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2026-07-13 12:49:10 +08:00

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/*
* Copyright 2024 CloudWeGo Authors
*
* 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 embedding
import "context"
// Embedder converts a batch of strings into dense vector representations.
//
// EmbedStrings returns one vector per input text, in the same order. The
// vector length (dimensions) is fixed by the underlying model and identical
// for every text in the batch.
//
// The returned [][]float64 maps as:
//
// embeddings[i] → vector for texts[i]
// len(embeddings[i]) → model's embedding dimension (e.g. 1536 for ada-002)
//
// Both [Indexer] and [Retriever] use an Embedder to convert documents and
// queries into vectors. They must share the exact same model — mismatched
// dimensions or model families break semantic similarity.
//
//go:generate mockgen -destination ../../internal/mock/components/embedding/Embedding_mock.go --package embedding -source interface.go
type Embedder interface {
EmbedStrings(ctx context.Context, texts []string, opts ...Option) ([][]float64, error) // invoke
}