perf: search prompt, upload step and psw len

client/src/service/moduleDispatch/agent/classifyQuestion.ts

@@ -30,6 +30,10 @@ const maxTokens = 3000;
 export const dispatchClassifyQuestion = async (props: Record<string, any>): Promise<CQResponse> => {
   const { agents, systemPrompt, history = [], userChatInput, userOpenaiAccount } = props as CQProps;
 
+  if (!userChatInput) {
+    return Promise.reject('Input is empty');
+  }
+
   const messages: ChatItemType[] = [
     ...(systemPrompt
       ? [

client/src/service/moduleDispatch/chat/oneapi.ts

@@ -192,7 +192,7 @@ function filterQuote({
     maxToken: model.quoteMaxToken,
     messages: quoteQA.map((item, i) => ({
       obj: ChatRoleEnum.System,
-      value: `${i + 1}. [${item.q}\n${item.a}]`
+      value: item.a ? `{instruction:${item.q},output:${item.a}}` : `{instruction:${item.q}}`
     }))
   });
 
@@ -202,7 +202,9 @@ function filterQuote({
   const quotePrompt =
     filterQuoteQA.length > 0
       ? `下面是知识库内容:
-${filterQuoteQA.map((item) => `{Q:${item.q},A:${item.a}}`).join('\n')}
+${filterQuoteQA
+  .map((item) => (item.a ? `{instruction:${item.q},output:${item.a}}` : `{instruction:${item.q}}`))
+  .join('\n')}
 `
       : '';
 

client/src/service/utils/chat/index.ts

@@ -21,13 +21,16 @@ export type StreamResponseType = {
 /* slice chat context by tokens */
 export const ChatContextFilter = ({
   model,
-  prompts,
+  prompts = [],
   maxTokens
 }: {
   model: string;
   prompts: ChatItemType[];
   maxTokens: number;
 }) => {
+  if (!Array.isArray(prompts)) {
+    return [];
+  }
   const rawTextLen = prompts.reduce((sum, item) => sum + item.value.length, 0);
 
   // If the text length is less than half of the maximum token, no calculation is required