/* * # Licensed to the LF AI & Data foundation under one * # or more contributor license agreements. See the NOTICE file * # distributed with this work for additional information * # regarding copyright ownership. The ASF licenses this file * # to you 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 function import ( "fmt" "os" "strconv" "strings" "github.com/milvus-io/milvus-proto/go-api/v2/schemapb" "github.com/milvus-io/milvus/internal/util/function/models/tei" "github.com/milvus-io/milvus/pkg/v2/util/typeutil" ) type TeiEmbeddingProvider struct { fieldDim int64 client *tei.TEIEmbedding ingestionPrompt string searchPrompt string truncate bool truncationDirection string maxBatch int timeoutSec int64 } func createTEIEmbeddingClient(apiKey string, endpoint string) (*tei.TEIEmbedding, error) { enable := os.Getenv(enableTeiEnvStr) if strings.ToLower(enable) == "false" { return nil, fmt.Errorf("TEI model serving is not enabled") } return tei.NewTEIEmbeddingClient(apiKey, endpoint) } func NewTEIEmbeddingProvider(fieldSchema *schemapb.FieldSchema, functionSchema *schemapb.FunctionSchema, params map[string]string) (*TeiEmbeddingProvider, error) { fieldDim, err := typeutil.GetDim(fieldSchema) if err != nil { return nil, err } var apiKey, endpoint, ingestionPrompt, searchPrompt string // TEI default client batch size maxBatch := 32 truncate := false // TEI default is right truncationDirection := "" for _, param := range functionSchema.Params { switch strings.ToLower(param.Key) { case apiKeyParamKey: apiKey = param.Value case endpointParamKey: endpoint = param.Value case ingestionPromptParamKey: ingestionPrompt = param.Value case searchPromptParamKey: searchPrompt = param.Value case maxClientBatchSizeParamKey: if maxBatch, err = strconv.Atoi(param.Value); err != nil { return nil, fmt.Errorf("[%s param's value: %s] is not a valid number", maxClientBatchSizeParamKey, param.Value) } case truncationDirectionParamKey: if truncationDirection = param.Value; truncationDirection != "Left" && truncationDirection != "Right" { return nil, fmt.Errorf("[%s param's value: %s] is not invalid, only supports [Left/Right]", truncationDirectionParamKey, param.Value) } case truncateParamKey: if truncate, err = strconv.ParseBool(param.Value); err != nil { return nil, fmt.Errorf("[%s param's value: %s] is invalid, only supports: [true/false]", truncateParamKey, param.Value) } default: } } c, err := createTEIEmbeddingClient(apiKey, endpoint) if err != nil { return nil, err } provider := TeiEmbeddingProvider{ client: c, fieldDim: fieldDim, ingestionPrompt: ingestionPrompt, searchPrompt: searchPrompt, truncationDirection: truncationDirection, maxBatch: maxBatch, truncate: truncate, timeoutSec: 30, } return &provider, nil } func (provider *TeiEmbeddingProvider) MaxBatch() int { return 5 * provider.maxBatch } func (provider *TeiEmbeddingProvider) FieldDim() int64 { return provider.fieldDim } func (provider *TeiEmbeddingProvider) CallEmbedding(texts []string, mode TextEmbeddingMode) (any, error) { numRows := len(texts) data := make([][]float32, 0, numRows) var prompt string if mode == InsertMode { prompt = provider.ingestionPrompt } else { prompt = provider.searchPrompt } for i := 0; i < numRows; i += provider.maxBatch { end := i + provider.maxBatch if end > numRows { end = numRows } resp, err := provider.client.Embedding(texts[i:end], provider.truncate, provider.truncationDirection, prompt, provider.timeoutSec) if err != nil { return nil, err } if end-i != len(resp) { return nil, fmt.Errorf("Get embedding failed. The number of texts and embeddings does not match text:[%d], embedding:[%d]", end-i, len(resp)) } for _, item := range resp { if len(item) != int(provider.fieldDim) { return nil, fmt.Errorf("The required embedding dim is [%d], but the embedding obtained from the model is [%d]", provider.fieldDim, len(item)) } data = append(data, item) } } return data, nil }