mirror of
https://github.com/labring/FastGPT.git
synced 2025-07-23 13:03:50 +00:00
feat: limit prompt
This commit is contained in:
1
client/src/api/response/chat.d.ts
vendored
1
client/src/api/response/chat.d.ts
vendored
@@ -5,6 +5,7 @@ export interface InitChatResponse {
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chatId: string;
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modelId: string;
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systemPrompt?: string;
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limitPrompt?: string;
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model: {
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name: string;
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avatar: string;
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@@ -26,7 +26,7 @@ const MySelect = ({ placeholder, value, width = 'auto', list, onchange, ...props
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return (
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<Menu autoSelect={false} onOpen={onOpen} onClose={onClose}>
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<MenuButton as={'span'}>
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<MenuButton style={{ width: '100%' }} as={'span'}>
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<Button
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width={width}
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px={3}
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@@ -82,6 +82,7 @@ export const defaultModel: ModelSchema = {
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searchLimit: 5,
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searchEmptyText: '',
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systemPrompt: '',
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limitPrompt: '',
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temperature: 0,
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maxToken: 4000,
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chatModel: OpenAiChatEnum.GPT35
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@@ -101,6 +101,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
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},
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chatModel: model.chat.chatModel,
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systemPrompt: isOwner ? model.chat.systemPrompt : '',
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limitPrompt: isOwner ? model.chat.limitPrompt : '',
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history
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}
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});
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@@ -28,7 +28,11 @@ type Response = {
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userSystemPrompt: {
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obj: ChatRoleEnum;
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value: string;
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};
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}[];
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userLimitPrompt: {
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obj: ChatRoleEnum;
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value: string;
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}[];
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quotePrompt: {
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obj: ChatRoleEnum;
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value: string;
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@@ -130,17 +134,24 @@ export async function appKbSearch({
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// 计算固定提示词的 token 数量
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const userSystemPrompt = model.chat.systemPrompt // user system prompt
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? {
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obj: ChatRoleEnum.Human,
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value: model.chat.systemPrompt
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}
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: {
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obj: ChatRoleEnum.Human,
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value: `知识库是关于 ${model.name} 的内容,参考知识库回答问题。与 "${model.name}" 无关内容,直接回复: "我不知道"。`
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};
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? [
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{
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obj: ChatRoleEnum.System,
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value: model.chat.systemPrompt
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}
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]
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: [];
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const userLimitPrompt = [
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{
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obj: ChatRoleEnum.Human,
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value: model.chat.limitPrompt
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? model.chat.limitPrompt
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: `知识库是关于 ${model.name} 的内容,参考知识库回答问题。与 "${model.name}" 无关内容,直接回复: "我不知道"。`
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}
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];
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const fixedSystemTokens = modelToolMap[model.chat.chatModel].countTokens({
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messages: [userSystemPrompt]
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messages: [...userSystemPrompt, ...userLimitPrompt]
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});
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// filter part quote by maxToken
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@@ -164,6 +175,7 @@ export async function appKbSearch({
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return {
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rawSearch,
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userSystemPrompt,
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userLimitPrompt,
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quotePrompt: {
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obj: ChatRoleEnum.System,
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value: quoteText
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@@ -108,11 +108,12 @@ export default withNextCors(async function handler(req: NextApiRequest, res: Nex
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const {
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rawSearch = [],
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userSystemPrompt = [],
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userLimitPrompt = [],
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quotePrompt = []
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} = await (async () => {
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// 使用了知识库搜索
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if (model.chat.relatedKbs?.length > 0) {
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const { rawSearch, userSystemPrompt, quotePrompt } = await appKbSearch({
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const { rawSearch, quotePrompt, userSystemPrompt, userLimitPrompt } = await appKbSearch({
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model,
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userId,
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fixedQuote: history[history.length - 1]?.quote,
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@@ -123,21 +124,29 @@ export default withNextCors(async function handler(req: NextApiRequest, res: Nex
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return {
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rawSearch,
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userSystemPrompt: userSystemPrompt ? [userSystemPrompt] : [],
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userSystemPrompt,
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userLimitPrompt,
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quotePrompt: [quotePrompt]
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};
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}
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if (model.chat.systemPrompt) {
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return {
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userSystemPrompt: [
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{
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obj: ChatRoleEnum.System,
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value: model.chat.systemPrompt
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}
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]
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};
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}
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return {};
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return {
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userSystemPrompt: model.chat.systemPrompt
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? [
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{
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obj: ChatRoleEnum.System,
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value: model.chat.systemPrompt
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}
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]
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: [],
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userLimitPrompt: model.chat.limitPrompt
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? [
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{
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obj: ChatRoleEnum.Human,
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value: model.chat.limitPrompt
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}
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]
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: []
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};
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})();
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// search result is empty
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@@ -167,7 +176,13 @@ export default withNextCors(async function handler(req: NextApiRequest, res: Nex
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}
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// api messages. [quote,context,systemPrompt,question]
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const completePrompts = [...quotePrompt, ...prompts.slice(0, -1), ...userSystemPrompt, prompt];
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const completePrompts = [
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...quotePrompt,
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...userSystemPrompt,
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...prompts.slice(0, -1),
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...userLimitPrompt,
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prompt
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];
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// chat temperature
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const modelConstantsData = ChatModelMap[model.chat.chatModel];
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// FastGpt temperature range: 1~10
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@@ -176,7 +191,7 @@ export default withNextCors(async function handler(req: NextApiRequest, res: Nex
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);
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await sensitiveCheck({
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input: `${prompt.value}`
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input: `${userSystemPrompt[0]?.value}\n${userLimitPrompt[0]?.value}\n${prompt.value}`
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});
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// start model api. responseText and totalTokens: valid only if stream = false
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@@ -259,7 +274,7 @@ export default withNextCors(async function handler(req: NextApiRequest, res: Nex
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...(showAppDetail
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? {
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quote: rawSearch,
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systemPrompt: userSystemPrompt?.[0]?.value
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systemPrompt: `${userSystemPrompt[0]?.value}\n\n${userLimitPrompt[0]?.value}`
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}
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: {})
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}
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@@ -219,7 +219,7 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => {
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...item,
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status: 'finish',
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quoteLen,
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systemPrompt: chatData.systemPrompt
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systemPrompt: `${chatData.systemPrompt}\n\n${chatData.limitPrompt}`
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};
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})
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}));
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@@ -234,13 +234,14 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => {
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[
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chatId,
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modelId,
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chatData.systemPrompt,
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setChatData,
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loadHistory,
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loadMyModels,
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generatingMessage,
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setForbidLoadChatData,
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router
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router,
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chatData.systemPrompt,
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chatData.limitPrompt,
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loadHistory,
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loadMyModels
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]
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);
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@@ -749,7 +750,7 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => {
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px={[2, 4]}
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onClick={() => setShowSystemPrompt(item.systemPrompt || '')}
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>
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提示词
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提示词 & 限定词
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</Button>
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)}
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{!!item.quoteLen && (
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@@ -1,5 +1,15 @@
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import React, { useCallback, useState, useMemo } from 'react';
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import { Box, Flex, Button, FormControl, Input, Textarea, Divider } from '@chakra-ui/react';
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import {
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Box,
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Flex,
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Button,
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FormControl,
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Input,
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Textarea,
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Divider,
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Tooltip
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} from '@chakra-ui/react';
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import { QuestionOutlineIcon } from '@chakra-ui/icons';
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import { useQuery } from '@tanstack/react-query';
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import { useForm } from 'react-hook-form';
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import { useRouter } from 'next/router';
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@@ -20,6 +30,11 @@ import Avatar from '@/components/Avatar';
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import MySelect from '@/components/Select';
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import MySlider from '@/components/Slider';
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const systemPromptTip =
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'模型固定的引导词,通过调整该内容,可以引导模型聊天方向。该内容会被固定在上下文的开头。';
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const limitPromptTip =
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'限定模型对话范围,会被放置在本次提问前,拥有强引导和限定性。例如:\n1. 知识库是关于 Laf 的介绍,参考知识库回答问题,与 "Laf" 无关内容,直接回复: "我不知道"。\n2. 你仅回答关于 "xxx" 的问题,其他问题回复: "xxxx"';
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const Settings = ({ modelId }: { modelId: string }) => {
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const { toast } = useToast();
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const router = useRouter();
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@@ -60,7 +75,7 @@ const Settings = ({ modelId }: { modelId: string }) => {
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}
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return max;
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}, [getValues, setValue, refresh]);
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}, [getValues, setValue]);
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// 提交保存模型修改
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const saveSubmitSuccess = useCallback(
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@@ -211,7 +226,7 @@ const Settings = ({ modelId }: { modelId: string }) => {
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介绍
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</Box>
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<Textarea
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rows={5}
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rows={4}
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maxLength={500}
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placeholder={'给你的 AI 应用一个介绍'}
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{...register('intro')}
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@@ -225,11 +240,14 @@ const Settings = ({ modelId }: { modelId: string }) => {
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对话模型
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</Box>
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<MySelect
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width={['200px', '240px']}
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width={['100%', '280px']}
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value={getValues('chat.chatModel')}
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list={chatModelList.map((item) => ({
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id: item.chatModel,
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label: item.name
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label: `${item.name} (${formatPrice(
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ChatModelMap[getValues('chat.chatModel')]?.price,
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1000
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)} 元/1k tokens)`
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}))}
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onchange={(val: any) => {
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setValue('chat.chatModel', val);
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@@ -237,15 +255,6 @@ const Settings = ({ modelId }: { modelId: string }) => {
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}}
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/>
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</Flex>
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<Flex alignItems={'center'} mt={5}>
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<Box w={['60px', '100px', '140px']} flexShrink={0}>
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价格
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</Box>
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<Box fontSize={['sm', 'md']}>
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{formatPrice(ChatModelMap[getValues('chat.chatModel')]?.price, 1000)}
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元/1K tokens(包括上下文和回答)
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</Box>
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</Flex>
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<Flex alignItems={'center'} my={10}>
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<Box w={['60px', '100px', '140px']} flexShrink={0}>
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温度
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@@ -269,7 +278,7 @@ const Settings = ({ modelId }: { modelId: string }) => {
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</Flex>
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<Flex alignItems={'center'} mt={12} mb={10}>
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<Box w={['60px', '100px', '140px']} flexShrink={0}>
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最大长度
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回复上限
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</Box>
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<Box flex={1} ml={'10px'}>
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<MySlider
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@@ -292,15 +301,29 @@ const Settings = ({ modelId }: { modelId: string }) => {
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<Flex mt={10} alignItems={'flex-start'}>
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<Box w={['60px', '100px', '140px']} flexShrink={0}>
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提示词
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<Tooltip label={systemPromptTip}>
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<QuestionOutlineIcon display={['none', 'inline']} ml={1} />
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</Tooltip>
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</Box>
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<Textarea
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rows={8}
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placeholder={
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'模型默认的 prompt 词,通过调整该内容,可以引导模型聊天方向。\n\n如果使用了知识库搜索,没有填写该内容时,系统会自动补充提示词;如果填写了内容,则以填写的内容为准。'
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}
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placeholder={systemPromptTip}
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{...register('chat.systemPrompt')}
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></Textarea>
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</Flex>
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<Flex mt={5} alignItems={'flex-start'}>
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<Box w={['60px', '100px', '140px']} flexShrink={0}>
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限定词
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<Tooltip label={limitPromptTip}>
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<QuestionOutlineIcon display={['none', 'inline']} ml={1} />
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</Tooltip>
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</Box>
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<Textarea
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rows={5}
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placeholder={limitPromptTip}
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{...register('chat.limitPrompt')}
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></Textarea>
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</Flex>
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<Flex mt={5} alignItems={'center'}>
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<Box w={['60px', '100px', '140px']} flexShrink={0}></Box>
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@@ -43,7 +43,10 @@ const ModelSchema = new Schema({
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default: ''
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},
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systemPrompt: {
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// 系统提示词
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type: String,
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default: ''
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},
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limitPrompt: {
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type: String,
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default: ''
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},
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1
client/src/types/mongoSchema.d.ts
vendored
1
client/src/types/mongoSchema.d.ts
vendored
@@ -43,6 +43,7 @@ export interface ModelSchema {
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searchLimit: number;
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searchEmptyText: string;
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systemPrompt: string;
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limitPrompt: string;
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temperature: number;
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maxToken: number;
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chatModel: ChatModelType; // 聊天时用的模型,训练后就是训练的模型
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