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Add parameter `embeddedBy` field to support vector embedding & semantic search. Major change in `internal/util/parameters/parameters.go` This PR only adds vector formatter for the postgressql tool. Other tools requiring vector formatting may not work with embeddedBy. Second part of the Semantic Search support. First part: https://github.com/googleapis/genai-toolbox/pull/2121
60 lines
1.6 KiB
Go
60 lines
1.6 KiB
Go
// Copyright 2026 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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// http://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 embeddingmodels
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import (
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"context"
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"strconv"
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"strings"
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)
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// EmbeddingModelConfig is the interface for configuring embedding models.
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type EmbeddingModelConfig interface {
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EmbeddingModelConfigKind() string
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Initialize(context.Context) (EmbeddingModel, error)
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}
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type EmbeddingModel interface {
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EmbeddingModelKind() string
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ToConfig() EmbeddingModelConfig
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EmbedParameters(context.Context, []string) ([][]float32, error)
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}
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type VectorFormatter func(vectorFloats []float32) any
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// FormatVectorForPgvector converts a slice of floats into a PostgreSQL vector literal string: '[x, y, z]'
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func FormatVectorForPgvector(vectorFloats []float32) any {
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if len(vectorFloats) == 0 {
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return "[]"
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}
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// Pre-allocate the builder.
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var b strings.Builder
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b.Grow(len(vectorFloats) * 10)
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b.WriteByte('[')
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for i, f := range vectorFloats {
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if i > 0 {
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b.WriteString(", ")
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}
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b.Write(strconv.AppendFloat(nil, float64(f), 'g', -1, 32))
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}
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b.WriteByte(']')
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return b.String()
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}
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var _ VectorFormatter = FormatVectorForPgvector
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