= 200; StatusCode =:= 202; StatusCode =:= 204; StatusCode =:= 206; StatusCode =:= SuccessStatusCode -> case hackney:body(Client) of {ok, <<>>} when StatusCode =:= 200; StatusCode =:= SuccessStatusCode -> {ok, #{}, {StatusCode, ResponseHeaders, Client}}; {ok, Body} -> Result = case DecodeBody of true -> try jsx:decode(Body) catch Error:Reason:Stack -> erlang:raise(error, {body_decode_failed, Error, Reason, StatusCode, Body}, Stack) end; false -> #{<<"Body">> => Body} end, {ok, Result, {StatusCode, ResponseHeaders, Client}} end; handle_response({ok, StatusCode, _ResponseHeaders, _Client}, _, _DecodeBody) when StatusCode =:= 503 -> %% Retriable error if retries are enabled {error, service_unavailable}; handle_response({ok, StatusCode, ResponseHeaders, Client}, _, _DecodeBody) -> {ok, Body} = hackney:body(Client), try DecodedError = jsx:decode(Body), {error, DecodedError, {StatusCode, ResponseHeaders, Client}} catch Error:Reason:Stack -> erlang:raise(error, {body_decode_failed, Error, Reason, StatusCode, Body}, Stack) end; handle_response({error, Reason}, _, _DecodeBody) -> {error, Reason}. build_host(_EndpointPrefix, #{region := <<"local">>, endpoint := Endpoint}) -> Endpoint; build_host(_EndpointPrefix, #{region := <<"local">>}) -> <<"localhost">>; build_host(EndpointPrefix, #{region := Region, endpoint := Endpoint}) -> aws_util:binary_join([EndpointPrefix, Region, Endpoint], <<".">>). build_url(Host, Path0, Client) -> Proto = aws_client:proto(Client), Path = erlang:iolist_to_binary(Path0), Port = aws_client:port(Client), aws_util:binary_join([Proto, <<"://">>, Host, <<":">>, Port, Path], <<"">>). -spec encode_payload(undefined | map()) -> binary(). encode_payload(undefined) -> <<>>; encode_payload(Input) -> jsx:encode(Input).