feat: chat quote

src/service/plugins/searchKb.ts

@@ -1,175 +0,0 @@
-import { PgClient } from '@/service/pg';
-import { ModelDataStatusEnum, ModelVectorSearchModeEnum, ChatModelMap } from '@/constants/model';
-import { ModelSchema } from '@/types/mongoSchema';
-import { openaiCreateEmbedding } from '../utils/chat/openai';
-import { ChatRoleEnum } from '@/constants/chat';
-import { modelToolMap } from '@/utils/chat';
-import { ChatItemSimpleType } from '@/types/chat';
-
-/**
- *  use openai embedding search kb
- */
-export const searchKb = async ({
-  userOpenAiKey,
-  prompts,
-  similarity = 0.2,
-  model,
-  userId
-}: {
-  userOpenAiKey?: string;
-  prompts: ChatItemSimpleType[];
-  model: ModelSchema;
-  userId: string;
-  similarity?: number;
-}): Promise<{
-  code: 200 | 201;
-  searchPrompts: {
-    obj: ChatRoleEnum;
-    value: string;
-  }[];
-}> => {
-  async function search(textArr: string[] = []) {
-    const limitMap: Record<ModelVectorSearchModeEnum, number> = {
-      [ModelVectorSearchModeEnum.hightSimilarity]: 15,
-      [ModelVectorSearchModeEnum.noContext]: 15,
-      [ModelVectorSearchModeEnum.lowSimilarity]: 20
-    };
-    // 获取提示词的向量
-    const { vectors: promptVectors } = await openaiCreateEmbedding({
-      userOpenAiKey,
-      userId,
-      textArr
-    });
-
-    const searchRes = await Promise.all(
-      promptVectors.map((promptVector) =>
-        PgClient.select<{ id: string; q: string; a: string }>('modelData', {
-          fields: ['id', 'q', 'a'],
-          where: [
-            ['status', ModelDataStatusEnum.ready],
-            'AND',
-            `kb_id IN (${model.chat.relatedKbs.map((item) => `'${item}'`).join(',')})`,
-            'AND',
-            `vector <=> '[${promptVector}]' < ${similarity}`
-          ],
-          order: [{ field: 'vector', mode: `<=> '[${promptVector}]'` }],
-          limit: limitMap[model.chat.searchMode]
-        }).then((res) => res.rows)
-      )
-    );
-
-    // Remove repeat record
-    const idSet = new Set<string>();
-    const filterSearch = searchRes.map((search) =>
-      search.filter((item) => {
-        if (idSet.has(item.id)) {
-          return false;
-        }
-        idSet.add(item.id);
-        return true;
-      })
-    );
-
-    return filterSearch.map((item) => item.map((item) => `${item.q}\n${item.a}`).join('\n'));
-  }
-  const modelConstantsData = ChatModelMap[model.chat.chatModel];
-
-  // search three times
-  const userPrompts = prompts.filter((item) => item.obj === 'Human');
-
-  const searchArr: string[] = [
-    userPrompts[userPrompts.length - 1].value,
-    userPrompts[userPrompts.length - 2]?.value
-  ].filter((item) => item);
-  const systemPrompts = await search(searchArr);
-
-  // filter system prompts.
-  const filterRateMap: Record<number, number[]> = {
-    1: [1],
-    2: [0.7, 0.3]
-  };
-  const filterRate = filterRateMap[systemPrompts.length] || filterRateMap[0];
-
-  // 计算固定提示词的 token 数量
-  const fixedPrompts = [
-    ...(model.chat.systemPrompt
-      ? [
-          {
-            obj: ChatRoleEnum.System,
-            value: model.chat.systemPrompt
-          }
-        ]
-      : []),
-    ...(model.chat.searchMode === ModelVectorSearchModeEnum.noContext
-      ? [
-          {
-            obj: ChatRoleEnum.System,
-            value: `知识库是关于"${model.name}"的内容,根据知识库内容回答问题.`
-          }
-        ]
-      : [
-          {
-            obj: ChatRoleEnum.System,
-            value: `玩一个问答游戏,规则为:
-1.你完全忘记你已有的知识
-2.你只回答关于"${model.name}"的问题
-3.你只从知识库中选择内容进行回答
-4.如果问题不在知识库中,你会回答:"我不知道。"
-请务必遵守规则`
-          }
-        ])
-  ];
-  const fixedSystemTokens = modelToolMap[model.chat.chatModel].countTokens({
-    messages: fixedPrompts
-  });
-  const maxTokens = modelConstantsData.systemMaxToken - fixedSystemTokens;
-
-  const filterSystemPrompt = filterRate
-    .map((rate, i) =>
-      modelToolMap[model.chat.chatModel].sliceText({
-        text: systemPrompts[i],
-        length: Math.floor(maxTokens * rate)
-      })
-    )
-    .join('\n')
-    .trim();
-
-  /* 高相似度+不回复 */
-  if (!filterSystemPrompt && model.chat.searchMode === ModelVectorSearchModeEnum.hightSimilarity) {
-    return {
-      code: 201,
-      searchPrompts: [
-        {
-          obj: ChatRoleEnum.System,
-          value: '对不起，你的问题不在知识库中。'
-        }
-      ]
-    };
-  }
-  /* 高相似度+无上下文，不添加额外知识,仅用系统提示词 */
-  if (!filterSystemPrompt && model.chat.searchMode === ModelVectorSearchModeEnum.noContext) {
-    return {
-      code: 200,
-      searchPrompts: model.chat.systemPrompt
-        ? [
-            {
-              obj: ChatRoleEnum.System,
-              value: model.chat.systemPrompt
-            }
-          ]
-        : []
-    };
-  }
-
-  /* 有匹配 */
-  return {
-    code: 200,
-    searchPrompts: [
-      {
-        obj: ChatRoleEnum.System,
-        value: `知识库:${filterSystemPrompt}`
-      },
-      ...fixedPrompts
-    ]
-  };
-};