mirror of
https://github.com/songquanpeng/one-api.git
synced 2025-11-12 11:23:42 +08:00
Merge branch 'main' into doubao-cache
This commit is contained in:
@@ -4,6 +4,7 @@ var ModelList = []string{
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"claude-instant-1.2", "claude-2.0", "claude-2.1",
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"claude-3-haiku-20240307",
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"claude-3-5-haiku-20241022",
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"claude-3-5-haiku-latest",
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"claude-3-sonnet-20240229",
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"claude-3-opus-20240229",
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"claude-3-5-sonnet-20240620",
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@@ -2,5 +2,5 @@ package deepseek
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var ModelList = []string{
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"deepseek-chat",
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"deepseek-coder",
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"deepseek-reasoner",
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}
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@@ -7,7 +7,7 @@ import (
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"net/http"
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"github.com/gin-gonic/gin"
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"github.com/songquanpeng/one-api/common/config"
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"github.com/songquanpeng/one-api/common/helper"
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channelhelper "github.com/songquanpeng/one-api/relay/adaptor"
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"github.com/songquanpeng/one-api/relay/adaptor/openai"
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@@ -24,8 +24,13 @@ func (a *Adaptor) Init(meta *meta.Meta) {
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}
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func (a *Adaptor) GetRequestURL(meta *meta.Meta) (string, error) {
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defaultVersion := config.GeminiVersion
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if meta.ActualModelName == "gemini-2.0-flash-exp" {
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var defaultVersion string
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switch meta.ActualModelName {
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case "gemini-2.0-flash-exp",
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"gemini-2.0-flash-thinking-exp",
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"gemini-2.0-flash-thinking-exp-01-21":
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defaultVersion = "v1beta"
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default:
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defaultVersion = "v1beta"
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}
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@@ -7,5 +7,5 @@ var ModelList = []string{
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"gemini-1.5-flash", "gemini-1.5-pro",
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"text-embedding-004", "aqa",
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"gemini-2.0-flash-exp",
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"gemini-2.0-flash-thinking-exp",
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"gemini-2.0-flash-thinking-exp", "gemini-2.0-flash-thinking-exp-01-21",
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}
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@@ -3,7 +3,6 @@ package groq
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// https://console.groq.com/docs/models
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var ModelList = []string{
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"gemma-7b-it",
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"gemma2-9b-it",
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"llama-3.1-70b-versatile",
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"llama-3.1-8b-instant",
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@@ -11,7 +10,6 @@ var ModelList = []string{
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"llama-3.2-11b-vision-preview",
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"llama-3.2-1b-preview",
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"llama-3.2-3b-preview",
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"llama-3.2-11b-vision-preview",
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"llama-3.2-90b-text-preview",
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"llama-3.2-90b-vision-preview",
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"llama-guard-3-8b",
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@@ -24,4 +22,6 @@ var ModelList = []string{
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"distil-whisper-large-v3-en",
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"whisper-large-v3",
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"whisper-large-v3-turbo",
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"deepseek-r1-distill-llama-70b-specdec",
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"deepseek-r1-distill-llama-70b",
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}
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@@ -3,14 +3,16 @@ package openai
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import (
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"errors"
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"fmt"
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"math"
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"strings"
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"github.com/pkoukk/tiktoken-go"
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"github.com/songquanpeng/one-api/common/config"
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"github.com/songquanpeng/one-api/common/image"
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"github.com/songquanpeng/one-api/common/logger"
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billingratio "github.com/songquanpeng/one-api/relay/billing/ratio"
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"github.com/songquanpeng/one-api/relay/model"
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"math"
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"strings"
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)
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// tokenEncoderMap won't grow after initialization
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@@ -21,7 +23,8 @@ func InitTokenEncoders() {
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logger.SysLog("initializing token encoders")
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gpt35TokenEncoder, err := tiktoken.EncodingForModel("gpt-3.5-turbo")
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if err != nil {
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logger.FatalLog(fmt.Sprintf("failed to get gpt-3.5-turbo token encoder: %s", err.Error()))
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logger.FatalLog(fmt.Sprintf("failed to get gpt-3.5-turbo token encoder: %s, "+
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"if you are using in offline environment, please set TIKTOKEN_CACHE_DIR to use exsited files, check this link for more information: https://stackoverflow.com/questions/76106366/how-to-use-tiktoken-in-offline-mode-computer ", err.Error()))
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}
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defaultTokenEncoder = gpt35TokenEncoder
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gpt4oTokenEncoder, err := tiktoken.EncodingForModel("gpt-4o")
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@@ -2,16 +2,19 @@ package tencent
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import (
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"errors"
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"io"
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"net/http"
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"strconv"
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"strings"
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"github.com/gin-gonic/gin"
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"github.com/songquanpeng/one-api/common/helper"
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"github.com/songquanpeng/one-api/relay/adaptor"
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"github.com/songquanpeng/one-api/relay/adaptor/openai"
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"github.com/songquanpeng/one-api/relay/meta"
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"github.com/songquanpeng/one-api/relay/model"
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"io"
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"net/http"
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"strconv"
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"strings"
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"github.com/songquanpeng/one-api/relay/relaymode"
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)
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// https://cloud.tencent.com/document/api/1729/101837
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@@ -52,10 +55,18 @@ func (a *Adaptor) ConvertRequest(c *gin.Context, relayMode int, request *model.G
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if err != nil {
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return nil, err
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}
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tencentRequest := ConvertRequest(*request)
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var convertedRequest any
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switch relayMode {
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case relaymode.Embeddings:
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a.Action = "GetEmbedding"
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convertedRequest = ConvertEmbeddingRequest(*request)
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default:
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a.Action = "ChatCompletions"
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convertedRequest = ConvertRequest(*request)
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}
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// we have to calculate the sign here
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a.Sign = GetSign(*tencentRequest, a, secretId, secretKey)
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return tencentRequest, nil
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a.Sign = GetSign(convertedRequest, a, secretId, secretKey)
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return convertedRequest, nil
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}
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func (a *Adaptor) ConvertImageRequest(request *model.ImageRequest) (any, error) {
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@@ -75,7 +86,12 @@ func (a *Adaptor) DoResponse(c *gin.Context, resp *http.Response, meta *meta.Met
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err, responseText = StreamHandler(c, resp)
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usage = openai.ResponseText2Usage(responseText, meta.ActualModelName, meta.PromptTokens)
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} else {
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err, usage = Handler(c, resp)
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switch meta.Mode {
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case relaymode.Embeddings:
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err, usage = EmbeddingHandler(c, resp)
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default:
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err, usage = Handler(c, resp)
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}
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}
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return
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}
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@@ -6,4 +6,5 @@ var ModelList = []string{
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"hunyuan-standard-256K",
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"hunyuan-pro",
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"hunyuan-vision",
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"hunyuan-embedding",
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}
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@@ -8,7 +8,6 @@ import (
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"encoding/json"
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"errors"
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"fmt"
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"github.com/songquanpeng/one-api/common/render"
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"io"
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"net/http"
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"strconv"
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@@ -16,11 +15,14 @@ import (
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"time"
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"github.com/gin-gonic/gin"
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"github.com/songquanpeng/one-api/common"
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"github.com/songquanpeng/one-api/common/conv"
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"github.com/songquanpeng/one-api/common/ctxkey"
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"github.com/songquanpeng/one-api/common/helper"
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"github.com/songquanpeng/one-api/common/logger"
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"github.com/songquanpeng/one-api/common/random"
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"github.com/songquanpeng/one-api/common/render"
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"github.com/songquanpeng/one-api/relay/adaptor/openai"
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"github.com/songquanpeng/one-api/relay/constant"
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"github.com/songquanpeng/one-api/relay/model"
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@@ -44,8 +46,68 @@ func ConvertRequest(request model.GeneralOpenAIRequest) *ChatRequest {
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}
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}
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func ConvertEmbeddingRequest(request model.GeneralOpenAIRequest) *EmbeddingRequest {
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return &EmbeddingRequest{
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InputList: request.ParseInput(),
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}
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}
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func EmbeddingHandler(c *gin.Context, resp *http.Response) (*model.ErrorWithStatusCode, *model.Usage) {
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var tencentResponseP EmbeddingResponseP
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err := json.NewDecoder(resp.Body).Decode(&tencentResponseP)
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if err != nil {
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return openai.ErrorWrapper(err, "unmarshal_response_body_failed", http.StatusInternalServerError), nil
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}
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err = resp.Body.Close()
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if err != nil {
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return openai.ErrorWrapper(err, "close_response_body_failed", http.StatusInternalServerError), nil
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}
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tencentResponse := tencentResponseP.Response
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if tencentResponse.Error.Code != "" {
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return &model.ErrorWithStatusCode{
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Error: model.Error{
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Message: tencentResponse.Error.Message,
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Code: tencentResponse.Error.Code,
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},
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StatusCode: resp.StatusCode,
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}, nil
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}
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requestModel := c.GetString(ctxkey.RequestModel)
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fullTextResponse := embeddingResponseTencent2OpenAI(&tencentResponse)
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fullTextResponse.Model = requestModel
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jsonResponse, err := json.Marshal(fullTextResponse)
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if err != nil {
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return openai.ErrorWrapper(err, "marshal_response_body_failed", http.StatusInternalServerError), nil
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}
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c.Writer.Header().Set("Content-Type", "application/json")
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c.Writer.WriteHeader(resp.StatusCode)
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_, err = c.Writer.Write(jsonResponse)
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return nil, &fullTextResponse.Usage
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}
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func embeddingResponseTencent2OpenAI(response *EmbeddingResponse) *openai.EmbeddingResponse {
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openAIEmbeddingResponse := openai.EmbeddingResponse{
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Object: "list",
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Data: make([]openai.EmbeddingResponseItem, 0, len(response.Data)),
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Model: "hunyuan-embedding",
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Usage: model.Usage{TotalTokens: response.EmbeddingUsage.TotalTokens},
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}
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for _, item := range response.Data {
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openAIEmbeddingResponse.Data = append(openAIEmbeddingResponse.Data, openai.EmbeddingResponseItem{
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Object: item.Object,
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Index: item.Index,
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Embedding: item.Embedding,
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})
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}
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return &openAIEmbeddingResponse
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}
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func responseTencent2OpenAI(response *ChatResponse) *openai.TextResponse {
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fullTextResponse := openai.TextResponse{
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Id: response.ReqID,
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Object: "chat.completion",
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Created: helper.GetTimestamp(),
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Usage: model.Usage{
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@@ -148,7 +210,7 @@ func Handler(c *gin.Context, resp *http.Response) (*model.ErrorWithStatusCode, *
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return openai.ErrorWrapper(err, "unmarshal_response_body_failed", http.StatusInternalServerError), nil
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}
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TencentResponse = responseP.Response
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if TencentResponse.Error.Code != 0 {
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if TencentResponse.Error.Code != "" {
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return &model.ErrorWithStatusCode{
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Error: model.Error{
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Message: TencentResponse.Error.Message,
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@@ -195,7 +257,7 @@ func hmacSha256(s, key string) string {
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return string(hashed.Sum(nil))
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}
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func GetSign(req ChatRequest, adaptor *Adaptor, secId, secKey string) string {
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func GetSign(req any, adaptor *Adaptor, secId, secKey string) string {
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// build canonical request string
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host := "hunyuan.tencentcloudapi.com"
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httpRequestMethod := "POST"
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@@ -35,16 +35,16 @@ type ChatRequest struct {
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// 1. 影响输出文本的多样性,取值越大,生成文本的多样性越强。
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// 2. 取值区间为 [0.0, 1.0],未传值时使用各模型推荐值。
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// 3. 非必要不建议使用,不合理的取值会影响效果。
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TopP *float64 `json:"TopP"`
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TopP *float64 `json:"TopP,omitempty"`
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// 说明:
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// 1. 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。
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// 2. 取值区间为 [0.0, 2.0],未传值时使用各模型推荐值。
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// 3. 非必要不建议使用,不合理的取值会影响效果。
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Temperature *float64 `json:"Temperature"`
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Temperature *float64 `json:"Temperature,omitempty"`
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}
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type Error struct {
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Code int `json:"Code"`
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Code string `json:"Code"`
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Message string `json:"Message"`
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}
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@@ -61,15 +61,41 @@ type ResponseChoices struct {
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}
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type ChatResponse struct {
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Choices []ResponseChoices `json:"Choices,omitempty"` // 结果
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Created int64 `json:"Created,omitempty"` // unix 时间戳的字符串
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Id string `json:"Id,omitempty"` // 会话 id
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Usage Usage `json:"Usage,omitempty"` // token 数量
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Error Error `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
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Note string `json:"Note,omitempty"` // 注释
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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
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Choices []ResponseChoices `json:"Choices,omitempty"` // 结果
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Created int64 `json:"Created,omitempty"` // unix 时间戳的字符串
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Id string `json:"Id,omitempty"` // 会话 id
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Usage Usage `json:"Usage,omitempty"` // token 数量
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Error Error `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
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Note string `json:"Note,omitempty"` // 注释
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ReqID string `json:"RequestId,omitempty"` // 唯一请求 Id,每次请求都会返回。用于反馈接口入参
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}
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type ChatResponseP struct {
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Response ChatResponse `json:"Response,omitempty"`
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}
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type EmbeddingRequest struct {
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InputList []string `json:"InputList"`
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}
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type EmbeddingData struct {
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Embedding []float64 `json:"Embedding"`
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Index int `json:"Index"`
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Object string `json:"Object"`
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}
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|
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type EmbeddingUsage struct {
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PromptTokens int `json:"PromptTokens"`
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TotalTokens int `json:"TotalTokens"`
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}
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type EmbeddingResponse struct {
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Data []EmbeddingData `json:"Data"`
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EmbeddingUsage EmbeddingUsage `json:"Usage,omitempty"`
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RequestId string `json:"RequestId,omitempty"`
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Error Error `json:"Error,omitempty"`
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}
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|
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type EmbeddingResponseP struct {
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Response EmbeddingResponse `json:"Response,omitempty"`
|
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}
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@@ -18,7 +18,8 @@ var ModelList = []string{
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"gemini-pro", "gemini-pro-vision",
|
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"gemini-1.5-pro-001", "gemini-1.5-flash-001",
|
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"gemini-1.5-pro-002", "gemini-1.5-flash-002",
|
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"gemini-2.0-flash-exp", "gemini-2.0-flash-thinking-exp",
|
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"gemini-2.0-flash-exp",
|
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"gemini-2.0-flash-thinking-exp", "gemini-2.0-flash-thinking-exp-01-21",
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}
|
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|
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type Adaptor struct {
|
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|
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@@ -1,7 +1,14 @@
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package zhipu
|
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|
||||
// https://open.bigmodel.cn/pricing
|
||||
|
||||
var ModelList = []string{
|
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"chatglm_turbo", "chatglm_pro", "chatglm_std", "chatglm_lite",
|
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"glm-4", "glm-4v", "glm-3-turbo", "embedding-2",
|
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"cogview-3",
|
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"glm-zero-preview", "glm-4-plus", "glm-4-0520", "glm-4-airx",
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"glm-4-air", "glm-4-long", "glm-4-flashx", "glm-4-flash",
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"glm-4", "glm-3-turbo",
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"glm-4v-plus", "glm-4v", "glm-4v-flash",
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"cogview-3-plus", "cogview-3", "cogview-3-flash",
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"cogviewx", "cogviewx-flash",
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"charglm-4", "emohaa", "codegeex-4",
|
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"embedding-2", "embedding-3",
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||||
}
|
||||
|
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