mirror of https://github.com/milvus-io/milvus.git
130 lines
4.0 KiB
Go
130 lines
4.0 KiB
Go
/*
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* # Licensed to the LF AI & Data foundation under one
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* # or more contributor license agreements. See the NOTICE file
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* # distributed with this work for additional information
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* # regarding copyright ownership. The ASF licenses this file
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* # to you under the Apache License, Version 2.0 (the
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* # "License"); you may not use this file except in compliance
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* # with the License. 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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*/
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package function
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import (
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"fmt"
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"os"
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"strings"
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"github.com/milvus-io/milvus-proto/go-api/v2/schemapb"
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"github.com/milvus-io/milvus/internal/util/function/models/siliconflow"
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"github.com/milvus-io/milvus/pkg/v2/util/typeutil"
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)
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type SiliconflowEmbeddingProvider struct {
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fieldDim int64
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client *siliconflow.SiliconflowEmbedding
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modelName string
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embedDimParam int64
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maxBatch int
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timeoutSec int64
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}
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func createSiliconflowEmbeddingClient(apiKey string, url string) (*siliconflow.SiliconflowEmbedding, error) {
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if apiKey == "" {
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apiKey = os.Getenv(siliconflowAKEnvStr)
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}
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if apiKey == "" {
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return nil, fmt.Errorf("Missing credentials. Please pass `api_key`, or configure the %s environment variable in the Milvus service.", siliconflowAKEnvStr)
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}
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if url == "" {
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url = "https://api.siliconflow.cn/v1/embeddings"
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}
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c := siliconflow.NewSiliconflowEmbeddingClient(apiKey, url)
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return c, nil
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}
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func NewSiliconflowEmbeddingProvider(fieldSchema *schemapb.FieldSchema, functionSchema *schemapb.FunctionSchema) (*SiliconflowEmbeddingProvider, error) {
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fieldDim, err := typeutil.GetDim(fieldSchema)
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if err != nil {
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return nil, err
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}
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var apiKey, url, modelName string
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for _, param := range functionSchema.Params {
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switch strings.ToLower(param.Key) {
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case modelNameParamKey:
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modelName = param.Value
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case apiKeyParamKey:
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apiKey = param.Value
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case embeddingURLParamKey:
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url = param.Value
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default:
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}
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}
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if modelName != bAAIBgeLargeZhV15 && modelName != bAAIBgeLargeEhV15 && modelName != neteaseYoudaoBceEmbeddingBasev1 && modelName != bAAIBgeM3 && modelName != proBAAIBgeM3 {
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return nil, fmt.Errorf("Unsupported model: %s, only support [%s, %s, %s, %s, %s]",
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modelName, bAAIBgeLargeZhV15, bAAIBgeLargeEhV15, neteaseYoudaoBceEmbeddingBasev1, bAAIBgeM3, proBAAIBgeM3)
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}
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c, err := createSiliconflowEmbeddingClient(apiKey, url)
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if err != nil {
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return nil, err
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}
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provider := SiliconflowEmbeddingProvider{
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client: c,
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fieldDim: fieldDim,
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modelName: modelName,
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maxBatch: 32,
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timeoutSec: 30,
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}
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return &provider, nil
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}
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func (provider *SiliconflowEmbeddingProvider) MaxBatch() int {
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return 5 * provider.maxBatch
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}
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func (provider *SiliconflowEmbeddingProvider) FieldDim() int64 {
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return provider.fieldDim
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}
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func (provider *SiliconflowEmbeddingProvider) CallEmbedding(texts []string, _ TextEmbeddingMode) ([][]float32, error) {
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numRows := len(texts)
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data := make([][]float32, 0, numRows)
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for i := 0; i < numRows; i += provider.maxBatch {
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end := i + provider.maxBatch
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if end > numRows {
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end = numRows
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}
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resp, err := provider.client.Embedding(provider.modelName, texts[i:end], "float", provider.timeoutSec)
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if err != nil {
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return nil, err
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}
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if end-i != len(resp.Data) {
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return nil, fmt.Errorf("Get embedding failed. The number of texts and embeddings does not match text:[%d], embedding:[%d]", end-i, len(resp.Data))
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}
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for _, item := range resp.Data {
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if len(item.Embedding) != int(provider.fieldDim) {
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return nil, fmt.Errorf("The required embedding dim is [%d], but the embedding obtained from the model is [%d]",
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provider.fieldDim, len(item.Embedding))
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}
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data = append(data, item.Embedding)
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}
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}
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return data, nil
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}
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