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182 lines
6.0 KiB
Go
182 lines
6.0 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 embedding
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import (
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"context"
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"strings"
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"github.com/milvus-io/milvus-proto/go-api/v3/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/cohere"
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"github.com/milvus-io/milvus/pkg/v3/util/merr"
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"github.com/milvus-io/milvus/pkg/v3/util/typeutil"
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)
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type CohereEmbeddingProvider struct {
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fieldDim int64
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client *cohere.CohereClient
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url string
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modelName string
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truncate string
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embedDimParam int64
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embdType models.EmbeddingType
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outputType string
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maxBatch int
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timeoutMs int64
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extraInfo *models.ModelExtraInfo
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}
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func NewCohereEmbeddingProvider(fieldSchema *schemapb.FieldSchema, functionSchema *schemapb.FunctionSchema, params map[string]string, credentials *credentials.Credentials, extraInfo *models.ModelExtraInfo) (*CohereEmbeddingProvider, 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.CohereAIAKEnvStr, 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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var dim int64
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truncate := "END"
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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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case models.DimParamKey:
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dim, err = models.ParseAndCheckFieldDim(param.Value, fieldDim, fieldSchema.Name)
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if err != nil {
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return nil, err
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}
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case models.TruncateParamKey:
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if param.Value != "NONE" && param.Value != "START" && param.Value != "END" {
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return nil, merr.WrapErrParameterInvalidMsg("illegal parameters, %s only supports [NONE, START, END]", models.TruncateParamKey)
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}
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truncate = param.Value
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default:
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}
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}
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c, err := cohere.NewCohereClient(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.cohere.com/v2/embed"
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}
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embdType := models.GetEmbdType(fieldSchema.DataType)
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if embdType == models.UnsupportEmbd {
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return nil, merr.WrapErrParameterInvalidMsg("unsupport output type: %s", fieldSchema.DataType)
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}
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outputType := func() string {
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if embdType == models.Float32Embd {
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return "float"
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}
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return "int8"
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}()
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timeoutMs := models.ResolveTimeoutMs(functionSchema.Params)
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provider := CohereEmbeddingProvider{
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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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truncate: truncate,
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embedDimParam: dim,
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embdType: embdType,
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outputType: outputType,
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maxBatch: 96,
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timeoutMs: timeoutMs,
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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 *CohereEmbeddingProvider) MaxBatch() int {
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return provider.extraInfo.BatchFactor * provider.maxBatch
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}
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func (provider *CohereEmbeddingProvider) FieldDim() int64 {
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return provider.fieldDim
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}
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// Specifies the type of input passed to the model. Required for embedding models v3 and higher.
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func (provider *CohereEmbeddingProvider) getInputType(mode models.TextEmbeddingMode) string {
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// v2 models not support instructor
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if strings.HasSuffix(provider.modelName, "v2.0") {
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return ""
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}
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if mode == models.InsertMode {
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return "search_document" // Used for embeddings stored in a vector database for search use-cases.
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}
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return "search_query" // Used for embeddings of search queries run against a vector DB to find relevant documents.
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}
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func (provider *CohereEmbeddingProvider) CallEmbedding(ctx context.Context, texts []string, mode models.TextEmbeddingMode) (any, error) {
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numRows := len(texts)
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inputType := provider.getInputType(mode)
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embRet := models.NewEmbdResult(numRows, provider.embdType)
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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], inputType, provider.outputType, provider.truncate, int(provider.embedDimParam), provider.timeoutMs)
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if err != nil {
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return nil, err
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}
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if provider.embdType == models.Float32Embd {
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if end-i != len(resp.Embeddings.Float) {
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return nil, merr.WrapErrFunctionFailedMsg("get embedding failed. The number of texts and embeddings does not match text:[%d], embedding:[%d]", end-i, len(resp.Embeddings.Float))
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}
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for _, item := range resp.Embeddings.Float {
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if len(item) != int(provider.fieldDim) {
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return nil, merr.WrapErrFunctionFailedMsg("the required embedding dim is [%d], but the embedding obtained from the model is [%d]",
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provider.fieldDim, len(item))
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}
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}
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embRet.Append(resp.Embeddings.Float)
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} else {
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if end-i != len(resp.Embeddings.Int8) {
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return nil, merr.WrapErrFunctionFailedMsg("get embedding failed. The number of texts and embeddings does not match text:[%d], embedding:[%d]", end-i, len(resp.Embeddings.Int8))
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}
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for _, item := range resp.Embeddings.Int8 {
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if len(item) != int(provider.fieldDim) {
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return nil, merr.WrapErrFunctionFailedMsg("the required embedding dim is [%d], but the embedding obtained from the model is [%d]",
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provider.fieldDim, len(item))
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}
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}
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embRet.Append(resp.Embeddings.Int8)
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}
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}
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if embRet.EmbdType == models.Float32Embd {
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return embRet.FloatEmbds, nil
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}
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return embRet.Int8Embds, nil
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}
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