v4.5 (#403)

2025-08-03 05:19:51 +00:00 · 2023-10-17 10:00:32 +08:00
parent dd8f2744bf
commit 3b776b6639
98 changed files with 1525 additions and 983 deletions
--- a/projects/app/src/service/moduleDispatch/agent/classifyQuestion.ts
+++ b/projects/app/src/service/moduleDispatch/agent/classifyQuestion.ts
@@ -10,9 +10,11 @@ import { FlowModuleTypeEnum } from '@/constants/flow';
 import type { ModuleDispatchProps } from '@/types/core/chat/type';
 import { replaceVariable } from '@/utils/common/tools/text';
 import { Prompt_CQJson } from '@/global/core/prompt/agent';
-import { defaultCQModel } from '@/pages/api/system/getInitData';
+import { FunctionModelItemType } from '@/types/model';
+import { getCQModel } from '@/service/core/ai/model';

 type Props = ModuleDispatchProps<{
+  model: string;
  systemPrompt?: string;
  history?: ChatItemType[];
  [SystemInputEnum.userChatInput]: string;
@@ -30,20 +32,26 @@ export const dispatchClassifyQuestion = async (props: Props): Promise<CQResponse
  const {
    moduleName,
    user,
-    inputs: { agents, userChatInput }
+    inputs: { model, agents, userChatInput }
  } = props as Props;

  if (!userChatInput) {
    return Promise.reject('Input is empty');
  }

-  const cqModel = global.cqModel || defaultCQModel;
+  const cqModel = getCQModel(model);

  const { arg, tokens } = await (async () => {
    if (cqModel.functionCall) {
-      return functionCall(props);
+      return functionCall({
+        ...props,
+        cqModel
+      });
    }
-    return completions(props);
+    return completions({
+      ...props,
+      cqModel
+    });
  })();

  const result = agents.find((item) => item.key === arg?.type) || agents[agents.length - 1];
@@ -64,45 +72,45 @@ export const dispatchClassifyQuestion = async (props: Props): Promise<CQResponse

 async function functionCall({
  user,
+  cqModel,
  inputs: { agents, systemPrompt, history = [], userChatInput }
-}: Props) {
-  const cqModel = global.cqModel;
-
+}: Props & { cqModel: FunctionModelItemType }) {
  const messages: ChatItemType[] = [
-    ...(systemPrompt
-      ? [
-          {
-            obj: ChatRoleEnum.System,
-            value: systemPrompt
-          }
-        ]
-      : []),
    ...history,
    {
      obj: ChatRoleEnum.Human,
-      value: userChatInput
+      value: systemPrompt
+        ? `补充的背景知识:
+"""
+${systemPrompt}
+"""
+我的问题: ${userChatInput}
+      `
+        : userChatInput
    }
  ];
+
  const filterMessages = ChatContextFilter({
    messages,
    maxTokens: cqModel.maxToken
  });
  const adaptMessages = adaptChat2GptMessages({ messages: filterMessages, reserveId: false });

-  //   function body
+  // function body
  const agentFunction = {
    name: agentFunName,
-    description: '判断用户问题的类型属于哪方面，返回对应的字段',
+    description: '请根据对话记录及补充的背景知识，判断用户的问题类型，并返回对应的字段',
    parameters: {
      type: 'object',
      properties: {
        type: {
          type: 'string',
-          description: agents.map((item) => `${item.value}，返回：'${item.key}'`).join('；'),
+          description: `判断用户的问题类型，并返回对应的字段。下面是几种问题类型: ${agents
+            .map((item) => `${item.value}，返回：'${item.key}'`)
+            .join('；')}`,
          enum: agents.map((item) => item.key)
        }
-      },
-      required: ['type']
+      }
    }
  };
  const ai = getAIApi(user.openaiAccount, 48000);
@@ -133,15 +141,14 @@ async function functionCall({
 }

 async function completions({
+  cqModel,
  user,
  inputs: { agents, systemPrompt = '', history = [], userChatInput }
-}: Props) {
-  const extractModel = global.extractModel;
-
+}: Props & { cqModel: FunctionModelItemType }) {
  const messages: ChatItemType[] = [
    {
      obj: ChatRoleEnum.Human,
-      value: replaceVariable(extractModel.prompt || Prompt_CQJson, {
+      value: replaceVariable(cqModel.functionPrompt || Prompt_CQJson, {
        systemPrompt,
        typeList: agents.map((item) => `ID: "${item.key}", 问题类型:${item.value}`).join('\n'),
        text: `${history.map((item) => `${item.obj}:${item.value}`).join('\n')}
@@ -153,7 +160,7 @@ Human:${userChatInput}`
  const ai = getAIApi(user.openaiAccount, 480000);

  const data = await ai.chat.completions.create({
-    model: extractModel.model,
+    model: cqModel.model,
    temperature: 0.01,
    messages: adaptChat2GptMessages({ messages, reserveId: false }),
    stream: false
--- a/projects/app/src/service/moduleDispatch/agent/extract.ts
+++ b/projects/app/src/service/moduleDispatch/agent/extract.ts
@@ -9,7 +9,7 @@ import { FlowModuleTypeEnum } from '@/constants/flow';
 import type { ModuleDispatchProps } from '@/types/core/chat/type';
 import { Prompt_ExtractJson } from '@/global/core/prompt/agent';
 import { replaceVariable } from '@/utils/common/tools/text';
-import { defaultExtractModel } from '@/pages/api/system/getInitData';
+import { FunctionModelItemType } from '@/types/model';

 type Props = ModuleDispatchProps<{
  history?: ChatItemType[];
@@ -37,13 +37,19 @@ export async function dispatchContentExtract(props: Props): Promise<Response> {
    return Promise.reject('Input is empty');
  }

-  const extractModel = global.extractModel || defaultExtractModel;
+  const extractModel = global.extractModels[0];

  const { arg, tokens } = await (async () => {
    if (extractModel.functionCall) {
-      return functionCall(props);
+      return functionCall({
+        ...props,
+        extractModel
+      });
    }
-    return completions(props);
+    return completions({
+      ...props,
+      extractModel
+    });
  })();

  // remove invalid key
@@ -83,11 +89,10 @@ export async function dispatchContentExtract(props: Props): Promise<Response> {
 }

 async function functionCall({
+  extractModel,
  user,
  inputs: { history = [], content, extractKeys, description }
-}: Props) {
-  const extractModel = global.extractModel;
-
+}: Props & { extractModel: FunctionModelItemType }) {
  const messages: ChatItemType[] = [
    ...history,
    {
@@ -152,15 +157,14 @@ async function functionCall({
 }

 async function completions({
+  extractModel,
  user,
  inputs: { history = [], content, extractKeys, description }
-}: Props) {
-  const extractModel = global.extractModel;
-
+}: Props & { extractModel: FunctionModelItemType }) {
  const messages: ChatItemType[] = [
    {
      obj: ChatRoleEnum.Human,
-      value: replaceVariable(extractModel.prompt || Prompt_ExtractJson, {
+      value: replaceVariable(extractModel.functionPrompt || Prompt_ExtractJson, {
        description,
        json: extractKeys
          .map(
--- a/projects/app/src/service/moduleDispatch/chat/oneapi.ts
+++ b/projects/app/src/service/moduleDispatch/chat/oneapi.ts
@@ -7,7 +7,6 @@ import { textAdaptGptResponse } from '@/utils/adapt';
 import { getAIApi } from '@fastgpt/core/ai/config';
 import type { ChatCompletion, StreamChatType } from '@fastgpt/core/ai/type';
 import { TaskResponseKeyEnum } from '@/constants/chat';
-import { getChatModel } from '@/service/utils/data';
 import { countModelPrice } from '@/service/common/bill/push';
 import { ChatModelItemType } from '@/types/model';
 import { postTextCensor } from '@fastgpt/common/plusApi/censor';
@@ -15,12 +14,13 @@ import { ChatCompletionRequestMessageRoleEnum } from '@fastgpt/core/ai/constant'
 import { AppModuleItemType } from '@/types/app';
 import { countMessagesTokens, sliceMessagesTB } from '@/utils/common/tiktoken';
 import { adaptChat2GptMessages } from '@/utils/common/adapt/message';
-import { defaultQuotePrompt, defaultQuoteTemplate } from '@/global/core/prompt/AIChat';
+import { Prompt_QuotePromptList, Prompt_QuoteTemplateList } from '@/global/core/prompt/AIChat';
 import type { AIChatProps } from '@/types/core/aiChat';
 import { replaceVariable } from '@/utils/common/tools/text';
 import { FlowModuleTypeEnum } from '@/constants/flow';
 import type { ModuleDispatchProps } from '@/types/core/chat/type';
-import { responseWrite, responseWriteController } from '@/service/common/stream';
+import { responseWrite, responseWriteController } from '@fastgpt/common/tools/stream';
+import { getChatModel, ModelTypeEnum } from '@/service/core/ai/model';

 export type ChatProps = ModuleDispatchProps<
  AIChatProps & {
@@ -47,12 +47,13 @@ export const dispatchChatCompletion = async (props: ChatProps): Promise<ChatResp
    user,
    outputs,
    inputs: {
-      model = global.chatModels[0]?.model,
+      model,
      temperature = 0,
      maxToken = 4000,
      history = [],
      quoteQA = [],
      userChatInput,
+      isResponseAnswerText = true,
      systemPrompt = '',
      limitPrompt,
      quoteTemplate,
@@ -63,6 +64,8 @@ export const dispatchChatCompletion = async (props: ChatProps): Promise<ChatResp
    return Promise.reject('Question is empty');
  }

+  stream = stream && isResponseAnswerText;
+
  // temperature adapt
  const modelConstantsData = getChatModel(model);

@@ -110,18 +113,18 @@ export const dispatchChatCompletion = async (props: ChatProps): Promise<ChatResp
    model,
    temperature,
    max_tokens,
+    stream,
    messages: [
-      ...(modelConstantsData.defaultSystem
+      ...(modelConstantsData.defaultSystemChatPrompt
        ? [
            {
              role: ChatCompletionRequestMessageRoleEnum.System,
-              content: modelConstantsData.defaultSystem
+              content: modelConstantsData.defaultSystemChatPrompt
            }
          ]
        : []),
      ...messages
-    ],
-    stream
+    ]
  });

  const { answerText, totalTokens, completeMessages } = await (async () => {
@@ -172,7 +175,9 @@ export const dispatchChatCompletion = async (props: ChatProps): Promise<ChatResp
    [TaskResponseKeyEnum.responseData]: {
      moduleType: FlowModuleTypeEnum.chatNode,
      moduleName,
-      price: user.openaiAccount?.key ? 0 : countModelPrice({ model, tokens: totalTokens }),
+      price: user.openaiAccount?.key
+        ? 0
+        : countModelPrice({ model, tokens: totalTokens, type: ModelTypeEnum.chat }),
      model: modelConstantsData.name,
      tokens: totalTokens,
      question: userChatInput,
@@ -198,7 +203,7 @@ function filterQuote({
    maxTokens: model.quoteMaxToken,
    messages: quoteQA.map((item, index) => ({
      obj: ChatRoleEnum.System,
-      value: replaceVariable(quoteTemplate || defaultQuoteTemplate, {
+      value: replaceVariable(quoteTemplate || Prompt_QuoteTemplateList[0].value, {
        ...item,
        index: index + 1
      })
@@ -212,7 +217,7 @@ function filterQuote({
    filterQuoteQA.length > 0
      ? `${filterQuoteQA
          .map((item, index) =>
-            replaceVariable(quoteTemplate || defaultQuoteTemplate, {
+            replaceVariable(quoteTemplate || Prompt_QuoteTemplateList[0].value, {
              ...item,
              index: `${index + 1}`
            })
@@ -243,7 +248,7 @@ function getChatMessages({
  model: ChatModelItemType;
 }) {
  const question = quoteText
-    ? replaceVariable(quotePrompt || defaultQuotePrompt, {
+    ? replaceVariable(quotePrompt || Prompt_QuotePromptList[0].value, {
        quote: quoteText,
        question: userChatInput
      })
@@ -275,7 +280,7 @@ function getChatMessages({

  const filterMessages = ChatContextFilter({
    messages,
-    maxTokens: Math.ceil(model.contextMaxToken - 300) // filter token. not response maxToken
+    maxTokens: Math.ceil(model.maxToken - 300) // filter token. not response maxToken
  });

  const adaptMessages = adaptChat2GptMessages({ messages: filterMessages, reserveId: false });
@@ -294,7 +299,7 @@ function getMaxTokens({
  model: ChatModelItemType;
  filterMessages: ChatProps['inputs']['history'];
 }) {
-  const tokensLimit = model.contextMaxToken;
+  const tokensLimit = model.maxToken;
  /* count response max token */

  const promptsToken = countMessagesTokens({
@@ -349,7 +354,7 @@ async function streamResponse({
      stream.controller?.abort();
      break;
    }
-    const content = part.choices[0]?.delta?.content || '';
+    const content = part.choices?.[0]?.delta?.content || '';
    answer += content;

    responseWrite({
--- a/projects/app/src/service/moduleDispatch/kb/search.ts
+++ b/projects/app/src/service/moduleDispatch/kb/search.ts
@@ -8,6 +8,7 @@ import type { QuoteItemType } from '@/types/chat';
 import { PgDatasetTableName } from '@/constants/plugin';
 import { FlowModuleTypeEnum } from '@/constants/flow';
 import type { ModuleDispatchProps } from '@/types/core/chat/type';
+import { ModelTypeEnum } from '@/service/core/ai/model';
 type KBSearchProps = ModuleDispatchProps<{
  kbList: SelectedDatasetType;
  similarity: number;
@@ -66,7 +67,11 @@ export async function dispatchKBSearch(props: Record<string, any>): Promise<KBSe
    responseData: {
      moduleType: FlowModuleTypeEnum.kbSearchNode,
      moduleName,
-      price: countModelPrice({ model: vectorModel.model, tokens: tokenLen }),
+      price: countModelPrice({
+        model: vectorModel.model,
+        tokens: tokenLen,
+        type: ModelTypeEnum.vector
+      }),
      model: vectorModel.name,
      tokens: tokenLen,
      similarity,
--- a/projects/app/src/service/moduleDispatch/tools/answer.ts
+++ b/projects/app/src/service/moduleDispatch/tools/answer.ts
@@ -1,5 +1,5 @@
 import { sseResponseEventEnum, TaskResponseKeyEnum } from '@/constants/chat';
-import { sseResponse } from '@/service/utils/tools';
+import { responseWrite } from '@fastgpt/common/tools/stream';
 import { textAdaptGptResponse } from '@/utils/adapt';
 import type { ModuleDispatchProps } from '@/types/core/chat/type';
 export type AnswerProps = ModuleDispatchProps<{
@@ -21,7 +21,7 @@ export const dispatchAnswer = (props: Record<string, any>): AnswerResponse => {
  const formatText = typeof text === 'string' ? text : JSON.stringify(text, null, 2);

  if (stream) {
-    sseResponse({
+    responseWrite({
      res,
      event: detail ? sseResponseEventEnum.answer : undefined,
      data: textAdaptGptResponse({
--- a/projects/app/src/service/moduleDispatch/tools/runApp.ts
+++ b/projects/app/src/service/moduleDispatch/tools/runApp.ts
@@ -3,7 +3,7 @@ import type { ModuleDispatchProps } from '@/types/core/chat/type';
 import { SelectAppItemType } from '@/types/core/app/flow';
 import { dispatchModules } from '@/pages/api/v1/chat/completions';
 import { App } from '@/service/mongo';
-import { responseWrite } from '@/service/common/stream';
+import { responseWrite } from '@fastgpt/common/tools/stream';
 import { ChatRoleEnum, TaskResponseKeyEnum, sseResponseEventEnum } from '@/constants/chat';
 import { textAdaptGptResponse } from '@/utils/adapt';