V4.6.9-first commit (#899)
* perf: insert mongo dataset data session * perf: dataset data index * remove delay * rename bill schema * rename bill record * perf: bill table * perf: prompt * perf: sub plan * change the usage count * feat: usage bill * publish usages * doc * 新增团队聊天功能 (#20) * perf: doc * feat 添加标签部分 feat 信息团队标签配置 feat 新增团队同步管理 feat team分享页面 feat 完成team分享页面 feat 实现模糊搜索 style 格式化 fix 修复迷糊匹配 style 样式修改 fix 团队标签功能修复 * fix 修复鉴权功能 * merge 合并代码 * fix 修复引用错误 * fix 修复pr问题 * fix 修复ts格式问题 --------- Co-authored-by: archer <545436317@qq.com> Co-authored-by: liuxingwan <liuxingwan.lxw@alibaba-inc.com> * update extra plan * fix: ts * format * perf: bill field * feat: standard plan * fix: ts * feat 个人账号页面修改 (#22) * feat 添加标签部分 feat 信息团队标签配置 feat 新增团队同步管理 feat team分享页面 feat 完成team分享页面 feat 实现模糊搜索 style 格式化 fix 修复迷糊匹配 style 样式修改 fix 团队标签功能修复 * fix 修复鉴权功能 * merge 合并代码 * fix 修复引用错误 * fix 修复pr问题 * fix 修复ts格式问题 * feat 修改个人账号页 --------- Co-authored-by: liuxingwan <liuxingwan.lxw@alibaba-inc.com> * sub plan page (#23) * fix chunk index; error page text * feat: dataset process Integral prediction * feat: stand plan field * feat: sub plan limit * perf: index * query extension * perf: share link push app name * perf: plan point unit * perf: get sub plan * perf: account page * feat 新增套餐详情弹窗代码 (#24) * merge 合并代码 * fix 新增套餐详情弹框 * fix 修复pr问题 * feat: change http node input to prompt editor (#21) * feat: change http node input to prompt editor * fix * split PromptEditor to HttpInput * Team plans (#25) * perf: pay check * perf: team plan test * plan limit check * replace sensitive text * perf: fix some null * collection null check * perf: plans modal * perf: http module * pacakge (#26) * individuation page and pay modal amount (#27) * feat: individuation page * team chat config * pay modal * plan count and replace invalid chars (#29) * fix: user oneapi * fix: training queue * fix: qa queue * perf: remove space chars * replace invalid chars * change httpinput dropdown menu (#28) * perf: http * reseet free plan * perf: plan code to packages * remove llm config to package * perf: code * perf: faq * fix: get team plan --------- Co-authored-by: yst <77910600+yu-and-liu@users.noreply.github.com> Co-authored-by: liuxingwan <liuxingwan.lxw@alibaba-inc.com> Co-authored-by: heheer <71265218+newfish-cmyk@users.noreply.github.com>
This commit is contained in:
Archer
@@ -1,17 +1,20 @@
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import { adaptChat2GptMessages } from '@fastgpt/global/core/chat/adapt';
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import { ChatContextFilter } from '@fastgpt/service/core/chat/utils';
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import { ChatContextFilter, countMessagesChars } from '@fastgpt/service/core/chat/utils';
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import type { moduleDispatchResType, ChatItemType } from '@fastgpt/global/core/chat/type.d';
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import { ChatRoleEnum } from '@fastgpt/global/core/chat/constants';
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import { getAIApi } from '@fastgpt/service/core/ai/config';
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import type { ClassifyQuestionAgentItemType } from '@fastgpt/global/core/module/type.d';
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import type {
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ClassifyQuestionAgentItemType,
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ModuleDispatchResponse
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} from '@fastgpt/global/core/module/type.d';
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import { ModuleInputKeyEnum, ModuleOutputKeyEnum } from '@fastgpt/global/core/module/constants';
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import type { ModuleDispatchProps } from '@fastgpt/global/core/module/type.d';
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import { replaceVariable } from '@fastgpt/global/common/string/tools';
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import { Prompt_CQJson } from '@/global/core/prompt/agent';
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import { LLMModelItemType } from '@fastgpt/global/core/ai/model.d';
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import { ModelTypeEnum, getLLMModel } from '@/service/core/ai/model';
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import { ModelTypeEnum, getLLMModel } from '@fastgpt/service/core/ai/model';
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import { getHistories } from '../utils';
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import { formatModelPrice2Store } from '@/service/support/wallet/bill/utils';
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import { formatModelChars2Points } from '@/service/support/wallet/usage/utils';
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type Props = ModuleDispatchProps<{
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[ModuleInputKeyEnum.aiModel]: string;
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@@ -20,10 +23,9 @@ type Props = ModuleDispatchProps<{
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[ModuleInputKeyEnum.userChatInput]: string;
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[ModuleInputKeyEnum.agents]: ClassifyQuestionAgentItemType[];
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}>;
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type CQResponse = {
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[ModuleOutputKeyEnum.responseData]: moduleDispatchResType;
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type CQResponse = ModuleDispatchResponse<{
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[key: string]: any;
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};
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}>;
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const agentFunName = 'classify_question';
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@@ -31,6 +33,7 @@ const agentFunName = 'classify_question';
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export const dispatchClassifyQuestion = async (props: Props): Promise<CQResponse> => {
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const {
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user,
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module: { name },
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histories,
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params: { model, history = 6, agents, userChatInput }
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} = props as Props;
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@@ -43,7 +46,7 @@ export const dispatchClassifyQuestion = async (props: Props): Promise<CQResponse
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const chatHistories = getHistories(history, histories);
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const { arg, inputTokens, outputTokens } = await (async () => {
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const { arg, charsLength } = await (async () => {
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if (cqModel.toolChoice) {
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return toolChoice({
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...props,
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@@ -60,25 +63,31 @@ export const dispatchClassifyQuestion = async (props: Props): Promise<CQResponse
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const result = agents.find((item) => item.key === arg?.type) || agents[agents.length - 1];
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const { total, modelName } = formatModelPrice2Store({
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const { totalPoints, modelName } = formatModelChars2Points({
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model: cqModel.model,
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inputLen: inputTokens,
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outputLen: outputTokens,
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type: ModelTypeEnum.llm
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charsLength,
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modelType: ModelTypeEnum.llm
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});
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return {
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[result.key]: true,
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[ModuleOutputKeyEnum.responseData]: {
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price: user.openaiAccount?.key ? 0 : total,
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totalPoints: user.openaiAccount?.key ? 0 : totalPoints,
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model: modelName,
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query: userChatInput,
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inputTokens,
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outputTokens,
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charsLength,
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cqList: agents,
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cqResult: result.value,
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contextTotalLen: chatHistories.length + 2
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}
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},
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[ModuleOutputKeyEnum.moduleDispatchBills]: [
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{
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moduleName: name,
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totalPoints: user.openaiAccount?.key ? 0 : totalPoints,
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model: modelName,
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charsLength
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}
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]
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};
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};
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@@ -149,11 +158,13 @@ ${systemPrompt}
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const arg = JSON.parse(
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response?.choices?.[0]?.message?.tool_calls?.[0]?.function?.arguments || ''
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);
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const functionChars =
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agentFunction.description.length +
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agentFunction.parameters.properties.type.description.length;
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return {
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arg,
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inputTokens: response.usage?.prompt_tokens || 0,
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outputTokens: response.usage?.completion_tokens || 0
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charsLength: countMessagesChars(messages) + functionChars
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};
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} catch (error) {
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console.log(agentFunction.parameters);
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@@ -163,8 +174,7 @@ ${systemPrompt}
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return {
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arg: {},
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inputTokens: 0,
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outputTokens: 0
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charsLength: 0
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};
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}
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}
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@@ -206,8 +216,7 @@ async function completions({
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agents.find((item) => answer.includes(item.key) || answer.includes(item.value))?.key || '';
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return {
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inputTokens: data.usage?.prompt_tokens || 0,
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outputTokens: data.usage?.completion_tokens || 0,
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charsLength: countMessagesChars(messages),
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arg: { type: id }
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};
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}
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