perf: agent call code

2026-01-21 01:15:42 +08:00 · 2025-09-16 23:11:54 +08:00
parent b31345a710
commit f1c5efa6cb
7 changed files with 133 additions and 163 deletions
--- a/packages/service/core/workflow/dispatch/ai/agent/constants.ts
+++ b/packages/service/core/workflow/dispatch/ai/agent/constants.ts
@@ -1,37 +1,40 @@
+import { SubAppIds } from './sub/constants';
+
 export const getMasterAgentDefaultPrompt = () => {
-  return `## 角色定位
-你是一个高级任务调度器（Task Orchestrator），负责分析用户需求、拆解并分派子任务、整合多Agent成果，确保最终产出具备高度专业性、系统性与洞见力。
+  return `## 工作流程
+你需要严格按照 [${SubAppIds.plan}] 提供的步骤逐步完成执行任务。`;
+  //   return `## 角色定位
+  // 你是一个高级任务调度器（Task Orchestrator），负责分析用户需求、拆解并分派子任务、整合多Agent成果，确保最终产出具备高度专业性、系统性与洞见力。

-## 核心职责
-### 粒度控制
- **原子任务原则**：每个子任务必须是单一、明确、可独立完成的
- **专业匹配原则**：根据任务属性，将子任务分配给最合适的专业Agent
- **避免任务过载**：不得将多个复杂任务打包给单个Agent
+  // ## 核心职责
+  // ### 粒度控制
+  // - **原子任务原则**：每个子任务必须是单一、明确、可独立完成的
+  // - **专业匹配原则**：根据任务属性，将子任务分配给最合适的专业Agent
+  // - **避免任务过载**：不得将多个复杂任务打包给单个Agent

-### 过程管理
- 制定清晰的执行顺序，保证任务逻辑链条完整
- 动态监控子任务进展，必要时调整分工或策略
- 保持信息透明，确保上下游Agent输出可直接衔接
+  // ### 过程管理
+  // - 制定清晰的执行顺序，保证任务逻辑链条完整
+  // - 动态监控子任务进展，必要时调整分工或策略
+  // - 保持信息透明，确保上下游Agent输出可直接衔接

-### 结果验证
- 校验每个子任务是否达成预期目标
- 严格检查输出的准确性、完整性和格式规范
- 确保所有结果的一致性、逻辑连贯性和互补性
+  // ### 结果验证
+  // - 校验每个子任务是否达成预期目标
+  // - 严格检查输出的准确性、完整性和格式规范
+  // - 确保所有结果的一致性、逻辑连贯性和互补性

-## 最终产出标准
-1. **专业性**：输出必须具备专家级深度，避免表面化结论
-2. **系统性**：结果需结构化呈现，覆盖任务的各个核心维度
-3. **多视角**：从战略、执行、风险、机遇等不同角度进行分析
-4. **洞见力**：在满足需求的基础上，提出更高层次的见解、趋势判断或改进建议
-5. **可操作性**：输出不仅是分析，还应包含可执行的步骤、优先级和资源需求
-6. **用户导向**：确保最终成果切合用户需求，且超出用户的预期价值
+  // ## 最终产出标准
+  // 1. **专业性**：输出必须具备专家级深度，避免表面化结论
+  // 2. **系统性**：结果需结构化呈现，覆盖任务的各个核心维度
+  // 3. **多视角**：从战略、执行、风险、机遇等不同角度进行分析
+  // 4. **洞见力**：在满足需求的基础上，提出更高层次的见解、趋势判断或改进建议
+  // 5. **可操作性**：输出不仅是分析，还应包含可执行的步骤、优先级和资源需求
+  // 6. **用户导向**：确保最终成果切合用户需求，且超出用户的预期价值

-## 关键原则
-1. **分而治之**：复杂任务必须拆解，禁止直接交由单个Agent
-2. **专业对口**：匹配最合适的Agent来执行对应任务
-3. **循序渐进**：按照逻辑顺序推进，确保结果可堆叠与传递
-4. **结果导向**：始终聚焦最终输出的质量与用户满意度
-5. **灵活调整**：在任务推进中，根据结果反馈动态优化策略
-6. **高标准产出**：最终结果必须是专业、详细、系统且具备洞见的完整方案
-`;
+  // ## 关键原则
+  // 1. **分而治之**：复杂任务必须拆解，禁止直接交由单个Agent
+  // 2. **专业对口**：匹配最合适的Agent来执行对应任务
+  // 3. **循序渐进**：按照逻辑顺序推进，确保结果可堆叠与传递
+  // 4. **结果导向**：始终聚焦最终输出的质量与用户满意度
+  // 5. **灵活调整**：在任务推进中，根据结果反馈动态优化策略
+  // 6. **高标准产出**：最终结果必须是专业、详细、系统且具备洞见的完整方案`;
 };
--- a/packages/service/core/workflow/dispatch/ai/agent/index.ts
+++ b/packages/service/core/workflow/dispatch/ai/agent/index.ts
@@ -46,6 +46,7 @@ import type { ChatCompletionMessageParam } from '@fastgpt/global/core/ai/type';
 import { dispatchFileRead } from './sub/file';
 import { dispatchApp, dispatchPlugin } from './sub/app';
 import { getSubAppsPrompt } from './sub/plan/prompt';
+import { parseAgentSystemPrompt } from './utils';

 export type DispatchAgentModuleProps = ModuleDispatchProps<{
  [NodeInputKeyEnum.history]?: ChatItemType[];
@@ -101,21 +102,25 @@ export const dispatchRunAgent = async (props: DispatchAgentModuleProps): Promise

  const masterMessagesKey = `masterMessages-${nodeId}`;
  const planMessagesKey = `planMessages-${nodeId}`;
+  const planToolCallMessagesKey = `planToolCallMessages-${nodeId}`;

  // Get history messages
-  const { masterHistoryMessages, planHistoryMessages } = (() => {
+  let { masterHistoryMessages, planHistoryMessages, planToolCallMessages } = (() => {
    const lastHistory = chatHistories[chatHistories.length - 1];
    if (lastHistory && lastHistory.obj === ChatRoleEnum.AI) {
      return {
        masterHistoryMessages: (lastHistory.memories?.[masterMessagesKey] ||
          []) as ChatCompletionMessageParam[],
        planHistoryMessages: (lastHistory.memories?.[planMessagesKey] ||
+          []) as ChatCompletionMessageParam[],
+        planToolCallMessages: (lastHistory.memories?.[planToolCallMessagesKey] ||
          []) as ChatCompletionMessageParam[]
      };
    }
    return {
      masterHistoryMessages: [],
-      planHistoryMessages: []
+      planHistoryMessages: [],
+      planToolCallMessages: []
    };
  })();

@@ -188,65 +193,69 @@ export const dispatchRunAgent = async (props: DispatchAgentModuleProps): Promise
      Sub agent
      只会执行一次，肯定有。
    */
-    let masterPlanToolCallMessages: ChatCompletionMessageParam[] = [];
-
    if (
-      // 不为 userSelect 和 userInput，或者如果为 agentPlanCheck 并且 interactiveInput !== ConfirmPlanAgentText 都会执行
-      (lastInteractive?.type !== 'userSelect' &&
-        lastInteractive?.type !== 'userInput' &&
-        lastInteractive?.type !== 'agentPlanCheck') ||
-      (lastInteractive?.type === 'agentPlanCheck' && interactiveInput !== ConfirmPlanAgentText)
+      // 如果是 userSelect 和 userInput，说明不是 plan 触发的交互。
+      lastInteractive?.type !== 'userSelect' &&
+      lastInteractive?.type !== 'userInput'
    ) {
-      // 临时代码
-      const tmpText = '正在进行规划生成...\n';
-      workflowStreamResponse?.({
-        event: SseResponseEventEnum.answer,
-        data: textAdaptGptResponse({
-          text: tmpText
-        })
-      });
+      // Confirm 操作
+      if (lastInteractive?.type === 'agentPlanCheck' && interactiveInput === ConfirmPlanAgentText) {
+      } else {
+        // 临时代码
+        const tmpText = '正在进行规划生成...\n';
+        workflowStreamResponse?.({
+          event: SseResponseEventEnum.answer,
+          data: textAdaptGptResponse({
+            text: tmpText
+          })
+        });

-      const {
-        answerText,
-        planList,
-        planToolCallMessages,
-        completeMessages,
-        usages,
-        interactiveResponse
-      } = await dispatchPlanAgent({
-        historyMessages: planHistoryMessages,
-        userInput: lastInteractive ? interactiveInput : taskInput,
-        interactive: lastInteractive,
-        subAppPrompt: getSubAppsPrompt({ subAppList, getSubAppInfo }),
-        model,
-        systemPrompt,
-        temperature,
-        top_p: aiChatTopP,
-        stream,
-        isTopPlanAgent: workflowDispatchDeep === 1
-      });
+        const {
+          answerText,
+          planList,
+          planToolCallMessages: newPlanToolCallMessages,
+          completeMessages,
+          usages,
+          interactiveResponse
+        } = await dispatchPlanAgent({
+          historyMessages: planHistoryMessages,
+          userInput: lastInteractive ? interactiveInput : taskInput,
+          interactive: lastInteractive,
+          subAppPrompt: getSubAppsPrompt({ subAppList, getSubAppInfo }),
+          model,
+          systemPrompt: parseAgentSystemPrompt({
+            systemPrompt,
+            getSubAppInfo
+          }),
+          temperature,
+          top_p: aiChatTopP,
+          stream,
+          isTopPlanAgent: workflowDispatchDeep === 1
+        });

-      const text = `${answerText}${planList ? `\n\`\`\`json\n${JSON.stringify(planList, null, 2)}\n\`\`\`` : ''}`;
-      workflowStreamResponse?.({
-        event: SseResponseEventEnum.answer,
-        data: textAdaptGptResponse({
-          text
-        })
-      });
+        const text = `${answerText}${planList ? `\n\`\`\`json\n${JSON.stringify(planList, null, 2)}\n\`\`\`` : ''}`;
+        workflowStreamResponse?.({
+          event: SseResponseEventEnum.answer,
+          data: textAdaptGptResponse({
+            text
+          })
+        });

-      planMessages = completeMessages;
-      masterPlanToolCallMessages = planToolCallMessages;
+        planMessages = completeMessages;
+        planToolCallMessages = newPlanToolCallMessages;

-      // TODO: usage 合并
-      // Sub agent plan 不会有交互响应。Top agent plan 肯定会有。
-      if (interactiveResponse) {
-        return {
-          [DispatchNodeResponseKeyEnum.answerText]: `${tmpText}${text}`,
-          [DispatchNodeResponseKeyEnum.memories]: {
-            [planMessagesKey]: filterMemoryMessages(planMessages)
-          },
-          [DispatchNodeResponseKeyEnum.interactive]: interactiveResponse
-        };
+        // TODO: usage 合并
+        // Sub agent plan 不会有交互响应。Top agent plan 肯定会有。
+        if (interactiveResponse) {
+          return {
+            [DispatchNodeResponseKeyEnum.answerText]: `${tmpText}${text}`,
+            [DispatchNodeResponseKeyEnum.memories]: {
+              [planMessagesKey]: filterMemoryMessages(planMessages),
+              [planToolCallMessagesKey]: planToolCallMessages
+            },
+            [DispatchNodeResponseKeyEnum.interactive]: interactiveResponse
+          };
+        }
      }
    }

@@ -262,7 +271,7 @@ export const dispatchRunAgent = async (props: DispatchAgentModuleProps): Promise
        return masterHistoryMessages;
      }

-      return chats2GPTMessages({ messages: chatHistories, reserveId: false });
+      return [];
    })();

    const userMessages = chats2GPTMessages({
@@ -280,9 +289,10 @@ export const dispatchRunAgent = async (props: DispatchAgentModuleProps): Promise
    const requestMessages = [
      ...systemMessages,
      ...historyMessages,
-      ...masterPlanToolCallMessages,
-      ...userMessages
+      ...userMessages,
+      ...planToolCallMessages
    ];
+    console.log(JSON.stringify({ requestMessages }, null, 2));

    const dispatchFlowResponse: ChatHistoryItemResType[] = [];
    const {
--- a/packages/service/core/workflow/dispatch/ai/agent/sub/constants.ts
+++ b/packages/service/core/workflow/dispatch/ai/agent/sub/constants.ts
@@ -15,7 +15,7 @@ export const systemSubInfo: Record<
  [SubAppIds.plan]: {
    name: i18nT('chat:plan_agent'),
    avatar: 'common/detail',
-    toolDescription: '分析和拆解用户问题，制定分步计划。'
+    toolDescription: '分析和拆解用户问题，制定执行步骤。'
  },
  [SubAppIds.fileRead]: {
    name: i18nT('chat:file_parse'),
--- a/packages/service/core/workflow/dispatch/ai/agent/sub/index.ts
+++ b/packages/service/core/workflow/dispatch/ai/agent/sub/index.ts
@@ -1,5 +1,4 @@
 import type { ChatCompletionTool } from '@fastgpt/global/core/ai/type';
-import { PlanAgentTool } from './plan/constants';
 import { readFileTool } from './file/utils';
 import type { FlowNodeInputItemType } from '@fastgpt/global/core/workflow/type/io';
 import type { JSONSchemaInputType } from '@fastgpt/global/core/app/jsonschema';
@@ -79,7 +78,11 @@ export const getSubApps = ({
  ];

  // Node Tools
-  const nodeTools = subApps.map<ChatCompletionTool>((item) => {
+  const unitNodeTools = subApps.filter(
+    (item, index, array) => array.findIndex((app) => app.pluginId === item.pluginId) === index
+  );
+
+  const nodeTools = unitNodeTools.map<ChatCompletionTool>((item) => {
    const toolParams: FlowNodeInputItemType[] = [];
    let jsonSchema: JSONSchemaInputType | undefined;

--- a/packages/service/core/workflow/dispatch/ai/agent/sub/plan/index.ts
+++ b/packages/service/core/workflow/dispatch/ai/agent/sub/plan/index.ts
@@ -1,7 +1,4 @@
-import type {
-  ChatCompletionMessageParam,
-  ChatCompletionTool
-} from '@fastgpt/global/core/ai/type.d';
+import type { ChatCompletionMessageParam } from '@fastgpt/global/core/ai/type.d';
 import { createLLMResponse } from '../../../../../../ai/llm/request';
 import { getPlanAgentPrompt } from './prompt';
 import { getLLMModel } from '../../../../../../ai/model';
@@ -85,7 +82,7 @@ export const dispatchPlanAgent = async ({
      content: userInput
    });
  }
-  console.log(JSON.stringify({ requestMessages }, null, 2));
+  // console.log(JSON.stringify({ requestMessages }, null, 2));

  const {
    answerText,
--- a/packages/service/core/workflow/dispatch/ai/agent/utils.ts
+++ b/packages/service/core/workflow/dispatch/ai/agent/utils.ts
@@ -1,64 +1,30 @@
-import type {
-  ChatCompletionAssistantMessageParam,
-  ChatCompletionMessageParam
-} from '@fastgpt/global/core/ai/type';
-import type { ToolNodeItemType } from './type';
-
-const namespaceMap = new Map<string, string>([
-  ['a', '子应用'],
-  ['t', '工具'],
-  ['d', '知识库'],
-  ['m', '模型']
-]);
-
-// e.g: {{@a.appId@}} -> a.appId
-const buildPattern = (options?: { prefix?: string }): RegExp => {
-  const config = {
-    prefix: '@',
-    ...options
-  };
-
-  const escapedPrefix = config.prefix.replace(/[.*+?^${}()|[\]\\]/g, '\\$&');
-  return new RegExp(`\\{\\{${escapedPrefix}([^${escapedPrefix}]+)${escapedPrefix}\\}\\}`, 'g');
-};
-
-export const getSubIdsByAgentSystem = (
-  systemPrompt: string,
-  options?: { prefix?: string }
-): string[] => {
-  const pattern = buildPattern(options);
-  const ids: string[] = [];
-  let match;
-
-  while ((match = pattern.exec(systemPrompt)) !== null) {
-    const fullName = match[1];
-    const [, id] = fullName.split('.');
-    if (id) {
-      ids.push(id);
-    }
-  }
-
-  return ids;
-};
-
-export const parseAgentSystem = ({
+/* 
+  匹配 {{@toolId@}}，转化成: @name 的格式。
+*/
+export const parseAgentSystemPrompt = ({
  systemPrompt,
-  toolNodesMap,
-  options
+  getSubAppInfo
 }: {
  systemPrompt: string;
-  toolNodesMap: Map<string, ToolNodeItemType>;
-  options?: { prefix?: string };
+  getSubAppInfo: (id: string) => {
+    name: string;
+    avatar: string;
+    toolDescription: string;
+  };
 }): string => {
-  const pattern = buildPattern(options);
+  if (!systemPrompt) return '';

-  const processedPrompt = systemPrompt.replace(pattern, (_, toolName) => {
-    const [namespace, id] = toolName.split('.');
-    const toolNode = toolNodesMap.get(id);
-    const name = toolNode?.name || toolNode?.toolDescription || toolNode?.intro || 'unknown';
+  // Match pattern {{@toolId@}} and convert to @name format
+  const pattern = /\{\{@([^@]+)@\}\}/g;

-    const prefix = namespaceMap.get(namespace) ?? 'unknown';
-    return `${prefix}:${name}`;
+  const processedPrompt = systemPrompt.replace(pattern, (match, toolId) => {
+    const toolInfo = getSubAppInfo(toolId);
+    if (!toolInfo) {
+      console.warn(`Tool not found for ID: ${toolId}`);
+      return match; // Return original match if tool not found
+    }
+
+    return `@${toolInfo.name}`;
  });

  return processedPrompt;
--- a/projects/app/src/components/core/chat/components/AIResponseBox.tsx
+++ b/projects/app/src/components/core/chat/components/AIResponseBox.tsx
@@ -14,13 +14,12 @@ import type {
  AIChatItemValueItemType,
  ToolModuleResponseItemType
 } from '@fastgpt/global/core/chat/type';
-import React, { useState, useCallback, useMemo } from 'react';
+import React, { useCallback, useMemo } from 'react';
 import MyIcon from '@fastgpt/web/components/common/Icon';
 import Avatar from '@fastgpt/web/components/common/Avatar';
 import type {
  InteractiveBasicType,
  PaymentPauseInteractive,
-  InteractiveNodeResponseType,
  UserInputInteractive,
  UserSelectInteractive
 } from '@fastgpt/global/core/workflow/template/system/interactive/type';
@@ -148,7 +147,6 @@ const RenderTool = React.memo(
    onOpenCiteModal?: (e?: OnOpenCiteModalProps) => void;
  }) {
    const { t } = useSafeTranslation();
-    const [userOnchange, setUserOnchange] = useState(false);
    const formatJson = (string: string) => {
      try {
        return JSON.stringify(JSON.parse(string), null, 2);
@@ -160,14 +158,7 @@ const RenderTool = React.memo(
    const response = formatJson(tool.response);

    return (
-      <Accordion
-        key={tool.id}
-        allowToggle
-        index={userOnchange ? undefined : showAnimation ? 0 : undefined}
-        onChange={() => {
-          setUserOnchange(true);
-        }}
-      >
+      <Accordion key={tool.id} allowToggle>
        <AccordionItem borderTop={'none'} borderBottom={'none'}>
          <AccordionButton {...accordionButtonStyle}>
            <Avatar src={tool.toolAvatar} w={'1.25rem'} h={'1.25rem'} borderRadius={'sm'} />
@@ -200,7 +191,7 @@ ${params}`}
 ${response}`}
              />
            )}
-            {subAppValue && (
+            {subAppValue && subAppValue.length > 0 && (
              <Box bg={'white'} p={2}>
                {subAppValue.map((value, index) => (
                  <AIResponseBox