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Feat: Add Spark llm support for plugins/ai-proxy (#1139)
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urlyy
GitHub
207
plugins/wasm-go/extensions/ai-proxy/provider/spark.go
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207
plugins/wasm-go/extensions/ai-proxy/provider/spark.go
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package provider
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import (
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"encoding/json"
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"errors"
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"fmt"
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"strings"
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"time"
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"github.com/alibaba/higress/plugins/wasm-go/extensions/ai-proxy/util"
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"github.com/alibaba/higress/plugins/wasm-go/pkg/wrapper"
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"github.com/higress-group/proxy-wasm-go-sdk/proxywasm"
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"github.com/higress-group/proxy-wasm-go-sdk/proxywasm/types"
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)
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// sparkProvider is the provider for SparkLLM AI service.
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const (
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sparkHost = "spark-api-open.xf-yun.com"
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sparkChatCompletionPath = "/v1/chat/completions"
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)
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type sparkProviderInitializer struct {
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}
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type sparkProvider struct {
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config ProviderConfig
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contextCache *contextCache
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}
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type sparkRequest struct {
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Model string `json:"model"`
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Messages []chatMessage `json:"messages"`
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MaxTokens int `json:"max_tokens,omitempty"`
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TopK int `json:"top_k,omitempty"`
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Stream bool `json:"stream,omitempty"`
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Temperature float64 `json:"temperature,omitempty"`
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Tools []tool `json:"tools,omitempty"`
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ToolChoice string `json:"tool_choice,omitempty"`
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}
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type sparkResponse struct {
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Code int `json:"code"`
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Message string `json:"message"`
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Sid string `json:"sid"`
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Choices []chatCompletionChoice `json:"choices"`
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Usage usage `json:"usage,omitempty"`
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}
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type sparkStreamResponse struct {
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sparkResponse
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Id string `json:"id"`
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Created int64 `json:"created"`
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}
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func (i *sparkProviderInitializer) ValidateConfig(config ProviderConfig) error {
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return nil
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}
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func (i *sparkProviderInitializer) CreateProvider(config ProviderConfig) (Provider, error) {
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return &sparkProvider{
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config: config,
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contextCache: createContextCache(&config),
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}, nil
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}
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func (p *sparkProvider) GetProviderType() string {
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return providerTypeSpark
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}
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func (p *sparkProvider) OnRequestHeaders(ctx wrapper.HttpContext, apiName ApiName, log wrapper.Log) (types.Action, error) {
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if apiName != ApiNameChatCompletion {
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return types.ActionContinue, errUnsupportedApiName
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}
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_ = util.OverwriteRequestHost(sparkHost)
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_ = util.OverwriteRequestPath(sparkChatCompletionPath)
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_ = util.OverwriteRequestAuthorization("Bearer " + p.config.GetRandomToken())
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_ = proxywasm.RemoveHttpRequestHeader("Accept-Encoding")
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_ = proxywasm.RemoveHttpRequestHeader("Content-Length")
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return types.ActionContinue, nil
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}
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func (p *sparkProvider) OnRequestBody(ctx wrapper.HttpContext, apiName ApiName, body []byte, log wrapper.Log) (types.Action, error) {
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if apiName != ApiNameChatCompletion {
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return types.ActionContinue, errUnsupportedApiName
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}
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// 使用Spark协议
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if p.config.protocol == protocolOriginal {
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request := &sparkRequest{}
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if err := json.Unmarshal(body, request); err != nil {
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return types.ActionContinue, fmt.Errorf("unable to unmarshal request: %v", err)
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}
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if request.Model == "" {
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return types.ActionContinue, errors.New("request model is empty")
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}
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// 目前星火在模型名称错误时，也会调用generalv3，这里还是按照输入的模型名称设置响应里的模型名称
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ctx.SetContext(ctxKeyFinalRequestModel, request.Model)
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return types.ActionContinue, replaceJsonRequestBody(request, log)
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} else {
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// 使用openai协议
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request := &chatCompletionRequest{}
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if err := decodeChatCompletionRequest(body, request); err != nil {
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return types.ActionContinue, err
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}
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if request.Model == "" {
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return types.ActionContinue, errors.New("missing model in chat completion request")
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}
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// 映射模型
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mappedModel := getMappedModel(request.Model, p.config.modelMapping, log)
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if mappedModel == "" {
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return types.ActionContinue, errors.New("model becomes empty after applying the configured mapping")
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}
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ctx.SetContext(ctxKeyFinalRequestModel, mappedModel)
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request.Model = mappedModel
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return types.ActionContinue, replaceJsonRequestBody(request, log)
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}
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}
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func (p *sparkProvider) OnResponseHeaders(ctx wrapper.HttpContext, apiName ApiName, log wrapper.Log) (types.Action, error) {
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_ = proxywasm.RemoveHttpResponseHeader("Content-Length")
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return types.ActionContinue, nil
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}
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func (p *sparkProvider) OnResponseBody(ctx wrapper.HttpContext, apiName ApiName, body []byte, log wrapper.Log) (types.Action, error) {
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sparkResponse := &sparkResponse{}
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if err := json.Unmarshal(body, sparkResponse); err != nil {
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return types.ActionContinue, fmt.Errorf("unable to unmarshal spark response: %v", err)
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}
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if sparkResponse.Code != 0 {
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return types.ActionContinue, fmt.Errorf("spark response error, error_code: %d, error_message: %s", sparkResponse.Code, sparkResponse.Message)
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}
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response := p.responseSpark2OpenAI(ctx, sparkResponse)
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return types.ActionContinue, replaceJsonResponseBody(response, log)
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}
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func (p *sparkProvider) OnStreamingResponseBody(ctx wrapper.HttpContext, name ApiName, chunk []byte, isLastChunk bool, log wrapper.Log) ([]byte, error) {
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if isLastChunk || len(chunk) == 0 {
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return nil, nil
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}
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responseBuilder := &strings.Builder{}
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lines := strings.Split(string(chunk), "\n")
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for _, data := range lines {
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if len(data) < 6 {
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// ignore blank line or wrong format
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continue
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}
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data = data[6:]
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// The final response is `data: [DONE]`
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if data == "[DONE]" {
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continue
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}
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var sparkResponse sparkStreamResponse
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if err := json.Unmarshal([]byte(data), &sparkResponse); err != nil {
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log.Errorf("unable to unmarshal spark response: %v", err)
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continue
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}
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response := p.streamResponseSpark2OpenAI(ctx, &sparkResponse)
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responseBody, err := json.Marshal(response)
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if err != nil {
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log.Errorf("unable to marshal response: %v", err)
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return nil, err
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}
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p.appendResponse(responseBuilder, string(responseBody))
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}
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modifiedResponseChunk := responseBuilder.String()
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log.Debugf("=== modified response chunk: %s", modifiedResponseChunk)
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return []byte(modifiedResponseChunk), nil
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}
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func (p *sparkProvider) responseSpark2OpenAI(ctx wrapper.HttpContext, response *sparkResponse) *chatCompletionResponse {
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choices := make([]chatCompletionChoice, len(response.Choices))
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for idx, c := range response.Choices {
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choices[idx] = chatCompletionChoice{
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Index: c.Index,
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Message: &chatMessage{Role: c.Message.Role, Content: c.Message.Content},
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}
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}
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return &chatCompletionResponse{
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Id: response.Sid,
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Created: time.Now().UnixMilli() / 1000,
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Object: objectChatCompletion,
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Model: ctx.GetStringContext(ctxKeyFinalRequestModel, ""),
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Choices: choices,
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Usage: response.Usage,
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}
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}
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func (p *sparkProvider) streamResponseSpark2OpenAI(ctx wrapper.HttpContext, response *sparkStreamResponse) *chatCompletionResponse {
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choices := make([]chatCompletionChoice, len(response.Choices))
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for idx, c := range response.Choices {
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choices[idx] = chatCompletionChoice{
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Index: c.Index,
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Delta: &chatMessage{Role: c.Delta.Role, Content: c.Delta.Content},
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}
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}
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return &chatCompletionResponse{
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Id: response.Sid,
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Created: response.Created,
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Model: ctx.GetStringContext(ctxKeyFinalRequestModel, ""),
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Object: objectChatCompletion,
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Choices: choices,
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Usage: response.Usage,
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}
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}
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func (p *sparkProvider) appendResponse(responseBuilder *strings.Builder, responseBody string) {
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responseBuilder.WriteString(fmt.Sprintf("%s %s\n\n", streamDataItemKey, responseBody))
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}
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