Merge remote-tracking branch 'origin/alpha' into alpha
This commit is contained in:
@@ -40,4 +40,6 @@ const (
|
||||
ContextKeyUserGroup ContextKey = "user_group"
|
||||
ContextKeyUsingGroup ContextKey = "group"
|
||||
ContextKeyUserName ContextKey = "username"
|
||||
|
||||
ContextKeySystemPromptOverride ContextKey = "system_prompt_override"
|
||||
)
|
||||
|
||||
@@ -145,6 +145,22 @@ func UpdateMidjourneyTaskBulk() {
|
||||
buttonStr, _ := json.Marshal(responseItem.Buttons)
|
||||
task.Buttons = string(buttonStr)
|
||||
}
|
||||
// 映射 VideoUrl
|
||||
task.VideoUrl = responseItem.VideoUrl
|
||||
|
||||
// 映射 VideoUrls - 将数组序列化为 JSON 字符串
|
||||
if responseItem.VideoUrls != nil && len(responseItem.VideoUrls) > 0 {
|
||||
videoUrlsStr, err := json.Marshal(responseItem.VideoUrls)
|
||||
if err != nil {
|
||||
common.LogError(ctx, fmt.Sprintf("序列化 VideoUrls 失败: %v", err))
|
||||
task.VideoUrls = "[]" // 失败时设置为空数组
|
||||
} else {
|
||||
task.VideoUrls = string(videoUrlsStr)
|
||||
}
|
||||
} else {
|
||||
task.VideoUrls = "" // 空值时清空字段
|
||||
}
|
||||
|
||||
shouldReturnQuota := false
|
||||
if (task.Progress != "100%" && responseItem.FailReason != "") || (task.Progress == "100%" && task.Status == "FAILURE") {
|
||||
common.LogInfo(ctx, task.MjId+" 构建失败,"+task.FailReason)
|
||||
@@ -208,6 +224,20 @@ func checkMjTaskNeedUpdate(oldTask *model.Midjourney, newTask dto.MidjourneyDto)
|
||||
if oldTask.Progress != "100%" && newTask.FailReason != "" {
|
||||
return true
|
||||
}
|
||||
// 检查 VideoUrl 是否需要更新
|
||||
if oldTask.VideoUrl != newTask.VideoUrl {
|
||||
return true
|
||||
}
|
||||
// 检查 VideoUrls 是否需要更新
|
||||
if newTask.VideoUrls != nil && len(newTask.VideoUrls) > 0 {
|
||||
newVideoUrlsStr, _ := json.Marshal(newTask.VideoUrls)
|
||||
if oldTask.VideoUrls != string(newVideoUrlsStr) {
|
||||
return true
|
||||
}
|
||||
} else if oldTask.VideoUrls != "" {
|
||||
// 如果新数据没有 VideoUrls 但旧数据有,需要更新(清空)
|
||||
return true
|
||||
}
|
||||
|
||||
return false
|
||||
}
|
||||
|
||||
@@ -6,4 +6,5 @@ type ChannelSettings struct {
|
||||
Proxy string `json:"proxy"`
|
||||
PassThroughBodyEnabled bool `json:"pass_through_body_enabled,omitempty"`
|
||||
SystemPrompt string `json:"system_prompt,omitempty"`
|
||||
SystemPromptOverride bool `json:"system_prompt_override,omitempty"`
|
||||
}
|
||||
|
||||
@@ -216,10 +216,14 @@ type GeminiEmbeddingRequest struct {
|
||||
OutputDimensionality int `json:"outputDimensionality,omitempty"`
|
||||
}
|
||||
|
||||
type GeminiEmbeddingResponse struct {
|
||||
Embedding ContentEmbedding `json:"embedding"`
|
||||
type GeminiBatchEmbeddingRequest struct {
|
||||
Requests []*GeminiEmbeddingRequest `json:"requests"`
|
||||
}
|
||||
|
||||
type ContentEmbedding struct {
|
||||
type GeminiEmbedding struct {
|
||||
Values []float64 `json:"values"`
|
||||
}
|
||||
|
||||
type GeminiBatchEmbeddingResponse struct {
|
||||
Embeddings []*GeminiEmbedding `json:"embeddings"`
|
||||
}
|
||||
|
||||
@@ -78,6 +78,8 @@ func (r *GeneralOpenAIRequest) GetSystemRoleName() string {
|
||||
if !strings.HasPrefix(r.Model, "o1-mini") && !strings.HasPrefix(r.Model, "o1-preview") {
|
||||
return "developer"
|
||||
}
|
||||
} else if strings.HasPrefix(r.Model, "gpt-5") {
|
||||
return "developer"
|
||||
}
|
||||
return "system"
|
||||
}
|
||||
|
||||
@@ -267,6 +267,8 @@ func SetupContextForSelectedChannel(c *gin.Context, channel *model.Channel, mode
|
||||
common.SetContextKey(c, constant.ContextKeyChannelKey, key)
|
||||
common.SetContextKey(c, constant.ContextKeyChannelBaseUrl, channel.GetBaseURL())
|
||||
|
||||
common.SetContextKey(c, constant.ContextKeySystemPromptOverride, false)
|
||||
|
||||
// TODO: api_version统一
|
||||
switch channel.Type {
|
||||
case constant.ChannelTypeAzure:
|
||||
|
||||
@@ -114,7 +114,7 @@ func (a *Adaptor) GetRequestURL(info *relaycommon.RelayInfo) (string, error) {
|
||||
if strings.HasPrefix(info.UpstreamModelName, "text-embedding") ||
|
||||
strings.HasPrefix(info.UpstreamModelName, "embedding") ||
|
||||
strings.HasPrefix(info.UpstreamModelName, "gemini-embedding") {
|
||||
return fmt.Sprintf("%s/%s/models/%s:embedContent", info.BaseUrl, version, info.UpstreamModelName), nil
|
||||
return fmt.Sprintf("%s/%s/models/%s:batchEmbedContents", info.BaseUrl, version, info.UpstreamModelName), nil
|
||||
}
|
||||
|
||||
action := "generateContent"
|
||||
@@ -159,29 +159,35 @@ func (a *Adaptor) ConvertEmbeddingRequest(c *gin.Context, info *relaycommon.Rela
|
||||
if len(inputs) == 0 {
|
||||
return nil, errors.New("input is empty")
|
||||
}
|
||||
|
||||
// only process the first input
|
||||
geminiRequest := dto.GeminiEmbeddingRequest{
|
||||
Content: dto.GeminiChatContent{
|
||||
Parts: []dto.GeminiPart{
|
||||
{
|
||||
Text: inputs[0],
|
||||
// process all inputs
|
||||
geminiRequests := make([]map[string]interface{}, 0, len(inputs))
|
||||
for _, input := range inputs {
|
||||
geminiRequest := map[string]interface{}{
|
||||
"model": fmt.Sprintf("models/%s", info.UpstreamModelName),
|
||||
"content": dto.GeminiChatContent{
|
||||
Parts: []dto.GeminiPart{
|
||||
{
|
||||
Text: input,
|
||||
},
|
||||
},
|
||||
},
|
||||
},
|
||||
}
|
||||
|
||||
// set specific parameters for different models
|
||||
// https://ai.google.dev/api/embeddings?hl=zh-cn#method:-models.embedcontent
|
||||
switch info.UpstreamModelName {
|
||||
case "text-embedding-004":
|
||||
// except embedding-001 supports setting `OutputDimensionality`
|
||||
if request.Dimensions > 0 {
|
||||
geminiRequest.OutputDimensionality = request.Dimensions
|
||||
}
|
||||
|
||||
// set specific parameters for different models
|
||||
// https://ai.google.dev/api/embeddings?hl=zh-cn#method:-models.embedcontent
|
||||
switch info.UpstreamModelName {
|
||||
case "text-embedding-004","gemini-embedding-exp-03-07","gemini-embedding-001":
|
||||
// Only newer models introduced after 2024 support OutputDimensionality
|
||||
if request.Dimensions > 0 {
|
||||
geminiRequest["outputDimensionality"] = request.Dimensions
|
||||
}
|
||||
}
|
||||
geminiRequests = append(geminiRequests, geminiRequest)
|
||||
}
|
||||
|
||||
return geminiRequest, nil
|
||||
return map[string]interface{}{
|
||||
"requests": geminiRequests,
|
||||
}, nil
|
||||
}
|
||||
|
||||
func (a *Adaptor) ConvertOpenAIResponsesRequest(c *gin.Context, info *relaycommon.RelayInfo, request dto.OpenAIResponsesRequest) (any, error) {
|
||||
|
||||
@@ -1071,7 +1071,7 @@ func GeminiEmbeddingHandler(c *gin.Context, info *relaycommon.RelayInfo, resp *h
|
||||
return nil, types.NewOpenAIError(readErr, types.ErrorCodeBadResponseBody, http.StatusInternalServerError)
|
||||
}
|
||||
|
||||
var geminiResponse dto.GeminiEmbeddingResponse
|
||||
var geminiResponse dto.GeminiBatchEmbeddingResponse
|
||||
if jsonErr := common.Unmarshal(responseBody, &geminiResponse); jsonErr != nil {
|
||||
return nil, types.NewOpenAIError(jsonErr, types.ErrorCodeBadResponseBody, http.StatusInternalServerError)
|
||||
}
|
||||
@@ -1079,14 +1079,16 @@ func GeminiEmbeddingHandler(c *gin.Context, info *relaycommon.RelayInfo, resp *h
|
||||
// convert to openai format response
|
||||
openAIResponse := dto.OpenAIEmbeddingResponse{
|
||||
Object: "list",
|
||||
Data: []dto.OpenAIEmbeddingResponseItem{
|
||||
{
|
||||
Object: "embedding",
|
||||
Embedding: geminiResponse.Embedding.Values,
|
||||
Index: 0,
|
||||
},
|
||||
},
|
||||
Model: info.UpstreamModelName,
|
||||
Data: make([]dto.OpenAIEmbeddingResponseItem, 0, len(geminiResponse.Embeddings)),
|
||||
Model: info.UpstreamModelName,
|
||||
}
|
||||
|
||||
for i, embedding := range geminiResponse.Embeddings {
|
||||
openAIResponse.Data = append(openAIResponse.Data, dto.OpenAIEmbeddingResponseItem{
|
||||
Object: "embedding",
|
||||
Embedding: embedding.Values,
|
||||
Index: i,
|
||||
})
|
||||
}
|
||||
|
||||
// calculate usage
|
||||
|
||||
@@ -54,8 +54,7 @@ func (a *Adaptor) GetRequestURL(info *relaycommon.RelayInfo) (string, error) {
|
||||
|
||||
func (a *Adaptor) SetupRequestHeader(c *gin.Context, req *http.Header, info *relaycommon.RelayInfo) error {
|
||||
channel.SetupApiRequestHeader(info, c, req)
|
||||
token := getZhipuToken(info.ApiKey)
|
||||
req.Set("Authorization", token)
|
||||
req.Set("Authorization", "Bearer "+info.ApiKey)
|
||||
return nil
|
||||
}
|
||||
|
||||
|
||||
@@ -1,69 +1,10 @@
|
||||
package zhipu_4v
|
||||
|
||||
import (
|
||||
"github.com/golang-jwt/jwt"
|
||||
"one-api/common"
|
||||
"one-api/dto"
|
||||
"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
|
||||
|
||||
var zhipuTokens sync.Map
|
||||
var expSeconds int64 = 24 * 3600
|
||||
|
||||
func getZhipuToken(apikey string) string {
|
||||
data, ok := zhipuTokens.Load(apikey)
|
||||
if ok {
|
||||
tokenData := data.(tokenData)
|
||||
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, tokenData{
|
||||
Token: tokenString,
|
||||
ExpiryTime: expiryTime,
|
||||
})
|
||||
|
||||
return tokenString
|
||||
}
|
||||
|
||||
func requestOpenAI2Zhipu(request dto.GeneralOpenAIRequest) *dto.GeneralOpenAIRequest {
|
||||
messages := make([]dto.Message, 0, len(request.Messages))
|
||||
for _, message := range request.Messages {
|
||||
|
||||
@@ -201,6 +201,26 @@ func TextHelper(c *gin.Context) (newAPIError *types.NewAPIError) {
|
||||
Content: relayInfo.ChannelSetting.SystemPrompt,
|
||||
}
|
||||
request.Messages = append([]dto.Message{systemMessage}, request.Messages...)
|
||||
} else if relayInfo.ChannelSetting.SystemPromptOverride {
|
||||
common.SetContextKey(c, constant.ContextKeySystemPromptOverride, true)
|
||||
// 如果有系统提示,且允许覆盖,则拼接到前面
|
||||
for i, message := range request.Messages {
|
||||
if message.Role == request.GetSystemRoleName() {
|
||||
if message.IsStringContent() {
|
||||
request.Messages[i].SetStringContent(relayInfo.ChannelSetting.SystemPrompt + "\n" + message.StringContent())
|
||||
} else {
|
||||
contents := message.ParseContent()
|
||||
contents = append([]dto.MediaContent{
|
||||
{
|
||||
Type: dto.ContentTypeText,
|
||||
Text: relayInfo.ChannelSetting.SystemPrompt,
|
||||
},
|
||||
}, contents...)
|
||||
request.Messages[i].Content = contents
|
||||
}
|
||||
break
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@@ -28,6 +28,12 @@ func GenerateTextOtherInfo(ctx *gin.Context, relayInfo *relaycommon.RelayInfo, m
|
||||
other["is_model_mapped"] = true
|
||||
other["upstream_model_name"] = relayInfo.UpstreamModelName
|
||||
}
|
||||
|
||||
isSystemPromptOverwritten := common.GetContextKeyBool(ctx, constant.ContextKeySystemPromptOverride)
|
||||
if isSystemPromptOverwritten {
|
||||
other["is_system_prompt_overwritten"] = true
|
||||
}
|
||||
|
||||
adminInfo := make(map[string]interface{})
|
||||
adminInfo["use_channel"] = ctx.GetStringSlice("use_channel")
|
||||
isMultiKey := common.GetContextKeyBool(ctx, constant.ContextKeyChannelIsMultiKey)
|
||||
|
||||
@@ -131,6 +131,7 @@ const EditChannelModal = (props) => {
|
||||
proxy: '',
|
||||
pass_through_body_enabled: false,
|
||||
system_prompt: '',
|
||||
system_prompt_override: false,
|
||||
};
|
||||
const [batch, setBatch] = useState(false);
|
||||
const [multiToSingle, setMultiToSingle] = useState(false);
|
||||
@@ -340,12 +341,15 @@ const EditChannelModal = (props) => {
|
||||
data.proxy = parsedSettings.proxy || '';
|
||||
data.pass_through_body_enabled = parsedSettings.pass_through_body_enabled || false;
|
||||
data.system_prompt = parsedSettings.system_prompt || '';
|
||||
data.system_prompt_override = parsedSettings.system_prompt_override || false;
|
||||
} catch (error) {
|
||||
console.error('解析渠道设置失败:', error);
|
||||
data.force_format = false;
|
||||
data.thinking_to_content = false;
|
||||
data.proxy = '';
|
||||
data.pass_through_body_enabled = false;
|
||||
data.system_prompt = '';
|
||||
data.system_prompt_override = false;
|
||||
}
|
||||
} else {
|
||||
data.force_format = false;
|
||||
@@ -353,6 +357,7 @@ const EditChannelModal = (props) => {
|
||||
data.proxy = '';
|
||||
data.pass_through_body_enabled = false;
|
||||
data.system_prompt = '';
|
||||
data.system_prompt_override = false;
|
||||
}
|
||||
|
||||
setInputs(data);
|
||||
@@ -372,6 +377,7 @@ const EditChannelModal = (props) => {
|
||||
proxy: data.proxy,
|
||||
pass_through_body_enabled: data.pass_through_body_enabled,
|
||||
system_prompt: data.system_prompt,
|
||||
system_prompt_override: data.system_prompt_override || false,
|
||||
});
|
||||
// console.log(data);
|
||||
} else {
|
||||
@@ -573,6 +579,7 @@ const EditChannelModal = (props) => {
|
||||
proxy: '',
|
||||
pass_through_body_enabled: false,
|
||||
system_prompt: '',
|
||||
system_prompt_override: false,
|
||||
});
|
||||
// 重置密钥模式状态
|
||||
setKeyMode('append');
|
||||
@@ -721,6 +728,7 @@ const EditChannelModal = (props) => {
|
||||
proxy: localInputs.proxy || '',
|
||||
pass_through_body_enabled: localInputs.pass_through_body_enabled || false,
|
||||
system_prompt: localInputs.system_prompt || '',
|
||||
system_prompt_override: localInputs.system_prompt_override || false,
|
||||
};
|
||||
localInputs.setting = JSON.stringify(channelExtraSettings);
|
||||
|
||||
@@ -730,6 +738,7 @@ const EditChannelModal = (props) => {
|
||||
delete localInputs.proxy;
|
||||
delete localInputs.pass_through_body_enabled;
|
||||
delete localInputs.system_prompt;
|
||||
delete localInputs.system_prompt_override;
|
||||
|
||||
let res;
|
||||
localInputs.auto_ban = localInputs.auto_ban ? 1 : 0;
|
||||
@@ -1722,6 +1731,14 @@ const EditChannelModal = (props) => {
|
||||
showClear
|
||||
extraText={t('用户优先:如果用户在请求中指定了系统提示词,将优先使用用户的设置')}
|
||||
/>
|
||||
<Form.Switch
|
||||
field='system_prompt_override'
|
||||
label={t('系统提示词拼接')}
|
||||
checkedText={t('开')}
|
||||
uncheckedText={t('关')}
|
||||
onChange={(value) => handleChannelSettingsChange('system_prompt_override', value)}
|
||||
extraText={t('如果用户请求中包含系统提示词,则使用此设置拼接到用户的系统提示词前面')}
|
||||
/>
|
||||
</Card>
|
||||
</div>
|
||||
</Spin>
|
||||
|
||||
@@ -211,6 +211,7 @@ export const getTaskLogsColumns = ({
|
||||
copyText,
|
||||
openContentModal,
|
||||
isAdminUser,
|
||||
openVideoModal,
|
||||
}) => {
|
||||
return [
|
||||
{
|
||||
@@ -342,7 +343,13 @@ export const getTaskLogsColumns = ({
|
||||
const isUrl = typeof text === 'string' && /^https?:\/\//.test(text);
|
||||
if (isSuccess && isVideoTask && isUrl) {
|
||||
return (
|
||||
<a href={text} target="_blank" rel="noopener noreferrer">
|
||||
<a
|
||||
href="#"
|
||||
onClick={e => {
|
||||
e.preventDefault();
|
||||
openVideoModal(text);
|
||||
}}
|
||||
>
|
||||
{t('点击预览视频')}
|
||||
</a>
|
||||
);
|
||||
|
||||
@@ -39,6 +39,7 @@ const TaskLogsTable = (taskLogsData) => {
|
||||
handlePageSizeChange,
|
||||
copyText,
|
||||
openContentModal,
|
||||
openVideoModal,
|
||||
isAdminUser,
|
||||
t,
|
||||
COLUMN_KEYS,
|
||||
@@ -51,6 +52,7 @@ const TaskLogsTable = (taskLogsData) => {
|
||||
COLUMN_KEYS,
|
||||
copyText,
|
||||
openContentModal,
|
||||
openVideoModal,
|
||||
isAdminUser,
|
||||
});
|
||||
}, [
|
||||
@@ -58,6 +60,7 @@ const TaskLogsTable = (taskLogsData) => {
|
||||
COLUMN_KEYS,
|
||||
copyText,
|
||||
openContentModal,
|
||||
openVideoModal,
|
||||
isAdminUser,
|
||||
]);
|
||||
|
||||
|
||||
@@ -37,7 +37,14 @@ const TaskLogsPage = () => {
|
||||
<>
|
||||
{/* Modals */}
|
||||
<ColumnSelectorModal {...taskLogsData} />
|
||||
<ContentModal {...taskLogsData} />
|
||||
<ContentModal {...taskLogsData} isVideo={false} />
|
||||
{/* 新增:视频预览弹窗 */}
|
||||
<ContentModal
|
||||
isModalOpen={taskLogsData.isVideoModalOpen}
|
||||
setIsModalOpen={taskLogsData.setIsVideoModalOpen}
|
||||
modalContent={taskLogsData.videoUrl}
|
||||
isVideo={true}
|
||||
/>
|
||||
|
||||
<Layout>
|
||||
<CardPro
|
||||
|
||||
@@ -24,6 +24,7 @@ const ContentModal = ({
|
||||
isModalOpen,
|
||||
setIsModalOpen,
|
||||
modalContent,
|
||||
isVideo,
|
||||
}) => {
|
||||
return (
|
||||
<Modal
|
||||
@@ -34,7 +35,11 @@ const ContentModal = ({
|
||||
bodyStyle={{ height: '400px', overflow: 'auto' }}
|
||||
width={800}
|
||||
>
|
||||
<p style={{ whiteSpace: 'pre-line' }}>{modalContent}</p>
|
||||
{isVideo ? (
|
||||
<video src={modalContent} controls style={{ width: '100%' }} autoPlay />
|
||||
) : (
|
||||
<p style={{ whiteSpace: 'pre-line' }}>{modalContent}</p>
|
||||
)}
|
||||
</Modal>
|
||||
);
|
||||
};
|
||||
|
||||
@@ -34,7 +34,6 @@ import {
|
||||
getLogOther,
|
||||
renderModelTag,
|
||||
renderClaudeLogContent,
|
||||
renderClaudeModelPriceSimple,
|
||||
renderLogContent,
|
||||
renderModelPriceSimple,
|
||||
renderAudioModelPrice,
|
||||
@@ -538,7 +537,7 @@ export const getLogsColumns = ({
|
||||
);
|
||||
}
|
||||
let content = other?.claude
|
||||
? renderClaudeModelPriceSimple(
|
||||
? renderModelPriceSimple(
|
||||
other.model_ratio,
|
||||
other.model_price,
|
||||
other.group_ratio,
|
||||
@@ -547,6 +546,10 @@ export const getLogsColumns = ({
|
||||
other.cache_ratio || 1.0,
|
||||
other.cache_creation_tokens || 0,
|
||||
other.cache_creation_ratio || 1.0,
|
||||
false,
|
||||
1.0,
|
||||
other?.is_system_prompt_overwritten,
|
||||
'claude'
|
||||
)
|
||||
: renderModelPriceSimple(
|
||||
other.model_ratio,
|
||||
@@ -555,13 +558,19 @@ export const getLogsColumns = ({
|
||||
other?.user_group_ratio,
|
||||
other.cache_tokens || 0,
|
||||
other.cache_ratio || 1.0,
|
||||
0,
|
||||
1.0,
|
||||
false,
|
||||
1.0,
|
||||
other?.is_system_prompt_overwritten,
|
||||
'openai'
|
||||
);
|
||||
return (
|
||||
<Typography.Paragraph
|
||||
ellipsis={{
|
||||
rows: 2,
|
||||
rows: 3,
|
||||
}}
|
||||
style={{ maxWidth: 240 }}
|
||||
style={{ maxWidth: 240, whiteSpace: 'pre-line' }}
|
||||
>
|
||||
{content}
|
||||
</Typography.Paragraph>
|
||||
|
||||
@@ -215,14 +215,16 @@ export async function getOAuthState() {
|
||||
export async function onOIDCClicked(auth_url, client_id, openInNewTab = false) {
|
||||
const state = await getOAuthState();
|
||||
if (!state) return;
|
||||
const redirect_uri = `${window.location.origin}/oauth/oidc`;
|
||||
const response_type = 'code';
|
||||
const scope = 'openid profile email';
|
||||
const url = `${auth_url}?client_id=${client_id}&redirect_uri=${redirect_uri}&response_type=${response_type}&scope=${scope}&state=${state}`;
|
||||
const url = new URL(auth_url);
|
||||
url.searchParams.set('client_id', client_id);
|
||||
url.searchParams.set('redirect_uri', `${window.location.origin}/oauth/oidc`);
|
||||
url.searchParams.set('response_type', 'code');
|
||||
url.searchParams.set('scope', 'openid profile email');
|
||||
url.searchParams.set('state', state);
|
||||
if (openInNewTab) {
|
||||
window.open(url);
|
||||
window.open(url.toString(), '_blank');
|
||||
} else {
|
||||
window.location.href = url;
|
||||
window.location.href = url.toString();
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@@ -953,6 +953,71 @@ function getEffectiveRatio(groupRatio, user_group_ratio) {
|
||||
};
|
||||
}
|
||||
|
||||
// Shared core for simple price rendering (used by OpenAI-like and Claude-like variants)
|
||||
function renderPriceSimpleCore({
|
||||
modelRatio,
|
||||
modelPrice = -1,
|
||||
groupRatio,
|
||||
user_group_ratio,
|
||||
cacheTokens = 0,
|
||||
cacheRatio = 1.0,
|
||||
cacheCreationTokens = 0,
|
||||
cacheCreationRatio = 1.0,
|
||||
image = false,
|
||||
imageRatio = 1.0,
|
||||
isSystemPromptOverride = false
|
||||
}) {
|
||||
const { ratio: effectiveGroupRatio, label: ratioLabel } = getEffectiveRatio(
|
||||
groupRatio,
|
||||
user_group_ratio,
|
||||
);
|
||||
const finalGroupRatio = effectiveGroupRatio;
|
||||
|
||||
if (modelPrice !== -1) {
|
||||
return i18next.t('价格:${{price}} * {{ratioType}}:{{ratio}}', {
|
||||
price: modelPrice,
|
||||
ratioType: ratioLabel,
|
||||
ratio: finalGroupRatio,
|
||||
});
|
||||
}
|
||||
|
||||
const parts = [];
|
||||
// base: model ratio
|
||||
parts.push(i18next.t('模型: {{ratio}}'));
|
||||
|
||||
// cache part (label differs when with image)
|
||||
if (cacheTokens !== 0) {
|
||||
parts.push(i18next.t('缓存: {{cacheRatio}}'));
|
||||
}
|
||||
|
||||
// cache creation part (Claude specific if passed)
|
||||
if (cacheCreationTokens !== 0) {
|
||||
parts.push(i18next.t('缓存创建: {{cacheCreationRatio}}'));
|
||||
}
|
||||
|
||||
// image part
|
||||
if (image) {
|
||||
parts.push(i18next.t('图片输入: {{imageRatio}}'));
|
||||
}
|
||||
|
||||
parts.push(`{{ratioType}}: {{groupRatio}}`);
|
||||
|
||||
let result = i18next.t(parts.join(' * '), {
|
||||
ratio: modelRatio,
|
||||
ratioType: ratioLabel,
|
||||
groupRatio: finalGroupRatio,
|
||||
cacheRatio: cacheRatio,
|
||||
cacheCreationRatio: cacheCreationRatio,
|
||||
imageRatio: imageRatio,
|
||||
})
|
||||
|
||||
if (isSystemPromptOverride) {
|
||||
result += '\n\r' + i18next.t('系统提示覆盖');
|
||||
}
|
||||
|
||||
return result;
|
||||
}
|
||||
|
||||
export function renderModelPrice(
|
||||
inputTokens,
|
||||
completionTokens,
|
||||
@@ -1245,56 +1310,26 @@ export function renderModelPriceSimple(
|
||||
user_group_ratio,
|
||||
cacheTokens = 0,
|
||||
cacheRatio = 1.0,
|
||||
cacheCreationTokens = 0,
|
||||
cacheCreationRatio = 1.0,
|
||||
image = false,
|
||||
imageRatio = 1.0,
|
||||
isSystemPromptOverride = false,
|
||||
provider = 'openai',
|
||||
) {
|
||||
const { ratio: effectiveGroupRatio, label: ratioLabel } = getEffectiveRatio(groupRatio, user_group_ratio);
|
||||
groupRatio = effectiveGroupRatio;
|
||||
if (modelPrice !== -1) {
|
||||
return i18next.t('价格:${{price}} * {{ratioType}}:{{ratio}}', {
|
||||
price: modelPrice,
|
||||
ratioType: ratioLabel,
|
||||
ratio: groupRatio,
|
||||
});
|
||||
} else {
|
||||
if (image && cacheTokens !== 0) {
|
||||
return i18next.t(
|
||||
'模型: {{ratio}} * {{ratioType}}: {{groupRatio}} * 缓存倍率: {{cacheRatio}} * 图片输入倍率: {{imageRatio}}',
|
||||
{
|
||||
ratio: modelRatio,
|
||||
ratioType: ratioLabel,
|
||||
groupRatio: groupRatio,
|
||||
cacheRatio: cacheRatio,
|
||||
imageRatio: imageRatio,
|
||||
},
|
||||
);
|
||||
} else if (image) {
|
||||
return i18next.t(
|
||||
'模型: {{ratio}} * {{ratioType}}: {{groupRatio}} * 图片输入倍率: {{imageRatio}}',
|
||||
{
|
||||
ratio: modelRatio,
|
||||
ratioType: ratioLabel,
|
||||
groupRatio: groupRatio,
|
||||
imageRatio: imageRatio,
|
||||
},
|
||||
);
|
||||
} else if (cacheTokens !== 0) {
|
||||
return i18next.t(
|
||||
'模型: {{ratio}} * 分组: {{groupRatio}} * 缓存: {{cacheRatio}}',
|
||||
{
|
||||
ratio: modelRatio,
|
||||
groupRatio: groupRatio,
|
||||
cacheRatio: cacheRatio,
|
||||
},
|
||||
);
|
||||
} else {
|
||||
return i18next.t('模型: {{ratio}} * {{ratioType}}:{{groupRatio}}', {
|
||||
ratio: modelRatio,
|
||||
ratioType: ratioLabel,
|
||||
groupRatio: groupRatio,
|
||||
});
|
||||
}
|
||||
}
|
||||
return renderPriceSimpleCore({
|
||||
modelRatio,
|
||||
modelPrice,
|
||||
groupRatio,
|
||||
user_group_ratio,
|
||||
cacheTokens,
|
||||
cacheRatio,
|
||||
cacheCreationTokens,
|
||||
cacheCreationRatio,
|
||||
image,
|
||||
imageRatio,
|
||||
isSystemPromptOverride
|
||||
});
|
||||
}
|
||||
|
||||
export function renderAudioModelPrice(
|
||||
@@ -1635,46 +1670,7 @@ export function renderClaudeLogContent(
|
||||
}
|
||||
}
|
||||
|
||||
export function renderClaudeModelPriceSimple(
|
||||
modelRatio,
|
||||
modelPrice = -1,
|
||||
groupRatio,
|
||||
user_group_ratio,
|
||||
cacheTokens = 0,
|
||||
cacheRatio = 1.0,
|
||||
cacheCreationTokens = 0,
|
||||
cacheCreationRatio = 1.0,
|
||||
) {
|
||||
const { ratio: effectiveGroupRatio, label: ratioLabel } = getEffectiveRatio(groupRatio, user_group_ratio);
|
||||
groupRatio = effectiveGroupRatio;
|
||||
|
||||
if (modelPrice !== -1) {
|
||||
return i18next.t('价格:${{price}} * {{ratioType}}:{{ratio}}', {
|
||||
price: modelPrice,
|
||||
ratioType: ratioLabel,
|
||||
ratio: groupRatio,
|
||||
});
|
||||
} else {
|
||||
if (cacheTokens !== 0 || cacheCreationTokens !== 0) {
|
||||
return i18next.t(
|
||||
'模型: {{ratio}} * {{ratioType}}: {{groupRatio}} * 缓存: {{cacheRatio}}',
|
||||
{
|
||||
ratio: modelRatio,
|
||||
ratioType: ratioLabel,
|
||||
groupRatio: groupRatio,
|
||||
cacheRatio: cacheRatio,
|
||||
cacheCreationRatio: cacheCreationRatio,
|
||||
},
|
||||
);
|
||||
} else {
|
||||
return i18next.t('模型: {{ratio}} * {{ratioType}}: {{groupRatio}}', {
|
||||
ratio: modelRatio,
|
||||
ratioType: ratioLabel,
|
||||
groupRatio: groupRatio,
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
// 已统一至 renderModelPriceSimple,若仍有遗留引用,请改为传入 provider='claude'
|
||||
|
||||
/**
|
||||
* rehype 插件:将段落等文本节点拆分为逐词 <span>,并添加淡入动画 class。
|
||||
|
||||
@@ -65,6 +65,10 @@ export const useTaskLogsData = () => {
|
||||
const [isModalOpen, setIsModalOpen] = useState(false);
|
||||
const [modalContent, setModalContent] = useState('');
|
||||
|
||||
// 新增:视频预览弹窗状态
|
||||
const [isVideoModalOpen, setIsVideoModalOpen] = useState(false);
|
||||
const [videoUrl, setVideoUrl] = useState('');
|
||||
|
||||
// Form state
|
||||
const [formApi, setFormApi] = useState(null);
|
||||
let now = new Date();
|
||||
@@ -250,6 +254,12 @@ export const useTaskLogsData = () => {
|
||||
setIsModalOpen(true);
|
||||
};
|
||||
|
||||
// 新增:打开视频预览弹窗
|
||||
const openVideoModal = (url) => {
|
||||
setVideoUrl(url);
|
||||
setIsVideoModalOpen(true);
|
||||
};
|
||||
|
||||
// Initialize data
|
||||
useEffect(() => {
|
||||
const localPageSize = parseInt(localStorage.getItem('task-page-size')) || ITEMS_PER_PAGE;
|
||||
@@ -271,6 +281,11 @@ export const useTaskLogsData = () => {
|
||||
setIsModalOpen,
|
||||
modalContent,
|
||||
|
||||
// 新增:视频弹窗状态
|
||||
isVideoModalOpen,
|
||||
setIsVideoModalOpen,
|
||||
videoUrl,
|
||||
|
||||
// Form state
|
||||
formApi,
|
||||
setFormApi,
|
||||
@@ -297,6 +312,7 @@ export const useTaskLogsData = () => {
|
||||
refresh,
|
||||
copyText,
|
||||
openContentModal,
|
||||
openVideoModal, // 新增
|
||||
enrichLogs,
|
||||
syncPageData,
|
||||
|
||||
|
||||
@@ -1804,5 +1804,11 @@
|
||||
"已选择 {{selected}} / {{total}}": "Selected {{selected}} / {{total}}",
|
||||
"新获取的模型": "New models",
|
||||
"已有的模型": "Existing models",
|
||||
"搜索模型": "Search models"
|
||||
"搜索模型": "Search models",
|
||||
"缓存: {{cacheRatio}}": "Cache: {{cacheRatio}}",
|
||||
"缓存创建: {{cacheCreationRatio}}": "Cache creation: {{cacheCreationRatio}}",
|
||||
"图片输入: {{imageRatio}}": "Image input: {{imageRatio}}",
|
||||
"系统提示覆盖": "System prompt override",
|
||||
"模型: {{ratio}}": "Model: {{ratio}}",
|
||||
"专属倍率": "Exclusive group ratio"
|
||||
}
|
||||
Reference in New Issue
Block a user