package embedding import ( "encoding/json" "errors" "fmt" "net/http" "github.com/alibaba/higress/plugins/wasm-go/pkg/log" "github.com/alibaba/higress/plugins/wasm-go/pkg/wrapper" "github.com/tidwall/gjson" ) const ( OPENAI_DOMAIN = "api.openai.com" OPENAI_PORT = 443 OPENAI_DEFAULT_MODEL_NAME = "text-embedding-3-small" OPENAI_ENDPOINT = "/v1/embeddings" ) type openAIProviderInitializer struct { } var openAIConfig openAIProviderConfig type openAIProviderConfig struct { // @Title zh-CN 文本特征提取服务 API Key // @Description zh-CN 文本特征提取服务 API Key apiKey string } func (c *openAIProviderInitializer) InitConfig(json gjson.Result) { openAIConfig.apiKey = json.Get("apiKey").String() } func (c *openAIProviderInitializer) ValidateConfig() error { if openAIConfig.apiKey == "" { return errors.New("[openAI] apiKey is required") } return nil } func (t *openAIProviderInitializer) CreateProvider(c ProviderConfig) (Provider, error) { if c.servicePort == 0 { c.servicePort = OPENAI_PORT } if c.serviceHost == "" { c.serviceHost = OPENAI_DOMAIN } if c.model == "" { c.model = OPENAI_DEFAULT_MODEL_NAME } return &OpenAIProvider{ config: c, client: wrapper.NewClusterClient(wrapper.FQDNCluster{ FQDN: c.serviceName, Host: c.serviceHost, Port: c.servicePort, }), }, nil } func (t *OpenAIProvider) GetProviderType() string { return PROVIDER_TYPE_OPENAI } type OpenAIResponse struct { Object string `json:"object"` Data []OpenAIResult `json:"data"` Model string `json:"model"` Error *OpenAIError `json:"error"` } type OpenAIResult struct { Object string `json:"object"` Embedding []float64 `json:"embedding"` Index int `json:"index"` } type OpenAIError struct { Message string `json:"prompt_tokens"` Type string `json:"type"` Code string `json:"code"` Param string `json:"param"` } type OpenAIEmbeddingRequest struct { Input string `json:"input"` Model string `json:"model"` } type OpenAIProvider struct { config ProviderConfig client wrapper.HttpClient } func (t *OpenAIProvider) constructParameters(text string) (string, [][2]string, []byte, error) { if text == "" { err := errors.New("queryString text cannot be empty") return "", nil, nil, err } data := OpenAIEmbeddingRequest{ Input: text, Model: t.config.model, } requestBody, err := json.Marshal(data) if err != nil { log.Errorf("failed to marshal request data: %v", err) return "", nil, nil, err } headers := [][2]string{ {"Authorization", fmt.Sprintf("Bearer %s", openAIConfig.apiKey)}, {"Content-Type", "application/json"}, } return OPENAI_ENDPOINT, headers, requestBody, err } func (t *OpenAIProvider) parseTextEmbedding(responseBody []byte) (*OpenAIResponse, error) { var resp OpenAIResponse err := json.Unmarshal(responseBody, &resp) if err != nil { return nil, err } return &resp, nil } func (t *OpenAIProvider) GetEmbedding( queryString string, ctx wrapper.HttpContext, callback func(emb []float64, err error)) error { embUrl, embHeaders, embRequestBody, err := t.constructParameters(queryString) if err != nil { log.Errorf("failed to construct parameters: %v", err) return err } var resp *OpenAIResponse err = t.client.Post(embUrl, embHeaders, embRequestBody, func(statusCode int, responseHeaders http.Header, responseBody []byte) { if statusCode != http.StatusOK { err = fmt.Errorf("failed to get embedding due to status code: %d, resp: %s", statusCode, responseBody) callback(nil, err) return } resp, err = t.parseTextEmbedding(responseBody) if err != nil { err = fmt.Errorf("failed to parse response: %v", err) callback(nil, err) return } log.Debugf("get embedding response: %d, %s", statusCode, responseBody) if len(resp.Data) == 0 { err = errors.New("no embedding found in response") callback(nil, err) return } callback(resp.Data[0].Embedding, nil) }, t.config.timeout) return err }