v4.5.1 (#417)

projects/app/src/global/common/api/billReq.d.ts

@@ -1,3 +0,0 @@
-export type CreateTrainingBillType = {
-  name: string;
-};

projects/app/src/global/common/api/pluginRes.d.ts

@@ -1,4 +0,0 @@
-export type FetchResultItem = {
-  url: string;
-  content: string;
-};

projects/app/src/global/common/api/systemRes.d.ts

@@ -4,7 +4,7 @@ import type {
   LLMModelItemType,
   VectorModelItemType
 } from '@/types/model';
-import type { FeConfigsType } from '@fastgpt/common/type/index.d';
+import type { FeConfigsType } from '@fastgpt/global/common/system/types/index.d';
 
 export type InitDateResponse = {
   chatModels: ChatModelItemType[];

projects/app/src/global/common/string/tools.ts

@@ -0,0 +1,108 @@
+import { getErrText } from '@fastgpt/global/common/error/utils';
+import { countPromptTokens } from '@/global/common/tiktoken';
+
+/* 
+    replace {{variable}} to value
+*/
+export function replaceVariable(text: string, obj: Record<string, string | number>) {
+  for (const key in obj) {
+    const val = obj[key];
+    if (typeof val !== 'string') continue;
+
+    text = text.replace(new RegExp(`{{(${key})}}`, 'g'), val);
+  }
+  return text || '';
+}
+
+/**
+ * text split into chunks
+ * maxLen - one chunk len. max: 3500
+ * overlapLen - The size of the before and after Text
+ * maxLen > overlapLen
+ */
+export const splitText2Chunks = ({ text = '', maxLen }: { text: string; maxLen: number }) => {
+  const overlapLen = Math.floor(maxLen * 0.2); // Overlap length
+  const tempMarker = 'SPLIT_HERE_SPLIT_HERE';
+
+  const stepReg: Record<number, RegExp> = {
+    0: /(\n\n)/g,
+    1: /([\n])/g,
+    2: /([。]|\.\s)/g,
+    3: /([！？]|!\s|\?\s)/g,
+    4: /([；]|;\s)/g,
+    5: /([，]|,\s)/g
+  };
+
+  const splitTextRecursively = ({ text = '', step }: { text: string; step: number }) => {
+    if (text.length <= maxLen) {
+      return [text];
+    }
+    const reg = stepReg[step];
+
+    if (!reg) {
+      // use slice-maxLen to split text
+      const chunks: string[] = [];
+      let chunk = '';
+      for (let i = 0; i < text.length; i += maxLen - overlapLen) {
+        chunk = text.slice(i, i + maxLen);
+        chunks.push(chunk);
+      }
+      return chunks;
+    }
+
+    // split text by delimiters
+    const splitTexts = text
+      .replace(reg, `$1${tempMarker}`)
+      .split(`${tempMarker}`)
+      .filter((part) => part);
+
+    let chunks: string[] = [];
+    let preChunk = '';
+    let chunk = '';
+    for (let i = 0; i < splitTexts.length; i++) {
+      let text = splitTexts[i];
+      // chunk over size
+      if (text.length > maxLen) {
+        const innerChunks = splitTextRecursively({ text, step: step + 1 });
+        if (innerChunks.length === 0) continue;
+        // If the last chunk is too small, it is merged into the next chunk
+        if (innerChunks[innerChunks.length - 1].length <= maxLen * 0.5) {
+          text = innerChunks.pop() || '';
+          chunks = chunks.concat(innerChunks);
+        } else {
+          chunks = chunks.concat(innerChunks);
+          continue;
+        }
+      }
+
+      chunk += text;
+      // size over lapLen, push it to next chunk
+      if (chunk.length > maxLen - overlapLen) {
+        preChunk += text;
+      }
+      if (chunk.length >= maxLen) {
+        chunks.push(chunk);
+        chunk = preChunk;
+        preChunk = '';
+      }
+    }
+
+    if (chunk && !chunks[chunks.length - 1].endsWith(chunk)) {
+      chunks.push(chunk);
+    }
+    return chunks;
+  };
+
+  try {
+    const chunks = splitTextRecursively({ text, step: 0 });
+
+    const tokens = chunks.reduce((sum, chunk) => sum + countPromptTokens(chunk, 'system'), 0);
+
+    return {
+      chunks,
+      tokens
+    };
+  } catch (err) {
+    throw new Error(getErrText(err));
+  }
+};

projects/app/src/global/common/tiktoken/index.ts

@@ -0,0 +1,95 @@
+/* Only the token of gpt-3.5-turbo is used */
+import { ChatItemType } from '@/types/chat';
+import { Tiktoken } from 'js-tiktoken/lite';
+import { adaptChat2GptMessages } from '@/utils/common/adapt/message';
+import { ChatCompletionRequestMessageRoleEnum } from '@fastgpt/global/core/ai/constant';
+import encodingJson from './cl100k_base.json';
+
+/* init tikToken obj */
+export function getTikTokenEnc() {
+  if (typeof window !== 'undefined' && window.TikToken) {
+    return window.TikToken;
+  }
+  if (typeof global !== 'undefined' && global.TikToken) {
+    return global.TikToken;
+  }
+
+  const enc = new Tiktoken(encodingJson);
+
+  if (typeof window !== 'undefined') {
+    window.TikToken = enc;
+  }
+  if (typeof global !== 'undefined') {
+    global.TikToken = enc;
+  }
+
+  return enc;
+}
+
+/* count one prompt tokens */
+export function countPromptTokens(
+  prompt = '',
+  role: '' | `${ChatCompletionRequestMessageRoleEnum}` = ''
+) {
+  const enc = getTikTokenEnc();
+  const text = `${role}\n${prompt}`;
+  try {
+    const encodeText = enc.encode(text);
+    return encodeText.length + 3; // 补充 role 估算值
+  } catch (error) {
+    return text.length;
+  }
+}
+
+/* count messages tokens */
+export function countMessagesTokens({ messages }: { messages: ChatItemType[] }) {
+  const adaptMessages = adaptChat2GptMessages({ messages, reserveId: true });
+
+  let totalTokens = 0;
+  for (let i = 0; i < adaptMessages.length; i++) {
+    const item = adaptMessages[i];
+    const tokens = countPromptTokens(item.content, item.role);
+    totalTokens += tokens;
+  }
+
+  return totalTokens;
+}
+
+export function sliceTextByTokens({ text, length }: { text: string; length: number }) {
+  const enc = getTikTokenEnc();
+
+  try {
+    const encodeText = enc.encode(text);
+    return enc.decode(encodeText.slice(0, length));
+  } catch (error) {
+    return text.slice(0, length);
+  }
+}
+
+/* slice messages from top to bottom by maxTokens */
+export function sliceMessagesTB({
+  messages,
+  maxTokens
+}: {
+  messages: ChatItemType[];
+  maxTokens: number;
+}) {
+  const adaptMessages = adaptChat2GptMessages({ messages, reserveId: true });
+  let reduceTokens = maxTokens;
+  let result: ChatItemType[] = [];
+
+  for (let i = 0; i < adaptMessages.length; i++) {
+    const item = adaptMessages[i];
+
+    const tokens = countPromptTokens(item.content, item.role);
+    reduceTokens -= tokens;
+
+    if (reduceTokens > 0) {
+      result.push(messages[i]);
+    } else {
+      break;
+    }
+  }
+
+  return result.length === 0 && messages[0] ? [messages[0]] : result;
+}