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doc(aiplatform): add Vertex AI samples (#14703)
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‎google/cloud/aiplatform/CMakeLists.txt‎

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@@ -33,3 +33,5 @@ if (BUILD_TESTING AND GOOGLE_CLOUD_CPP_ENABLE_CXX_EXCEPTIONS)
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set_tests_properties(aiplatform_quickstart
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PROPERTIES LABELS "integration-test;quickstart")
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endif ()
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add_subdirectory(samples)

‎google/cloud/aiplatform/samples/BUILD.bazel‎

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# Copyright 2024 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# https://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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package(default_visibility = ["//visibility:private"])
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licenses(["notice"]) # Apache 2.0
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[cc_test(
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name = sample.replace(".cc", ""),
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srcs = [sample],
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tags = [
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"integration-test",
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],
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deps = [
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"//:aiplatform",
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"//google/cloud/testing_util:google_cloud_cpp_testing_private",
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],
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) for sample in glob(["*.cc"])]

‎google/cloud/aiplatform/samples/CMakeLists.txt‎

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# Copyright 2024 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License"); you may not
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# use this file except in compliance with the License. You may obtain a copy of
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# the License at
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#
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# https://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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# License for the specific language governing permissions and limitations under
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# the License.
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if ((NOT BUILD_TESTING) OR (NOT GOOGLE_CLOUD_CPP_ENABLE_CXX_EXCEPTIONS))
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return()
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endif ()
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google_cloud_cpp_add_samples(aiplatform)

‎google/cloud/aiplatform/samples/samples.cc‎

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// Copyright 2024 Google LLC
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// https://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include "google/cloud/aiplatform/v1/prediction_client.h"
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#include "google/cloud/internal/getenv.h"
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#include "google/cloud/location.h"
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#include "google/cloud/testing_util/example_driver.h"
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#include <string>
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#include <vector>
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namespace {
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void GeminiGenerateFromTextInput(std::vector<std::string> const& argv) {
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if (argv.size() < 4) {
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throw google::cloud::testing_util::Usage(
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"gemini-generate-from-text-input <project> <location> <model-name> "
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"[<content>]+");
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}
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// [START generativeaionvertexai_gemini_generate_from_text_input]
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namespace vertex_ai = ::google::cloud::aiplatform_v1;
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namespace vertex_ai_proto = ::google::cloud::aiplatform::v1;
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[](std::string const& project_id, std::string const& location_id,
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std::string const& model, std::vector<std::string> const& content) {
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google::cloud::Location location(project_id, location_id);
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auto client = vertex_ai::PredictionServiceClient(
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vertex_ai::MakePredictionServiceConnection(location.location_id()));
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std::vector<vertex_ai_proto::Content> contents;
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for (auto const& c : content) {
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vertex_ai_proto::Content content;
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content.set_role("user");
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content.add_parts()->set_text(c);
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contents.push_back(std::move(content));
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}
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auto response = client.GenerateContent(
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location.FullName() + "/publishers/google/models/" + model, contents);
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if (!response) throw std::move(response).status();
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for (auto const& candidate : response->candidates()) {
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for (auto const& p : candidate.content().parts()) {
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std::cout << p.text() << "\n";
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}
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}
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}
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// [END generativeaionvertexai_gemini_generate_from_text_input]
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(argv.at(0), argv.at(1), argv.at(2), {argv.begin() + 3, argv.end()});
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}
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void GeminiGenerateWithImage(std::vector<std::string> const& argv) {
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if (argv.size() != 6) {
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throw google::cloud::testing_util::Usage(
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"gemini-generate-with-image <project> <location> <model-name> "
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"<prompt> <mime-type> <file-uri>");
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}
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// [START generativeaionvertexai_gemini_get_started]
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namespace vertex_ai = ::google::cloud::aiplatform_v1;
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namespace vertex_ai_proto = ::google::cloud::aiplatform::v1;
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[](std::string const& project_id, std::string const& location_id,
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std::string const& model, std::string const& prompt,
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std::string const& mime_type, std::string const& file_uri) {
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google::cloud::Location location(project_id, location_id);
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auto client = vertex_ai::PredictionServiceClient(
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vertex_ai::MakePredictionServiceConnection(location.location_id()));
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vertex_ai_proto::GenerateContentRequest request;
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request.set_model(location.FullName() + "/publishers/google/models/" +
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model);
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auto generation_config = request.mutable_generation_config();
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generation_config->set_temperature(0.4f);
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generation_config->set_top_k(32);
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generation_config->set_top_p(1);
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generation_config->set_max_output_tokens(2048);
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auto contents = request.add_contents();
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contents->set_role("user");
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contents->add_parts()->set_text(prompt);
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auto image_part = contents->add_parts();
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image_part->mutable_file_data()->set_file_uri(file_uri);
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image_part->mutable_file_data()->set_mime_type(mime_type);
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auto response = client.GenerateContent(request);
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if (!response) throw std::move(response).status();
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for (auto const& candidate : response->candidates()) {
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for (auto const& p : candidate.content().parts()) {
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std::cout << p.text() << "\n";
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}
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}
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}
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// [END generativeaionvertexai_gemini_get_started]
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(argv.at(0), argv.at(1), argv.at(2), argv.at(3), argv.at(4), argv.at(5));
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}
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void GeminiVideoWithAudio(std::vector<std::string> const& argv) {
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if (argv.size() != 6) {
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throw google::cloud::testing_util::Usage(
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"gemini-video-with-audio <project> <location> <model-name> "
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"<prompt> <mime-type> <file-uri>");
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}
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// [START generativeaionvertexai_gemini_video_with_audio]
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namespace vertex_ai = ::google::cloud::aiplatform_v1;
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namespace vertex_ai_proto = ::google::cloud::aiplatform::v1;
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[](std::string const& project_id, std::string const& location_id,
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std::string const& model, std::string const& prompt,
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std::string const& mime_type, std::string const& file_uri) {
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google::cloud::Location location(project_id, location_id);
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auto client = vertex_ai::PredictionServiceClient(
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vertex_ai::MakePredictionServiceConnection(location.location_id()));
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vertex_ai_proto::GenerateContentRequest request;
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request.set_model(location.FullName() + "/publishers/google/models/" +
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model);
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auto contents = request.add_contents();
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contents->set_role("user");
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contents->add_parts()->set_text(prompt);
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auto image_part = contents->add_parts();
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image_part->mutable_file_data()->set_file_uri(file_uri);
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image_part->mutable_file_data()->set_mime_type(mime_type);
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auto response = client.GenerateContent(request);
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if (!response) throw std::move(response).status();
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for (auto const& candidate : response->candidates()) {
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for (auto const& p : candidate.content().parts()) {
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std::cout << p.text() << "\n";
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}
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}
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}
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// [END generativeaionvertexai_gemini_video_with_audio]
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(argv.at(0), argv.at(1), argv.at(2), argv.at(3), argv.at(4), argv.at(5));
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}
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void AutoRun(std::vector<std::string> const& argv) {
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namespace examples = ::google::cloud::testing_util;
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if (!argv.empty()) throw examples::Usage{"auto"};
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examples::CheckEnvironmentVariablesAreSet({
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"GOOGLE_CLOUD_PROJECT",
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});
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auto const project_id =
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google::cloud::internal::GetEnv("GOOGLE_CLOUD_PROJECT").value();
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std::cout << "Executing GeminiGenerateFromTextInput sample:\n";
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GeminiGenerateFromTextInput(
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{project_id, "us-central1", "gemini-1.5-flash-001",
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"What's a good name for a flower shop that specializes in selling "
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"bouquets of dried flowers?"});
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std::cout << "\nExecuting GeminiGenerateWithImage sample:\n";
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GeminiGenerateWithImage({project_id, "us-central1", "gemini-1.5-flash-001",
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"What's in this photo?", "image/png",
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"gs://generativeai-downloads/images/scones.jpg"});
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std::cout << "\nExecuting GeminiVideoWithAudio sample:\n";
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GeminiVideoWithAudio(
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{project_id, "us-central1", "gemini-1.5-flash-001",
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"Provide a description of the video.\n"
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"The description should also contain anything important which people "
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"say in the video.",
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"video/mp4", "gs://cloud-samples-data/generative-ai/video/pixel8.mp4"});
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std::cout << "\nAutoRun done" << std::endl;
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}
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} // namespace
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int main(int argc, char* argv[]) { // NOLINT(bugprone-exception-escape)
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google::cloud::testing_util::Example example(
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{{"gemini-generate-with-image", GeminiGenerateWithImage},
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{"gemini-generate-from-text-input", GeminiGenerateFromTextInput},
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{"gemini-video-with-audio", GeminiVideoWithAudio},
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{"auto", AutoRun}});
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return example.Run(argc, argv);
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}

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