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d3164e8030
https://github.com/milvus-io/milvus/issues/45544 - Add batch_factor configuration parameter (default: 5) to control embedding provider batch sizes - Add disable_func_runtime_check property to bypass function validation during collection creation - Add database interceptor support for AddCollectionFunction, AlterCollectionFunction, and DropCollectionFunction requests Signed-off-by: junjie.jiang <junjie.jiang@zilliz.com>
119 lines
3.6 KiB
Go
119 lines
3.6 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 embedding
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import (
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"context"
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"fmt"
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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/credentials"
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"github.com/milvus-io/milvus/internal/util/function/models"
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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.SiliconflowClient
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url string
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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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extraInfo *models.ModelExtraInfo
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}
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func NewSiliconflowEmbeddingProvider(fieldSchema *schemapb.FieldSchema, functionSchema *schemapb.FunctionSchema, params map[string]string, credentials *credentials.Credentials, extraInfo *models.ModelExtraInfo) (*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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apiKey, url, err := models.ParseAKAndURL(credentials, functionSchema.Params, params, models.SiliconflowAKEnvStr, extraInfo)
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if err != nil {
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return nil, err
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}
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var 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 models.ModelNameParamKey:
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modelName = param.Value
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default:
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}
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}
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c, err := siliconflow.NewSiliconflowClient(apiKey)
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if err != nil {
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return nil, err
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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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provider := SiliconflowEmbeddingProvider{
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client: c,
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url: url,
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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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extraInfo: extraInfo,
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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 provider.extraInfo.BatchFactor * 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(ctx context.Context, texts []string, _ models.TextEmbeddingMode) (any, 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.url, 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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