mirror of
https://github.com/songquanpeng/one-api.git
synced 2025-11-19 22:53:41 +08:00
Merge branch 'main' into customer-function
This commit is contained in:
cxk-521
GitHub
@@ -4,6 +4,7 @@ import (
|
||||
"github.com/gin-gonic/gin"
|
||||
"one-api/common"
|
||||
"one-api/model"
|
||||
"one-api/relay/channel/openai"
|
||||
)
|
||||
|
||||
func GetSubscription(c *gin.Context) {
|
||||
@@ -27,12 +28,12 @@ func GetSubscription(c *gin.Context) {
|
||||
expiredTime = 0
|
||||
}
|
||||
if err != nil {
|
||||
openAIError := OpenAIError{
|
||||
Error := openai.Error{
|
||||
Message: err.Error(),
|
||||
Type: "upstream_error",
|
||||
}
|
||||
c.JSON(200, gin.H{
|
||||
"error": openAIError,
|
||||
"error": Error,
|
||||
})
|
||||
return
|
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}
|
||||
@@ -69,12 +70,12 @@ func GetUsage(c *gin.Context) {
|
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quota, err = model.GetUserUsedQuota(userId)
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}
|
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if err != nil {
|
||||
openAIError := OpenAIError{
|
||||
Error := openai.Error{
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||||
Message: err.Error(),
|
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Type: "one_api_error",
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}
|
||||
c.JSON(200, gin.H{
|
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"error": openAIError,
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||||
"error": Error,
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||||
})
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return
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}
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|
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@@ -8,6 +8,7 @@ import (
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"net/http"
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"one-api/common"
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"one-api/model"
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"one-api/relay/util"
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"strconv"
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"time"
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@@ -92,7 +93,7 @@ func GetResponseBody(method, url string, channel *model.Channel, headers http.He
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for k := range headers {
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req.Header.Add(k, headers.Get(k))
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}
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res, err := httpClient.Do(req)
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res, err := util.HTTPClient.Do(req)
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if err != nil {
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return nil, err
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}
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|
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@@ -9,6 +9,8 @@ import (
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"net/http"
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"one-api/common"
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"one-api/model"
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"one-api/relay/channel/openai"
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"one-api/relay/util"
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"strconv"
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"sync"
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"time"
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@@ -16,7 +18,7 @@ import (
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"github.com/gin-gonic/gin"
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)
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func testChannel(channel *model.Channel, request ChatRequest) (err error, openaiErr *OpenAIError) {
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func testChannel(channel *model.Channel, request openai.ChatRequest) (err error, openaiErr *openai.Error) {
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switch channel.Type {
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case common.ChannelTypePaLM:
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fallthrough
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@@ -46,13 +48,13 @@ func testChannel(channel *model.Channel, request ChatRequest) (err error, openai
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}
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requestURL := common.ChannelBaseURLs[channel.Type]
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if channel.Type == common.ChannelTypeAzure {
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requestURL = getFullRequestURL(channel.GetBaseURL(), fmt.Sprintf("/openai/deployments/%s/chat/completions?api-version=2023-03-15-preview", request.Model), channel.Type)
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requestURL = util.GetFullRequestURL(channel.GetBaseURL(), fmt.Sprintf("/openai/deployments/%s/chat/completions?api-version=2023-03-15-preview", request.Model), channel.Type)
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} else {
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if baseURL := channel.GetBaseURL(); len(baseURL) > 0 {
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requestURL = baseURL
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}
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requestURL = getFullRequestURL(requestURL, "/v1/chat/completions", channel.Type)
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requestURL = util.GetFullRequestURL(requestURL, "/v1/chat/completions", channel.Type)
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}
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jsonData, err := json.Marshal(request)
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if err != nil {
|
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@@ -68,12 +70,12 @@ func testChannel(channel *model.Channel, request ChatRequest) (err error, openai
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req.Header.Set("Authorization", "Bearer "+channel.Key)
|
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}
|
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req.Header.Set("Content-Type", "application/json")
|
||||
resp, err := httpClient.Do(req)
|
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resp, err := util.HTTPClient.Do(req)
|
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if err != nil {
|
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return err, nil
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}
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defer resp.Body.Close()
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var response TextResponse
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var response openai.SlimTextResponse
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body, err := io.ReadAll(resp.Body)
|
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if err != nil {
|
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return err, nil
|
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@@ -91,12 +93,12 @@ func testChannel(channel *model.Channel, request ChatRequest) (err error, openai
|
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return nil, nil
|
||||
}
|
||||
|
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func buildTestRequest() *ChatRequest {
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||||
testRequest := &ChatRequest{
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||||
func buildTestRequest() *openai.ChatRequest {
|
||||
testRequest := &openai.ChatRequest{
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||||
Model: "", // this will be set later
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MaxTokens: 1,
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}
|
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testMessage := Message{
|
||||
testMessage := openai.Message{
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Role: "user",
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Content: "hi",
|
||||
}
|
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@@ -204,10 +206,10 @@ func testAllChannels(notify bool) error {
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err = errors.New(fmt.Sprintf("响应时间 %.2fs 超过阈值 %.2fs", float64(milliseconds)/1000.0, float64(disableThreshold)/1000.0))
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disableChannel(channel.Id, channel.Name, err.Error())
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}
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if isChannelEnabled && shouldDisableChannel(openaiErr, -1) {
|
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if isChannelEnabled && util.ShouldDisableChannel(openaiErr, -1) {
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disableChannel(channel.Id, channel.Name, err.Error())
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}
|
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if !isChannelEnabled && shouldEnableChannel(err, openaiErr) {
|
||||
if !isChannelEnabled && util.ShouldEnableChannel(err, openaiErr) {
|
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enableChannel(channel.Id, channel.Name)
|
||||
}
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channel.UpdateResponseTime(milliseconds)
|
||||
|
||||
@@ -2,8 +2,8 @@ package controller
|
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|
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import (
|
||||
"fmt"
|
||||
|
||||
"github.com/gin-gonic/gin"
|
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"one-api/relay/channel/openai"
|
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)
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|
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// https://platform.openai.com/docs/api-reference/models/list
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@@ -613,14 +613,14 @@ func RetrieveModel(c *gin.Context) {
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if model, ok := openAIModelsMap[modelId]; ok {
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c.JSON(200, model)
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||||
} else {
|
||||
openAIError := OpenAIError{
|
||||
Error := openai.Error{
|
||||
Message: fmt.Sprintf("The model '%s' does not exist", modelId),
|
||||
Type: "invalid_request_error",
|
||||
Param: "model",
|
||||
Code: "model_not_found",
|
||||
}
|
||||
c.JSON(200, gin.H{
|
||||
"error": openAIError,
|
||||
"error": Error,
|
||||
})
|
||||
}
|
||||
}
|
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|
||||
@@ -1,220 +0,0 @@
|
||||
package controller
|
||||
|
||||
import (
|
||||
"bufio"
|
||||
"encoding/json"
|
||||
"fmt"
|
||||
"github.com/gin-gonic/gin"
|
||||
"io"
|
||||
"net/http"
|
||||
"one-api/common"
|
||||
"strconv"
|
||||
"strings"
|
||||
)
|
||||
|
||||
// https://docs.aiproxy.io/dev/library#使用已经定制好的知识库进行对话问答
|
||||
|
||||
type AIProxyLibraryRequest struct {
|
||||
Model string `json:"model"`
|
||||
Query string `json:"query"`
|
||||
LibraryId string `json:"libraryId"`
|
||||
Stream bool `json:"stream"`
|
||||
}
|
||||
|
||||
type AIProxyLibraryError struct {
|
||||
ErrCode int `json:"errCode"`
|
||||
Message string `json:"message"`
|
||||
}
|
||||
|
||||
type AIProxyLibraryDocument struct {
|
||||
Title string `json:"title"`
|
||||
URL string `json:"url"`
|
||||
}
|
||||
|
||||
type AIProxyLibraryResponse struct {
|
||||
Success bool `json:"success"`
|
||||
Answer string `json:"answer"`
|
||||
Documents []AIProxyLibraryDocument `json:"documents"`
|
||||
AIProxyLibraryError
|
||||
}
|
||||
|
||||
type AIProxyLibraryStreamResponse struct {
|
||||
Content string `json:"content"`
|
||||
Finish bool `json:"finish"`
|
||||
Model string `json:"model"`
|
||||
Documents []AIProxyLibraryDocument `json:"documents"`
|
||||
}
|
||||
|
||||
func requestOpenAI2AIProxyLibrary(request GeneralOpenAIRequest) *AIProxyLibraryRequest {
|
||||
query := ""
|
||||
if len(request.Messages) != 0 {
|
||||
query = request.Messages[len(request.Messages)-1].StringContent()
|
||||
}
|
||||
return &AIProxyLibraryRequest{
|
||||
Model: request.Model,
|
||||
Stream: request.Stream,
|
||||
Query: query,
|
||||
}
|
||||
}
|
||||
|
||||
func aiProxyDocuments2Markdown(documents []AIProxyLibraryDocument) string {
|
||||
if len(documents) == 0 {
|
||||
return ""
|
||||
}
|
||||
content := "\n\n参考文档：\n"
|
||||
for i, document := range documents {
|
||||
content += fmt.Sprintf("%d. [%s](%s)\n", i+1, document.Title, document.URL)
|
||||
}
|
||||
return content
|
||||
}
|
||||
|
||||
func responseAIProxyLibrary2OpenAI(response *AIProxyLibraryResponse) *OpenAITextResponse {
|
||||
content := response.Answer + aiProxyDocuments2Markdown(response.Documents)
|
||||
choice := OpenAITextResponseChoice{
|
||||
Index: 0,
|
||||
Message: Message{
|
||||
Role: "assistant",
|
||||
Content: content,
|
||||
},
|
||||
FinishReason: "stop",
|
||||
}
|
||||
fullTextResponse := OpenAITextResponse{
|
||||
Id: common.GetUUID(),
|
||||
Object: "chat.completion",
|
||||
Created: common.GetTimestamp(),
|
||||
Choices: []OpenAITextResponseChoice{choice},
|
||||
}
|
||||
return &fullTextResponse
|
||||
}
|
||||
|
||||
func documentsAIProxyLibrary(documents []AIProxyLibraryDocument) *ChatCompletionsStreamResponse {
|
||||
var choice ChatCompletionsStreamResponseChoice
|
||||
choice.Delta.Content = aiProxyDocuments2Markdown(documents)
|
||||
choice.FinishReason = &stopFinishReason
|
||||
return &ChatCompletionsStreamResponse{
|
||||
Id: common.GetUUID(),
|
||||
Object: "chat.completion.chunk",
|
||||
Created: common.GetTimestamp(),
|
||||
Model: "",
|
||||
Choices: []ChatCompletionsStreamResponseChoice{choice},
|
||||
}
|
||||
}
|
||||
|
||||
func streamResponseAIProxyLibrary2OpenAI(response *AIProxyLibraryStreamResponse) *ChatCompletionsStreamResponse {
|
||||
var choice ChatCompletionsStreamResponseChoice
|
||||
choice.Delta.Content = response.Content
|
||||
return &ChatCompletionsStreamResponse{
|
||||
Id: common.GetUUID(),
|
||||
Object: "chat.completion.chunk",
|
||||
Created: common.GetTimestamp(),
|
||||
Model: response.Model,
|
||||
Choices: []ChatCompletionsStreamResponseChoice{choice},
|
||||
}
|
||||
}
|
||||
|
||||
func aiProxyLibraryStreamHandler(c *gin.Context, resp *http.Response) (*OpenAIErrorWithStatusCode, *Usage) {
|
||||
var usage Usage
|
||||
scanner := bufio.NewScanner(resp.Body)
|
||||
scanner.Split(func(data []byte, atEOF bool) (advance int, token []byte, err error) {
|
||||
if atEOF && len(data) == 0 {
|
||||
return 0, nil, nil
|
||||
}
|
||||
if i := strings.Index(string(data), "\n"); i >= 0 {
|
||||
return i + 1, data[0:i], nil
|
||||
}
|
||||
if atEOF {
|
||||
return len(data), data, nil
|
||||
}
|
||||
return 0, nil, nil
|
||||
})
|
||||
dataChan := make(chan string)
|
||||
stopChan := make(chan bool)
|
||||
go func() {
|
||||
for scanner.Scan() {
|
||||
data := scanner.Text()
|
||||
if len(data) < 5 { // ignore blank line or wrong format
|
||||
continue
|
||||
}
|
||||
if data[:5] != "data:" {
|
||||
continue
|
||||
}
|
||||
data = data[5:]
|
||||
dataChan <- data
|
||||
}
|
||||
stopChan <- true
|
||||
}()
|
||||
setEventStreamHeaders(c)
|
||||
var documents []AIProxyLibraryDocument
|
||||
c.Stream(func(w io.Writer) bool {
|
||||
select {
|
||||
case data := <-dataChan:
|
||||
var AIProxyLibraryResponse AIProxyLibraryStreamResponse
|
||||
err := json.Unmarshal([]byte(data), &AIProxyLibraryResponse)
|
||||
if err != nil {
|
||||
common.SysError("error unmarshalling stream response: " + err.Error())
|
||||
return true
|
||||
}
|
||||
if len(AIProxyLibraryResponse.Documents) != 0 {
|
||||
documents = AIProxyLibraryResponse.Documents
|
||||
}
|
||||
response := streamResponseAIProxyLibrary2OpenAI(&AIProxyLibraryResponse)
|
||||
jsonResponse, err := json.Marshal(response)
|
||||
if err != nil {
|
||||
common.SysError("error marshalling stream response: " + err.Error())
|
||||
return true
|
||||
}
|
||||
c.Render(-1, common.CustomEvent{Data: "data: " + string(jsonResponse)})
|
||||
return true
|
||||
case <-stopChan:
|
||||
response := documentsAIProxyLibrary(documents)
|
||||
jsonResponse, err := json.Marshal(response)
|
||||
if err != nil {
|
||||
common.SysError("error marshalling stream response: " + err.Error())
|
||||
return true
|
||||
}
|
||||
c.Render(-1, common.CustomEvent{Data: "data: " + string(jsonResponse)})
|
||||
c.Render(-1, common.CustomEvent{Data: "data: [DONE]"})
|
||||
return false
|
||||
}
|
||||
})
|
||||
err := resp.Body.Close()
|
||||
if err != nil {
|
||||
return errorWrapper(err, "close_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
return nil, &usage
|
||||
}
|
||||
|
||||
func aiProxyLibraryHandler(c *gin.Context, resp *http.Response) (*OpenAIErrorWithStatusCode, *Usage) {
|
||||
var AIProxyLibraryResponse AIProxyLibraryResponse
|
||||
responseBody, err := io.ReadAll(resp.Body)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "read_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
err = resp.Body.Close()
|
||||
if err != nil {
|
||||
return errorWrapper(err, "close_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
err = json.Unmarshal(responseBody, &AIProxyLibraryResponse)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "unmarshal_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
if AIProxyLibraryResponse.ErrCode != 0 {
|
||||
return &OpenAIErrorWithStatusCode{
|
||||
OpenAIError: OpenAIError{
|
||||
Message: AIProxyLibraryResponse.Message,
|
||||
Type: strconv.Itoa(AIProxyLibraryResponse.ErrCode),
|
||||
Code: AIProxyLibraryResponse.ErrCode,
|
||||
},
|
||||
StatusCode: resp.StatusCode,
|
||||
}, nil
|
||||
}
|
||||
fullTextResponse := responseAIProxyLibrary2OpenAI(&AIProxyLibraryResponse)
|
||||
jsonResponse, err := json.Marshal(fullTextResponse)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "marshal_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
c.Writer.Header().Set("Content-Type", "application/json")
|
||||
c.Writer.WriteHeader(resp.StatusCode)
|
||||
_, err = c.Writer.Write(jsonResponse)
|
||||
return nil, &fullTextResponse.Usage
|
||||
}
|
||||
@@ -1,322 +0,0 @@
|
||||
package controller
|
||||
|
||||
import (
|
||||
"bufio"
|
||||
"encoding/json"
|
||||
"github.com/gin-gonic/gin"
|
||||
"io"
|
||||
"net/http"
|
||||
"one-api/common"
|
||||
"strings"
|
||||
)
|
||||
|
||||
// https://help.aliyun.com/document_detail/613695.html?spm=a2c4g.2399480.0.0.1adb778fAdzP9w#341800c0f8w0r
|
||||
|
||||
type AliMessage struct {
|
||||
Content string `json:"content"`
|
||||
Role string `json:"role"`
|
||||
}
|
||||
|
||||
type AliInput struct {
|
||||
//Prompt string `json:"prompt"`
|
||||
Messages []AliMessage `json:"messages"`
|
||||
}
|
||||
|
||||
type AliParameters struct {
|
||||
TopP float64 `json:"top_p,omitempty"`
|
||||
TopK int `json:"top_k,omitempty"`
|
||||
Seed uint64 `json:"seed,omitempty"`
|
||||
EnableSearch bool `json:"enable_search,omitempty"`
|
||||
IncrementalOutput bool `json:"incremental_output,omitempty"`
|
||||
}
|
||||
|
||||
type AliChatRequest struct {
|
||||
Model string `json:"model"`
|
||||
Input AliInput `json:"input"`
|
||||
Parameters AliParameters `json:"parameters,omitempty"`
|
||||
}
|
||||
|
||||
type AliEmbeddingRequest struct {
|
||||
Model string `json:"model"`
|
||||
Input struct {
|
||||
Texts []string `json:"texts"`
|
||||
} `json:"input"`
|
||||
Parameters *struct {
|
||||
TextType string `json:"text_type,omitempty"`
|
||||
} `json:"parameters,omitempty"`
|
||||
}
|
||||
|
||||
type AliEmbedding struct {
|
||||
Embedding []float64 `json:"embedding"`
|
||||
TextIndex int `json:"text_index"`
|
||||
}
|
||||
|
||||
type AliEmbeddingResponse struct {
|
||||
Output struct {
|
||||
Embeddings []AliEmbedding `json:"embeddings"`
|
||||
} `json:"output"`
|
||||
Usage AliUsage `json:"usage"`
|
||||
AliError
|
||||
}
|
||||
|
||||
type AliError struct {
|
||||
Code string `json:"code"`
|
||||
Message string `json:"message"`
|
||||
RequestId string `json:"request_id"`
|
||||
}
|
||||
|
||||
type AliUsage struct {
|
||||
InputTokens int `json:"input_tokens"`
|
||||
OutputTokens int `json:"output_tokens"`
|
||||
TotalTokens int `json:"total_tokens"`
|
||||
}
|
||||
|
||||
type AliOutput struct {
|
||||
Text string `json:"text"`
|
||||
FinishReason string `json:"finish_reason"`
|
||||
}
|
||||
|
||||
type AliChatResponse struct {
|
||||
Output AliOutput `json:"output"`
|
||||
Usage AliUsage `json:"usage"`
|
||||
AliError
|
||||
}
|
||||
|
||||
const AliEnableSearchModelSuffix = "-internet"
|
||||
|
||||
func requestOpenAI2Ali(request GeneralOpenAIRequest) *AliChatRequest {
|
||||
messages := make([]AliMessage, 0, len(request.Messages))
|
||||
for i := 0; i < len(request.Messages); i++ {
|
||||
message := request.Messages[i]
|
||||
messages = append(messages, AliMessage{
|
||||
Content: message.StringContent(),
|
||||
Role: strings.ToLower(message.Role),
|
||||
})
|
||||
}
|
||||
enableSearch := false
|
||||
aliModel := request.Model
|
||||
if strings.HasSuffix(aliModel, AliEnableSearchModelSuffix) {
|
||||
enableSearch = true
|
||||
aliModel = strings.TrimSuffix(aliModel, AliEnableSearchModelSuffix)
|
||||
}
|
||||
return &AliChatRequest{
|
||||
Model: aliModel,
|
||||
Input: AliInput{
|
||||
Messages: messages,
|
||||
},
|
||||
Parameters: AliParameters{
|
||||
EnableSearch: enableSearch,
|
||||
IncrementalOutput: request.Stream,
|
||||
},
|
||||
}
|
||||
}
|
||||
|
||||
func embeddingRequestOpenAI2Ali(request GeneralOpenAIRequest) *AliEmbeddingRequest {
|
||||
return &AliEmbeddingRequest{
|
||||
Model: "text-embedding-v1",
|
||||
Input: struct {
|
||||
Texts []string `json:"texts"`
|
||||
}{
|
||||
Texts: request.ParseInput(),
|
||||
},
|
||||
}
|
||||
}
|
||||
|
||||
func aliEmbeddingHandler(c *gin.Context, resp *http.Response) (*OpenAIErrorWithStatusCode, *Usage) {
|
||||
var aliResponse AliEmbeddingResponse
|
||||
err := json.NewDecoder(resp.Body).Decode(&aliResponse)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "unmarshal_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
|
||||
err = resp.Body.Close()
|
||||
if err != nil {
|
||||
return errorWrapper(err, "close_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
|
||||
if aliResponse.Code != "" {
|
||||
return &OpenAIErrorWithStatusCode{
|
||||
OpenAIError: OpenAIError{
|
||||
Message: aliResponse.Message,
|
||||
Type: aliResponse.Code,
|
||||
Param: aliResponse.RequestId,
|
||||
Code: aliResponse.Code,
|
||||
},
|
||||
StatusCode: resp.StatusCode,
|
||||
}, nil
|
||||
}
|
||||
|
||||
fullTextResponse := embeddingResponseAli2OpenAI(&aliResponse)
|
||||
jsonResponse, err := json.Marshal(fullTextResponse)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "marshal_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
c.Writer.Header().Set("Content-Type", "application/json")
|
||||
c.Writer.WriteHeader(resp.StatusCode)
|
||||
_, err = c.Writer.Write(jsonResponse)
|
||||
return nil, &fullTextResponse.Usage
|
||||
}
|
||||
|
||||
func embeddingResponseAli2OpenAI(response *AliEmbeddingResponse) *OpenAIEmbeddingResponse {
|
||||
openAIEmbeddingResponse := OpenAIEmbeddingResponse{
|
||||
Object: "list",
|
||||
Data: make([]OpenAIEmbeddingResponseItem, 0, len(response.Output.Embeddings)),
|
||||
Model: "text-embedding-v1",
|
||||
Usage: Usage{TotalTokens: response.Usage.TotalTokens},
|
||||
}
|
||||
|
||||
for _, item := range response.Output.Embeddings {
|
||||
openAIEmbeddingResponse.Data = append(openAIEmbeddingResponse.Data, OpenAIEmbeddingResponseItem{
|
||||
Object: `embedding`,
|
||||
Index: item.TextIndex,
|
||||
Embedding: item.Embedding,
|
||||
})
|
||||
}
|
||||
return &openAIEmbeddingResponse
|
||||
}
|
||||
|
||||
func responseAli2OpenAI(response *AliChatResponse) *OpenAITextResponse {
|
||||
choice := OpenAITextResponseChoice{
|
||||
Index: 0,
|
||||
Message: Message{
|
||||
Role: "assistant",
|
||||
Content: response.Output.Text,
|
||||
},
|
||||
FinishReason: response.Output.FinishReason,
|
||||
}
|
||||
fullTextResponse := OpenAITextResponse{
|
||||
Id: response.RequestId,
|
||||
Object: "chat.completion",
|
||||
Created: common.GetTimestamp(),
|
||||
Choices: []OpenAITextResponseChoice{choice},
|
||||
Usage: Usage{
|
||||
PromptTokens: response.Usage.InputTokens,
|
||||
CompletionTokens: response.Usage.OutputTokens,
|
||||
TotalTokens: response.Usage.InputTokens + response.Usage.OutputTokens,
|
||||
},
|
||||
}
|
||||
return &fullTextResponse
|
||||
}
|
||||
|
||||
func streamResponseAli2OpenAI(aliResponse *AliChatResponse) *ChatCompletionsStreamResponse {
|
||||
var choice ChatCompletionsStreamResponseChoice
|
||||
choice.Delta.Content = aliResponse.Output.Text
|
||||
if aliResponse.Output.FinishReason != "null" {
|
||||
finishReason := aliResponse.Output.FinishReason
|
||||
choice.FinishReason = &finishReason
|
||||
}
|
||||
response := ChatCompletionsStreamResponse{
|
||||
Id: aliResponse.RequestId,
|
||||
Object: "chat.completion.chunk",
|
||||
Created: common.GetTimestamp(),
|
||||
Model: "qwen",
|
||||
Choices: []ChatCompletionsStreamResponseChoice{choice},
|
||||
}
|
||||
return &response
|
||||
}
|
||||
|
||||
func aliStreamHandler(c *gin.Context, resp *http.Response) (*OpenAIErrorWithStatusCode, *Usage) {
|
||||
var usage Usage
|
||||
scanner := bufio.NewScanner(resp.Body)
|
||||
scanner.Split(func(data []byte, atEOF bool) (advance int, token []byte, err error) {
|
||||
if atEOF && len(data) == 0 {
|
||||
return 0, nil, nil
|
||||
}
|
||||
if i := strings.Index(string(data), "\n"); i >= 0 {
|
||||
return i + 1, data[0:i], nil
|
||||
}
|
||||
if atEOF {
|
||||
return len(data), data, nil
|
||||
}
|
||||
return 0, nil, nil
|
||||
})
|
||||
dataChan := make(chan string)
|
||||
stopChan := make(chan bool)
|
||||
go func() {
|
||||
for scanner.Scan() {
|
||||
data := scanner.Text()
|
||||
if len(data) < 5 { // ignore blank line or wrong format
|
||||
continue
|
||||
}
|
||||
if data[:5] != "data:" {
|
||||
continue
|
||||
}
|
||||
data = data[5:]
|
||||
dataChan <- data
|
||||
}
|
||||
stopChan <- true
|
||||
}()
|
||||
setEventStreamHeaders(c)
|
||||
//lastResponseText := ""
|
||||
c.Stream(func(w io.Writer) bool {
|
||||
select {
|
||||
case data := <-dataChan:
|
||||
var aliResponse AliChatResponse
|
||||
err := json.Unmarshal([]byte(data), &aliResponse)
|
||||
if err != nil {
|
||||
common.SysError("error unmarshalling stream response: " + err.Error())
|
||||
return true
|
||||
}
|
||||
if aliResponse.Usage.OutputTokens != 0 {
|
||||
usage.PromptTokens = aliResponse.Usage.InputTokens
|
||||
usage.CompletionTokens = aliResponse.Usage.OutputTokens
|
||||
usage.TotalTokens = aliResponse.Usage.InputTokens + aliResponse.Usage.OutputTokens
|
||||
}
|
||||
response := streamResponseAli2OpenAI(&aliResponse)
|
||||
//response.Choices[0].Delta.Content = strings.TrimPrefix(response.Choices[0].Delta.Content, lastResponseText)
|
||||
//lastResponseText = aliResponse.Output.Text
|
||||
jsonResponse, err := json.Marshal(response)
|
||||
if err != nil {
|
||||
common.SysError("error marshalling stream response: " + err.Error())
|
||||
return true
|
||||
}
|
||||
c.Render(-1, common.CustomEvent{Data: "data: " + string(jsonResponse)})
|
||||
return true
|
||||
case <-stopChan:
|
||||
c.Render(-1, common.CustomEvent{Data: "data: [DONE]"})
|
||||
return false
|
||||
}
|
||||
})
|
||||
err := resp.Body.Close()
|
||||
if err != nil {
|
||||
return errorWrapper(err, "close_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
return nil, &usage
|
||||
}
|
||||
|
||||
func aliHandler(c *gin.Context, resp *http.Response) (*OpenAIErrorWithStatusCode, *Usage) {
|
||||
var aliResponse AliChatResponse
|
||||
responseBody, err := io.ReadAll(resp.Body)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "read_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
err = resp.Body.Close()
|
||||
if err != nil {
|
||||
return errorWrapper(err, "close_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
err = json.Unmarshal(responseBody, &aliResponse)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "unmarshal_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
if aliResponse.Code != "" {
|
||||
return &OpenAIErrorWithStatusCode{
|
||||
OpenAIError: OpenAIError{
|
||||
Message: aliResponse.Message,
|
||||
Type: aliResponse.Code,
|
||||
Param: aliResponse.RequestId,
|
||||
Code: aliResponse.Code,
|
||||
},
|
||||
StatusCode: resp.StatusCode,
|
||||
}, nil
|
||||
}
|
||||
fullTextResponse := responseAli2OpenAI(&aliResponse)
|
||||
fullTextResponse.Model = "qwen"
|
||||
jsonResponse, err := json.Marshal(fullTextResponse)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "marshal_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
c.Writer.Header().Set("Content-Type", "application/json")
|
||||
c.Writer.WriteHeader(resp.StatusCode)
|
||||
_, err = c.Writer.Write(jsonResponse)
|
||||
return nil, &fullTextResponse.Usage
|
||||
}
|
||||
@@ -1,262 +0,0 @@
|
||||
package controller
|
||||
|
||||
import (
|
||||
"bufio"
|
||||
"bytes"
|
||||
"context"
|
||||
"encoding/json"
|
||||
"errors"
|
||||
"fmt"
|
||||
"github.com/gin-gonic/gin"
|
||||
"io"
|
||||
"net/http"
|
||||
"one-api/common"
|
||||
"one-api/model"
|
||||
"strings"
|
||||
)
|
||||
|
||||
func relayAudioHelper(c *gin.Context, relayMode int) *OpenAIErrorWithStatusCode {
|
||||
audioModel := "whisper-1"
|
||||
|
||||
tokenId := c.GetInt("token_id")
|
||||
channelType := c.GetInt("channel")
|
||||
channelId := c.GetInt("channel_id")
|
||||
userId := c.GetInt("id")
|
||||
group := c.GetString("group")
|
||||
tokenName := c.GetString("token_name")
|
||||
|
||||
var ttsRequest TextToSpeechRequest
|
||||
if relayMode == RelayModeAudioSpeech {
|
||||
// Read JSON
|
||||
err := common.UnmarshalBodyReusable(c, &ttsRequest)
|
||||
// Check if JSON is valid
|
||||
if err != nil {
|
||||
return errorWrapper(err, "invalid_json", http.StatusBadRequest)
|
||||
}
|
||||
audioModel = ttsRequest.Model
|
||||
// Check if text is too long 4096
|
||||
if len(ttsRequest.Input) > 4096 {
|
||||
return errorWrapper(errors.New("input is too long (over 4096 characters)"), "text_too_long", http.StatusBadRequest)
|
||||
}
|
||||
}
|
||||
|
||||
modelRatio := common.GetModelRatio(audioModel)
|
||||
groupRatio := common.GetGroupRatio(group)
|
||||
ratio := modelRatio * groupRatio
|
||||
var quota int
|
||||
var preConsumedQuota int
|
||||
switch relayMode {
|
||||
case RelayModeAudioSpeech:
|
||||
preConsumedQuota = int(float64(len(ttsRequest.Input)) * ratio)
|
||||
quota = preConsumedQuota
|
||||
default:
|
||||
preConsumedQuota = int(float64(common.PreConsumedQuota) * ratio)
|
||||
}
|
||||
userQuota, err := model.CacheGetUserQuota(userId)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "get_user_quota_failed", http.StatusInternalServerError)
|
||||
}
|
||||
|
||||
// Check if user quota is enough
|
||||
if userQuota-preConsumedQuota < 0 {
|
||||
return errorWrapper(errors.New("user quota is not enough"), "insufficient_user_quota", http.StatusForbidden)
|
||||
}
|
||||
err = model.CacheDecreaseUserQuota(userId, preConsumedQuota)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "decrease_user_quota_failed", http.StatusInternalServerError)
|
||||
}
|
||||
if userQuota > 100*preConsumedQuota {
|
||||
// in this case, we do not pre-consume quota
|
||||
// because the user has enough quota
|
||||
preConsumedQuota = 0
|
||||
}
|
||||
if preConsumedQuota > 0 {
|
||||
err := model.PreConsumeTokenQuota(tokenId, preConsumedQuota)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "pre_consume_token_quota_failed", http.StatusForbidden)
|
||||
}
|
||||
}
|
||||
|
||||
// map model name
|
||||
modelMapping := c.GetString("model_mapping")
|
||||
if modelMapping != "" {
|
||||
modelMap := make(map[string]string)
|
||||
err := json.Unmarshal([]byte(modelMapping), &modelMap)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "unmarshal_model_mapping_failed", http.StatusInternalServerError)
|
||||
}
|
||||
if modelMap[audioModel] != "" {
|
||||
audioModel = modelMap[audioModel]
|
||||
}
|
||||
}
|
||||
|
||||
baseURL := common.ChannelBaseURLs[channelType]
|
||||
requestURL := c.Request.URL.String()
|
||||
if c.GetString("base_url") != "" {
|
||||
baseURL = c.GetString("base_url")
|
||||
}
|
||||
|
||||
fullRequestURL := getFullRequestURL(baseURL, requestURL, channelType)
|
||||
if relayMode == RelayModeAudioTranscription && channelType == common.ChannelTypeAzure {
|
||||
// https://learn.microsoft.com/en-us/azure/ai-services/openai/whisper-quickstart?tabs=command-line#rest-api
|
||||
apiVersion := GetAPIVersion(c)
|
||||
fullRequestURL = fmt.Sprintf("%s/openai/deployments/%s/audio/transcriptions?api-version=%s", baseURL, audioModel, apiVersion)
|
||||
}
|
||||
|
||||
requestBody := &bytes.Buffer{}
|
||||
_, err = io.Copy(requestBody, c.Request.Body)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "new_request_body_failed", http.StatusInternalServerError)
|
||||
}
|
||||
c.Request.Body = io.NopCloser(bytes.NewBuffer(requestBody.Bytes()))
|
||||
responseFormat := c.DefaultPostForm("response_format", "json")
|
||||
|
||||
req, err := http.NewRequest(c.Request.Method, fullRequestURL, requestBody)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "new_request_failed", http.StatusInternalServerError)
|
||||
}
|
||||
|
||||
if relayMode == RelayModeAudioTranscription && channelType == common.ChannelTypeAzure {
|
||||
// https://learn.microsoft.com/en-us/azure/ai-services/openai/whisper-quickstart?tabs=command-line#rest-api
|
||||
apiKey := c.Request.Header.Get("Authorization")
|
||||
apiKey = strings.TrimPrefix(apiKey, "Bearer ")
|
||||
req.Header.Set("api-key", apiKey)
|
||||
req.ContentLength = c.Request.ContentLength
|
||||
} else {
|
||||
req.Header.Set("Authorization", c.Request.Header.Get("Authorization"))
|
||||
}
|
||||
req.Header.Set("Content-Type", c.Request.Header.Get("Content-Type"))
|
||||
req.Header.Set("Accept", c.Request.Header.Get("Accept"))
|
||||
|
||||
resp, err := httpClient.Do(req)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "do_request_failed", http.StatusInternalServerError)
|
||||
}
|
||||
|
||||
err = req.Body.Close()
|
||||
if err != nil {
|
||||
return errorWrapper(err, "close_request_body_failed", http.StatusInternalServerError)
|
||||
}
|
||||
err = c.Request.Body.Close()
|
||||
if err != nil {
|
||||
return errorWrapper(err, "close_request_body_failed", http.StatusInternalServerError)
|
||||
}
|
||||
|
||||
if relayMode != RelayModeAudioSpeech {
|
||||
responseBody, err := io.ReadAll(resp.Body)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "read_response_body_failed", http.StatusInternalServerError)
|
||||
}
|
||||
err = resp.Body.Close()
|
||||
if err != nil {
|
||||
return errorWrapper(err, "close_response_body_failed", http.StatusInternalServerError)
|
||||
}
|
||||
|
||||
var openAIErr TextResponse
|
||||
if err = json.Unmarshal(responseBody, &openAIErr); err == nil {
|
||||
if openAIErr.Error.Message != "" {
|
||||
return errorWrapper(fmt.Errorf("type %s, code %v, message %s", openAIErr.Error.Type, openAIErr.Error.Code, openAIErr.Error.Message), "request_error", http.StatusInternalServerError)
|
||||
}
|
||||
}
|
||||
|
||||
var text string
|
||||
switch responseFormat {
|
||||
case "json":
|
||||
text, err = getTextFromJSON(responseBody)
|
||||
case "text":
|
||||
text, err = getTextFromText(responseBody)
|
||||
case "srt":
|
||||
text, err = getTextFromSRT(responseBody)
|
||||
case "verbose_json":
|
||||
text, err = getTextFromVerboseJSON(responseBody)
|
||||
case "vtt":
|
||||
text, err = getTextFromVTT(responseBody)
|
||||
default:
|
||||
return errorWrapper(errors.New("unexpected_response_format"), "unexpected_response_format", http.StatusInternalServerError)
|
||||
}
|
||||
if err != nil {
|
||||
return errorWrapper(err, "get_text_from_body_err", http.StatusInternalServerError)
|
||||
}
|
||||
quota = countTokenText(text, audioModel)
|
||||
resp.Body = io.NopCloser(bytes.NewBuffer(responseBody))
|
||||
}
|
||||
if resp.StatusCode != http.StatusOK {
|
||||
if preConsumedQuota > 0 {
|
||||
// we need to roll back the pre-consumed quota
|
||||
defer func(ctx context.Context) {
|
||||
go func() {
|
||||
// negative means add quota back for token & user
|
||||
err := model.PostConsumeTokenQuota(tokenId, -preConsumedQuota)
|
||||
if err != nil {
|
||||
common.LogError(ctx, fmt.Sprintf("error rollback pre-consumed quota: %s", err.Error()))
|
||||
}
|
||||
}()
|
||||
}(c.Request.Context())
|
||||
}
|
||||
return relayErrorHandler(resp)
|
||||
}
|
||||
quotaDelta := quota - preConsumedQuota
|
||||
defer func(ctx context.Context) {
|
||||
go postConsumeQuota(ctx, tokenId, quotaDelta, quota, userId, channelId, modelRatio, groupRatio, audioModel, tokenName)
|
||||
}(c.Request.Context())
|
||||
|
||||
for k, v := range resp.Header {
|
||||
c.Writer.Header().Set(k, v[0])
|
||||
}
|
||||
c.Writer.WriteHeader(resp.StatusCode)
|
||||
|
||||
_, err = io.Copy(c.Writer, resp.Body)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "copy_response_body_failed", http.StatusInternalServerError)
|
||||
}
|
||||
err = resp.Body.Close()
|
||||
if err != nil {
|
||||
return errorWrapper(err, "close_response_body_failed", http.StatusInternalServerError)
|
||||
}
|
||||
return nil
|
||||
}
|
||||
|
||||
func getTextFromVTT(body []byte) (string, error) {
|
||||
return getTextFromSRT(body)
|
||||
}
|
||||
|
||||
func getTextFromVerboseJSON(body []byte) (string, error) {
|
||||
var whisperResponse WhisperVerboseJSONResponse
|
||||
if err := json.Unmarshal(body, &whisperResponse); err != nil {
|
||||
return "", fmt.Errorf("unmarshal_response_body_failed err :%w", err)
|
||||
}
|
||||
return whisperResponse.Text, nil
|
||||
}
|
||||
|
||||
func getTextFromSRT(body []byte) (string, error) {
|
||||
scanner := bufio.NewScanner(strings.NewReader(string(body)))
|
||||
var builder strings.Builder
|
||||
var textLine bool
|
||||
for scanner.Scan() {
|
||||
line := scanner.Text()
|
||||
if textLine {
|
||||
builder.WriteString(line)
|
||||
textLine = false
|
||||
continue
|
||||
} else if strings.Contains(line, "-->") {
|
||||
textLine = true
|
||||
continue
|
||||
}
|
||||
}
|
||||
if err := scanner.Err(); err != nil {
|
||||
return "", err
|
||||
}
|
||||
return builder.String(), nil
|
||||
}
|
||||
|
||||
func getTextFromText(body []byte) (string, error) {
|
||||
return strings.TrimSuffix(string(body), "\n"), nil
|
||||
}
|
||||
|
||||
func getTextFromJSON(body []byte) (string, error) {
|
||||
var whisperResponse WhisperJSONResponse
|
||||
if err := json.Unmarshal(body, &whisperResponse); err != nil {
|
||||
return "", fmt.Errorf("unmarshal_response_body_failed err :%w", err)
|
||||
}
|
||||
return whisperResponse.Text, nil
|
||||
}
|
||||
@@ -1,360 +0,0 @@
|
||||
package controller
|
||||
|
||||
import (
|
||||
"bufio"
|
||||
"encoding/json"
|
||||
"errors"
|
||||
"fmt"
|
||||
"github.com/gin-gonic/gin"
|
||||
"io"
|
||||
"net/http"
|
||||
"one-api/common"
|
||||
"strings"
|
||||
"sync"
|
||||
"time"
|
||||
)
|
||||
|
||||
// https://cloud.baidu.com/doc/WENXINWORKSHOP/s/flfmc9do2
|
||||
|
||||
type BaiduTokenResponse struct {
|
||||
ExpiresIn int `json:"expires_in"`
|
||||
AccessToken string `json:"access_token"`
|
||||
}
|
||||
|
||||
type BaiduMessage struct {
|
||||
Role string `json:"role"`
|
||||
Content string `json:"content"`
|
||||
}
|
||||
|
||||
type BaiduChatRequest struct {
|
||||
Messages []BaiduMessage `json:"messages"`
|
||||
Stream bool `json:"stream"`
|
||||
UserId string `json:"user_id,omitempty"`
|
||||
}
|
||||
|
||||
type BaiduError struct {
|
||||
ErrorCode int `json:"error_code"`
|
||||
ErrorMsg string `json:"error_msg"`
|
||||
}
|
||||
|
||||
type BaiduChatResponse struct {
|
||||
Id string `json:"id"`
|
||||
Object string `json:"object"`
|
||||
Created int64 `json:"created"`
|
||||
Result string `json:"result"`
|
||||
IsTruncated bool `json:"is_truncated"`
|
||||
NeedClearHistory bool `json:"need_clear_history"`
|
||||
Usage Usage `json:"usage"`
|
||||
BaiduError
|
||||
}
|
||||
|
||||
type BaiduChatStreamResponse struct {
|
||||
BaiduChatResponse
|
||||
SentenceId int `json:"sentence_id"`
|
||||
IsEnd bool `json:"is_end"`
|
||||
}
|
||||
|
||||
type BaiduEmbeddingRequest struct {
|
||||
Input []string `json:"input"`
|
||||
}
|
||||
|
||||
type BaiduEmbeddingData struct {
|
||||
Object string `json:"object"`
|
||||
Embedding []float64 `json:"embedding"`
|
||||
Index int `json:"index"`
|
||||
}
|
||||
|
||||
type BaiduEmbeddingResponse struct {
|
||||
Id string `json:"id"`
|
||||
Object string `json:"object"`
|
||||
Created int64 `json:"created"`
|
||||
Data []BaiduEmbeddingData `json:"data"`
|
||||
Usage Usage `json:"usage"`
|
||||
BaiduError
|
||||
}
|
||||
|
||||
type BaiduAccessToken struct {
|
||||
AccessToken string `json:"access_token"`
|
||||
Error string `json:"error,omitempty"`
|
||||
ErrorDescription string `json:"error_description,omitempty"`
|
||||
ExpiresIn int64 `json:"expires_in,omitempty"`
|
||||
ExpiresAt time.Time `json:"-"`
|
||||
}
|
||||
|
||||
var baiduTokenStore sync.Map
|
||||
|
||||
func requestOpenAI2Baidu(request GeneralOpenAIRequest) *BaiduChatRequest {
|
||||
messages := make([]BaiduMessage, 0, len(request.Messages))
|
||||
for _, message := range request.Messages {
|
||||
if message.Role == "system" {
|
||||
messages = append(messages, BaiduMessage{
|
||||
Role: "user",
|
||||
Content: message.StringContent(),
|
||||
})
|
||||
messages = append(messages, BaiduMessage{
|
||||
Role: "assistant",
|
||||
Content: "Okay",
|
||||
})
|
||||
} else {
|
||||
messages = append(messages, BaiduMessage{
|
||||
Role: message.Role,
|
||||
Content: message.StringContent(),
|
||||
})
|
||||
}
|
||||
}
|
||||
return &BaiduChatRequest{
|
||||
Messages: messages,
|
||||
Stream: request.Stream,
|
||||
}
|
||||
}
|
||||
|
||||
func responseBaidu2OpenAI(response *BaiduChatResponse) *OpenAITextResponse {
|
||||
choice := OpenAITextResponseChoice{
|
||||
Index: 0,
|
||||
Message: Message{
|
||||
Role: "assistant",
|
||||
Content: response.Result,
|
||||
},
|
||||
FinishReason: "stop",
|
||||
}
|
||||
fullTextResponse := OpenAITextResponse{
|
||||
Id: response.Id,
|
||||
Object: "chat.completion",
|
||||
Created: response.Created,
|
||||
Choices: []OpenAITextResponseChoice{choice},
|
||||
Usage: response.Usage,
|
||||
}
|
||||
return &fullTextResponse
|
||||
}
|
||||
|
||||
func streamResponseBaidu2OpenAI(baiduResponse *BaiduChatStreamResponse) *ChatCompletionsStreamResponse {
|
||||
var choice ChatCompletionsStreamResponseChoice
|
||||
choice.Delta.Content = baiduResponse.Result
|
||||
if baiduResponse.IsEnd {
|
||||
choice.FinishReason = &stopFinishReason
|
||||
}
|
||||
response := ChatCompletionsStreamResponse{
|
||||
Id: baiduResponse.Id,
|
||||
Object: "chat.completion.chunk",
|
||||
Created: baiduResponse.Created,
|
||||
Model: "ernie-bot",
|
||||
Choices: []ChatCompletionsStreamResponseChoice{choice},
|
||||
}
|
||||
return &response
|
||||
}
|
||||
|
||||
func embeddingRequestOpenAI2Baidu(request GeneralOpenAIRequest) *BaiduEmbeddingRequest {
|
||||
return &BaiduEmbeddingRequest{
|
||||
Input: request.ParseInput(),
|
||||
}
|
||||
}
|
||||
|
||||
func embeddingResponseBaidu2OpenAI(response *BaiduEmbeddingResponse) *OpenAIEmbeddingResponse {
|
||||
openAIEmbeddingResponse := OpenAIEmbeddingResponse{
|
||||
Object: "list",
|
||||
Data: make([]OpenAIEmbeddingResponseItem, 0, len(response.Data)),
|
||||
Model: "baidu-embedding",
|
||||
Usage: response.Usage,
|
||||
}
|
||||
for _, item := range response.Data {
|
||||
openAIEmbeddingResponse.Data = append(openAIEmbeddingResponse.Data, OpenAIEmbeddingResponseItem{
|
||||
Object: item.Object,
|
||||
Index: item.Index,
|
||||
Embedding: item.Embedding,
|
||||
})
|
||||
}
|
||||
return &openAIEmbeddingResponse
|
||||
}
|
||||
|
||||
func baiduStreamHandler(c *gin.Context, resp *http.Response) (*OpenAIErrorWithStatusCode, *Usage) {
|
||||
var usage Usage
|
||||
scanner := bufio.NewScanner(resp.Body)
|
||||
scanner.Split(func(data []byte, atEOF bool) (advance int, token []byte, err error) {
|
||||
if atEOF && len(data) == 0 {
|
||||
return 0, nil, nil
|
||||
}
|
||||
if i := strings.Index(string(data), "\n"); i >= 0 {
|
||||
return i + 1, data[0:i], nil
|
||||
}
|
||||
if atEOF {
|
||||
return len(data), data, nil
|
||||
}
|
||||
return 0, nil, nil
|
||||
})
|
||||
dataChan := make(chan string)
|
||||
stopChan := make(chan bool)
|
||||
go func() {
|
||||
for scanner.Scan() {
|
||||
data := scanner.Text()
|
||||
if len(data) < 6 { // ignore blank line or wrong format
|
||||
continue
|
||||
}
|
||||
data = data[6:]
|
||||
dataChan <- data
|
||||
}
|
||||
stopChan <- true
|
||||
}()
|
||||
setEventStreamHeaders(c)
|
||||
c.Stream(func(w io.Writer) bool {
|
||||
select {
|
||||
case data := <-dataChan:
|
||||
var baiduResponse BaiduChatStreamResponse
|
||||
err := json.Unmarshal([]byte(data), &baiduResponse)
|
||||
if err != nil {
|
||||
common.SysError("error unmarshalling stream response: " + err.Error())
|
||||
return true
|
||||
}
|
||||
if baiduResponse.Usage.TotalTokens != 0 {
|
||||
usage.TotalTokens = baiduResponse.Usage.TotalTokens
|
||||
usage.PromptTokens = baiduResponse.Usage.PromptTokens
|
||||
usage.CompletionTokens = baiduResponse.Usage.TotalTokens - baiduResponse.Usage.PromptTokens
|
||||
}
|
||||
response := streamResponseBaidu2OpenAI(&baiduResponse)
|
||||
jsonResponse, err := json.Marshal(response)
|
||||
if err != nil {
|
||||
common.SysError("error marshalling stream response: " + err.Error())
|
||||
return true
|
||||
}
|
||||
c.Render(-1, common.CustomEvent{Data: "data: " + string(jsonResponse)})
|
||||
return true
|
||||
case <-stopChan:
|
||||
c.Render(-1, common.CustomEvent{Data: "data: [DONE]"})
|
||||
return false
|
||||
}
|
||||
})
|
||||
err := resp.Body.Close()
|
||||
if err != nil {
|
||||
return errorWrapper(err, "close_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
return nil, &usage
|
||||
}
|
||||
|
||||
func baiduHandler(c *gin.Context, resp *http.Response) (*OpenAIErrorWithStatusCode, *Usage) {
|
||||
var baiduResponse BaiduChatResponse
|
||||
responseBody, err := io.ReadAll(resp.Body)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "read_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
err = resp.Body.Close()
|
||||
if err != nil {
|
||||
return errorWrapper(err, "close_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
err = json.Unmarshal(responseBody, &baiduResponse)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "unmarshal_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
if baiduResponse.ErrorMsg != "" {
|
||||
return &OpenAIErrorWithStatusCode{
|
||||
OpenAIError: OpenAIError{
|
||||
Message: baiduResponse.ErrorMsg,
|
||||
Type: "baidu_error",
|
||||
Param: "",
|
||||
Code: baiduResponse.ErrorCode,
|
||||
},
|
||||
StatusCode: resp.StatusCode,
|
||||
}, nil
|
||||
}
|
||||
fullTextResponse := responseBaidu2OpenAI(&baiduResponse)
|
||||
fullTextResponse.Model = "ernie-bot"
|
||||
jsonResponse, err := json.Marshal(fullTextResponse)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "marshal_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
c.Writer.Header().Set("Content-Type", "application/json")
|
||||
c.Writer.WriteHeader(resp.StatusCode)
|
||||
_, err = c.Writer.Write(jsonResponse)
|
||||
return nil, &fullTextResponse.Usage
|
||||
}
|
||||
|
||||
func baiduEmbeddingHandler(c *gin.Context, resp *http.Response) (*OpenAIErrorWithStatusCode, *Usage) {
|
||||
var baiduResponse BaiduEmbeddingResponse
|
||||
responseBody, err := io.ReadAll(resp.Body)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "read_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
err = resp.Body.Close()
|
||||
if err != nil {
|
||||
return errorWrapper(err, "close_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
err = json.Unmarshal(responseBody, &baiduResponse)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "unmarshal_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
if baiduResponse.ErrorMsg != "" {
|
||||
return &OpenAIErrorWithStatusCode{
|
||||
OpenAIError: OpenAIError{
|
||||
Message: baiduResponse.ErrorMsg,
|
||||
Type: "baidu_error",
|
||||
Param: "",
|
||||
Code: baiduResponse.ErrorCode,
|
||||
},
|
||||
StatusCode: resp.StatusCode,
|
||||
}, nil
|
||||
}
|
||||
fullTextResponse := embeddingResponseBaidu2OpenAI(&baiduResponse)
|
||||
jsonResponse, err := json.Marshal(fullTextResponse)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "marshal_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
c.Writer.Header().Set("Content-Type", "application/json")
|
||||
c.Writer.WriteHeader(resp.StatusCode)
|
||||
_, err = c.Writer.Write(jsonResponse)
|
||||
return nil, &fullTextResponse.Usage
|
||||
}
|
||||
|
||||
func getBaiduAccessToken(apiKey string) (string, error) {
|
||||
if val, ok := baiduTokenStore.Load(apiKey); ok {
|
||||
var accessToken BaiduAccessToken
|
||||
if accessToken, ok = val.(BaiduAccessToken); ok {
|
||||
// soon this will expire
|
||||
if time.Now().Add(time.Hour).After(accessToken.ExpiresAt) {
|
||||
go func() {
|
||||
_, _ = getBaiduAccessTokenHelper(apiKey)
|
||||
}()
|
||||
}
|
||||
return accessToken.AccessToken, nil
|
||||
}
|
||||
}
|
||||
accessToken, err := getBaiduAccessTokenHelper(apiKey)
|
||||
if err != nil {
|
||||
return "", err
|
||||
}
|
||||
if accessToken == nil {
|
||||
return "", errors.New("getBaiduAccessToken return a nil token")
|
||||
}
|
||||
return (*accessToken).AccessToken, nil
|
||||
}
|
||||
|
||||
func getBaiduAccessTokenHelper(apiKey string) (*BaiduAccessToken, error) {
|
||||
parts := strings.Split(apiKey, "|")
|
||||
if len(parts) != 2 {
|
||||
return nil, errors.New("invalid baidu apikey")
|
||||
}
|
||||
req, err := http.NewRequest("POST", fmt.Sprintf("https://aip.baidubce.com/oauth/2.0/token?grant_type=client_credentials&client_id=%s&client_secret=%s",
|
||||
parts[0], parts[1]), nil)
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
req.Header.Add("Content-Type", "application/json")
|
||||
req.Header.Add("Accept", "application/json")
|
||||
res, err := impatientHTTPClient.Do(req)
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
defer res.Body.Close()
|
||||
|
||||
var accessToken BaiduAccessToken
|
||||
err = json.NewDecoder(res.Body).Decode(&accessToken)
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
if accessToken.Error != "" {
|
||||
return nil, errors.New(accessToken.Error + ": " + accessToken.ErrorDescription)
|
||||
}
|
||||
if accessToken.AccessToken == "" {
|
||||
return nil, errors.New("getBaiduAccessTokenHelper get empty access token")
|
||||
}
|
||||
accessToken.ExpiresAt = time.Now().Add(time.Duration(accessToken.ExpiresIn) * time.Second)
|
||||
baiduTokenStore.Store(apiKey, accessToken)
|
||||
return &accessToken, nil
|
||||
}
|
||||
@@ -1,223 +0,0 @@
|
||||
package controller
|
||||
|
||||
import (
|
||||
"bufio"
|
||||
"encoding/json"
|
||||
"fmt"
|
||||
"github.com/gin-gonic/gin"
|
||||
"io"
|
||||
"net/http"
|
||||
"one-api/common"
|
||||
"strings"
|
||||
)
|
||||
|
||||
type ClaudeMetadata struct {
|
||||
UserId string `json:"user_id"`
|
||||
}
|
||||
|
||||
type ClaudeRequest struct {
|
||||
Model string `json:"model"`
|
||||
Prompt string `json:"prompt"`
|
||||
MaxTokensToSample int `json:"max_tokens_to_sample"`
|
||||
StopSequences []string `json:"stop_sequences,omitempty"`
|
||||
Temperature float64 `json:"temperature,omitempty"`
|
||||
TopP float64 `json:"top_p,omitempty"`
|
||||
TopK int `json:"top_k,omitempty"`
|
||||
//ClaudeMetadata `json:"metadata,omitempty"`
|
||||
Stream bool `json:"stream,omitempty"`
|
||||
}
|
||||
|
||||
type ClaudeError struct {
|
||||
Type string `json:"type"`
|
||||
Message string `json:"message"`
|
||||
}
|
||||
|
||||
type ClaudeResponse struct {
|
||||
Completion string `json:"completion"`
|
||||
StopReason string `json:"stop_reason"`
|
||||
Model string `json:"model"`
|
||||
Error ClaudeError `json:"error"`
|
||||
}
|
||||
|
||||
func stopReasonClaude2OpenAI(reason string) string {
|
||||
switch reason {
|
||||
case "stop_sequence":
|
||||
return "stop"
|
||||
case "max_tokens":
|
||||
return "length"
|
||||
default:
|
||||
return reason
|
||||
}
|
||||
}
|
||||
|
||||
func requestOpenAI2Claude(textRequest GeneralOpenAIRequest) *ClaudeRequest {
|
||||
claudeRequest := ClaudeRequest{
|
||||
Model: textRequest.Model,
|
||||
Prompt: "",
|
||||
MaxTokensToSample: textRequest.MaxTokens,
|
||||
StopSequences: nil,
|
||||
Temperature: textRequest.Temperature,
|
||||
TopP: textRequest.TopP,
|
||||
Stream: textRequest.Stream,
|
||||
}
|
||||
if claudeRequest.MaxTokensToSample == 0 {
|
||||
claudeRequest.MaxTokensToSample = 1000000
|
||||
}
|
||||
prompt := ""
|
||||
for _, message := range textRequest.Messages {
|
||||
if message.Role == "user" {
|
||||
prompt += fmt.Sprintf("\n\nHuman: %s", message.Content)
|
||||
} else if message.Role == "assistant" {
|
||||
prompt += fmt.Sprintf("\n\nAssistant: %s", message.Content)
|
||||
} else if message.Role == "system" {
|
||||
if prompt == "" {
|
||||
prompt = message.StringContent()
|
||||
}
|
||||
}
|
||||
}
|
||||
prompt += "\n\nAssistant:"
|
||||
claudeRequest.Prompt = prompt
|
||||
return &claudeRequest
|
||||
}
|
||||
|
||||
func streamResponseClaude2OpenAI(claudeResponse *ClaudeResponse) *ChatCompletionsStreamResponse {
|
||||
var choice ChatCompletionsStreamResponseChoice
|
||||
choice.Delta.Content = claudeResponse.Completion
|
||||
finishReason := stopReasonClaude2OpenAI(claudeResponse.StopReason)
|
||||
if finishReason != "null" {
|
||||
choice.FinishReason = &finishReason
|
||||
}
|
||||
var response ChatCompletionsStreamResponse
|
||||
response.Object = "chat.completion.chunk"
|
||||
response.Model = claudeResponse.Model
|
||||
response.Choices = []ChatCompletionsStreamResponseChoice{choice}
|
||||
return &response
|
||||
}
|
||||
|
||||
func responseClaude2OpenAI(claudeResponse *ClaudeResponse) *OpenAITextResponse {
|
||||
choice := OpenAITextResponseChoice{
|
||||
Index: 0,
|
||||
Message: Message{
|
||||
Role: "assistant",
|
||||
Content: strings.TrimPrefix(claudeResponse.Completion, " "),
|
||||
Name: nil,
|
||||
},
|
||||
FinishReason: stopReasonClaude2OpenAI(claudeResponse.StopReason),
|
||||
}
|
||||
fullTextResponse := OpenAITextResponse{
|
||||
Id: fmt.Sprintf("chatcmpl-%s", common.GetUUID()),
|
||||
Object: "chat.completion",
|
||||
Created: common.GetTimestamp(),
|
||||
Choices: []OpenAITextResponseChoice{choice},
|
||||
}
|
||||
return &fullTextResponse
|
||||
}
|
||||
|
||||
func claudeStreamHandler(c *gin.Context, resp *http.Response) (*OpenAIErrorWithStatusCode, string) {
|
||||
responseText := ""
|
||||
responseId := fmt.Sprintf("chatcmpl-%s", common.GetUUID())
|
||||
createdTime := common.GetTimestamp()
|
||||
scanner := bufio.NewScanner(resp.Body)
|
||||
scanner.Split(func(data []byte, atEOF bool) (advance int, token []byte, err error) {
|
||||
if atEOF && len(data) == 0 {
|
||||
return 0, nil, nil
|
||||
}
|
||||
if i := strings.Index(string(data), "\r\n\r\n"); i >= 0 {
|
||||
return i + 4, data[0:i], nil
|
||||
}
|
||||
if atEOF {
|
||||
return len(data), data, nil
|
||||
}
|
||||
return 0, nil, nil
|
||||
})
|
||||
dataChan := make(chan string)
|
||||
stopChan := make(chan bool)
|
||||
go func() {
|
||||
for scanner.Scan() {
|
||||
data := scanner.Text()
|
||||
if !strings.HasPrefix(data, "event: completion") {
|
||||
continue
|
||||
}
|
||||
data = strings.TrimPrefix(data, "event: completion\r\ndata: ")
|
||||
dataChan <- data
|
||||
}
|
||||
stopChan <- true
|
||||
}()
|
||||
setEventStreamHeaders(c)
|
||||
c.Stream(func(w io.Writer) bool {
|
||||
select {
|
||||
case data := <-dataChan:
|
||||
// some implementations may add \r at the end of data
|
||||
data = strings.TrimSuffix(data, "\r")
|
||||
var claudeResponse ClaudeResponse
|
||||
err := json.Unmarshal([]byte(data), &claudeResponse)
|
||||
if err != nil {
|
||||
common.SysError("error unmarshalling stream response: " + err.Error())
|
||||
return true
|
||||
}
|
||||
responseText += claudeResponse.Completion
|
||||
response := streamResponseClaude2OpenAI(&claudeResponse)
|
||||
response.Id = responseId
|
||||
response.Created = createdTime
|
||||
jsonStr, err := json.Marshal(response)
|
||||
if err != nil {
|
||||
common.SysError("error marshalling stream response: " + err.Error())
|
||||
return true
|
||||
}
|
||||
c.Render(-1, common.CustomEvent{Data: "data: " + string(jsonStr)})
|
||||
return true
|
||||
case <-stopChan:
|
||||
c.Render(-1, common.CustomEvent{Data: "data: [DONE]"})
|
||||
return false
|
||||
}
|
||||
})
|
||||
err := resp.Body.Close()
|
||||
if err != nil {
|
||||
return errorWrapper(err, "close_response_body_failed", http.StatusInternalServerError), ""
|
||||
}
|
||||
return nil, responseText
|
||||
}
|
||||
|
||||
func claudeHandler(c *gin.Context, resp *http.Response, promptTokens int, model string) (*OpenAIErrorWithStatusCode, *Usage) {
|
||||
responseBody, err := io.ReadAll(resp.Body)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "read_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
err = resp.Body.Close()
|
||||
if err != nil {
|
||||
return errorWrapper(err, "close_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
var claudeResponse ClaudeResponse
|
||||
err = json.Unmarshal(responseBody, &claudeResponse)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "unmarshal_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
if claudeResponse.Error.Type != "" {
|
||||
return &OpenAIErrorWithStatusCode{
|
||||
OpenAIError: OpenAIError{
|
||||
Message: claudeResponse.Error.Message,
|
||||
Type: claudeResponse.Error.Type,
|
||||
Param: "",
|
||||
Code: claudeResponse.Error.Type,
|
||||
},
|
||||
StatusCode: resp.StatusCode,
|
||||
}, nil
|
||||
}
|
||||
fullTextResponse := responseClaude2OpenAI(&claudeResponse)
|
||||
fullTextResponse.Model = model
|
||||
completionTokens := countTokenText(claudeResponse.Completion, model)
|
||||
usage := Usage{
|
||||
PromptTokens: promptTokens,
|
||||
CompletionTokens: completionTokens,
|
||||
TotalTokens: promptTokens + completionTokens,
|
||||
}
|
||||
fullTextResponse.Usage = usage
|
||||
jsonResponse, err := json.Marshal(fullTextResponse)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "marshal_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
c.Writer.Header().Set("Content-Type", "application/json")
|
||||
c.Writer.WriteHeader(resp.StatusCode)
|
||||
_, err = c.Writer.Write(jsonResponse)
|
||||
return nil, &usage
|
||||
}
|
||||
@@ -1,337 +0,0 @@
|
||||
package controller
|
||||
|
||||
import (
|
||||
"bufio"
|
||||
"encoding/json"
|
||||
"fmt"
|
||||
"io"
|
||||
"net/http"
|
||||
"one-api/common"
|
||||
"one-api/common/image"
|
||||
"strings"
|
||||
|
||||
"github.com/gin-gonic/gin"
|
||||
)
|
||||
|
||||
// https://ai.google.dev/docs/gemini_api_overview?hl=zh-cn
|
||||
|
||||
const (
|
||||
GeminiVisionMaxImageNum = 16
|
||||
)
|
||||
|
||||
type GeminiChatRequest struct {
|
||||
Contents []GeminiChatContent `json:"contents"`
|
||||
SafetySettings []GeminiChatSafetySettings `json:"safety_settings,omitempty"`
|
||||
GenerationConfig GeminiChatGenerationConfig `json:"generation_config,omitempty"`
|
||||
Tools []GeminiChatTools `json:"tools,omitempty"`
|
||||
}
|
||||
|
||||
type GeminiInlineData struct {
|
||||
MimeType string `json:"mimeType"`
|
||||
Data string `json:"data"`
|
||||
}
|
||||
|
||||
type GeminiPart struct {
|
||||
Text string `json:"text,omitempty"`
|
||||
InlineData *GeminiInlineData `json:"inlineData,omitempty"`
|
||||
}
|
||||
|
||||
type GeminiChatContent struct {
|
||||
Role string `json:"role,omitempty"`
|
||||
Parts []GeminiPart `json:"parts"`
|
||||
}
|
||||
|
||||
type GeminiChatSafetySettings struct {
|
||||
Category string `json:"category"`
|
||||
Threshold string `json:"threshold"`
|
||||
}
|
||||
|
||||
type GeminiChatTools struct {
|
||||
FunctionDeclarations any `json:"functionDeclarations,omitempty"`
|
||||
}
|
||||
|
||||
type GeminiChatGenerationConfig struct {
|
||||
Temperature float64 `json:"temperature,omitempty"`
|
||||
TopP float64 `json:"topP,omitempty"`
|
||||
TopK float64 `json:"topK,omitempty"`
|
||||
MaxOutputTokens int `json:"maxOutputTokens,omitempty"`
|
||||
CandidateCount int `json:"candidateCount,omitempty"`
|
||||
StopSequences []string `json:"stopSequences,omitempty"`
|
||||
}
|
||||
|
||||
// Setting safety to the lowest possible values since Gemini is already powerless enough
|
||||
func requestOpenAI2Gemini(textRequest GeneralOpenAIRequest) *GeminiChatRequest {
|
||||
geminiRequest := GeminiChatRequest{
|
||||
Contents: make([]GeminiChatContent, 0, len(textRequest.Messages)),
|
||||
SafetySettings: []GeminiChatSafetySettings{
|
||||
{
|
||||
Category: "HARM_CATEGORY_HARASSMENT",
|
||||
Threshold: common.GeminiSafetySetting,
|
||||
},
|
||||
{
|
||||
Category: "HARM_CATEGORY_HATE_SPEECH",
|
||||
Threshold: common.GeminiSafetySetting,
|
||||
},
|
||||
{
|
||||
Category: "HARM_CATEGORY_SEXUALLY_EXPLICIT",
|
||||
Threshold: common.GeminiSafetySetting,
|
||||
},
|
||||
{
|
||||
Category: "HARM_CATEGORY_DANGEROUS_CONTENT",
|
||||
Threshold: common.GeminiSafetySetting,
|
||||
},
|
||||
},
|
||||
GenerationConfig: GeminiChatGenerationConfig{
|
||||
Temperature: textRequest.Temperature,
|
||||
TopP: textRequest.TopP,
|
||||
MaxOutputTokens: textRequest.MaxTokens,
|
||||
},
|
||||
}
|
||||
if textRequest.Functions != nil {
|
||||
geminiRequest.Tools = []GeminiChatTools{
|
||||
{
|
||||
FunctionDeclarations: textRequest.Functions,
|
||||
},
|
||||
}
|
||||
}
|
||||
shouldAddDummyModelMessage := false
|
||||
for _, message := range textRequest.Messages {
|
||||
content := GeminiChatContent{
|
||||
Role: message.Role,
|
||||
Parts: []GeminiPart{
|
||||
{
|
||||
Text: message.StringContent(),
|
||||
},
|
||||
},
|
||||
}
|
||||
openaiContent := message.ParseContent()
|
||||
var parts []GeminiPart
|
||||
imageNum := 0
|
||||
for _, part := range openaiContent {
|
||||
if part.Type == ContentTypeText {
|
||||
parts = append(parts, GeminiPart{
|
||||
Text: part.Text,
|
||||
})
|
||||
} else if part.Type == ContentTypeImageURL {
|
||||
imageNum += 1
|
||||
if imageNum > GeminiVisionMaxImageNum {
|
||||
continue
|
||||
}
|
||||
mimeType, data, _ := image.GetImageFromUrl(part.ImageURL.Url)
|
||||
parts = append(parts, GeminiPart{
|
||||
InlineData: &GeminiInlineData{
|
||||
MimeType: mimeType,
|
||||
Data: data,
|
||||
},
|
||||
})
|
||||
}
|
||||
}
|
||||
content.Parts = parts
|
||||
|
||||
// there's no assistant role in gemini and API shall vomit if Role is not user or model
|
||||
if content.Role == "assistant" {
|
||||
content.Role = "model"
|
||||
}
|
||||
// Converting system prompt to prompt from user for the same reason
|
||||
if content.Role == "system" {
|
||||
content.Role = "user"
|
||||
shouldAddDummyModelMessage = true
|
||||
}
|
||||
geminiRequest.Contents = append(geminiRequest.Contents, content)
|
||||
|
||||
// If a system message is the last message, we need to add a dummy model message to make gemini happy
|
||||
if shouldAddDummyModelMessage {
|
||||
geminiRequest.Contents = append(geminiRequest.Contents, GeminiChatContent{
|
||||
Role: "model",
|
||||
Parts: []GeminiPart{
|
||||
{
|
||||
Text: "Okay",
|
||||
},
|
||||
},
|
||||
})
|
||||
shouldAddDummyModelMessage = false
|
||||
}
|
||||
}
|
||||
|
||||
return &geminiRequest
|
||||
}
|
||||
|
||||
type GeminiChatResponse struct {
|
||||
Candidates []GeminiChatCandidate `json:"candidates"`
|
||||
PromptFeedback GeminiChatPromptFeedback `json:"promptFeedback"`
|
||||
}
|
||||
|
||||
func (g *GeminiChatResponse) GetResponseText() string {
|
||||
if g == nil {
|
||||
return ""
|
||||
}
|
||||
if len(g.Candidates) > 0 && len(g.Candidates[0].Content.Parts) > 0 {
|
||||
return g.Candidates[0].Content.Parts[0].Text
|
||||
}
|
||||
return ""
|
||||
}
|
||||
|
||||
type GeminiChatCandidate struct {
|
||||
Content GeminiChatContent `json:"content"`
|
||||
FinishReason string `json:"finishReason"`
|
||||
Index int64 `json:"index"`
|
||||
SafetyRatings []GeminiChatSafetyRating `json:"safetyRatings"`
|
||||
}
|
||||
|
||||
type GeminiChatSafetyRating struct {
|
||||
Category string `json:"category"`
|
||||
Probability string `json:"probability"`
|
||||
}
|
||||
|
||||
type GeminiChatPromptFeedback struct {
|
||||
SafetyRatings []GeminiChatSafetyRating `json:"safetyRatings"`
|
||||
}
|
||||
|
||||
func responseGeminiChat2OpenAI(response *GeminiChatResponse) *OpenAITextResponse {
|
||||
fullTextResponse := OpenAITextResponse{
|
||||
Id: fmt.Sprintf("chatcmpl-%s", common.GetUUID()),
|
||||
Object: "chat.completion",
|
||||
Created: common.GetTimestamp(),
|
||||
Choices: make([]OpenAITextResponseChoice, 0, len(response.Candidates)),
|
||||
}
|
||||
for i, candidate := range response.Candidates {
|
||||
choice := OpenAITextResponseChoice{
|
||||
Index: i,
|
||||
Message: Message{
|
||||
Role: "assistant",
|
||||
Content: "",
|
||||
},
|
||||
FinishReason: stopFinishReason,
|
||||
}
|
||||
if len(candidate.Content.Parts) > 0 {
|
||||
choice.Message.Content = candidate.Content.Parts[0].Text
|
||||
}
|
||||
fullTextResponse.Choices = append(fullTextResponse.Choices, choice)
|
||||
}
|
||||
return &fullTextResponse
|
||||
}
|
||||
|
||||
func streamResponseGeminiChat2OpenAI(geminiResponse *GeminiChatResponse) *ChatCompletionsStreamResponse {
|
||||
var choice ChatCompletionsStreamResponseChoice
|
||||
choice.Delta.Content = geminiResponse.GetResponseText()
|
||||
choice.FinishReason = &stopFinishReason
|
||||
var response ChatCompletionsStreamResponse
|
||||
response.Object = "chat.completion.chunk"
|
||||
response.Model = "gemini"
|
||||
response.Choices = []ChatCompletionsStreamResponseChoice{choice}
|
||||
return &response
|
||||
}
|
||||
|
||||
func geminiChatStreamHandler(c *gin.Context, resp *http.Response) (*OpenAIErrorWithStatusCode, string) {
|
||||
responseText := ""
|
||||
dataChan := make(chan string)
|
||||
stopChan := make(chan bool)
|
||||
scanner := bufio.NewScanner(resp.Body)
|
||||
scanner.Split(func(data []byte, atEOF bool) (advance int, token []byte, err error) {
|
||||
if atEOF && len(data) == 0 {
|
||||
return 0, nil, nil
|
||||
}
|
||||
if i := strings.Index(string(data), "\n"); i >= 0 {
|
||||
return i + 1, data[0:i], nil
|
||||
}
|
||||
if atEOF {
|
||||
return len(data), data, nil
|
||||
}
|
||||
return 0, nil, nil
|
||||
})
|
||||
go func() {
|
||||
for scanner.Scan() {
|
||||
data := scanner.Text()
|
||||
data = strings.TrimSpace(data)
|
||||
if !strings.HasPrefix(data, "\"text\": \"") {
|
||||
continue
|
||||
}
|
||||
data = strings.TrimPrefix(data, "\"text\": \"")
|
||||
data = strings.TrimSuffix(data, "\"")
|
||||
dataChan <- data
|
||||
}
|
||||
stopChan <- true
|
||||
}()
|
||||
setEventStreamHeaders(c)
|
||||
c.Stream(func(w io.Writer) bool {
|
||||
select {
|
||||
case data := <-dataChan:
|
||||
// this is used to prevent annoying \ related format bug
|
||||
data = fmt.Sprintf("{\"content\": \"%s\"}", data)
|
||||
type dummyStruct struct {
|
||||
Content string `json:"content"`
|
||||
}
|
||||
var dummy dummyStruct
|
||||
err := json.Unmarshal([]byte(data), &dummy)
|
||||
responseText += dummy.Content
|
||||
var choice ChatCompletionsStreamResponseChoice
|
||||
choice.Delta.Content = dummy.Content
|
||||
response := ChatCompletionsStreamResponse{
|
||||
Id: fmt.Sprintf("chatcmpl-%s", common.GetUUID()),
|
||||
Object: "chat.completion.chunk",
|
||||
Created: common.GetTimestamp(),
|
||||
Model: "gemini-pro",
|
||||
Choices: []ChatCompletionsStreamResponseChoice{choice},
|
||||
}
|
||||
jsonResponse, err := json.Marshal(response)
|
||||
if err != nil {
|
||||
common.SysError("error marshalling stream response: " + err.Error())
|
||||
return true
|
||||
}
|
||||
c.Render(-1, common.CustomEvent{Data: "data: " + string(jsonResponse)})
|
||||
return true
|
||||
case <-stopChan:
|
||||
c.Render(-1, common.CustomEvent{Data: "data: [DONE]"})
|
||||
return false
|
||||
}
|
||||
})
|
||||
err := resp.Body.Close()
|
||||
if err != nil {
|
||||
return errorWrapper(err, "close_response_body_failed", http.StatusInternalServerError), ""
|
||||
}
|
||||
return nil, responseText
|
||||
}
|
||||
|
||||
func geminiChatHandler(c *gin.Context, resp *http.Response, promptTokens int, model string) (*OpenAIErrorWithStatusCode, *Usage) {
|
||||
responseBody, err := io.ReadAll(resp.Body)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "read_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
err = resp.Body.Close()
|
||||
if err != nil {
|
||||
return errorWrapper(err, "close_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
var geminiResponse GeminiChatResponse
|
||||
err = json.Unmarshal(responseBody, &geminiResponse)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "unmarshal_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
if len(geminiResponse.Candidates) == 0 {
|
||||
return &OpenAIErrorWithStatusCode{
|
||||
OpenAIError: OpenAIError{
|
||||
Message: "No candidates returned",
|
||||
Type: "server_error",
|
||||
Param: "",
|
||||
Code: 500,
|
||||
},
|
||||
StatusCode: resp.StatusCode,
|
||||
}, nil
|
||||
}
|
||||
fullTextResponse := responseGeminiChat2OpenAI(&geminiResponse)
|
||||
fullTextResponse.Model = model
|
||||
completionTokens := countTokenText(geminiResponse.GetResponseText(), model)
|
||||
usage := Usage{
|
||||
PromptTokens: promptTokens,
|
||||
CompletionTokens: completionTokens,
|
||||
TotalTokens: promptTokens + completionTokens,
|
||||
}
|
||||
fullTextResponse.Usage = usage
|
||||
jsonResponse, err := json.Marshal(fullTextResponse)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "marshal_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
c.Writer.Header().Set("Content-Type", "application/json")
|
||||
c.Writer.WriteHeader(resp.StatusCode)
|
||||
_, err = c.Writer.Write(jsonResponse)
|
||||
return nil, &usage
|
||||
}
|
||||
@@ -1,222 +0,0 @@
|
||||
package controller
|
||||
|
||||
import (
|
||||
"bytes"
|
||||
"context"
|
||||
"encoding/json"
|
||||
"errors"
|
||||
"fmt"
|
||||
"io"
|
||||
"net/http"
|
||||
"one-api/common"
|
||||
"one-api/model"
|
||||
"strings"
|
||||
|
||||
"github.com/gin-gonic/gin"
|
||||
)
|
||||
|
||||
func isWithinRange(element string, value int) bool {
|
||||
if _, ok := common.DalleGenerationImageAmounts[element]; !ok {
|
||||
return false
|
||||
}
|
||||
min := common.DalleGenerationImageAmounts[element][0]
|
||||
max := common.DalleGenerationImageAmounts[element][1]
|
||||
|
||||
return value >= min && value <= max
|
||||
}
|
||||
|
||||
func relayImageHelper(c *gin.Context, relayMode int) *OpenAIErrorWithStatusCode {
|
||||
imageModel := "dall-e-2"
|
||||
imageSize := "1024x1024"
|
||||
|
||||
tokenId := c.GetInt("token_id")
|
||||
channelType := c.GetInt("channel")
|
||||
channelId := c.GetInt("channel_id")
|
||||
userId := c.GetInt("id")
|
||||
group := c.GetString("group")
|
||||
|
||||
var imageRequest ImageRequest
|
||||
err := common.UnmarshalBodyReusable(c, &imageRequest)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "bind_request_body_failed", http.StatusBadRequest)
|
||||
}
|
||||
|
||||
if imageRequest.N == 0 {
|
||||
imageRequest.N = 1
|
||||
}
|
||||
|
||||
// Size validation
|
||||
if imageRequest.Size != "" {
|
||||
imageSize = imageRequest.Size
|
||||
}
|
||||
|
||||
// Model validation
|
||||
if imageRequest.Model != "" {
|
||||
imageModel = imageRequest.Model
|
||||
}
|
||||
|
||||
imageCostRatio, hasValidSize := common.DalleSizeRatios[imageModel][imageSize]
|
||||
|
||||
// Check if model is supported
|
||||
if hasValidSize {
|
||||
if imageRequest.Quality == "hd" && imageModel == "dall-e-3" {
|
||||
if imageSize == "1024x1024" {
|
||||
imageCostRatio *= 2
|
||||
} else {
|
||||
imageCostRatio *= 1.5
|
||||
}
|
||||
}
|
||||
} else {
|
||||
return errorWrapper(errors.New("size not supported for this image model"), "size_not_supported", http.StatusBadRequest)
|
||||
}
|
||||
|
||||
// Prompt validation
|
||||
if imageRequest.Prompt == "" {
|
||||
return errorWrapper(errors.New("prompt is required"), "prompt_missing", http.StatusBadRequest)
|
||||
}
|
||||
|
||||
// Check prompt length
|
||||
if len(imageRequest.Prompt) > common.DalleImagePromptLengthLimitations[imageModel] {
|
||||
return errorWrapper(errors.New("prompt is too long"), "prompt_too_long", http.StatusBadRequest)
|
||||
}
|
||||
|
||||
// Number of generated images validation
|
||||
if isWithinRange(imageModel, imageRequest.N) == false {
|
||||
// channel not azure
|
||||
if channelType != common.ChannelTypeAzure {
|
||||
return errorWrapper(errors.New("invalid value of n"), "n_not_within_range", http.StatusBadRequest)
|
||||
}
|
||||
}
|
||||
|
||||
// map model name
|
||||
modelMapping := c.GetString("model_mapping")
|
||||
isModelMapped := false
|
||||
if modelMapping != "" {
|
||||
modelMap := make(map[string]string)
|
||||
err := json.Unmarshal([]byte(modelMapping), &modelMap)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "unmarshal_model_mapping_failed", http.StatusInternalServerError)
|
||||
}
|
||||
if modelMap[imageModel] != "" {
|
||||
imageModel = modelMap[imageModel]
|
||||
isModelMapped = true
|
||||
}
|
||||
}
|
||||
baseURL := common.ChannelBaseURLs[channelType]
|
||||
requestURL := c.Request.URL.String()
|
||||
if c.GetString("base_url") != "" {
|
||||
baseURL = c.GetString("base_url")
|
||||
}
|
||||
fullRequestURL := getFullRequestURL(baseURL, requestURL, channelType)
|
||||
if channelType == common.ChannelTypeAzure {
|
||||
// https://learn.microsoft.com/en-us/azure/ai-services/openai/dall-e-quickstart?tabs=dalle3%2Ccommand-line&pivots=rest-api
|
||||
apiVersion := GetAPIVersion(c)
|
||||
// https://{resource_name}.openai.azure.com/openai/deployments/dall-e-3/images/generations?api-version=2023-06-01-preview
|
||||
fullRequestURL = fmt.Sprintf("%s/openai/deployments/%s/images/generations?api-version=%s", baseURL, imageModel, apiVersion)
|
||||
}
|
||||
|
||||
var requestBody io.Reader
|
||||
if isModelMapped || channelType == common.ChannelTypeAzure { // make Azure channel request body
|
||||
jsonStr, err := json.Marshal(imageRequest)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "marshal_text_request_failed", http.StatusInternalServerError)
|
||||
}
|
||||
requestBody = bytes.NewBuffer(jsonStr)
|
||||
} else {
|
||||
requestBody = c.Request.Body
|
||||
}
|
||||
|
||||
modelRatio := common.GetModelRatio(imageModel)
|
||||
groupRatio := common.GetGroupRatio(group)
|
||||
ratio := modelRatio * groupRatio
|
||||
userQuota, err := model.CacheGetUserQuota(userId)
|
||||
|
||||
quota := int(ratio*imageCostRatio*1000) * imageRequest.N
|
||||
|
||||
if userQuota-quota < 0 {
|
||||
return errorWrapper(errors.New("user quota is not enough"), "insufficient_user_quota", http.StatusForbidden)
|
||||
}
|
||||
|
||||
req, err := http.NewRequest(c.Request.Method, fullRequestURL, requestBody)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "new_request_failed", http.StatusInternalServerError)
|
||||
}
|
||||
token := c.Request.Header.Get("Authorization")
|
||||
if channelType == common.ChannelTypeAzure { // Azure authentication
|
||||
token = strings.TrimPrefix(token, "Bearer ")
|
||||
req.Header.Set("api-key", token)
|
||||
} else {
|
||||
req.Header.Set("Authorization", token)
|
||||
}
|
||||
|
||||
req.Header.Set("Content-Type", c.Request.Header.Get("Content-Type"))
|
||||
req.Header.Set("Accept", c.Request.Header.Get("Accept"))
|
||||
|
||||
resp, err := httpClient.Do(req)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "do_request_failed", http.StatusInternalServerError)
|
||||
}
|
||||
|
||||
err = req.Body.Close()
|
||||
if err != nil {
|
||||
return errorWrapper(err, "close_request_body_failed", http.StatusInternalServerError)
|
||||
}
|
||||
err = c.Request.Body.Close()
|
||||
if err != nil {
|
||||
return errorWrapper(err, "close_request_body_failed", http.StatusInternalServerError)
|
||||
}
|
||||
var textResponse ImageResponse
|
||||
|
||||
defer func(ctx context.Context) {
|
||||
if resp.StatusCode != http.StatusOK {
|
||||
return
|
||||
}
|
||||
err := model.PostConsumeTokenQuota(tokenId, quota)
|
||||
if err != nil {
|
||||
common.SysError("error consuming token remain quota: " + err.Error())
|
||||
}
|
||||
err = model.CacheUpdateUserQuota(userId)
|
||||
if err != nil {
|
||||
common.SysError("error update user quota cache: " + err.Error())
|
||||
}
|
||||
if quota != 0 {
|
||||
tokenName := c.GetString("token_name")
|
||||
logContent := fmt.Sprintf("模型倍率 %.2f，分组倍率 %.2f", modelRatio, groupRatio)
|
||||
model.RecordConsumeLog(ctx, userId, channelId, 0, 0, imageModel, tokenName, quota, logContent)
|
||||
model.UpdateUserUsedQuotaAndRequestCount(userId, quota)
|
||||
channelId := c.GetInt("channel_id")
|
||||
model.UpdateChannelUsedQuota(channelId, quota)
|
||||
}
|
||||
}(c.Request.Context())
|
||||
|
||||
responseBody, err := io.ReadAll(resp.Body)
|
||||
|
||||
if err != nil {
|
||||
return errorWrapper(err, "read_response_body_failed", http.StatusInternalServerError)
|
||||
}
|
||||
err = resp.Body.Close()
|
||||
if err != nil {
|
||||
return errorWrapper(err, "close_response_body_failed", http.StatusInternalServerError)
|
||||
}
|
||||
err = json.Unmarshal(responseBody, &textResponse)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "unmarshal_response_body_failed", http.StatusInternalServerError)
|
||||
}
|
||||
|
||||
resp.Body = io.NopCloser(bytes.NewBuffer(responseBody))
|
||||
|
||||
for k, v := range resp.Header {
|
||||
c.Writer.Header().Set(k, v[0])
|
||||
}
|
||||
c.Writer.WriteHeader(resp.StatusCode)
|
||||
|
||||
_, err = io.Copy(c.Writer, resp.Body)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "copy_response_body_failed", http.StatusInternalServerError)
|
||||
}
|
||||
err = resp.Body.Close()
|
||||
if err != nil {
|
||||
return errorWrapper(err, "close_response_body_failed", http.StatusInternalServerError)
|
||||
}
|
||||
return nil
|
||||
}
|
||||
@@ -1,143 +0,0 @@
|
||||
package controller
|
||||
|
||||
import (
|
||||
"bufio"
|
||||
"bytes"
|
||||
"encoding/json"
|
||||
"github.com/gin-gonic/gin"
|
||||
"io"
|
||||
"net/http"
|
||||
"one-api/common"
|
||||
"strings"
|
||||
)
|
||||
|
||||
func openaiStreamHandler(c *gin.Context, resp *http.Response, relayMode int) (*OpenAIErrorWithStatusCode, string) {
|
||||
responseText := ""
|
||||
scanner := bufio.NewScanner(resp.Body)
|
||||
scanner.Split(func(data []byte, atEOF bool) (advance int, token []byte, err error) {
|
||||
if atEOF && len(data) == 0 {
|
||||
return 0, nil, nil
|
||||
}
|
||||
if i := strings.Index(string(data), "\n"); i >= 0 {
|
||||
return i + 1, data[0:i], nil
|
||||
}
|
||||
if atEOF {
|
||||
return len(data), data, nil
|
||||
}
|
||||
return 0, nil, nil
|
||||
})
|
||||
dataChan := make(chan string)
|
||||
stopChan := make(chan bool)
|
||||
go func() {
|
||||
for scanner.Scan() {
|
||||
data := scanner.Text()
|
||||
if len(data) < 6 { // ignore blank line or wrong format
|
||||
continue
|
||||
}
|
||||
if data[:6] != "data: " && data[:6] != "[DONE]" {
|
||||
continue
|
||||
}
|
||||
dataChan <- data
|
||||
data = data[6:]
|
||||
if !strings.HasPrefix(data, "[DONE]") {
|
||||
switch relayMode {
|
||||
case RelayModeChatCompletions:
|
||||
var streamResponse ChatCompletionsStreamResponse
|
||||
err := json.Unmarshal([]byte(data), &streamResponse)
|
||||
if err != nil {
|
||||
common.SysError("error unmarshalling stream response: " + err.Error())
|
||||
continue // just ignore the error
|
||||
}
|
||||
for _, choice := range streamResponse.Choices {
|
||||
responseText += choice.Delta.Content
|
||||
}
|
||||
case RelayModeCompletions:
|
||||
var streamResponse CompletionsStreamResponse
|
||||
err := json.Unmarshal([]byte(data), &streamResponse)
|
||||
if err != nil {
|
||||
common.SysError("error unmarshalling stream response: " + err.Error())
|
||||
continue
|
||||
}
|
||||
for _, choice := range streamResponse.Choices {
|
||||
responseText += choice.Text
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
stopChan <- true
|
||||
}()
|
||||
setEventStreamHeaders(c)
|
||||
c.Stream(func(w io.Writer) bool {
|
||||
select {
|
||||
case data := <-dataChan:
|
||||
if strings.HasPrefix(data, "data: [DONE]") {
|
||||
data = data[:12]
|
||||
}
|
||||
// some implementations may add \r at the end of data
|
||||
data = strings.TrimSuffix(data, "\r")
|
||||
c.Render(-1, common.CustomEvent{Data: data})
|
||||
return true
|
||||
case <-stopChan:
|
||||
return false
|
||||
}
|
||||
})
|
||||
err := resp.Body.Close()
|
||||
if err != nil {
|
||||
return errorWrapper(err, "close_response_body_failed", http.StatusInternalServerError), ""
|
||||
}
|
||||
return nil, responseText
|
||||
}
|
||||
|
||||
func openaiHandler(c *gin.Context, resp *http.Response, promptTokens int, model string) (*OpenAIErrorWithStatusCode, *Usage) {
|
||||
var textResponse TextResponse
|
||||
responseBody, err := io.ReadAll(resp.Body)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "read_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
err = resp.Body.Close()
|
||||
if err != nil {
|
||||
return errorWrapper(err, "close_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
err = json.Unmarshal(responseBody, &textResponse)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "unmarshal_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
if textResponse.Error.Type != "" {
|
||||
return &OpenAIErrorWithStatusCode{
|
||||
OpenAIError: textResponse.Error,
|
||||
StatusCode: resp.StatusCode,
|
||||
}, nil
|
||||
}
|
||||
// Reset response body
|
||||
resp.Body = io.NopCloser(bytes.NewBuffer(responseBody))
|
||||
|
||||
// We shouldn't set the header before we parse the response body, because the parse part may fail.
|
||||
// And then we will have to send an error response, but in this case, the header has already been set.
|
||||
// So the httpClient will be confused by the response.
|
||||
// For example, Postman will report error, and we cannot check the response at all.
|
||||
for k, v := range resp.Header {
|
||||
c.Writer.Header().Set(k, v[0])
|
||||
}
|
||||
c.Writer.WriteHeader(resp.StatusCode)
|
||||
_, err = io.Copy(c.Writer, resp.Body)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "copy_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
err = resp.Body.Close()
|
||||
if err != nil {
|
||||
return errorWrapper(err, "close_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
|
||||
if textResponse.Usage.TotalTokens == 0 {
|
||||
completionTokens := 0
|
||||
for _, choice := range textResponse.Choices {
|
||||
completionTokens += countTokenText(choice.Message.StringContent(), model)
|
||||
}
|
||||
textResponse.Usage = Usage{
|
||||
PromptTokens: promptTokens,
|
||||
CompletionTokens: completionTokens,
|
||||
TotalTokens: promptTokens + completionTokens,
|
||||
}
|
||||
}
|
||||
return nil, &textResponse.Usage
|
||||
}
|
||||
@@ -1,206 +0,0 @@
|
||||
package controller
|
||||
|
||||
import (
|
||||
"encoding/json"
|
||||
"fmt"
|
||||
"github.com/gin-gonic/gin"
|
||||
"io"
|
||||
"net/http"
|
||||
"one-api/common"
|
||||
)
|
||||
|
||||
// https://developers.generativeai.google/api/rest/generativelanguage/models/generateMessage#request-body
|
||||
// https://developers.generativeai.google/api/rest/generativelanguage/models/generateMessage#response-body
|
||||
|
||||
type PaLMChatMessage struct {
|
||||
Author string `json:"author"`
|
||||
Content string `json:"content"`
|
||||
}
|
||||
|
||||
type PaLMFilter struct {
|
||||
Reason string `json:"reason"`
|
||||
Message string `json:"message"`
|
||||
}
|
||||
|
||||
type PaLMPrompt struct {
|
||||
Messages []PaLMChatMessage `json:"messages"`
|
||||
}
|
||||
|
||||
type PaLMChatRequest struct {
|
||||
Prompt PaLMPrompt `json:"prompt"`
|
||||
Temperature float64 `json:"temperature,omitempty"`
|
||||
CandidateCount int `json:"candidateCount,omitempty"`
|
||||
TopP float64 `json:"topP,omitempty"`
|
||||
TopK int `json:"topK,omitempty"`
|
||||
}
|
||||
|
||||
type PaLMError struct {
|
||||
Code int `json:"code"`
|
||||
Message string `json:"message"`
|
||||
Status string `json:"status"`
|
||||
}
|
||||
|
||||
type PaLMChatResponse struct {
|
||||
Candidates []PaLMChatMessage `json:"candidates"`
|
||||
Messages []Message `json:"messages"`
|
||||
Filters []PaLMFilter `json:"filters"`
|
||||
Error PaLMError `json:"error"`
|
||||
}
|
||||
|
||||
func requestOpenAI2PaLM(textRequest GeneralOpenAIRequest) *PaLMChatRequest {
|
||||
palmRequest := PaLMChatRequest{
|
||||
Prompt: PaLMPrompt{
|
||||
Messages: make([]PaLMChatMessage, 0, len(textRequest.Messages)),
|
||||
},
|
||||
Temperature: textRequest.Temperature,
|
||||
CandidateCount: textRequest.N,
|
||||
TopP: textRequest.TopP,
|
||||
TopK: textRequest.MaxTokens,
|
||||
}
|
||||
for _, message := range textRequest.Messages {
|
||||
palmMessage := PaLMChatMessage{
|
||||
Content: message.StringContent(),
|
||||
}
|
||||
if message.Role == "user" {
|
||||
palmMessage.Author = "0"
|
||||
} else {
|
||||
palmMessage.Author = "1"
|
||||
}
|
||||
palmRequest.Prompt.Messages = append(palmRequest.Prompt.Messages, palmMessage)
|
||||
}
|
||||
return &palmRequest
|
||||
}
|
||||
|
||||
func responsePaLM2OpenAI(response *PaLMChatResponse) *OpenAITextResponse {
|
||||
fullTextResponse := OpenAITextResponse{
|
||||
Choices: make([]OpenAITextResponseChoice, 0, len(response.Candidates)),
|
||||
}
|
||||
for i, candidate := range response.Candidates {
|
||||
choice := OpenAITextResponseChoice{
|
||||
Index: i,
|
||||
Message: Message{
|
||||
Role: "assistant",
|
||||
Content: candidate.Content,
|
||||
},
|
||||
FinishReason: "stop",
|
||||
}
|
||||
fullTextResponse.Choices = append(fullTextResponse.Choices, choice)
|
||||
}
|
||||
return &fullTextResponse
|
||||
}
|
||||
|
||||
func streamResponsePaLM2OpenAI(palmResponse *PaLMChatResponse) *ChatCompletionsStreamResponse {
|
||||
var choice ChatCompletionsStreamResponseChoice
|
||||
if len(palmResponse.Candidates) > 0 {
|
||||
choice.Delta.Content = palmResponse.Candidates[0].Content
|
||||
}
|
||||
choice.FinishReason = &stopFinishReason
|
||||
var response ChatCompletionsStreamResponse
|
||||
response.Object = "chat.completion.chunk"
|
||||
response.Model = "palm2"
|
||||
response.Choices = []ChatCompletionsStreamResponseChoice{choice}
|
||||
return &response
|
||||
}
|
||||
|
||||
func palmStreamHandler(c *gin.Context, resp *http.Response) (*OpenAIErrorWithStatusCode, string) {
|
||||
responseText := ""
|
||||
responseId := fmt.Sprintf("chatcmpl-%s", common.GetUUID())
|
||||
createdTime := common.GetTimestamp()
|
||||
dataChan := make(chan string)
|
||||
stopChan := make(chan bool)
|
||||
go func() {
|
||||
responseBody, err := io.ReadAll(resp.Body)
|
||||
if err != nil {
|
||||
common.SysError("error reading stream response: " + err.Error())
|
||||
stopChan <- true
|
||||
return
|
||||
}
|
||||
err = resp.Body.Close()
|
||||
if err != nil {
|
||||
common.SysError("error closing stream response: " + err.Error())
|
||||
stopChan <- true
|
||||
return
|
||||
}
|
||||
var palmResponse PaLMChatResponse
|
||||
err = json.Unmarshal(responseBody, &palmResponse)
|
||||
if err != nil {
|
||||
common.SysError("error unmarshalling stream response: " + err.Error())
|
||||
stopChan <- true
|
||||
return
|
||||
}
|
||||
fullTextResponse := streamResponsePaLM2OpenAI(&palmResponse)
|
||||
fullTextResponse.Id = responseId
|
||||
fullTextResponse.Created = createdTime
|
||||
if len(palmResponse.Candidates) > 0 {
|
||||
responseText = palmResponse.Candidates[0].Content
|
||||
}
|
||||
jsonResponse, err := json.Marshal(fullTextResponse)
|
||||
if err != nil {
|
||||
common.SysError("error marshalling stream response: " + err.Error())
|
||||
stopChan <- true
|
||||
return
|
||||
}
|
||||
dataChan <- string(jsonResponse)
|
||||
stopChan <- true
|
||||
}()
|
||||
setEventStreamHeaders(c)
|
||||
c.Stream(func(w io.Writer) bool {
|
||||
select {
|
||||
case data := <-dataChan:
|
||||
c.Render(-1, common.CustomEvent{Data: "data: " + data})
|
||||
return true
|
||||
case <-stopChan:
|
||||
c.Render(-1, common.CustomEvent{Data: "data: [DONE]"})
|
||||
return false
|
||||
}
|
||||
})
|
||||
err := resp.Body.Close()
|
||||
if err != nil {
|
||||
return errorWrapper(err, "close_response_body_failed", http.StatusInternalServerError), ""
|
||||
}
|
||||
return nil, responseText
|
||||
}
|
||||
|
||||
func palmHandler(c *gin.Context, resp *http.Response, promptTokens int, model string) (*OpenAIErrorWithStatusCode, *Usage) {
|
||||
responseBody, err := io.ReadAll(resp.Body)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "read_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
err = resp.Body.Close()
|
||||
if err != nil {
|
||||
return errorWrapper(err, "close_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
var palmResponse PaLMChatResponse
|
||||
err = json.Unmarshal(responseBody, &palmResponse)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "unmarshal_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
if palmResponse.Error.Code != 0 || len(palmResponse.Candidates) == 0 {
|
||||
return &OpenAIErrorWithStatusCode{
|
||||
OpenAIError: OpenAIError{
|
||||
Message: palmResponse.Error.Message,
|
||||
Type: palmResponse.Error.Status,
|
||||
Param: "",
|
||||
Code: palmResponse.Error.Code,
|
||||
},
|
||||
StatusCode: resp.StatusCode,
|
||||
}, nil
|
||||
}
|
||||
fullTextResponse := responsePaLM2OpenAI(&palmResponse)
|
||||
fullTextResponse.Model = model
|
||||
completionTokens := countTokenText(palmResponse.Candidates[0].Content, model)
|
||||
usage := Usage{
|
||||
PromptTokens: promptTokens,
|
||||
CompletionTokens: completionTokens,
|
||||
TotalTokens: promptTokens + completionTokens,
|
||||
}
|
||||
fullTextResponse.Usage = usage
|
||||
jsonResponse, err := json.Marshal(fullTextResponse)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "marshal_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
c.Writer.Header().Set("Content-Type", "application/json")
|
||||
c.Writer.WriteHeader(resp.StatusCode)
|
||||
_, err = c.Writer.Write(jsonResponse)
|
||||
return nil, &usage
|
||||
}
|
||||
@@ -1,288 +0,0 @@
|
||||
package controller
|
||||
|
||||
import (
|
||||
"bufio"
|
||||
"crypto/hmac"
|
||||
"crypto/sha1"
|
||||
"encoding/base64"
|
||||
"encoding/json"
|
||||
"errors"
|
||||
"fmt"
|
||||
"github.com/gin-gonic/gin"
|
||||
"io"
|
||||
"net/http"
|
||||
"one-api/common"
|
||||
"sort"
|
||||
"strconv"
|
||||
"strings"
|
||||
)
|
||||
|
||||
// https://cloud.tencent.com/document/product/1729/97732
|
||||
|
||||
type TencentMessage struct {
|
||||
Role string `json:"role"`
|
||||
Content string `json:"content"`
|
||||
}
|
||||
|
||||
type TencentChatRequest struct {
|
||||
AppId int64 `json:"app_id"` // 腾讯云账号的 APPID
|
||||
SecretId string `json:"secret_id"` // 官网 SecretId
|
||||
// Timestamp当前 UNIX 时间戳，单位为秒，可记录发起 API 请求的时间。
|
||||
// 例如1529223702，如果与当前时间相差过大，会引起签名过期错误
|
||||
Timestamp int64 `json:"timestamp"`
|
||||
// Expired 签名的有效期，是一个符合 UNIX Epoch 时间戳规范的数值，
|
||||
// 单位为秒；Expired 必须大于 Timestamp 且 Expired-Timestamp 小于90天
|
||||
Expired int64 `json:"expired"`
|
||||
QueryID string `json:"query_id"` //请求 Id，用于问题排查
|
||||
// Temperature 较高的数值会使输出更加随机，而较低的数值会使其更加集中和确定
|
||||
// 默认 1.0，取值区间为[0.0,2.0]，非必要不建议使用,不合理的取值会影响效果
|
||||
// 建议该参数和 top_p 只设置1个，不要同时更改 top_p
|
||||
Temperature float64 `json:"temperature"`
|
||||
// TopP 影响输出文本的多样性，取值越大，生成文本的多样性越强
|
||||
// 默认1.0，取值区间为[0.0, 1.0]，非必要不建议使用, 不合理的取值会影响效果
|
||||
// 建议该参数和 temperature 只设置1个，不要同时更改
|
||||
TopP float64 `json:"top_p"`
|
||||
// Stream 0：同步，1：流式 （默认，协议：SSE)
|
||||
// 同步请求超时：60s，如果内容较长建议使用流式
|
||||
Stream int `json:"stream"`
|
||||
// Messages 会话内容, 长度最多为40, 按对话时间从旧到新在数组中排列
|
||||
// 输入 content 总数最大支持 3000 token。
|
||||
Messages []TencentMessage `json:"messages"`
|
||||
}
|
||||
|
||||
type TencentError struct {
|
||||
Code int `json:"code"`
|
||||
Message string `json:"message"`
|
||||
}
|
||||
|
||||
type TencentUsage struct {
|
||||
InputTokens int `json:"input_tokens"`
|
||||
OutputTokens int `json:"output_tokens"`
|
||||
TotalTokens int `json:"total_tokens"`
|
||||
}
|
||||
|
||||
type TencentResponseChoices struct {
|
||||
FinishReason string `json:"finish_reason,omitempty"` // 流式结束标志位，为 stop 则表示尾包
|
||||
Messages TencentMessage `json:"messages,omitempty"` // 内容，同步模式返回内容，流模式为 null 输出 content 内容总数最多支持 1024token。
|
||||
Delta TencentMessage `json:"delta,omitempty"` // 内容，流模式返回内容，同步模式为 null 输出 content 内容总数最多支持 1024token。
|
||||
}
|
||||
|
||||
type TencentChatResponse struct {
|
||||
Choices []TencentResponseChoices `json:"choices,omitempty"` // 结果
|
||||
Created string `json:"created,omitempty"` // unix 时间戳的字符串
|
||||
Id string `json:"id,omitempty"` // 会话 id
|
||||
Usage Usage `json:"usage,omitempty"` // token 数量
|
||||
Error TencentError `json:"error,omitempty"` // 错误信息 注意：此字段可能返回 null，表示取不到有效值
|
||||
Note string `json:"note,omitempty"` // 注释
|
||||
ReqID string `json:"req_id,omitempty"` // 唯一请求 Id，每次请求都会返回。用于反馈接口入参
|
||||
}
|
||||
|
||||
func requestOpenAI2Tencent(request GeneralOpenAIRequest) *TencentChatRequest {
|
||||
messages := make([]TencentMessage, 0, len(request.Messages))
|
||||
for i := 0; i < len(request.Messages); i++ {
|
||||
message := request.Messages[i]
|
||||
if message.Role == "system" {
|
||||
messages = append(messages, TencentMessage{
|
||||
Role: "user",
|
||||
Content: message.StringContent(),
|
||||
})
|
||||
messages = append(messages, TencentMessage{
|
||||
Role: "assistant",
|
||||
Content: "Okay",
|
||||
})
|
||||
continue
|
||||
}
|
||||
messages = append(messages, TencentMessage{
|
||||
Content: message.StringContent(),
|
||||
Role: message.Role,
|
||||
})
|
||||
}
|
||||
stream := 0
|
||||
if request.Stream {
|
||||
stream = 1
|
||||
}
|
||||
return &TencentChatRequest{
|
||||
Timestamp: common.GetTimestamp(),
|
||||
Expired: common.GetTimestamp() + 24*60*60,
|
||||
QueryID: common.GetUUID(),
|
||||
Temperature: request.Temperature,
|
||||
TopP: request.TopP,
|
||||
Stream: stream,
|
||||
Messages: messages,
|
||||
}
|
||||
}
|
||||
|
||||
func responseTencent2OpenAI(response *TencentChatResponse) *OpenAITextResponse {
|
||||
fullTextResponse := OpenAITextResponse{
|
||||
Object: "chat.completion",
|
||||
Created: common.GetTimestamp(),
|
||||
Usage: response.Usage,
|
||||
}
|
||||
if len(response.Choices) > 0 {
|
||||
choice := OpenAITextResponseChoice{
|
||||
Index: 0,
|
||||
Message: Message{
|
||||
Role: "assistant",
|
||||
Content: response.Choices[0].Messages.Content,
|
||||
},
|
||||
FinishReason: response.Choices[0].FinishReason,
|
||||
}
|
||||
fullTextResponse.Choices = append(fullTextResponse.Choices, choice)
|
||||
}
|
||||
return &fullTextResponse
|
||||
}
|
||||
|
||||
func streamResponseTencent2OpenAI(TencentResponse *TencentChatResponse) *ChatCompletionsStreamResponse {
|
||||
response := ChatCompletionsStreamResponse{
|
||||
Object: "chat.completion.chunk",
|
||||
Created: common.GetTimestamp(),
|
||||
Model: "tencent-hunyuan",
|
||||
}
|
||||
if len(TencentResponse.Choices) > 0 {
|
||||
var choice ChatCompletionsStreamResponseChoice
|
||||
choice.Delta.Content = TencentResponse.Choices[0].Delta.Content
|
||||
if TencentResponse.Choices[0].FinishReason == "stop" {
|
||||
choice.FinishReason = &stopFinishReason
|
||||
}
|
||||
response.Choices = append(response.Choices, choice)
|
||||
}
|
||||
return &response
|
||||
}
|
||||
|
||||
func tencentStreamHandler(c *gin.Context, resp *http.Response) (*OpenAIErrorWithStatusCode, string) {
|
||||
var responseText string
|
||||
scanner := bufio.NewScanner(resp.Body)
|
||||
scanner.Split(func(data []byte, atEOF bool) (advance int, token []byte, err error) {
|
||||
if atEOF && len(data) == 0 {
|
||||
return 0, nil, nil
|
||||
}
|
||||
if i := strings.Index(string(data), "\n"); i >= 0 {
|
||||
return i + 1, data[0:i], nil
|
||||
}
|
||||
if atEOF {
|
||||
return len(data), data, nil
|
||||
}
|
||||
return 0, nil, nil
|
||||
})
|
||||
dataChan := make(chan string)
|
||||
stopChan := make(chan bool)
|
||||
go func() {
|
||||
for scanner.Scan() {
|
||||
data := scanner.Text()
|
||||
if len(data) < 5 { // ignore blank line or wrong format
|
||||
continue
|
||||
}
|
||||
if data[:5] != "data:" {
|
||||
continue
|
||||
}
|
||||
data = data[5:]
|
||||
dataChan <- data
|
||||
}
|
||||
stopChan <- true
|
||||
}()
|
||||
setEventStreamHeaders(c)
|
||||
c.Stream(func(w io.Writer) bool {
|
||||
select {
|
||||
case data := <-dataChan:
|
||||
var TencentResponse TencentChatResponse
|
||||
err := json.Unmarshal([]byte(data), &TencentResponse)
|
||||
if err != nil {
|
||||
common.SysError("error unmarshalling stream response: " + err.Error())
|
||||
return true
|
||||
}
|
||||
response := streamResponseTencent2OpenAI(&TencentResponse)
|
||||
if len(response.Choices) != 0 {
|
||||
responseText += response.Choices[0].Delta.Content
|
||||
}
|
||||
jsonResponse, err := json.Marshal(response)
|
||||
if err != nil {
|
||||
common.SysError("error marshalling stream response: " + err.Error())
|
||||
return true
|
||||
}
|
||||
c.Render(-1, common.CustomEvent{Data: "data: " + string(jsonResponse)})
|
||||
return true
|
||||
case <-stopChan:
|
||||
c.Render(-1, common.CustomEvent{Data: "data: [DONE]"})
|
||||
return false
|
||||
}
|
||||
})
|
||||
err := resp.Body.Close()
|
||||
if err != nil {
|
||||
return errorWrapper(err, "close_response_body_failed", http.StatusInternalServerError), ""
|
||||
}
|
||||
return nil, responseText
|
||||
}
|
||||
|
||||
func tencentHandler(c *gin.Context, resp *http.Response) (*OpenAIErrorWithStatusCode, *Usage) {
|
||||
var TencentResponse TencentChatResponse
|
||||
responseBody, err := io.ReadAll(resp.Body)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "read_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
err = resp.Body.Close()
|
||||
if err != nil {
|
||||
return errorWrapper(err, "close_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
err = json.Unmarshal(responseBody, &TencentResponse)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "unmarshal_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
if TencentResponse.Error.Code != 0 {
|
||||
return &OpenAIErrorWithStatusCode{
|
||||
OpenAIError: OpenAIError{
|
||||
Message: TencentResponse.Error.Message,
|
||||
Code: TencentResponse.Error.Code,
|
||||
},
|
||||
StatusCode: resp.StatusCode,
|
||||
}, nil
|
||||
}
|
||||
fullTextResponse := responseTencent2OpenAI(&TencentResponse)
|
||||
fullTextResponse.Model = "hunyuan"
|
||||
jsonResponse, err := json.Marshal(fullTextResponse)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "marshal_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
c.Writer.Header().Set("Content-Type", "application/json")
|
||||
c.Writer.WriteHeader(resp.StatusCode)
|
||||
_, err = c.Writer.Write(jsonResponse)
|
||||
return nil, &fullTextResponse.Usage
|
||||
}
|
||||
|
||||
func parseTencentConfig(config string) (appId int64, secretId string, secretKey string, err error) {
|
||||
parts := strings.Split(config, "|")
|
||||
if len(parts) != 3 {
|
||||
err = errors.New("invalid tencent config")
|
||||
return
|
||||
}
|
||||
appId, err = strconv.ParseInt(parts[0], 10, 64)
|
||||
secretId = parts[1]
|
||||
secretKey = parts[2]
|
||||
return
|
||||
}
|
||||
|
||||
func getTencentSign(req TencentChatRequest, secretKey string) string {
|
||||
params := make([]string, 0)
|
||||
params = append(params, "app_id="+strconv.FormatInt(req.AppId, 10))
|
||||
params = append(params, "secret_id="+req.SecretId)
|
||||
params = append(params, "timestamp="+strconv.FormatInt(req.Timestamp, 10))
|
||||
params = append(params, "query_id="+req.QueryID)
|
||||
params = append(params, "temperature="+strconv.FormatFloat(req.Temperature, 'f', -1, 64))
|
||||
params = append(params, "top_p="+strconv.FormatFloat(req.TopP, 'f', -1, 64))
|
||||
params = append(params, "stream="+strconv.Itoa(req.Stream))
|
||||
params = append(params, "expired="+strconv.FormatInt(req.Expired, 10))
|
||||
|
||||
var messageStr string
|
||||
for _, msg := range req.Messages {
|
||||
messageStr += fmt.Sprintf(`{"role":"%s","content":"%s"},`, msg.Role, msg.Content)
|
||||
}
|
||||
messageStr = strings.TrimSuffix(messageStr, ",")
|
||||
params = append(params, "messages=["+messageStr+"]")
|
||||
|
||||
sort.Sort(sort.StringSlice(params))
|
||||
url := "hunyuan.cloud.tencent.com/hyllm/v1/chat/completions?" + strings.Join(params, "&")
|
||||
mac := hmac.New(sha1.New, []byte(secretKey))
|
||||
signURL := url
|
||||
mac.Write([]byte(signURL))
|
||||
sign := mac.Sum([]byte(nil))
|
||||
return base64.StdEncoding.EncodeToString(sign)
|
||||
}
|
||||
@@ -1,689 +0,0 @@
|
||||
package controller
|
||||
|
||||
import (
|
||||
"bytes"
|
||||
"context"
|
||||
"encoding/json"
|
||||
"errors"
|
||||
"fmt"
|
||||
"io"
|
||||
"math"
|
||||
"net/http"
|
||||
"one-api/common"
|
||||
"one-api/model"
|
||||
"strings"
|
||||
"time"
|
||||
|
||||
"github.com/gin-gonic/gin"
|
||||
)
|
||||
|
||||
const (
|
||||
APITypeOpenAI = iota
|
||||
APITypeClaude
|
||||
APITypePaLM
|
||||
APITypeBaidu
|
||||
APITypeZhipu
|
||||
APITypeAli
|
||||
APITypeXunfei
|
||||
APITypeAIProxyLibrary
|
||||
APITypeTencent
|
||||
APITypeGemini
|
||||
)
|
||||
|
||||
var httpClient *http.Client
|
||||
var impatientHTTPClient *http.Client
|
||||
|
||||
func init() {
|
||||
if common.RelayTimeout == 0 {
|
||||
httpClient = &http.Client{}
|
||||
} else {
|
||||
httpClient = &http.Client{
|
||||
Timeout: time.Duration(common.RelayTimeout) * time.Second,
|
||||
}
|
||||
}
|
||||
|
||||
impatientHTTPClient = &http.Client{
|
||||
Timeout: 5 * time.Second,
|
||||
}
|
||||
}
|
||||
|
||||
func relayTextHelper(c *gin.Context, relayMode int) *OpenAIErrorWithStatusCode {
|
||||
channelType := c.GetInt("channel")
|
||||
channelId := c.GetInt("channel_id")
|
||||
tokenId := c.GetInt("token_id")
|
||||
userId := c.GetInt("id")
|
||||
group := c.GetString("group")
|
||||
var textRequest GeneralOpenAIRequest
|
||||
err := common.UnmarshalBodyReusable(c, &textRequest)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "bind_request_body_failed", http.StatusBadRequest)
|
||||
}
|
||||
if textRequest.MaxTokens < 0 || textRequest.MaxTokens > math.MaxInt32/2 {
|
||||
return errorWrapper(errors.New("max_tokens is invalid"), "invalid_max_tokens", http.StatusBadRequest)
|
||||
}
|
||||
if relayMode == RelayModeModerations && textRequest.Model == "" {
|
||||
textRequest.Model = "text-moderation-latest"
|
||||
}
|
||||
if relayMode == RelayModeEmbeddings && textRequest.Model == "" {
|
||||
textRequest.Model = c.Param("model")
|
||||
}
|
||||
// request validation
|
||||
if textRequest.Model == "" {
|
||||
return errorWrapper(errors.New("model is required"), "required_field_missing", http.StatusBadRequest)
|
||||
}
|
||||
switch relayMode {
|
||||
case RelayModeCompletions:
|
||||
if textRequest.Prompt == "" {
|
||||
return errorWrapper(errors.New("field prompt is required"), "required_field_missing", http.StatusBadRequest)
|
||||
}
|
||||
case RelayModeChatCompletions:
|
||||
if textRequest.Messages == nil || len(textRequest.Messages) == 0 {
|
||||
return errorWrapper(errors.New("field messages is required"), "required_field_missing", http.StatusBadRequest)
|
||||
}
|
||||
case RelayModeEmbeddings:
|
||||
case RelayModeModerations:
|
||||
if textRequest.Input == "" {
|
||||
return errorWrapper(errors.New("field input is required"), "required_field_missing", http.StatusBadRequest)
|
||||
}
|
||||
case RelayModeEdits:
|
||||
if textRequest.Instruction == "" {
|
||||
return errorWrapper(errors.New("field instruction is required"), "required_field_missing", http.StatusBadRequest)
|
||||
}
|
||||
}
|
||||
// map model name
|
||||
modelMapping := c.GetString("model_mapping")
|
||||
isModelMapped := false
|
||||
if modelMapping != "" && modelMapping != "{}" {
|
||||
modelMap := make(map[string]string)
|
||||
err := json.Unmarshal([]byte(modelMapping), &modelMap)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "unmarshal_model_mapping_failed", http.StatusInternalServerError)
|
||||
}
|
||||
if modelMap[textRequest.Model] != "" {
|
||||
textRequest.Model = modelMap[textRequest.Model]
|
||||
isModelMapped = true
|
||||
}
|
||||
}
|
||||
apiType := APITypeOpenAI
|
||||
switch channelType {
|
||||
case common.ChannelTypeAnthropic:
|
||||
apiType = APITypeClaude
|
||||
case common.ChannelTypeBaidu:
|
||||
apiType = APITypeBaidu
|
||||
case common.ChannelTypePaLM:
|
||||
apiType = APITypePaLM
|
||||
case common.ChannelTypeZhipu:
|
||||
apiType = APITypeZhipu
|
||||
case common.ChannelTypeAli:
|
||||
apiType = APITypeAli
|
||||
case common.ChannelTypeXunfei:
|
||||
apiType = APITypeXunfei
|
||||
case common.ChannelTypeAIProxyLibrary:
|
||||
apiType = APITypeAIProxyLibrary
|
||||
case common.ChannelTypeTencent:
|
||||
apiType = APITypeTencent
|
||||
case common.ChannelTypeGemini:
|
||||
apiType = APITypeGemini
|
||||
}
|
||||
baseURL := common.ChannelBaseURLs[channelType]
|
||||
requestURL := c.Request.URL.String()
|
||||
if c.GetString("base_url") != "" {
|
||||
baseURL = c.GetString("base_url")
|
||||
}
|
||||
fullRequestURL := getFullRequestURL(baseURL, requestURL, channelType)
|
||||
switch apiType {
|
||||
case APITypeOpenAI:
|
||||
if channelType == common.ChannelTypeAzure {
|
||||
// https://learn.microsoft.com/en-us/azure/cognitive-services/openai/chatgpt-quickstart?pivots=rest-api&tabs=command-line#rest-api
|
||||
apiVersion := GetAPIVersion(c)
|
||||
requestURL := strings.Split(requestURL, "?")[0]
|
||||
requestURL = fmt.Sprintf("%s?api-version=%s", requestURL, apiVersion)
|
||||
baseURL = c.GetString("base_url")
|
||||
task := strings.TrimPrefix(requestURL, "/v1/")
|
||||
model_ := textRequest.Model
|
||||
model_ = strings.Replace(model_, ".", "", -1)
|
||||
// https://github.com/songquanpeng/one-api/issues/67
|
||||
model_ = strings.TrimSuffix(model_, "-0301")
|
||||
model_ = strings.TrimSuffix(model_, "-0314")
|
||||
model_ = strings.TrimSuffix(model_, "-0613")
|
||||
|
||||
requestURL = fmt.Sprintf("/openai/deployments/%s/%s", model_, task)
|
||||
fullRequestURL = getFullRequestURL(baseURL, requestURL, channelType)
|
||||
}
|
||||
case APITypeClaude:
|
||||
fullRequestURL = "https://api.anthropic.com/v1/complete"
|
||||
if baseURL != "" {
|
||||
fullRequestURL = fmt.Sprintf("%s/v1/complete", baseURL)
|
||||
}
|
||||
case APITypeBaidu:
|
||||
switch textRequest.Model {
|
||||
case "ERNIE-Bot":
|
||||
fullRequestURL = "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/completions"
|
||||
case "ERNIE-Bot-turbo":
|
||||
fullRequestURL = "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/eb-instant"
|
||||
case "ERNIE-Bot-4":
|
||||
fullRequestURL = "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/completions_pro"
|
||||
case "BLOOMZ-7B":
|
||||
fullRequestURL = "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/bloomz_7b1"
|
||||
case "Embedding-V1":
|
||||
fullRequestURL = "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/embeddings/embedding-v1"
|
||||
}
|
||||
apiKey := c.Request.Header.Get("Authorization")
|
||||
apiKey = strings.TrimPrefix(apiKey, "Bearer ")
|
||||
var err error
|
||||
if apiKey, err = getBaiduAccessToken(apiKey); err != nil {
|
||||
return errorWrapper(err, "invalid_baidu_config", http.StatusInternalServerError)
|
||||
}
|
||||
fullRequestURL += "?access_token=" + apiKey
|
||||
case APITypePaLM:
|
||||
fullRequestURL = "https://generativelanguage.googleapis.com/v1beta2/models/chat-bison-001:generateMessage"
|
||||
if baseURL != "" {
|
||||
fullRequestURL = fmt.Sprintf("%s/v1beta2/models/chat-bison-001:generateMessage", baseURL)
|
||||
}
|
||||
case APITypeGemini:
|
||||
requestBaseURL := "https://generativelanguage.googleapis.com"
|
||||
if baseURL != "" {
|
||||
requestBaseURL = baseURL
|
||||
}
|
||||
version := "v1"
|
||||
if c.GetString("api_version") != "" {
|
||||
version = c.GetString("api_version")
|
||||
}
|
||||
action := "generateContent"
|
||||
if textRequest.Stream {
|
||||
action = "streamGenerateContent"
|
||||
}
|
||||
fullRequestURL = fmt.Sprintf("%s/%s/models/%s:%s", requestBaseURL, version, textRequest.Model, action)
|
||||
case APITypeZhipu:
|
||||
method := "invoke"
|
||||
if textRequest.Stream {
|
||||
method = "sse-invoke"
|
||||
}
|
||||
fullRequestURL = fmt.Sprintf("https://open.bigmodel.cn/api/paas/v3/model-api/%s/%s", textRequest.Model, method)
|
||||
case APITypeAli:
|
||||
fullRequestURL = "https://dashscope.aliyuncs.com/api/v1/services/aigc/text-generation/generation"
|
||||
if relayMode == RelayModeEmbeddings {
|
||||
fullRequestURL = "https://dashscope.aliyuncs.com/api/v1/services/embeddings/text-embedding/text-embedding"
|
||||
}
|
||||
case APITypeTencent:
|
||||
fullRequestURL = "https://hunyuan.cloud.tencent.com/hyllm/v1/chat/completions"
|
||||
case APITypeAIProxyLibrary:
|
||||
fullRequestURL = fmt.Sprintf("%s/api/library/ask", baseURL)
|
||||
}
|
||||
var promptTokens int
|
||||
var completionTokens int
|
||||
switch relayMode {
|
||||
case RelayModeChatCompletions:
|
||||
promptTokens = countTokenMessages(textRequest.Messages, textRequest.Model)
|
||||
case RelayModeCompletions:
|
||||
promptTokens = countTokenInput(textRequest.Prompt, textRequest.Model)
|
||||
case RelayModeModerations:
|
||||
promptTokens = countTokenInput(textRequest.Input, textRequest.Model)
|
||||
}
|
||||
preConsumedTokens := common.PreConsumedQuota
|
||||
if textRequest.MaxTokens != 0 {
|
||||
preConsumedTokens = promptTokens + textRequest.MaxTokens
|
||||
}
|
||||
modelRatio := common.GetModelRatio(textRequest.Model)
|
||||
groupRatio := common.GetGroupRatio(group)
|
||||
ratio := modelRatio * groupRatio
|
||||
preConsumedQuota := int(float64(preConsumedTokens) * ratio)
|
||||
userQuota, err := model.CacheGetUserQuota(userId)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "get_user_quota_failed", http.StatusInternalServerError)
|
||||
}
|
||||
if userQuota-preConsumedQuota < 0 {
|
||||
return errorWrapper(errors.New("user quota is not enough"), "insufficient_user_quota", http.StatusForbidden)
|
||||
}
|
||||
err = model.CacheDecreaseUserQuota(userId, preConsumedQuota)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "decrease_user_quota_failed", http.StatusInternalServerError)
|
||||
}
|
||||
if userQuota > 100*preConsumedQuota {
|
||||
// in this case, we do not pre-consume quota
|
||||
// because the user has enough quota
|
||||
preConsumedQuota = 0
|
||||
common.LogInfo(c.Request.Context(), fmt.Sprintf("user %d has enough quota %d, trusted and no need to pre-consume", userId, userQuota))
|
||||
}
|
||||
if preConsumedQuota > 0 {
|
||||
err := model.PreConsumeTokenQuota(tokenId, preConsumedQuota)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "pre_consume_token_quota_failed", http.StatusForbidden)
|
||||
}
|
||||
}
|
||||
var requestBody io.Reader
|
||||
if isModelMapped {
|
||||
jsonStr, err := json.Marshal(textRequest)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "marshal_text_request_failed", http.StatusInternalServerError)
|
||||
}
|
||||
requestBody = bytes.NewBuffer(jsonStr)
|
||||
} else {
|
||||
requestBody = c.Request.Body
|
||||
}
|
||||
switch apiType {
|
||||
case APITypeClaude:
|
||||
claudeRequest := requestOpenAI2Claude(textRequest)
|
||||
jsonStr, err := json.Marshal(claudeRequest)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "marshal_text_request_failed", http.StatusInternalServerError)
|
||||
}
|
||||
requestBody = bytes.NewBuffer(jsonStr)
|
||||
case APITypeBaidu:
|
||||
var jsonData []byte
|
||||
var err error
|
||||
switch relayMode {
|
||||
case RelayModeEmbeddings:
|
||||
baiduEmbeddingRequest := embeddingRequestOpenAI2Baidu(textRequest)
|
||||
jsonData, err = json.Marshal(baiduEmbeddingRequest)
|
||||
default:
|
||||
baiduRequest := requestOpenAI2Baidu(textRequest)
|
||||
jsonData, err = json.Marshal(baiduRequest)
|
||||
}
|
||||
if err != nil {
|
||||
return errorWrapper(err, "marshal_text_request_failed", http.StatusInternalServerError)
|
||||
}
|
||||
requestBody = bytes.NewBuffer(jsonData)
|
||||
case APITypePaLM:
|
||||
palmRequest := requestOpenAI2PaLM(textRequest)
|
||||
jsonStr, err := json.Marshal(palmRequest)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "marshal_text_request_failed", http.StatusInternalServerError)
|
||||
}
|
||||
requestBody = bytes.NewBuffer(jsonStr)
|
||||
case APITypeGemini:
|
||||
geminiChatRequest := requestOpenAI2Gemini(textRequest)
|
||||
jsonStr, err := json.Marshal(geminiChatRequest)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "marshal_text_request_failed", http.StatusInternalServerError)
|
||||
}
|
||||
requestBody = bytes.NewBuffer(jsonStr)
|
||||
case APITypeZhipu:
|
||||
zhipuRequest := requestOpenAI2Zhipu(textRequest)
|
||||
jsonStr, err := json.Marshal(zhipuRequest)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "marshal_text_request_failed", http.StatusInternalServerError)
|
||||
}
|
||||
requestBody = bytes.NewBuffer(jsonStr)
|
||||
case APITypeAli:
|
||||
var jsonStr []byte
|
||||
var err error
|
||||
switch relayMode {
|
||||
case RelayModeEmbeddings:
|
||||
aliEmbeddingRequest := embeddingRequestOpenAI2Ali(textRequest)
|
||||
jsonStr, err = json.Marshal(aliEmbeddingRequest)
|
||||
default:
|
||||
aliRequest := requestOpenAI2Ali(textRequest)
|
||||
jsonStr, err = json.Marshal(aliRequest)
|
||||
}
|
||||
if err != nil {
|
||||
return errorWrapper(err, "marshal_text_request_failed", http.StatusInternalServerError)
|
||||
}
|
||||
requestBody = bytes.NewBuffer(jsonStr)
|
||||
case APITypeTencent:
|
||||
apiKey := c.Request.Header.Get("Authorization")
|
||||
apiKey = strings.TrimPrefix(apiKey, "Bearer ")
|
||||
appId, secretId, secretKey, err := parseTencentConfig(apiKey)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "invalid_tencent_config", http.StatusInternalServerError)
|
||||
}
|
||||
tencentRequest := requestOpenAI2Tencent(textRequest)
|
||||
tencentRequest.AppId = appId
|
||||
tencentRequest.SecretId = secretId
|
||||
jsonStr, err := json.Marshal(tencentRequest)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "marshal_text_request_failed", http.StatusInternalServerError)
|
||||
}
|
||||
sign := getTencentSign(*tencentRequest, secretKey)
|
||||
c.Request.Header.Set("Authorization", sign)
|
||||
requestBody = bytes.NewBuffer(jsonStr)
|
||||
case APITypeAIProxyLibrary:
|
||||
aiProxyLibraryRequest := requestOpenAI2AIProxyLibrary(textRequest)
|
||||
aiProxyLibraryRequest.LibraryId = c.GetString("library_id")
|
||||
jsonStr, err := json.Marshal(aiProxyLibraryRequest)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "marshal_text_request_failed", http.StatusInternalServerError)
|
||||
}
|
||||
requestBody = bytes.NewBuffer(jsonStr)
|
||||
}
|
||||
|
||||
var req *http.Request
|
||||
var resp *http.Response
|
||||
isStream := textRequest.Stream
|
||||
|
||||
if apiType != APITypeXunfei { // cause xunfei use websocket
|
||||
req, err = http.NewRequest(c.Request.Method, fullRequestURL, requestBody)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "new_request_failed", http.StatusInternalServerError)
|
||||
}
|
||||
apiKey := c.Request.Header.Get("Authorization")
|
||||
apiKey = strings.TrimPrefix(apiKey, "Bearer ")
|
||||
switch apiType {
|
||||
case APITypeOpenAI:
|
||||
if channelType == common.ChannelTypeAzure {
|
||||
req.Header.Set("api-key", apiKey)
|
||||
} else {
|
||||
req.Header.Set("Authorization", c.Request.Header.Get("Authorization"))
|
||||
if channelType == common.ChannelTypeOpenRouter {
|
||||
req.Header.Set("HTTP-Referer", "https://github.com/songquanpeng/one-api")
|
||||
req.Header.Set("X-Title", "One API")
|
||||
}
|
||||
}
|
||||
case APITypeClaude:
|
||||
req.Header.Set("x-api-key", apiKey)
|
||||
anthropicVersion := c.Request.Header.Get("anthropic-version")
|
||||
if anthropicVersion == "" {
|
||||
anthropicVersion = "2023-06-01"
|
||||
}
|
||||
req.Header.Set("anthropic-version", anthropicVersion)
|
||||
case APITypeZhipu:
|
||||
token := getZhipuToken(apiKey)
|
||||
req.Header.Set("Authorization", token)
|
||||
case APITypeAli:
|
||||
req.Header.Set("Authorization", "Bearer "+apiKey)
|
||||
if textRequest.Stream {
|
||||
req.Header.Set("X-DashScope-SSE", "enable")
|
||||
}
|
||||
if c.GetString("plugin") != "" {
|
||||
req.Header.Set("X-DashScope-Plugin", c.GetString("plugin"))
|
||||
}
|
||||
case APITypeTencent:
|
||||
req.Header.Set("Authorization", apiKey)
|
||||
case APITypePaLM:
|
||||
req.Header.Set("x-goog-api-key", apiKey)
|
||||
case APITypeGemini:
|
||||
req.Header.Set("x-goog-api-key", apiKey)
|
||||
default:
|
||||
req.Header.Set("Authorization", "Bearer "+apiKey)
|
||||
}
|
||||
req.Header.Set("Content-Type", c.Request.Header.Get("Content-Type"))
|
||||
req.Header.Set("Accept", c.Request.Header.Get("Accept"))
|
||||
if isStream && c.Request.Header.Get("Accept") == "" {
|
||||
req.Header.Set("Accept", "text/event-stream")
|
||||
}
|
||||
//req.Header.Set("Connection", c.Request.Header.Get("Connection"))
|
||||
resp, err = httpClient.Do(req)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "do_request_failed", http.StatusInternalServerError)
|
||||
}
|
||||
err = req.Body.Close()
|
||||
if err != nil {
|
||||
return errorWrapper(err, "close_request_body_failed", http.StatusInternalServerError)
|
||||
}
|
||||
err = c.Request.Body.Close()
|
||||
if err != nil {
|
||||
return errorWrapper(err, "close_request_body_failed", http.StatusInternalServerError)
|
||||
}
|
||||
isStream = isStream || strings.HasPrefix(resp.Header.Get("Content-Type"), "text/event-stream")
|
||||
|
||||
if resp.StatusCode != http.StatusOK {
|
||||
if preConsumedQuota != 0 {
|
||||
go func(ctx context.Context) {
|
||||
// return pre-consumed quota
|
||||
err := model.PostConsumeTokenQuota(tokenId, -preConsumedQuota)
|
||||
if err != nil {
|
||||
common.LogError(ctx, "error return pre-consumed quota: "+err.Error())
|
||||
}
|
||||
}(c.Request.Context())
|
||||
}
|
||||
return relayErrorHandler(resp)
|
||||
}
|
||||
}
|
||||
|
||||
var textResponse TextResponse
|
||||
tokenName := c.GetString("token_name")
|
||||
|
||||
defer func(ctx context.Context) {
|
||||
// c.Writer.Flush()
|
||||
go func() {
|
||||
quota := 0
|
||||
completionRatio := common.GetCompletionRatio(textRequest.Model)
|
||||
promptTokens = textResponse.Usage.PromptTokens
|
||||
completionTokens = textResponse.Usage.CompletionTokens
|
||||
quota = int(math.Ceil((float64(promptTokens) + float64(completionTokens)*completionRatio) * ratio))
|
||||
if ratio != 0 && quota <= 0 {
|
||||
quota = 1
|
||||
}
|
||||
totalTokens := promptTokens + completionTokens
|
||||
if totalTokens == 0 {
|
||||
// in this case, must be some error happened
|
||||
// we cannot just return, because we may have to return the pre-consumed quota
|
||||
quota = 0
|
||||
}
|
||||
quotaDelta := quota - preConsumedQuota
|
||||
err := model.PostConsumeTokenQuota(tokenId, quotaDelta)
|
||||
if err != nil {
|
||||
common.LogError(ctx, "error consuming token remain quota: "+err.Error())
|
||||
}
|
||||
err = model.CacheUpdateUserQuota(userId)
|
||||
if err != nil {
|
||||
common.LogError(ctx, "error update user quota cache: "+err.Error())
|
||||
}
|
||||
if quota != 0 {
|
||||
logContent := fmt.Sprintf("模型倍率 %.2f，分组倍率 %.2f", modelRatio, groupRatio)
|
||||
model.RecordConsumeLog(ctx, userId, channelId, promptTokens, completionTokens, textRequest.Model, tokenName, quota, logContent)
|
||||
model.UpdateUserUsedQuotaAndRequestCount(userId, quota)
|
||||
model.UpdateChannelUsedQuota(channelId, quota)
|
||||
}
|
||||
|
||||
}()
|
||||
}(c.Request.Context())
|
||||
switch apiType {
|
||||
case APITypeOpenAI:
|
||||
if isStream {
|
||||
err, responseText := openaiStreamHandler(c, resp, relayMode)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
textResponse.Usage.PromptTokens = promptTokens
|
||||
textResponse.Usage.CompletionTokens = countTokenText(responseText, textRequest.Model)
|
||||
return nil
|
||||
} else {
|
||||
err, usage := openaiHandler(c, resp, promptTokens, textRequest.Model)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
if usage != nil {
|
||||
textResponse.Usage = *usage
|
||||
}
|
||||
return nil
|
||||
}
|
||||
case APITypeClaude:
|
||||
if isStream {
|
||||
err, responseText := claudeStreamHandler(c, resp)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
textResponse.Usage.PromptTokens = promptTokens
|
||||
textResponse.Usage.CompletionTokens = countTokenText(responseText, textRequest.Model)
|
||||
return nil
|
||||
} else {
|
||||
err, usage := claudeHandler(c, resp, promptTokens, textRequest.Model)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
if usage != nil {
|
||||
textResponse.Usage = *usage
|
||||
}
|
||||
return nil
|
||||
}
|
||||
case APITypeBaidu:
|
||||
if isStream {
|
||||
err, usage := baiduStreamHandler(c, resp)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
if usage != nil {
|
||||
textResponse.Usage = *usage
|
||||
}
|
||||
return nil
|
||||
} else {
|
||||
var err *OpenAIErrorWithStatusCode
|
||||
var usage *Usage
|
||||
switch relayMode {
|
||||
case RelayModeEmbeddings:
|
||||
err, usage = baiduEmbeddingHandler(c, resp)
|
||||
default:
|
||||
err, usage = baiduHandler(c, resp)
|
||||
}
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
if usage != nil {
|
||||
textResponse.Usage = *usage
|
||||
}
|
||||
return nil
|
||||
}
|
||||
case APITypePaLM:
|
||||
if textRequest.Stream { // PaLM2 API does not support stream
|
||||
err, responseText := palmStreamHandler(c, resp)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
textResponse.Usage.PromptTokens = promptTokens
|
||||
textResponse.Usage.CompletionTokens = countTokenText(responseText, textRequest.Model)
|
||||
return nil
|
||||
} else {
|
||||
err, usage := palmHandler(c, resp, promptTokens, textRequest.Model)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
if usage != nil {
|
||||
textResponse.Usage = *usage
|
||||
}
|
||||
return nil
|
||||
}
|
||||
case APITypeGemini:
|
||||
if textRequest.Stream {
|
||||
err, responseText := geminiChatStreamHandler(c, resp)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
textResponse.Usage.PromptTokens = promptTokens
|
||||
textResponse.Usage.CompletionTokens = countTokenText(responseText, textRequest.Model)
|
||||
return nil
|
||||
} else {
|
||||
err, usage := geminiChatHandler(c, resp, promptTokens, textRequest.Model)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
if usage != nil {
|
||||
textResponse.Usage = *usage
|
||||
}
|
||||
return nil
|
||||
}
|
||||
case APITypeZhipu:
|
||||
if isStream {
|
||||
err, usage := zhipuStreamHandler(c, resp)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
if usage != nil {
|
||||
textResponse.Usage = *usage
|
||||
}
|
||||
// zhipu's API does not return prompt tokens & completion tokens
|
||||
textResponse.Usage.PromptTokens = textResponse.Usage.TotalTokens
|
||||
return nil
|
||||
} else {
|
||||
err, usage := zhipuHandler(c, resp)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
if usage != nil {
|
||||
textResponse.Usage = *usage
|
||||
}
|
||||
// zhipu's API does not return prompt tokens & completion tokens
|
||||
textResponse.Usage.PromptTokens = textResponse.Usage.TotalTokens
|
||||
return nil
|
||||
}
|
||||
case APITypeAli:
|
||||
if isStream {
|
||||
err, usage := aliStreamHandler(c, resp)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
if usage != nil {
|
||||
textResponse.Usage = *usage
|
||||
}
|
||||
return nil
|
||||
} else {
|
||||
var err *OpenAIErrorWithStatusCode
|
||||
var usage *Usage
|
||||
switch relayMode {
|
||||
case RelayModeEmbeddings:
|
||||
err, usage = aliEmbeddingHandler(c, resp)
|
||||
default:
|
||||
err, usage = aliHandler(c, resp)
|
||||
}
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
if usage != nil {
|
||||
textResponse.Usage = *usage
|
||||
}
|
||||
return nil
|
||||
}
|
||||
case APITypeXunfei:
|
||||
auth := c.Request.Header.Get("Authorization")
|
||||
auth = strings.TrimPrefix(auth, "Bearer ")
|
||||
splits := strings.Split(auth, "|")
|
||||
if len(splits) != 3 {
|
||||
return errorWrapper(errors.New("invalid auth"), "invalid_auth", http.StatusBadRequest)
|
||||
}
|
||||
var err *OpenAIErrorWithStatusCode
|
||||
var usage *Usage
|
||||
if isStream {
|
||||
err, usage = xunfeiStreamHandler(c, textRequest, splits[0], splits[1], splits[2])
|
||||
} else {
|
||||
err, usage = xunfeiHandler(c, textRequest, splits[0], splits[1], splits[2])
|
||||
}
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
if usage != nil {
|
||||
textResponse.Usage = *usage
|
||||
}
|
||||
return nil
|
||||
case APITypeAIProxyLibrary:
|
||||
if isStream {
|
||||
err, usage := aiProxyLibraryStreamHandler(c, resp)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
if usage != nil {
|
||||
textResponse.Usage = *usage
|
||||
}
|
||||
return nil
|
||||
} else {
|
||||
err, usage := aiProxyLibraryHandler(c, resp)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
if usage != nil {
|
||||
textResponse.Usage = *usage
|
||||
}
|
||||
return nil
|
||||
}
|
||||
case APITypeTencent:
|
||||
if isStream {
|
||||
err, responseText := tencentStreamHandler(c, resp)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
textResponse.Usage.PromptTokens = promptTokens
|
||||
textResponse.Usage.CompletionTokens = countTokenText(responseText, textRequest.Model)
|
||||
return nil
|
||||
} else {
|
||||
err, usage := tencentHandler(c, resp)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
if usage != nil {
|
||||
textResponse.Usage = *usage
|
||||
}
|
||||
return nil
|
||||
}
|
||||
default:
|
||||
return errorWrapper(errors.New("unknown api type"), "unknown_api_type", http.StatusInternalServerError)
|
||||
}
|
||||
}
|
||||
@@ -1,385 +0,0 @@
|
||||
package controller
|
||||
|
||||
import (
|
||||
"context"
|
||||
"encoding/json"
|
||||
"errors"
|
||||
"fmt"
|
||||
"io"
|
||||
"math"
|
||||
"net/http"
|
||||
"one-api/common"
|
||||
"one-api/common/image"
|
||||
"one-api/model"
|
||||
"strconv"
|
||||
"strings"
|
||||
|
||||
"github.com/gin-gonic/gin"
|
||||
"github.com/pkoukk/tiktoken-go"
|
||||
)
|
||||
|
||||
var stopFinishReason = "stop"
|
||||
|
||||
// tokenEncoderMap won't grow after initialization
|
||||
var tokenEncoderMap = map[string]*tiktoken.Tiktoken{}
|
||||
var defaultTokenEncoder *tiktoken.Tiktoken
|
||||
|
||||
func InitTokenEncoders() {
|
||||
common.SysLog("initializing token encoders")
|
||||
gpt35TokenEncoder, err := tiktoken.EncodingForModel("gpt-3.5-turbo")
|
||||
if err != nil {
|
||||
common.FatalLog(fmt.Sprintf("failed to get gpt-3.5-turbo token encoder: %s", err.Error()))
|
||||
}
|
||||
defaultTokenEncoder = gpt35TokenEncoder
|
||||
gpt4TokenEncoder, err := tiktoken.EncodingForModel("gpt-4")
|
||||
if err != nil {
|
||||
common.FatalLog(fmt.Sprintf("failed to get gpt-4 token encoder: %s", err.Error()))
|
||||
}
|
||||
for model, _ := range common.ModelRatio {
|
||||
if strings.HasPrefix(model, "gpt-3.5") {
|
||||
tokenEncoderMap[model] = gpt35TokenEncoder
|
||||
} else if strings.HasPrefix(model, "gpt-4") {
|
||||
tokenEncoderMap[model] = gpt4TokenEncoder
|
||||
} else {
|
||||
tokenEncoderMap[model] = nil
|
||||
}
|
||||
}
|
||||
common.SysLog("token encoders initialized")
|
||||
}
|
||||
|
||||
func getTokenEncoder(model string) *tiktoken.Tiktoken {
|
||||
tokenEncoder, ok := tokenEncoderMap[model]
|
||||
if ok && tokenEncoder != nil {
|
||||
return tokenEncoder
|
||||
}
|
||||
if ok {
|
||||
tokenEncoder, err := tiktoken.EncodingForModel(model)
|
||||
if err != nil {
|
||||
common.SysError(fmt.Sprintf("failed to get token encoder for model %s: %s, using encoder for gpt-3.5-turbo", model, err.Error()))
|
||||
tokenEncoder = defaultTokenEncoder
|
||||
}
|
||||
tokenEncoderMap[model] = tokenEncoder
|
||||
return tokenEncoder
|
||||
}
|
||||
return defaultTokenEncoder
|
||||
}
|
||||
|
||||
func getTokenNum(tokenEncoder *tiktoken.Tiktoken, text string) int {
|
||||
if common.ApproximateTokenEnabled {
|
||||
return int(float64(len(text)) * 0.38)
|
||||
}
|
||||
return len(tokenEncoder.Encode(text, nil, nil))
|
||||
}
|
||||
|
||||
func countTokenMessages(messages []Message, model string) int {
|
||||
tokenEncoder := getTokenEncoder(model)
|
||||
// Reference:
|
||||
// https://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb
|
||||
// https://github.com/pkoukk/tiktoken-go/issues/6
|
||||
//
|
||||
// Every message follows <|start|>{role/name}\n{content}<|end|>\n
|
||||
var tokensPerMessage int
|
||||
var tokensPerName int
|
||||
if model == "gpt-3.5-turbo-0301" {
|
||||
tokensPerMessage = 4
|
||||
tokensPerName = -1 // If there's a name, the role is omitted
|
||||
} else {
|
||||
tokensPerMessage = 3
|
||||
tokensPerName = 1
|
||||
}
|
||||
tokenNum := 0
|
||||
for _, message := range messages {
|
||||
tokenNum += tokensPerMessage
|
||||
switch v := message.Content.(type) {
|
||||
case string:
|
||||
tokenNum += getTokenNum(tokenEncoder, v)
|
||||
case []any:
|
||||
for _, it := range v {
|
||||
m := it.(map[string]any)
|
||||
switch m["type"] {
|
||||
case "text":
|
||||
tokenNum += getTokenNum(tokenEncoder, m["text"].(string))
|
||||
case "image_url":
|
||||
imageUrl, ok := m["image_url"].(map[string]any)
|
||||
if ok {
|
||||
url := imageUrl["url"].(string)
|
||||
detail := ""
|
||||
if imageUrl["detail"] != nil {
|
||||
detail = imageUrl["detail"].(string)
|
||||
}
|
||||
imageTokens, err := countImageTokens(url, detail)
|
||||
if err != nil {
|
||||
common.SysError("error counting image tokens: " + err.Error())
|
||||
} else {
|
||||
tokenNum += imageTokens
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
tokenNum += getTokenNum(tokenEncoder, message.Role)
|
||||
if message.Name != nil {
|
||||
tokenNum += tokensPerName
|
||||
tokenNum += getTokenNum(tokenEncoder, *message.Name)
|
||||
}
|
||||
}
|
||||
tokenNum += 3 // Every reply is primed with <|start|>assistant<|message|>
|
||||
return tokenNum
|
||||
}
|
||||
|
||||
const (
|
||||
lowDetailCost = 85
|
||||
highDetailCostPerTile = 170
|
||||
additionalCost = 85
|
||||
)
|
||||
|
||||
// https://platform.openai.com/docs/guides/vision/calculating-costs
|
||||
// https://github.com/openai/openai-cookbook/blob/05e3f9be4c7a2ae7ecf029a7c32065b024730ebe/examples/How_to_count_tokens_with_tiktoken.ipynb
|
||||
func countImageTokens(url string, detail string) (_ int, err error) {
|
||||
var fetchSize = true
|
||||
var width, height int
|
||||
// Reference: https://platform.openai.com/docs/guides/vision/low-or-high-fidelity-image-understanding
|
||||
// detail == "auto" is undocumented on how it works, it just said the model will use the auto setting which will look at the image input size and decide if it should use the low or high setting.
|
||||
// According to the official guide, "low" disable the high-res model,
|
||||
// and only receive low-res 512px x 512px version of the image, indicating
|
||||
// that image is treated as low-res when size is smaller than 512px x 512px,
|
||||
// then we can assume that image size larger than 512px x 512px is treated
|
||||
// as high-res. Then we have the following logic:
|
||||
// if detail == "" || detail == "auto" {
|
||||
// width, height, err = image.GetImageSize(url)
|
||||
// if err != nil {
|
||||
// return 0, err
|
||||
// }
|
||||
// fetchSize = false
|
||||
// // not sure if this is correct
|
||||
// if width > 512 || height > 512 {
|
||||
// detail = "high"
|
||||
// } else {
|
||||
// detail = "low"
|
||||
// }
|
||||
// }
|
||||
|
||||
// However, in my test, it seems to be always the same as "high".
|
||||
// The following image, which is 125x50, is still treated as high-res, taken
|
||||
// 255 tokens in the response of non-stream chat completion api.
|
||||
// https://upload.wikimedia.org/wikipedia/commons/1/10/18_Infantry_Division_Messina.jpg
|
||||
if detail == "" || detail == "auto" {
|
||||
// assume by test, not sure if this is correct
|
||||
detail = "high"
|
||||
}
|
||||
switch detail {
|
||||
case "low":
|
||||
return lowDetailCost, nil
|
||||
case "high":
|
||||
if fetchSize {
|
||||
width, height, err = image.GetImageSize(url)
|
||||
if err != nil {
|
||||
return 0, err
|
||||
}
|
||||
}
|
||||
if width > 2048 || height > 2048 { // max(width, height) > 2048
|
||||
ratio := float64(2048) / math.Max(float64(width), float64(height))
|
||||
width = int(float64(width) * ratio)
|
||||
height = int(float64(height) * ratio)
|
||||
}
|
||||
if width > 768 && height > 768 { // min(width, height) > 768
|
||||
ratio := float64(768) / math.Min(float64(width), float64(height))
|
||||
width = int(float64(width) * ratio)
|
||||
height = int(float64(height) * ratio)
|
||||
}
|
||||
numSquares := int(math.Ceil(float64(width)/512) * math.Ceil(float64(height)/512))
|
||||
result := numSquares*highDetailCostPerTile + additionalCost
|
||||
return result, nil
|
||||
default:
|
||||
return 0, errors.New("invalid detail option")
|
||||
}
|
||||
}
|
||||
|
||||
func countTokenInput(input any, model string) int {
|
||||
switch v := input.(type) {
|
||||
case string:
|
||||
return countTokenText(v, model)
|
||||
case []string:
|
||||
text := ""
|
||||
for _, s := range v {
|
||||
text += s
|
||||
}
|
||||
return countTokenText(text, model)
|
||||
}
|
||||
return 0
|
||||
}
|
||||
|
||||
func countTokenText(text string, model string) int {
|
||||
tokenEncoder := getTokenEncoder(model)
|
||||
return getTokenNum(tokenEncoder, text)
|
||||
}
|
||||
|
||||
func errorWrapper(err error, code string, statusCode int) *OpenAIErrorWithStatusCode {
|
||||
openAIError := OpenAIError{
|
||||
Message: err.Error(),
|
||||
Type: "one_api_error",
|
||||
Code: code,
|
||||
}
|
||||
return &OpenAIErrorWithStatusCode{
|
||||
OpenAIError: openAIError,
|
||||
StatusCode: statusCode,
|
||||
}
|
||||
}
|
||||
|
||||
func shouldDisableChannel(err *OpenAIError, statusCode int) bool {
|
||||
if !common.AutomaticDisableChannelEnabled {
|
||||
return false
|
||||
}
|
||||
if err == nil {
|
||||
return false
|
||||
}
|
||||
if statusCode == http.StatusUnauthorized {
|
||||
return true
|
||||
}
|
||||
if err.Type == "insufficient_quota" || err.Code == "invalid_api_key" || err.Code == "account_deactivated" {
|
||||
return true
|
||||
}
|
||||
return false
|
||||
}
|
||||
|
||||
func shouldEnableChannel(err error, openAIErr *OpenAIError) bool {
|
||||
if !common.AutomaticEnableChannelEnabled {
|
||||
return false
|
||||
}
|
||||
if err != nil {
|
||||
return false
|
||||
}
|
||||
if openAIErr != nil {
|
||||
return false
|
||||
}
|
||||
return true
|
||||
}
|
||||
|
||||
func setEventStreamHeaders(c *gin.Context) {
|
||||
c.Writer.Header().Set("Content-Type", "text/event-stream")
|
||||
c.Writer.Header().Set("Cache-Control", "no-cache")
|
||||
c.Writer.Header().Set("Connection", "keep-alive")
|
||||
c.Writer.Header().Set("Transfer-Encoding", "chunked")
|
||||
c.Writer.Header().Set("X-Accel-Buffering", "no")
|
||||
}
|
||||
|
||||
type GeneralErrorResponse struct {
|
||||
Error OpenAIError `json:"error"`
|
||||
Message string `json:"message"`
|
||||
Msg string `json:"msg"`
|
||||
Err string `json:"err"`
|
||||
ErrorMsg string `json:"error_msg"`
|
||||
Header struct {
|
||||
Message string `json:"message"`
|
||||
} `json:"header"`
|
||||
Response struct {
|
||||
Error struct {
|
||||
Message string `json:"message"`
|
||||
} `json:"error"`
|
||||
} `json:"response"`
|
||||
}
|
||||
|
||||
func (e GeneralErrorResponse) ToMessage() string {
|
||||
if e.Error.Message != "" {
|
||||
return e.Error.Message
|
||||
}
|
||||
if e.Message != "" {
|
||||
return e.Message
|
||||
}
|
||||
if e.Msg != "" {
|
||||
return e.Msg
|
||||
}
|
||||
if e.Err != "" {
|
||||
return e.Err
|
||||
}
|
||||
if e.ErrorMsg != "" {
|
||||
return e.ErrorMsg
|
||||
}
|
||||
if e.Header.Message != "" {
|
||||
return e.Header.Message
|
||||
}
|
||||
if e.Response.Error.Message != "" {
|
||||
return e.Response.Error.Message
|
||||
}
|
||||
return ""
|
||||
}
|
||||
|
||||
func relayErrorHandler(resp *http.Response) (openAIErrorWithStatusCode *OpenAIErrorWithStatusCode) {
|
||||
openAIErrorWithStatusCode = &OpenAIErrorWithStatusCode{
|
||||
StatusCode: resp.StatusCode,
|
||||
OpenAIError: OpenAIError{
|
||||
Message: "",
|
||||
Type: "upstream_error",
|
||||
Code: "bad_response_status_code",
|
||||
Param: strconv.Itoa(resp.StatusCode),
|
||||
},
|
||||
}
|
||||
responseBody, err := io.ReadAll(resp.Body)
|
||||
if err != nil {
|
||||
return
|
||||
}
|
||||
err = resp.Body.Close()
|
||||
if err != nil {
|
||||
return
|
||||
}
|
||||
var errResponse GeneralErrorResponse
|
||||
err = json.Unmarshal(responseBody, &errResponse)
|
||||
if err != nil {
|
||||
return
|
||||
}
|
||||
if errResponse.Error.Message != "" {
|
||||
// OpenAI format error, so we override the default one
|
||||
openAIErrorWithStatusCode.OpenAIError = errResponse.Error
|
||||
} else {
|
||||
openAIErrorWithStatusCode.OpenAIError.Message = errResponse.ToMessage()
|
||||
}
|
||||
if openAIErrorWithStatusCode.OpenAIError.Message == "" {
|
||||
openAIErrorWithStatusCode.OpenAIError.Message = fmt.Sprintf("bad response status code %d", resp.StatusCode)
|
||||
}
|
||||
return
|
||||
}
|
||||
|
||||
func getFullRequestURL(baseURL string, requestURL string, channelType int) string {
|
||||
fullRequestURL := fmt.Sprintf("%s%s", baseURL, requestURL)
|
||||
|
||||
if strings.HasPrefix(baseURL, "https://gateway.ai.cloudflare.com") {
|
||||
switch channelType {
|
||||
case common.ChannelTypeOpenAI:
|
||||
fullRequestURL = fmt.Sprintf("%s%s", baseURL, strings.TrimPrefix(requestURL, "/v1"))
|
||||
case common.ChannelTypeAzure:
|
||||
fullRequestURL = fmt.Sprintf("%s%s", baseURL, strings.TrimPrefix(requestURL, "/openai/deployments"))
|
||||
}
|
||||
}
|
||||
return fullRequestURL
|
||||
}
|
||||
|
||||
func postConsumeQuota(ctx context.Context, tokenId int, quotaDelta int, totalQuota int, userId int, channelId int, modelRatio float64, groupRatio float64, modelName string, tokenName string) {
|
||||
// quotaDelta is remaining quota to be consumed
|
||||
err := model.PostConsumeTokenQuota(tokenId, quotaDelta)
|
||||
if err != nil {
|
||||
common.SysError("error consuming token remain quota: " + err.Error())
|
||||
}
|
||||
err = model.CacheUpdateUserQuota(userId)
|
||||
if err != nil {
|
||||
common.SysError("error update user quota cache: " + err.Error())
|
||||
}
|
||||
// totalQuota is total quota consumed
|
||||
if totalQuota != 0 {
|
||||
logContent := fmt.Sprintf("模型倍率 %.2f，分组倍率 %.2f", modelRatio, groupRatio)
|
||||
model.RecordConsumeLog(ctx, userId, channelId, totalQuota, 0, modelName, tokenName, totalQuota, logContent)
|
||||
model.UpdateUserUsedQuotaAndRequestCount(userId, totalQuota)
|
||||
model.UpdateChannelUsedQuota(channelId, totalQuota)
|
||||
}
|
||||
if totalQuota <= 0 {
|
||||
common.LogError(ctx, fmt.Sprintf("totalQuota consumed is %d, something is wrong", totalQuota))
|
||||
}
|
||||
}
|
||||
|
||||
func GetAPIVersion(c *gin.Context) string {
|
||||
query := c.Request.URL.Query()
|
||||
apiVersion := query.Get("api-version")
|
||||
if apiVersion == "" {
|
||||
apiVersion = c.GetString("api_version")
|
||||
}
|
||||
return apiVersion
|
||||
}
|
||||
@@ -1,312 +0,0 @@
|
||||
package controller
|
||||
|
||||
import (
|
||||
"crypto/hmac"
|
||||
"crypto/sha256"
|
||||
"encoding/base64"
|
||||
"encoding/json"
|
||||
"fmt"
|
||||
"github.com/gin-gonic/gin"
|
||||
"github.com/gorilla/websocket"
|
||||
"io"
|
||||
"net/http"
|
||||
"net/url"
|
||||
"one-api/common"
|
||||
"strings"
|
||||
"time"
|
||||
)
|
||||
|
||||
// https://console.xfyun.cn/services/cbm
|
||||
// https://www.xfyun.cn/doc/spark/Web.html
|
||||
|
||||
type XunfeiMessage struct {
|
||||
Role string `json:"role"`
|
||||
Content string `json:"content"`
|
||||
}
|
||||
|
||||
type XunfeiChatRequest struct {
|
||||
Header struct {
|
||||
AppId string `json:"app_id"`
|
||||
} `json:"header"`
|
||||
Parameter struct {
|
||||
Chat struct {
|
||||
Domain string `json:"domain,omitempty"`
|
||||
Temperature float64 `json:"temperature,omitempty"`
|
||||
TopK int `json:"top_k,omitempty"`
|
||||
MaxTokens int `json:"max_tokens,omitempty"`
|
||||
Auditing bool `json:"auditing,omitempty"`
|
||||
} `json:"chat"`
|
||||
} `json:"parameter"`
|
||||
Payload struct {
|
||||
Message struct {
|
||||
Text []XunfeiMessage `json:"text"`
|
||||
} `json:"message"`
|
||||
} `json:"payload"`
|
||||
}
|
||||
|
||||
type XunfeiChatResponseTextItem struct {
|
||||
Content string `json:"content"`
|
||||
Role string `json:"role"`
|
||||
Index int `json:"index"`
|
||||
}
|
||||
|
||||
type XunfeiChatResponse struct {
|
||||
Header struct {
|
||||
Code int `json:"code"`
|
||||
Message string `json:"message"`
|
||||
Sid string `json:"sid"`
|
||||
Status int `json:"status"`
|
||||
} `json:"header"`
|
||||
Payload struct {
|
||||
Choices struct {
|
||||
Status int `json:"status"`
|
||||
Seq int `json:"seq"`
|
||||
Text []XunfeiChatResponseTextItem `json:"text"`
|
||||
} `json:"choices"`
|
||||
Usage struct {
|
||||
//Text struct {
|
||||
// QuestionTokens string `json:"question_tokens"`
|
||||
// PromptTokens string `json:"prompt_tokens"`
|
||||
// CompletionTokens string `json:"completion_tokens"`
|
||||
// TotalTokens string `json:"total_tokens"`
|
||||
//} `json:"text"`
|
||||
Text Usage `json:"text"`
|
||||
} `json:"usage"`
|
||||
} `json:"payload"`
|
||||
}
|
||||
|
||||
func requestOpenAI2Xunfei(request GeneralOpenAIRequest, xunfeiAppId string, domain string) *XunfeiChatRequest {
|
||||
messages := make([]XunfeiMessage, 0, len(request.Messages))
|
||||
for _, message := range request.Messages {
|
||||
if message.Role == "system" {
|
||||
messages = append(messages, XunfeiMessage{
|
||||
Role: "user",
|
||||
Content: message.StringContent(),
|
||||
})
|
||||
messages = append(messages, XunfeiMessage{
|
||||
Role: "assistant",
|
||||
Content: "Okay",
|
||||
})
|
||||
} else {
|
||||
messages = append(messages, XunfeiMessage{
|
||||
Role: message.Role,
|
||||
Content: message.StringContent(),
|
||||
})
|
||||
}
|
||||
}
|
||||
xunfeiRequest := XunfeiChatRequest{}
|
||||
xunfeiRequest.Header.AppId = xunfeiAppId
|
||||
xunfeiRequest.Parameter.Chat.Domain = domain
|
||||
xunfeiRequest.Parameter.Chat.Temperature = request.Temperature
|
||||
xunfeiRequest.Parameter.Chat.TopK = request.N
|
||||
xunfeiRequest.Parameter.Chat.MaxTokens = request.MaxTokens
|
||||
xunfeiRequest.Payload.Message.Text = messages
|
||||
return &xunfeiRequest
|
||||
}
|
||||
|
||||
func responseXunfei2OpenAI(response *XunfeiChatResponse) *OpenAITextResponse {
|
||||
if len(response.Payload.Choices.Text) == 0 {
|
||||
response.Payload.Choices.Text = []XunfeiChatResponseTextItem{
|
||||
{
|
||||
Content: "",
|
||||
},
|
||||
}
|
||||
}
|
||||
choice := OpenAITextResponseChoice{
|
||||
Index: 0,
|
||||
Message: Message{
|
||||
Role: "assistant",
|
||||
Content: response.Payload.Choices.Text[0].Content,
|
||||
},
|
||||
FinishReason: stopFinishReason,
|
||||
}
|
||||
fullTextResponse := OpenAITextResponse{
|
||||
Object: "chat.completion",
|
||||
Created: common.GetTimestamp(),
|
||||
Choices: []OpenAITextResponseChoice{choice},
|
||||
Usage: response.Payload.Usage.Text,
|
||||
}
|
||||
return &fullTextResponse
|
||||
}
|
||||
|
||||
func streamResponseXunfei2OpenAI(xunfeiResponse *XunfeiChatResponse) *ChatCompletionsStreamResponse {
|
||||
if len(xunfeiResponse.Payload.Choices.Text) == 0 {
|
||||
xunfeiResponse.Payload.Choices.Text = []XunfeiChatResponseTextItem{
|
||||
{
|
||||
Content: "",
|
||||
},
|
||||
}
|
||||
}
|
||||
var choice ChatCompletionsStreamResponseChoice
|
||||
choice.Delta.Content = xunfeiResponse.Payload.Choices.Text[0].Content
|
||||
if xunfeiResponse.Payload.Choices.Status == 2 {
|
||||
choice.FinishReason = &stopFinishReason
|
||||
}
|
||||
response := ChatCompletionsStreamResponse{
|
||||
Object: "chat.completion.chunk",
|
||||
Created: common.GetTimestamp(),
|
||||
Model: "SparkDesk",
|
||||
Choices: []ChatCompletionsStreamResponseChoice{choice},
|
||||
}
|
||||
return &response
|
||||
}
|
||||
|
||||
func buildXunfeiAuthUrl(hostUrl string, apiKey, apiSecret string) string {
|
||||
HmacWithShaToBase64 := func(algorithm, data, key string) string {
|
||||
mac := hmac.New(sha256.New, []byte(key))
|
||||
mac.Write([]byte(data))
|
||||
encodeData := mac.Sum(nil)
|
||||
return base64.StdEncoding.EncodeToString(encodeData)
|
||||
}
|
||||
ul, err := url.Parse(hostUrl)
|
||||
if err != nil {
|
||||
fmt.Println(err)
|
||||
}
|
||||
date := time.Now().UTC().Format(time.RFC1123)
|
||||
signString := []string{"host: " + ul.Host, "date: " + date, "GET " + ul.Path + " HTTP/1.1"}
|
||||
sign := strings.Join(signString, "\n")
|
||||
sha := HmacWithShaToBase64("hmac-sha256", sign, apiSecret)
|
||||
authUrl := fmt.Sprintf("hmac username=\"%s\", algorithm=\"%s\", headers=\"%s\", signature=\"%s\"", apiKey,
|
||||
"hmac-sha256", "host date request-line", sha)
|
||||
authorization := base64.StdEncoding.EncodeToString([]byte(authUrl))
|
||||
v := url.Values{}
|
||||
v.Add("host", ul.Host)
|
||||
v.Add("date", date)
|
||||
v.Add("authorization", authorization)
|
||||
callUrl := hostUrl + "?" + v.Encode()
|
||||
return callUrl
|
||||
}
|
||||
|
||||
func xunfeiStreamHandler(c *gin.Context, textRequest GeneralOpenAIRequest, appId string, apiSecret string, apiKey string) (*OpenAIErrorWithStatusCode, *Usage) {
|
||||
domain, authUrl := getXunfeiAuthUrl(c, apiKey, apiSecret)
|
||||
dataChan, stopChan, err := xunfeiMakeRequest(textRequest, domain, authUrl, appId)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "make xunfei request err", http.StatusInternalServerError), nil
|
||||
}
|
||||
setEventStreamHeaders(c)
|
||||
var usage Usage
|
||||
c.Stream(func(w io.Writer) bool {
|
||||
select {
|
||||
case xunfeiResponse := <-dataChan:
|
||||
usage.PromptTokens += xunfeiResponse.Payload.Usage.Text.PromptTokens
|
||||
usage.CompletionTokens += xunfeiResponse.Payload.Usage.Text.CompletionTokens
|
||||
usage.TotalTokens += xunfeiResponse.Payload.Usage.Text.TotalTokens
|
||||
response := streamResponseXunfei2OpenAI(&xunfeiResponse)
|
||||
jsonResponse, err := json.Marshal(response)
|
||||
if err != nil {
|
||||
common.SysError("error marshalling stream response: " + err.Error())
|
||||
return true
|
||||
}
|
||||
c.Render(-1, common.CustomEvent{Data: "data: " + string(jsonResponse)})
|
||||
return true
|
||||
case <-stopChan:
|
||||
c.Render(-1, common.CustomEvent{Data: "data: [DONE]"})
|
||||
return false
|
||||
}
|
||||
})
|
||||
return nil, &usage
|
||||
}
|
||||
|
||||
func xunfeiHandler(c *gin.Context, textRequest GeneralOpenAIRequest, appId string, apiSecret string, apiKey string) (*OpenAIErrorWithStatusCode, *Usage) {
|
||||
domain, authUrl := getXunfeiAuthUrl(c, apiKey, apiSecret)
|
||||
dataChan, stopChan, err := xunfeiMakeRequest(textRequest, domain, authUrl, appId)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "make xunfei request err", http.StatusInternalServerError), nil
|
||||
}
|
||||
var usage Usage
|
||||
var content string
|
||||
var xunfeiResponse XunfeiChatResponse
|
||||
stop := false
|
||||
for !stop {
|
||||
select {
|
||||
case xunfeiResponse = <-dataChan:
|
||||
if len(xunfeiResponse.Payload.Choices.Text) == 0 {
|
||||
continue
|
||||
}
|
||||
content += xunfeiResponse.Payload.Choices.Text[0].Content
|
||||
usage.PromptTokens += xunfeiResponse.Payload.Usage.Text.PromptTokens
|
||||
usage.CompletionTokens += xunfeiResponse.Payload.Usage.Text.CompletionTokens
|
||||
usage.TotalTokens += xunfeiResponse.Payload.Usage.Text.TotalTokens
|
||||
case stop = <-stopChan:
|
||||
}
|
||||
}
|
||||
if len(xunfeiResponse.Payload.Choices.Text) == 0 {
|
||||
xunfeiResponse.Payload.Choices.Text = []XunfeiChatResponseTextItem{
|
||||
{
|
||||
Content: "",
|
||||
},
|
||||
}
|
||||
}
|
||||
xunfeiResponse.Payload.Choices.Text[0].Content = content
|
||||
|
||||
response := responseXunfei2OpenAI(&xunfeiResponse)
|
||||
jsonResponse, err := json.Marshal(response)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "marshal_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
c.Writer.Header().Set("Content-Type", "application/json")
|
||||
_, _ = c.Writer.Write(jsonResponse)
|
||||
return nil, &usage
|
||||
}
|
||||
|
||||
func xunfeiMakeRequest(textRequest GeneralOpenAIRequest, domain, authUrl, appId string) (chan XunfeiChatResponse, chan bool, error) {
|
||||
d := websocket.Dialer{
|
||||
HandshakeTimeout: 5 * time.Second,
|
||||
}
|
||||
conn, resp, err := d.Dial(authUrl, nil)
|
||||
if err != nil || resp.StatusCode != 101 {
|
||||
return nil, nil, err
|
||||
}
|
||||
data := requestOpenAI2Xunfei(textRequest, appId, domain)
|
||||
err = conn.WriteJSON(data)
|
||||
if err != nil {
|
||||
return nil, nil, err
|
||||
}
|
||||
|
||||
dataChan := make(chan XunfeiChatResponse)
|
||||
stopChan := make(chan bool)
|
||||
go func() {
|
||||
for {
|
||||
_, msg, err := conn.ReadMessage()
|
||||
if err != nil {
|
||||
common.SysError("error reading stream response: " + err.Error())
|
||||
break
|
||||
}
|
||||
var response XunfeiChatResponse
|
||||
err = json.Unmarshal(msg, &response)
|
||||
if err != nil {
|
||||
common.SysError("error unmarshalling stream response: " + err.Error())
|
||||
break
|
||||
}
|
||||
dataChan <- response
|
||||
if response.Payload.Choices.Status == 2 {
|
||||
err := conn.Close()
|
||||
if err != nil {
|
||||
common.SysError("error closing websocket connection: " + err.Error())
|
||||
}
|
||||
break
|
||||
}
|
||||
}
|
||||
stopChan <- true
|
||||
}()
|
||||
|
||||
return dataChan, stopChan, nil
|
||||
}
|
||||
|
||||
func getXunfeiAuthUrl(c *gin.Context, apiKey string, apiSecret string) (string, string) {
|
||||
query := c.Request.URL.Query()
|
||||
apiVersion := query.Get("api-version")
|
||||
if apiVersion == "" {
|
||||
apiVersion = c.GetString("api_version")
|
||||
}
|
||||
if apiVersion == "" {
|
||||
apiVersion = "v1.1"
|
||||
common.SysLog("api_version not found, use default: " + apiVersion)
|
||||
}
|
||||
domain := "general"
|
||||
if apiVersion != "v1.1" {
|
||||
domain += strings.Split(apiVersion, ".")[0]
|
||||
}
|
||||
authUrl := buildXunfeiAuthUrl(fmt.Sprintf("wss://spark-api.xf-yun.com/%s/chat", apiVersion), apiKey, apiSecret)
|
||||
return domain, authUrl
|
||||
}
|
||||
@@ -1,302 +0,0 @@
|
||||
package controller
|
||||
|
||||
import (
|
||||
"bufio"
|
||||
"encoding/json"
|
||||
"github.com/gin-gonic/gin"
|
||||
"github.com/golang-jwt/jwt"
|
||||
"io"
|
||||
"net/http"
|
||||
"one-api/common"
|
||||
"strings"
|
||||
"sync"
|
||||
"time"
|
||||
)
|
||||
|
||||
// https://open.bigmodel.cn/doc/api#chatglm_std
|
||||
// chatglm_std, chatglm_lite
|
||||
// https://open.bigmodel.cn/api/paas/v3/model-api/chatglm_std/invoke
|
||||
// https://open.bigmodel.cn/api/paas/v3/model-api/chatglm_std/sse-invoke
|
||||
|
||||
type ZhipuMessage struct {
|
||||
Role string `json:"role"`
|
||||
Content string `json:"content"`
|
||||
}
|
||||
|
||||
type ZhipuRequest struct {
|
||||
Prompt []ZhipuMessage `json:"prompt"`
|
||||
Temperature float64 `json:"temperature,omitempty"`
|
||||
TopP float64 `json:"top_p,omitempty"`
|
||||
RequestId string `json:"request_id,omitempty"`
|
||||
Incremental bool `json:"incremental,omitempty"`
|
||||
}
|
||||
|
||||
type ZhipuResponseData struct {
|
||||
TaskId string `json:"task_id"`
|
||||
RequestId string `json:"request_id"`
|
||||
TaskStatus string `json:"task_status"`
|
||||
Choices []ZhipuMessage `json:"choices"`
|
||||
Usage `json:"usage"`
|
||||
}
|
||||
|
||||
type ZhipuResponse struct {
|
||||
Code int `json:"code"`
|
||||
Msg string `json:"msg"`
|
||||
Success bool `json:"success"`
|
||||
Data ZhipuResponseData `json:"data"`
|
||||
}
|
||||
|
||||
type ZhipuStreamMetaResponse struct {
|
||||
RequestId string `json:"request_id"`
|
||||
TaskId string `json:"task_id"`
|
||||
TaskStatus string `json:"task_status"`
|
||||
Usage `json:"usage"`
|
||||
}
|
||||
|
||||
type zhipuTokenData struct {
|
||||
Token string
|
||||
ExpiryTime time.Time
|
||||
}
|
||||
|
||||
var zhipuTokens sync.Map
|
||||
var expSeconds int64 = 24 * 3600
|
||||
|
||||
func getZhipuToken(apikey string) string {
|
||||
data, ok := zhipuTokens.Load(apikey)
|
||||
if ok {
|
||||
tokenData := data.(zhipuTokenData)
|
||||
if time.Now().Before(tokenData.ExpiryTime) {
|
||||
return tokenData.Token
|
||||
}
|
||||
}
|
||||
|
||||
split := strings.Split(apikey, ".")
|
||||
if len(split) != 2 {
|
||||
common.SysError("invalid zhipu key: " + apikey)
|
||||
return ""
|
||||
}
|
||||
|
||||
id := split[0]
|
||||
secret := split[1]
|
||||
|
||||
expMillis := time.Now().Add(time.Duration(expSeconds)*time.Second).UnixNano() / 1e6
|
||||
expiryTime := time.Now().Add(time.Duration(expSeconds) * time.Second)
|
||||
|
||||
timestamp := time.Now().UnixNano() / 1e6
|
||||
|
||||
payload := jwt.MapClaims{
|
||||
"api_key": id,
|
||||
"exp": expMillis,
|
||||
"timestamp": timestamp,
|
||||
}
|
||||
|
||||
token := jwt.NewWithClaims(jwt.SigningMethodHS256, payload)
|
||||
|
||||
token.Header["alg"] = "HS256"
|
||||
token.Header["sign_type"] = "SIGN"
|
||||
|
||||
tokenString, err := token.SignedString([]byte(secret))
|
||||
if err != nil {
|
||||
return ""
|
||||
}
|
||||
|
||||
zhipuTokens.Store(apikey, zhipuTokenData{
|
||||
Token: tokenString,
|
||||
ExpiryTime: expiryTime,
|
||||
})
|
||||
|
||||
return tokenString
|
||||
}
|
||||
|
||||
func requestOpenAI2Zhipu(request GeneralOpenAIRequest) *ZhipuRequest {
|
||||
messages := make([]ZhipuMessage, 0, len(request.Messages))
|
||||
for _, message := range request.Messages {
|
||||
if message.Role == "system" {
|
||||
messages = append(messages, ZhipuMessage{
|
||||
Role: "system",
|
||||
Content: message.StringContent(),
|
||||
})
|
||||
messages = append(messages, ZhipuMessage{
|
||||
Role: "user",
|
||||
Content: "Okay",
|
||||
})
|
||||
} else {
|
||||
messages = append(messages, ZhipuMessage{
|
||||
Role: message.Role,
|
||||
Content: message.StringContent(),
|
||||
})
|
||||
}
|
||||
}
|
||||
return &ZhipuRequest{
|
||||
Prompt: messages,
|
||||
Temperature: request.Temperature,
|
||||
TopP: request.TopP,
|
||||
Incremental: false,
|
||||
}
|
||||
}
|
||||
|
||||
func responseZhipu2OpenAI(response *ZhipuResponse) *OpenAITextResponse {
|
||||
fullTextResponse := OpenAITextResponse{
|
||||
Id: response.Data.TaskId,
|
||||
Object: "chat.completion",
|
||||
Created: common.GetTimestamp(),
|
||||
Choices: make([]OpenAITextResponseChoice, 0, len(response.Data.Choices)),
|
||||
Usage: response.Data.Usage,
|
||||
}
|
||||
for i, choice := range response.Data.Choices {
|
||||
openaiChoice := OpenAITextResponseChoice{
|
||||
Index: i,
|
||||
Message: Message{
|
||||
Role: choice.Role,
|
||||
Content: strings.Trim(choice.Content, "\""),
|
||||
},
|
||||
FinishReason: "",
|
||||
}
|
||||
if i == len(response.Data.Choices)-1 {
|
||||
openaiChoice.FinishReason = "stop"
|
||||
}
|
||||
fullTextResponse.Choices = append(fullTextResponse.Choices, openaiChoice)
|
||||
}
|
||||
return &fullTextResponse
|
||||
}
|
||||
|
||||
func streamResponseZhipu2OpenAI(zhipuResponse string) *ChatCompletionsStreamResponse {
|
||||
var choice ChatCompletionsStreamResponseChoice
|
||||
choice.Delta.Content = zhipuResponse
|
||||
response := ChatCompletionsStreamResponse{
|
||||
Object: "chat.completion.chunk",
|
||||
Created: common.GetTimestamp(),
|
||||
Model: "chatglm",
|
||||
Choices: []ChatCompletionsStreamResponseChoice{choice},
|
||||
}
|
||||
return &response
|
||||
}
|
||||
|
||||
func streamMetaResponseZhipu2OpenAI(zhipuResponse *ZhipuStreamMetaResponse) (*ChatCompletionsStreamResponse, *Usage) {
|
||||
var choice ChatCompletionsStreamResponseChoice
|
||||
choice.Delta.Content = ""
|
||||
choice.FinishReason = &stopFinishReason
|
||||
response := ChatCompletionsStreamResponse{
|
||||
Id: zhipuResponse.RequestId,
|
||||
Object: "chat.completion.chunk",
|
||||
Created: common.GetTimestamp(),
|
||||
Model: "chatglm",
|
||||
Choices: []ChatCompletionsStreamResponseChoice{choice},
|
||||
}
|
||||
return &response, &zhipuResponse.Usage
|
||||
}
|
||||
|
||||
func zhipuStreamHandler(c *gin.Context, resp *http.Response) (*OpenAIErrorWithStatusCode, *Usage) {
|
||||
var usage *Usage
|
||||
scanner := bufio.NewScanner(resp.Body)
|
||||
scanner.Split(func(data []byte, atEOF bool) (advance int, token []byte, err error) {
|
||||
if atEOF && len(data) == 0 {
|
||||
return 0, nil, nil
|
||||
}
|
||||
if i := strings.Index(string(data), "\n\n"); i >= 0 && strings.Index(string(data), ":") >= 0 {
|
||||
return i + 2, data[0:i], nil
|
||||
}
|
||||
if atEOF {
|
||||
return len(data), data, nil
|
||||
}
|
||||
return 0, nil, nil
|
||||
})
|
||||
dataChan := make(chan string)
|
||||
metaChan := make(chan string)
|
||||
stopChan := make(chan bool)
|
||||
go func() {
|
||||
for scanner.Scan() {
|
||||
data := scanner.Text()
|
||||
lines := strings.Split(data, "\n")
|
||||
for i, line := range lines {
|
||||
if len(line) < 5 {
|
||||
continue
|
||||
}
|
||||
if line[:5] == "data:" {
|
||||
dataChan <- line[5:]
|
||||
if i != len(lines)-1 {
|
||||
dataChan <- "\n"
|
||||
}
|
||||
} else if line[:5] == "meta:" {
|
||||
metaChan <- line[5:]
|
||||
}
|
||||
}
|
||||
}
|
||||
stopChan <- true
|
||||
}()
|
||||
setEventStreamHeaders(c)
|
||||
c.Stream(func(w io.Writer) bool {
|
||||
select {
|
||||
case data := <-dataChan:
|
||||
response := streamResponseZhipu2OpenAI(data)
|
||||
jsonResponse, err := json.Marshal(response)
|
||||
if err != nil {
|
||||
common.SysError("error marshalling stream response: " + err.Error())
|
||||
return true
|
||||
}
|
||||
c.Render(-1, common.CustomEvent{Data: "data: " + string(jsonResponse)})
|
||||
return true
|
||||
case data := <-metaChan:
|
||||
var zhipuResponse ZhipuStreamMetaResponse
|
||||
err := json.Unmarshal([]byte(data), &zhipuResponse)
|
||||
if err != nil {
|
||||
common.SysError("error unmarshalling stream response: " + err.Error())
|
||||
return true
|
||||
}
|
||||
response, zhipuUsage := streamMetaResponseZhipu2OpenAI(&zhipuResponse)
|
||||
jsonResponse, err := json.Marshal(response)
|
||||
if err != nil {
|
||||
common.SysError("error marshalling stream response: " + err.Error())
|
||||
return true
|
||||
}
|
||||
usage = zhipuUsage
|
||||
c.Render(-1, common.CustomEvent{Data: "data: " + string(jsonResponse)})
|
||||
return true
|
||||
case <-stopChan:
|
||||
c.Render(-1, common.CustomEvent{Data: "data: [DONE]"})
|
||||
return false
|
||||
}
|
||||
})
|
||||
err := resp.Body.Close()
|
||||
if err != nil {
|
||||
return errorWrapper(err, "close_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
return nil, usage
|
||||
}
|
||||
|
||||
func zhipuHandler(c *gin.Context, resp *http.Response) (*OpenAIErrorWithStatusCode, *Usage) {
|
||||
var zhipuResponse ZhipuResponse
|
||||
responseBody, err := io.ReadAll(resp.Body)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "read_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
err = resp.Body.Close()
|
||||
if err != nil {
|
||||
return errorWrapper(err, "close_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
err = json.Unmarshal(responseBody, &zhipuResponse)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "unmarshal_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
if !zhipuResponse.Success {
|
||||
return &OpenAIErrorWithStatusCode{
|
||||
OpenAIError: OpenAIError{
|
||||
Message: zhipuResponse.Msg,
|
||||
Type: "zhipu_error",
|
||||
Param: "",
|
||||
Code: zhipuResponse.Code,
|
||||
},
|
||||
StatusCode: resp.StatusCode,
|
||||
}, nil
|
||||
}
|
||||
fullTextResponse := responseZhipu2OpenAI(&zhipuResponse)
|
||||
fullTextResponse.Model = "chatglm"
|
||||
jsonResponse, err := json.Marshal(fullTextResponse)
|
||||
if err != nil {
|
||||
return errorWrapper(err, "marshal_response_body_failed", http.StatusInternalServerError), nil
|
||||
}
|
||||
c.Writer.Header().Set("Content-Type", "application/json")
|
||||
c.Writer.WriteHeader(resp.StatusCode)
|
||||
_, err = c.Writer.Write(jsonResponse)
|
||||
return nil, &fullTextResponse.Usage
|
||||
}
|
||||
@@ -4,349 +4,53 @@ import (
|
||||
"fmt"
|
||||
"net/http"
|
||||
"one-api/common"
|
||||
"one-api/relay/channel/openai"
|
||||
"one-api/relay/constant"
|
||||
"one-api/relay/controller"
|
||||
"one-api/relay/util"
|
||||
"strconv"
|
||||
"strings"
|
||||
|
||||
"github.com/gin-gonic/gin"
|
||||
)
|
||||
|
||||
type Message struct {
|
||||
Role string `json:"role"`
|
||||
Content any `json:"content"`
|
||||
Name *string `json:"name,omitempty"`
|
||||
}
|
||||
|
||||
type ImageURL struct {
|
||||
Url string `json:"url,omitempty"`
|
||||
Detail string `json:"detail,omitempty"`
|
||||
}
|
||||
|
||||
type TextContent struct {
|
||||
Type string `json:"type,omitempty"`
|
||||
Text string `json:"text,omitempty"`
|
||||
}
|
||||
|
||||
type ImageContent struct {
|
||||
Type string `json:"type,omitempty"`
|
||||
ImageURL *ImageURL `json:"image_url,omitempty"`
|
||||
}
|
||||
|
||||
const (
|
||||
ContentTypeText = "text"
|
||||
ContentTypeImageURL = "image_url"
|
||||
)
|
||||
|
||||
type OpenAIMessageContent struct {
|
||||
Type string `json:"type,omitempty"`
|
||||
Text string `json:"text"`
|
||||
ImageURL *ImageURL `json:"image_url,omitempty"`
|
||||
}
|
||||
|
||||
func (m Message) IsStringContent() bool {
|
||||
_, ok := m.Content.(string)
|
||||
return ok
|
||||
}
|
||||
|
||||
func (m Message) StringContent() string {
|
||||
content, ok := m.Content.(string)
|
||||
if ok {
|
||||
return content
|
||||
}
|
||||
contentList, ok := m.Content.([]any)
|
||||
if ok {
|
||||
var contentStr string
|
||||
for _, contentItem := range contentList {
|
||||
contentMap, ok := contentItem.(map[string]any)
|
||||
if !ok {
|
||||
continue
|
||||
}
|
||||
if contentMap["type"] == ContentTypeText {
|
||||
if subStr, ok := contentMap["text"].(string); ok {
|
||||
contentStr += subStr
|
||||
}
|
||||
}
|
||||
}
|
||||
return contentStr
|
||||
}
|
||||
return ""
|
||||
}
|
||||
|
||||
func (m Message) ParseContent() []OpenAIMessageContent {
|
||||
var contentList []OpenAIMessageContent
|
||||
content, ok := m.Content.(string)
|
||||
if ok {
|
||||
contentList = append(contentList, OpenAIMessageContent{
|
||||
Type: ContentTypeText,
|
||||
Text: content,
|
||||
})
|
||||
return contentList
|
||||
}
|
||||
anyList, ok := m.Content.([]any)
|
||||
if ok {
|
||||
for _, contentItem := range anyList {
|
||||
contentMap, ok := contentItem.(map[string]any)
|
||||
if !ok {
|
||||
continue
|
||||
}
|
||||
switch contentMap["type"] {
|
||||
case ContentTypeText:
|
||||
if subStr, ok := contentMap["text"].(string); ok {
|
||||
contentList = append(contentList, OpenAIMessageContent{
|
||||
Type: ContentTypeText,
|
||||
Text: subStr,
|
||||
})
|
||||
}
|
||||
case ContentTypeImageURL:
|
||||
if subObj, ok := contentMap["image_url"].(map[string]any); ok {
|
||||
contentList = append(contentList, OpenAIMessageContent{
|
||||
Type: ContentTypeImageURL,
|
||||
ImageURL: &ImageURL{
|
||||
Url: subObj["url"].(string),
|
||||
},
|
||||
})
|
||||
}
|
||||
}
|
||||
}
|
||||
return contentList
|
||||
}
|
||||
return nil
|
||||
}
|
||||
|
||||
const (
|
||||
RelayModeUnknown = iota
|
||||
RelayModeChatCompletions
|
||||
RelayModeCompletions
|
||||
RelayModeEmbeddings
|
||||
RelayModeModerations
|
||||
RelayModeImagesGenerations
|
||||
RelayModeEdits
|
||||
RelayModeAudioSpeech
|
||||
RelayModeAudioTranscription
|
||||
RelayModeAudioTranslation
|
||||
)
|
||||
|
||||
// https://platform.openai.com/docs/api-reference/chat
|
||||
|
||||
type ResponseFormat struct {
|
||||
Type string `json:"type,omitempty"`
|
||||
}
|
||||
|
||||
type GeneralOpenAIRequest struct {
|
||||
Model string `json:"model,omitempty"`
|
||||
Messages []Message `json:"messages,omitempty"`
|
||||
Prompt any `json:"prompt,omitempty"`
|
||||
Stream bool `json:"stream,omitempty"`
|
||||
MaxTokens int `json:"max_tokens,omitempty"`
|
||||
Temperature float64 `json:"temperature,omitempty"`
|
||||
TopP float64 `json:"top_p,omitempty"`
|
||||
N int `json:"n,omitempty"`
|
||||
Input any `json:"input,omitempty"`
|
||||
Instruction string `json:"instruction,omitempty"`
|
||||
Size string `json:"size,omitempty"`
|
||||
Functions any `json:"functions,omitempty"`
|
||||
FrequencyPenalty float64 `json:"frequency_penalty,omitempty"`
|
||||
PresencePenalty float64 `json:"presence_penalty,omitempty"`
|
||||
ResponseFormat *ResponseFormat `json:"response_format,omitempty"`
|
||||
Seed float64 `json:"seed,omitempty"`
|
||||
Tools any `json:"tools,omitempty"`
|
||||
ToolChoice any `json:"tool_choice,omitempty"`
|
||||
User string `json:"user,omitempty"`
|
||||
}
|
||||
|
||||
func (r GeneralOpenAIRequest) ParseInput() []string {
|
||||
if r.Input == nil {
|
||||
return nil
|
||||
}
|
||||
var input []string
|
||||
switch r.Input.(type) {
|
||||
case string:
|
||||
input = []string{r.Input.(string)}
|
||||
case []any:
|
||||
input = make([]string, 0, len(r.Input.([]any)))
|
||||
for _, item := range r.Input.([]any) {
|
||||
if str, ok := item.(string); ok {
|
||||
input = append(input, str)
|
||||
}
|
||||
}
|
||||
}
|
||||
return input
|
||||
}
|
||||
|
||||
type ChatRequest struct {
|
||||
Model string `json:"model"`
|
||||
Messages []Message `json:"messages"`
|
||||
MaxTokens int `json:"max_tokens"`
|
||||
}
|
||||
|
||||
type TextRequest struct {
|
||||
Model string `json:"model"`
|
||||
Messages []Message `json:"messages"`
|
||||
Prompt string `json:"prompt"`
|
||||
MaxTokens int `json:"max_tokens"`
|
||||
//Stream bool `json:"stream"`
|
||||
}
|
||||
|
||||
// ImageRequest docs: https://platform.openai.com/docs/api-reference/images/create
|
||||
type ImageRequest struct {
|
||||
Model string `json:"model"`
|
||||
Prompt string `json:"prompt" binding:"required"`
|
||||
N int `json:"n,omitempty"`
|
||||
Size string `json:"size,omitempty"`
|
||||
Quality string `json:"quality,omitempty"`
|
||||
ResponseFormat string `json:"response_format,omitempty"`
|
||||
Style string `json:"style,omitempty"`
|
||||
User string `json:"user,omitempty"`
|
||||
}
|
||||
|
||||
type WhisperJSONResponse struct {
|
||||
Text string `json:"text,omitempty"`
|
||||
}
|
||||
|
||||
type WhisperVerboseJSONResponse struct {
|
||||
Task string `json:"task,omitempty"`
|
||||
Language string `json:"language,omitempty"`
|
||||
Duration float64 `json:"duration,omitempty"`
|
||||
Text string `json:"text,omitempty"`
|
||||
Segments []Segment `json:"segments,omitempty"`
|
||||
}
|
||||
|
||||
type Segment struct {
|
||||
Id int `json:"id"`
|
||||
Seek int `json:"seek"`
|
||||
Start float64 `json:"start"`
|
||||
End float64 `json:"end"`
|
||||
Text string `json:"text"`
|
||||
Tokens []int `json:"tokens"`
|
||||
Temperature float64 `json:"temperature"`
|
||||
AvgLogprob float64 `json:"avg_logprob"`
|
||||
CompressionRatio float64 `json:"compression_ratio"`
|
||||
NoSpeechProb float64 `json:"no_speech_prob"`
|
||||
}
|
||||
|
||||
type TextToSpeechRequest struct {
|
||||
Model string `json:"model" binding:"required"`
|
||||
Input string `json:"input" binding:"required"`
|
||||
Voice string `json:"voice" binding:"required"`
|
||||
Speed float64 `json:"speed"`
|
||||
ResponseFormat string `json:"response_format"`
|
||||
}
|
||||
|
||||
type Usage struct {
|
||||
PromptTokens int `json:"prompt_tokens"`
|
||||
CompletionTokens int `json:"completion_tokens"`
|
||||
TotalTokens int `json:"total_tokens"`
|
||||
}
|
||||
|
||||
type OpenAIError struct {
|
||||
Message string `json:"message"`
|
||||
Type string `json:"type"`
|
||||
Param string `json:"param"`
|
||||
Code any `json:"code"`
|
||||
}
|
||||
|
||||
type OpenAIErrorWithStatusCode struct {
|
||||
OpenAIError
|
||||
StatusCode int `json:"status_code"`
|
||||
}
|
||||
|
||||
type TextResponse struct {
|
||||
Choices []OpenAITextResponseChoice `json:"choices"`
|
||||
Usage `json:"usage"`
|
||||
Error OpenAIError `json:"error"`
|
||||
}
|
||||
|
||||
type OpenAITextResponseChoice struct {
|
||||
Index int `json:"index"`
|
||||
Message `json:"message"`
|
||||
FinishReason string `json:"finish_reason"`
|
||||
}
|
||||
|
||||
type OpenAITextResponse struct {
|
||||
Id string `json:"id"`
|
||||
Model string `json:"model,omitempty"`
|
||||
Object string `json:"object"`
|
||||
Created int64 `json:"created"`
|
||||
Choices []OpenAITextResponseChoice `json:"choices"`
|
||||
Usage `json:"usage"`
|
||||
}
|
||||
|
||||
type OpenAIEmbeddingResponseItem struct {
|
||||
Object string `json:"object"`
|
||||
Index int `json:"index"`
|
||||
Embedding []float64 `json:"embedding"`
|
||||
}
|
||||
|
||||
type OpenAIEmbeddingResponse struct {
|
||||
Object string `json:"object"`
|
||||
Data []OpenAIEmbeddingResponseItem `json:"data"`
|
||||
Model string `json:"model"`
|
||||
Usage `json:"usage"`
|
||||
}
|
||||
|
||||
type ImageResponse struct {
|
||||
Created int `json:"created"`
|
||||
Data []struct {
|
||||
Url string `json:"url"`
|
||||
}
|
||||
}
|
||||
|
||||
type ChatCompletionsStreamResponseChoice struct {
|
||||
Delta struct {
|
||||
Content string `json:"content"`
|
||||
} `json:"delta"`
|
||||
FinishReason *string `json:"finish_reason,omitempty"`
|
||||
}
|
||||
|
||||
type ChatCompletionsStreamResponse struct {
|
||||
Id string `json:"id"`
|
||||
Object string `json:"object"`
|
||||
Created int64 `json:"created"`
|
||||
Model string `json:"model"`
|
||||
Choices []ChatCompletionsStreamResponseChoice `json:"choices"`
|
||||
}
|
||||
|
||||
type CompletionsStreamResponse struct {
|
||||
Choices []struct {
|
||||
Text string `json:"text"`
|
||||
FinishReason string `json:"finish_reason"`
|
||||
} `json:"choices"`
|
||||
}
|
||||
|
||||
func Relay(c *gin.Context) {
|
||||
relayMode := RelayModeUnknown
|
||||
relayMode := constant.RelayModeUnknown
|
||||
if strings.HasPrefix(c.Request.URL.Path, "/v1/chat/completions") {
|
||||
relayMode = RelayModeChatCompletions
|
||||
relayMode = constant.RelayModeChatCompletions
|
||||
} else if strings.HasPrefix(c.Request.URL.Path, "/v1/completions") {
|
||||
relayMode = RelayModeCompletions
|
||||
relayMode = constant.RelayModeCompletions
|
||||
} else if strings.HasPrefix(c.Request.URL.Path, "/v1/embeddings") {
|
||||
relayMode = RelayModeEmbeddings
|
||||
relayMode = constant.RelayModeEmbeddings
|
||||
} else if strings.HasSuffix(c.Request.URL.Path, "embeddings") {
|
||||
relayMode = RelayModeEmbeddings
|
||||
relayMode = constant.RelayModeEmbeddings
|
||||
} else if strings.HasPrefix(c.Request.URL.Path, "/v1/moderations") {
|
||||
relayMode = RelayModeModerations
|
||||
relayMode = constant.RelayModeModerations
|
||||
} else if strings.HasPrefix(c.Request.URL.Path, "/v1/images/generations") {
|
||||
relayMode = RelayModeImagesGenerations
|
||||
relayMode = constant.RelayModeImagesGenerations
|
||||
} else if strings.HasPrefix(c.Request.URL.Path, "/v1/edits") {
|
||||
relayMode = RelayModeEdits
|
||||
relayMode = constant.RelayModeEdits
|
||||
} else if strings.HasPrefix(c.Request.URL.Path, "/v1/audio/speech") {
|
||||
relayMode = RelayModeAudioSpeech
|
||||
relayMode = constant.RelayModeAudioSpeech
|
||||
} else if strings.HasPrefix(c.Request.URL.Path, "/v1/audio/transcriptions") {
|
||||
relayMode = RelayModeAudioTranscription
|
||||
relayMode = constant.RelayModeAudioTranscription
|
||||
} else if strings.HasPrefix(c.Request.URL.Path, "/v1/audio/translations") {
|
||||
relayMode = RelayModeAudioTranslation
|
||||
relayMode = constant.RelayModeAudioTranslation
|
||||
}
|
||||
var err *OpenAIErrorWithStatusCode
|
||||
var err *openai.ErrorWithStatusCode
|
||||
switch relayMode {
|
||||
case RelayModeImagesGenerations:
|
||||
err = relayImageHelper(c, relayMode)
|
||||
case RelayModeAudioSpeech:
|
||||
case constant.RelayModeImagesGenerations:
|
||||
err = controller.RelayImageHelper(c, relayMode)
|
||||
case constant.RelayModeAudioSpeech:
|
||||
fallthrough
|
||||
case RelayModeAudioTranslation:
|
||||
case constant.RelayModeAudioTranslation:
|
||||
fallthrough
|
||||
case RelayModeAudioTranscription:
|
||||
err = relayAudioHelper(c, relayMode)
|
||||
case constant.RelayModeAudioTranscription:
|
||||
err = controller.RelayAudioHelper(c, relayMode)
|
||||
default:
|
||||
err = relayTextHelper(c, relayMode)
|
||||
err = controller.RelayTextHelper(c, relayMode)
|
||||
}
|
||||
if err != nil {
|
||||
requestId := c.GetString(common.RequestIdKey)
|
||||
@@ -359,17 +63,19 @@ func Relay(c *gin.Context) {
|
||||
c.Redirect(http.StatusTemporaryRedirect, fmt.Sprintf("%s?retry=%d", c.Request.URL.Path, retryTimes-1))
|
||||
} else {
|
||||
if err.StatusCode == http.StatusTooManyRequests {
|
||||
err.OpenAIError.Message = "当前分组上游负载已饱和，请稍后再试"
|
||||
err.Error.Message = "当前分组上游负载已饱和，请稍后再试"
|
||||
}
|
||||
|
||||
err.OpenAIError.Message = common.MessageWithRequestId("Request From https://api.adamchatbot.chat Error", requestId)
|
||||
|
||||
c.JSON(err.StatusCode, gin.H{
|
||||
"error": err.OpenAIError,
|
||||
"error": err.Error,
|
||||
})
|
||||
}
|
||||
channelId := c.GetInt("channel_id")
|
||||
common.LogError(c.Request.Context(), fmt.Sprintf("relay error (channel #%d): %s", channelId, err.Message))
|
||||
// https://platform.openai.com/docs/guides/error-codes/api-errors
|
||||
if shouldDisableChannel(&err.OpenAIError, err.StatusCode) {
|
||||
if util.ShouldDisableChannel(&err.Error, err.StatusCode) {
|
||||
channelId := c.GetInt("channel_id")
|
||||
channelName := c.GetString("channel_name")
|
||||
disableChannel(channelId, channelName, err.Message)
|
||||
@@ -378,7 +84,7 @@ func Relay(c *gin.Context) {
|
||||
}
|
||||
|
||||
func RelayNotImplemented(c *gin.Context) {
|
||||
err := OpenAIError{
|
||||
err := openai.Error{
|
||||
Message: "API not implemented",
|
||||
Type: "one_api_error",
|
||||
Param: "",
|
||||
@@ -390,7 +96,7 @@ func RelayNotImplemented(c *gin.Context) {
|
||||
}
|
||||
|
||||
func RelayNotFound(c *gin.Context) {
|
||||
err := OpenAIError{
|
||||
err := openai.Error{
|
||||
Message: fmt.Sprintf("Invalid URL (%s %s)", c.Request.Method, c.Request.URL.Path),
|
||||
Type: "invalid_request_error",
|
||||
Param: "",
|
||||
|
||||
Reference in New Issue
Block a user