feat: use last quote

0cde9a10 · archer · 59ddf09b · 0cde9a10 · 0cde9a10 · 0cde9a10
Commit 0cde9a10 authored May 30, 2023 by archer
7 changed files
--- a/src/api/chat.ts
+++ b/src/api/chat.ts
@@ -5,7 +5,7 @@ import { RequestPaging } from '../types/index';
 import type { ShareChatSchema } from '@/types/mongoSchema';
 import type { ShareChatEditType } from '@/types/model';
 import { Obj2Query } from '@/utils/tools';
-import { QuoteItemType } from '@/pages/api/openapi/kb/appKbSearch';
+import type { QuoteItemType } from '@/pages/api/openapi/kb/appKbSearch';
 import type { Props as UpdateHistoryProps } from '@/pages/api/chat/history/updateChatHistory';
 /**

--- a/src/pages/api/chat/chat.ts
+++ b/src/pages/api/chat/chat.ts
@@ -50,6 +50,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
    // 读取对话内容
    const prompts = [...content, prompt[0]];
    const {
      code = 200,
      systemPrompts = [],
@@ -61,7 +62,8 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
        const { code, searchPrompts, rawSearch, guidePrompt } = await appKbSearch({
          model,
          userId,
-          prompts,
+          fixedQuote: content[content.length - 1]?.quote || [],
+          prompt: prompt[0],
          similarity: ModelVectorSearchModeMap[model.chat.searchMode]?.similarity
        });
@@ -114,7 +116,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
      return res.end(response);
    }
-    prompts.splice(prompts.length - 3, 0, ...systemPrompts);
+    prompts.unshift(...systemPrompts);
    // content check
    await sensitiveCheck({

--- a/src/pages/api/chat/shareChat/chat.ts
+++ b/src/pages/api/chat/shareChat/chat.ts
@@ -47,7 +47,8 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
        const { code, searchPrompts } = await appKbSearch({
          model,
          userId,
-          prompts,
+          fixedQuote: [],
+          prompt: prompts[prompts.length - 1],
          similarity: ModelVectorSearchModeMap[model.chat.searchMode]?.similarity
        });
@@ -74,7 +75,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
      return res.send(systemPrompts[0]?.value);
    }
-    prompts.splice(prompts.length - 3, 0, ...systemPrompts);
+    prompts.unshift(...systemPrompts);
    // content check
    await sensitiveCheck({

--- a/src/pages/api/openapi/chat/chat.ts
+++ b/src/pages/api/openapi/chat/chat.ts
@@ -75,10 +75,11 @@ export default withNextCors(async function handler(req: NextApiRequest, res: Nex
    // 使用了知识库搜索
    if (model.chat.relatedKbs.length > 0) {
      const { code, searchPrompts } = await appKbSearch({
-        prompts,
-        similarity: ModelVectorSearchModeMap[model.chat.searchMode]?.similarity,
        model,
-        userId
+        userId,
+        fixedQuote: [],
+        prompt: prompts[prompts.length - 1],
+        similarity: ModelVectorSearchModeMap[model.chat.searchMode]?.similarity
      });
      // search result is empty
@@ -101,7 +102,7 @@ export default withNextCors(async function handler(req: NextApiRequest, res: Nex
      ];
    }
-    prompts.splice(prompts.length - 3, 0, ...systemPrompts);
+    prompts.unshift(...systemPrompts);
    // content check
    await sensitiveCheck({

--- a/src/pages/api/openapi/kb/appKbSearch.ts
+++ b/src/pages/api/openapi/kb/appKbSearch.ts
@@ -49,10 +49,11 @@ export default withNextCors(async function handler(req: NextApiRequest, res: Nex
    });
    const result = await appKbSearch({
+      model,
      userId,
-      prompts,
+      fixedQuote: [],
-      similarity,
+      prompt: prompts[prompts.length - 1],
-      model
+      similarity
    });
    jsonRes<Response>(res, {
@@ -70,67 +71,53 @@ export default withNextCors(async function handler(req: NextApiRequest, res: Nex
 export async function appKbSearch({
  model,
  userId,
-  prompts,
+  fixedQuote,
+  prompt,
  similarity
 }: {
+  model: ModelSchema;
  userId: string;
-  prompts: ChatItemSimpleType[];
+  fixedQuote: QuoteItemType[];
+  prompt: ChatItemSimpleType;
  similarity: number;
-  model: ModelSchema;
 }): Promise<Response> {
  const modelConstantsData = ChatModelMap[model.chat.chatModel];
-  // search two times.
-  const userPrompts = prompts.filter((item) => item.obj === 'Human');
-  const input: string[] = [
-    userPrompts[userPrompts.length - 1].value,
-    userPrompts[userPrompts.length - 2]?.value
-  ].filter((item) => item);
  // get vector
-  const promptVectors = await openaiEmbedding({
+  const promptVector = await openaiEmbedding({
    userId,
-    input,
+    input: [prompt.value],
    type: 'chat'
  });
  // search kb
-  const searchRes = await Promise.all(
+  const { rows: searchRes } = await PgClient.select<QuoteItemType>('modelData', {
-    promptVectors.map((promptVector) =>
-      PgClient.select<QuoteItemType>('modelData', {
    fields: ['id', 'q', 'a'],
    where: [
      `kb_id IN (${model.chat.relatedKbs.map((item) => `'${item}'`).join(',')})`,
      'AND',
-          `vector <=> '[${promptVector}]' < ${similarity}`
+      `vector <=> '[${promptVector[0]}]' < ${similarity}`
    ],
-        order: [{ field: 'vector', mode: `<=> '[${promptVector}]'` }],
+    order: [{ field: 'vector', mode: `<=> '[${promptVector[0]}]'` }],
-        limit: promptVectors.length === 1 ? 15 : 10
+    limit: 8
-      }).then((res) => res.rows)
+  });
-    )
-  );
  // filter same search result
  const idSet = new Set<string>();
-  const filterSearch = searchRes.map((search) =>
+  const filterSearch = [
-    search.filter((item) => {
+    ...searchRes.slice(0, 3),
+    ...fixedQuote.slice(0, 2),
+    ...searchRes.slice(3),
+    ...fixedQuote.slice(2, 5)
+  ].filter((item) => {
    if (idSet.has(item.id)) {
      return false;
    }
    idSet.add(item.id);
    return true;
-    })
+  });
-  );
-  // slice search result by rate.
-  const sliceRateMap: Record<number, number[]> = {
-    1: [1],
-    2: [0.7, 0.3]
-  };
-  const sliceRate = sliceRateMap[searchRes.length] || sliceRateMap[0];
  // 计算固定提示词的 token 数量
  const guidePrompt = model.chat.systemPrompt // user system prompt
    ? {
        obj: ChatRoleEnum.System,
@@ -154,24 +141,21 @@ export async function appKbSearch({
  const fixedSystemTokens = modelToolMap[model.chat.chatModel].countTokens({
    messages: [guidePrompt]
  });
-  const maxTokens = modelConstantsData.systemMaxToken - fixedSystemTokens;
+  const sliceResult = modelToolMap[model.chat.chatModel]
-  const sliceResult = sliceRate.map((rate, i) =>
-    modelToolMap[model.chat.chatModel]
    .tokenSlice({
-        maxToken: Math.round(maxTokens * rate),
+      maxToken: modelConstantsData.systemMaxToken - fixedSystemTokens,
-        messages: filterSearch[i].map((item) => ({
+      messages: filterSearch.map((item) => ({
        obj: ChatRoleEnum.System,
        value: `${item.q}\n${item.a}`
      }))
    })
-      .map((item) => item.value)
+    .map((item) => item.value);
-  );
  // slice filterSearch
-  const sliceSearch = filterSearch.map((item, i) => item.slice(0, sliceResult[i].length)).flat();
+  const rawSearch = filterSearch.slice(0, sliceResult.length);
  //  system prompt
-  const systemPrompt = sliceResult.flat().join('\n').trim();
+  const systemPrompt = sliceResult.join('\n').trim();
  /* 高相似度+不回复 */
  if (!systemPrompt && model.chat.searchMode === appVectorSearchModeEnum.hightSimilarity) {
@@ -206,7 +190,7 @@ export async function appKbSearch({
  return {
    code: 200,
-    rawSearch: sliceSearch,
+    rawSearch,
    guidePrompt: guidePrompt.value || '',
    searchPrompts: [
      {

--- a/src/service/utils/auth.ts
+++ b/src/service/utils/auth.ts
@@ -280,7 +280,8 @@ export const authChat = async ({
      {
        $project: {
          obj: '$content.obj',
-          value: '$content.value'
+          value: '$content.value',
+          quote: '$content.quote'
        }
      }
    ]);

--- a/src/service/utils/chat/index.ts
+++ b/src/service/utils/chat/index.ts
@@ -89,39 +89,55 @@ export const ChatContextFilter = ({
  prompts: ChatItemSimpleType[];
  maxTokens: number;
 }) => {
+  const systemPrompts: ChatItemSimpleType[] = [];
+  const chatPrompts: ChatItemSimpleType[] = [];
  let rawTextLen = 0;
-  const formatPrompts = prompts.map<ChatItemSimpleType>((item) => {
+  prompts.forEach((item) => {
    const val = simplifyStr(item.value);
    rawTextLen += val.length;
-    return {
+    const data = {
      obj: item.obj,
      value: val
    };
+    if (item.obj === ChatRoleEnum.System) {
+      systemPrompts.push(data);
+    } else {
+      chatPrompts.push(data);
+    }
  });
  // 长度太小时，不需要进行 token 截断
-  if (formatPrompts.length <= 2 || rawTextLen < maxTokens * 0.5) {
+  if (rawTextLen < maxTokens * 0.5) {
-    return formatPrompts;
+    return [...systemPrompts, ...chatPrompts];
  }
+  // 去掉 system 的 token
+  maxTokens -= modelToolMap[model].countTokens({
+    messages: systemPrompts
+  });
  // 根据 tokens 截断内容
  const chats: ChatItemSimpleType[] = [];
  // 从后往前截取对话内容
-  for (let i = formatPrompts.length - 1; i >= 0; i--) {
+  for (let i = chatPrompts.length - 1; i >= 0; i--) {
-    chats.unshift(formatPrompts[i]);
+    chats.unshift(chatPrompts[i]);
    const tokens = modelToolMap[model].countTokens({
      messages: chats
    });
    /* 整体 tokens 超出范围, system必须保留 */
-    if (tokens >= maxTokens && formatPrompts[i].obj !== ChatRoleEnum.System) {
+    if (tokens >= maxTokens) {
-      return chats.slice(1);
+      chats.shift();
+      break;
    }
  }
-  return chats;
+  return [...systemPrompts, ...chats];
 };
 /* stream response */