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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,75 @@ | ||
| // Copyright 2024 Google LLC | ||
| // | ||
| // Licensed under the Apache License, Version 2.0 (the "License"); | ||
| // you may not use this file except in compliance with the License. | ||
| // You may obtain a copy of the License at | ||
| // | ||
| // http://www.apache.org/licenses/LICENSE-2.0 | ||
| // | ||
| // Unless required by applicable law or agreed to in writing, software | ||
| // distributed under the License is distributed on an "AS IS" BASIS, | ||
| // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| // See the License for the specific language governing permissions and | ||
| // limitations under the License. | ||
|
|
||
| package snippets | ||
|
|
||
| // [START aiplatform_text_embeddings] | ||
| import ( | ||
| "context" | ||
| "fmt" | ||
| "regexp" | ||
|
|
||
| aiplatform "cloud.google.com/go/aiplatform/apiv1" | ||
| "cloud.google.com/go/aiplatform/apiv1/aiplatformpb" | ||
|
|
||
| "google.golang.org/api/option" | ||
| "google.golang.org/protobuf/types/known/structpb" | ||
| ) | ||
|
|
||
| func embedTexts( | ||
| apiEndpoint, project, model string, texts []string, task string) ([][]float32, error) { | ||
| ctx := context.Background() | ||
|
|
||
| client, err := aiplatform.NewPredictionClient(ctx, option.WithEndpoint(apiEndpoint)) | ||
| if err != nil { | ||
| return nil, err | ||
| } | ||
| defer client.Close() | ||
|
|
||
| match := regexp.MustCompile(`^(\w+-\w+)`).FindStringSubmatch(apiEndpoint) | ||
| location := "us-central1" | ||
| if match != nil { | ||
| location = match[1] | ||
| } | ||
| endpoint := fmt.Sprintf("projects/%s/locations/%s/publishers/google/models/%s", project, location, model) | ||
| instances := make([]*structpb.Value, len(texts)) | ||
| for i, text := range texts { | ||
| instances[i] = structpb.NewStructValue(&structpb.Struct{ | ||
| Fields: map[string]*structpb.Value{ | ||
| "content": structpb.NewStringValue(text), | ||
| "task_type": structpb.NewStringValue(task), | ||
| }, | ||
| }) | ||
| } | ||
|
|
||
| req := &aiplatformpb.PredictRequest{ | ||
| Endpoint: endpoint, | ||
| Instances: instances, | ||
| } | ||
| resp, err := client.Predict(ctx, req) | ||
| if err != nil { | ||
| return nil, err | ||
| } | ||
| embeddings := make([][]float32, len(resp.Predictions)) | ||
| for i, prediction := range resp.Predictions { | ||
| values := prediction.GetStructValue().Fields["embeddings"].GetStructValue().Fields["values"].GetListValue().Values | ||
| embeddings[i] = make([]float32, len(values)) | ||
| for j, value := range values { | ||
| embeddings[i][j] = float32(value.GetNumberValue()) | ||
| } | ||
| } | ||
| return embeddings, nil | ||
| } | ||
|
|
||
| // [END aiplatform_text_embeddings] |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,84 @@ | ||
| // Copyright 2024 Google LLC | ||
| // | ||
| // Licensed under the Apache License, Version 2.0 (the "License"); | ||
| // you may not use this file except in compliance with the License. | ||
| // You may obtain a copy of the License at | ||
| // | ||
| // http://www.apache.org/licenses/LICENSE-2.0 | ||
| // | ||
| // Unless required by applicable law or agreed to in writing, software | ||
| // distributed under the License is distributed on an "AS IS" BASIS, | ||
| // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| // See the License for the specific language governing permissions and | ||
| // limitations under the License. | ||
|
|
||
| package snippets | ||
|
|
||
| // [START generativeaionvertexai_sdk_embedding] | ||
| import ( | ||
| "context" | ||
| "fmt" | ||
| "regexp" | ||
|
|
||
| aiplatform "cloud.google.com/go/aiplatform/apiv1" | ||
| "cloud.google.com/go/aiplatform/apiv1/aiplatformpb" | ||
|
|
||
| "google.golang.org/api/option" | ||
| "google.golang.org/protobuf/types/known/structpb" | ||
| ) | ||
|
|
||
| func embedTextsPreview( | ||
| apiEndpoint, project, model string, texts []string, | ||
| task string, dimensionality *int) ([][]float32, error) { | ||
| ctx := context.Background() | ||
|
|
||
| client, err := aiplatform.NewPredictionClient(ctx, option.WithEndpoint(apiEndpoint)) | ||
| if err != nil { | ||
| return nil, err | ||
| } | ||
| defer client.Close() | ||
|
|
||
| match := regexp.MustCompile(`^(\w+-\w+)`).FindStringSubmatch(apiEndpoint) | ||
| location := "us-central1" | ||
| if match != nil { | ||
| location = match[1] | ||
| } | ||
| endpoint := fmt.Sprintf("projects/%s/locations/%s/publishers/google/models/%s", project, location, model) | ||
| instances := make([]*structpb.Value, len(texts)) | ||
| for i, text := range texts { | ||
| instances[i] = structpb.NewStructValue(&structpb.Struct{ | ||
| Fields: map[string]*structpb.Value{ | ||
| "content": structpb.NewStringValue(text), | ||
| "task_type": structpb.NewStringValue(task), | ||
| }, | ||
| }) | ||
| } | ||
| outputDimensionality := structpb.NewNullValue() | ||
| if dimensionality != nil { | ||
| outputDimensionality = structpb.NewNumberValue(float64(*dimensionality)) | ||
| } | ||
| params := structpb.NewStructValue(&structpb.Struct{ | ||
| Fields: map[string]*structpb.Value{"outputDimensionality": outputDimensionality}, | ||
| }) | ||
|
|
||
| req := &aiplatformpb.PredictRequest{ | ||
| Endpoint: endpoint, | ||
| Instances: instances, | ||
| Parameters: params, | ||
| } | ||
| resp, err := client.Predict(ctx, req) | ||
| if err != nil { | ||
| return nil, err | ||
| } | ||
| embeddings := make([][]float32, len(resp.Predictions)) | ||
| for i, prediction := range resp.Predictions { | ||
| values := prediction.GetStructValue().Fields["embeddings"].GetStructValue().Fields["values"].GetListValue().Values | ||
| embeddings[i] = make([]float32, len(values)) | ||
| for j, value := range values { | ||
| embeddings[i][j] = float32(value.GetNumberValue()) | ||
| } | ||
| } | ||
| return embeddings, nil | ||
| } | ||
|
|
||
| // [END generativeaionvertexai_sdk_embedding] |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,50 @@ | ||
| // Copyright 2024 Google LLC | ||
| // | ||
| // Licensed under the Apache License, Version 2.0 (the "License"); | ||
| // you may not use this file except in compliance with the License. | ||
| // You may obtain a copy of the License at | ||
| // | ||
| // http://www.apache.org/licenses/LICENSE-2.0 | ||
| // | ||
| // Unless required by applicable law or agreed to in writing, software | ||
| // distributed under the License is distributed on an "AS IS" BASIS, | ||
| // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| // See the License for the specific language governing permissions and | ||
| // limitations under the License. | ||
|
|
||
| package snippets | ||
|
|
||
| import ( | ||
| "testing" | ||
|
|
||
| "github.com/GoogleCloudPlatform/golang-samples/internal/testutil" | ||
| ) | ||
|
|
||
| func TestGenerateEmbeddings(t *testing.T) { | ||
| tc := testutil.SystemTest(t) | ||
| apiEndpoint := "us-central1-aiplatform.googleapis.com:443" | ||
| model := "textembedding-gecko@003" | ||
| texts := []string{"banana muffins? ", "banana bread? banana muffins?"} | ||
| embeddings, err := embedTexts(apiEndpoint, tc.ProjectID, model, texts, "RETRIEVAL_DOCUMENT") | ||
| if err != nil { | ||
| t.Fatal(err) | ||
| } | ||
| if len(embeddings) != len(texts) || len(embeddings[0]) != 768 { | ||
| t.Errorf("len(embeddings), len(embeddings[0]) = %d, %d, want %d, 768", len(embeddings), len(embeddings[0]), len(texts)) | ||
| } | ||
| } | ||
|
|
||
| func TestGenerateEmbeddingsPreview(t *testing.T) { | ||
| tc := testutil.SystemTest(t) | ||
| apiEndpoint := "us-central1-aiplatform.googleapis.com:443" | ||
| model := "text-embedding-preview-0409" | ||
| texts := []string{"banana muffins? ", "banana bread? banana muffins?"} | ||
| dimensionality := 5 | ||
| embeddings, err := embedTextsPreview(apiEndpoint, tc.ProjectID, model, texts, "QUESTION_ANSWERING", &dimensionality) | ||
| if err != nil { | ||
| t.Fatal(err) | ||
| } | ||
| if len(embeddings) != len(texts) || len(embeddings[0]) != dimensionality { | ||
| t.Errorf("len(embeddings), len(embeddings[0]) = %d, %d, want %d, %d", len(embeddings), len(embeddings[0]), len(texts), dimensionality) | ||
| } | ||
| } |
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