milvus/internal/util/function/siliconflow_embedding_provi...

130 lines
4.0 KiB
Go

/*
* # 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"
"strings"
"github.com/milvus-io/milvus-proto/go-api/v2/schemapb"
"github.com/milvus-io/milvus/internal/util/function/models/siliconflow"
"github.com/milvus-io/milvus/pkg/v2/util/typeutil"
)
type SiliconflowEmbeddingProvider struct {
fieldDim int64
client *siliconflow.SiliconflowEmbedding
modelName string
embedDimParam int64
maxBatch int
timeoutSec int64
}
func createSiliconflowEmbeddingClient(apiKey string, url string) (*siliconflow.SiliconflowEmbedding, error) {
if apiKey == "" {
apiKey = os.Getenv(siliconflowAKEnvStr)
}
if apiKey == "" {
return nil, fmt.Errorf("Missing credentials. Please pass `api_key`, or configure the %s environment variable in the Milvus service.", siliconflowAKEnvStr)
}
if url == "" {
url = "https://api.siliconflow.cn/v1/embeddings"
}
c := siliconflow.NewSiliconflowEmbeddingClient(apiKey, url)
return c, nil
}
func NewSiliconflowEmbeddingProvider(fieldSchema *schemapb.FieldSchema, functionSchema *schemapb.FunctionSchema) (*SiliconflowEmbeddingProvider, error) {
fieldDim, err := typeutil.GetDim(fieldSchema)
if err != nil {
return nil, err
}
var apiKey, url, modelName string
for _, param := range functionSchema.Params {
switch strings.ToLower(param.Key) {
case modelNameParamKey:
modelName = param.Value
case apiKeyParamKey:
apiKey = param.Value
case embeddingURLParamKey:
url = param.Value
default:
}
}
if modelName != bAAIBgeLargeZhV15 && modelName != bAAIBgeLargeEhV15 && modelName != neteaseYoudaoBceEmbeddingBasev1 && modelName != bAAIBgeM3 && modelName != proBAAIBgeM3 {
return nil, fmt.Errorf("Unsupported model: %s, only support [%s, %s, %s, %s, %s]",
modelName, bAAIBgeLargeZhV15, bAAIBgeLargeEhV15, neteaseYoudaoBceEmbeddingBasev1, bAAIBgeM3, proBAAIBgeM3)
}
c, err := createSiliconflowEmbeddingClient(apiKey, url)
if err != nil {
return nil, err
}
provider := SiliconflowEmbeddingProvider{
client: c,
fieldDim: fieldDim,
modelName: modelName,
maxBatch: 32,
timeoutSec: 30,
}
return &provider, nil
}
func (provider *SiliconflowEmbeddingProvider) MaxBatch() int {
return 5 * provider.maxBatch
}
func (provider *SiliconflowEmbeddingProvider) FieldDim() int64 {
return provider.fieldDim
}
func (provider *SiliconflowEmbeddingProvider) CallEmbedding(texts []string, _ TextEmbeddingMode) ([][]float32, error) {
numRows := len(texts)
data := make([][]float32, 0, numRows)
for i := 0; i < numRows; i += provider.maxBatch {
end := i + provider.maxBatch
if end > numRows {
end = numRows
}
resp, err := provider.client.Embedding(provider.modelName, texts[i:end], "float", provider.timeoutSec)
if err != nil {
return nil, err
}
if end-i != len(resp.Data) {
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))
}
for _, item := range resp.Data {
if len(item.Embedding) != 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.Embedding))
}
data = append(data, item.Embedding)
}
}
return data, nil
}