agent test

2026-01-14 06:03:34 +08:00 · 2025-10-23 15:36:22 +08:00
parent 322dd28979
commit 9986d6ec34
5 changed files with 52 additions and 105 deletions
--- a/packages/service/core/workflow/dispatch/ai/agent/common/dependon.ts
+++ b/packages/service/core/workflow/dispatch/ai/agent/common/dependon.ts
@@ -17,9 +17,19 @@ export const getStepDependon = async ({
  addLog.debug('GetStepResponse start', { model, step });
  const historySummary = steps
    .filter((item) => item.summary)
-    .filter((item) => `- ${item.id}: ${item.summary}`)
+    .map((item) => `- ${item.id}: ${item.summary}`)
    .join('\n');

+  if (!historySummary) {
+    return {
+      depends: [],
+      usage: {
+        inputTokens: 0,
+        outputTokens: 0
+      }
+    };
+  }
+
  const prompt = `
  你是一个智能检索助手。现在需要执行一个新的步骤，请根据步骤描述和历史步骤的概括信息，判断哪些历史步骤的结果对当前步骤有帮助，并提取出来。
  
--- a/packages/service/core/workflow/dispatch/ai/agent/index.ts
+++ b/packages/service/core/workflow/dispatch/ai/agent/index.ts
@@ -27,7 +27,7 @@ import { getFileInputPrompt } from './sub/file/utils';
 import type { ChatCompletionMessageParam } from '@fastgpt/global/core/ai/type';
 import type { AgentPlanStepType, AgentPlanType } from './sub/plan/type';
 import type { localeType } from '@fastgpt/global/common/i18n/type';
-import { stepCall } from './call';
+import { stepCall } from './master/call';
 import type { ChatNodeUsageType } from '@fastgpt/global/support/wallet/bill/type';
 import { addLog } from '../../../../../common/system/log';

--- a/packages/service/core/workflow/dispatch/ai/agent/master/call.ts
+++ b/packages/service/core/workflow/dispatch/ai/agent/master/call.ts
@@ -1,11 +1,11 @@
 import type { ChatCompletionTool } from '@fastgpt/global/core/ai/type';
-import { runAgentCall } from '../../../../ai/llm/agentCall';
+import { runAgentCall } from '../../../../../ai/llm/agentCall';
 import { chats2GPTMessages, runtimePrompt2ChatsValue } from '@fastgpt/global/core/chat/adapt';
 import { ChatRoleEnum } from '@fastgpt/global/core/chat/constants';
-import { addFilePrompt2Input } from './sub/file/utils';
-import type { AgentPlanStepType } from './sub/plan/type';
-import type { GetSubAppInfoFnType } from './type';
-import { getMasterAgentSystemPrompt } from './constants';
+import { addFilePrompt2Input } from '../sub/file/utils';
+import type { AgentPlanStepType } from '../sub/plan/type';
+import type { GetSubAppInfoFnType } from '../type';
+import { getMasterAgentSystemPrompt } from '../constants';
 import type { RuntimeNodeItemType } from '@fastgpt/global/core/workflow/runtime/type';
 import { SseResponseEventEnum } from '@fastgpt/global/core/workflow/runtime/constants';
 import {
@@ -14,20 +14,20 @@ import {
  textAdaptGptResponse,
  valueTypeFormat
 } from '@fastgpt/global/core/workflow/runtime/utils';
-import { getWorkflowChildResponseWrite } from '../../utils';
-import { SubAppIds } from './sub/constants';
-import { parseToolArgs } from '../utils';
-import { dispatchModelAgent } from './sub/model';
-import { dispatchFileRead } from './sub/file';
+import { getWorkflowChildResponseWrite } from '../../../utils';
+import { SubAppIds } from '../sub/constants';
+import { parseToolArgs } from '../../utils';
+import { dispatchFileRead } from '../sub/file';
 import { NodeInputKeyEnum } from '@fastgpt/global/core/workflow/constants';
 import { FlowNodeTypeEnum } from '@fastgpt/global/core/workflow/node/constant';
-import { dispatchTool } from './sub/tool';
-import { dispatchApp, dispatchPlugin } from './sub/app';
+import { dispatchTool } from '../sub/tool';
+import { dispatchApp, dispatchPlugin } from '../sub/app';
 import { getErrText } from '@fastgpt/global/common/error/utils';
-import type { DispatchAgentModuleProps } from '.';
-import { getLLMModel } from '../../../../ai/model';
-import { createLLMResponse } from '../../../../ai/llm/request';
-import { addLog } from '../../../../../common/system/log';
+import type { DispatchAgentModuleProps } from '..';
+import { getLLMModel } from '../../../../../ai/model';
+import { createLLMResponse } from '../../../../../ai/llm/request';
+import { addLog } from '../../../../../../common/system/log';
+import { getStepDependon } from '../common/dependon';

 const getResponseSummary = async ({ response, model }: { response: string; model: string }) => {
  addLog.debug('GetResponseSummary start');
@@ -60,80 +60,6 @@ ${response}
    usage
  };
 };
-const getStepDependon = async ({
-  model,
-  steps,
-  step
-}: {
-  model: string;
-  steps: AgentPlanStepType[];
-  step: AgentPlanStepType;
-}) => {
-  const modelData = getLLMModel(model);
-  addLog.debug('GetStepResponse start', { model, step });
-  const historySummary = steps
-    .filter((item) => item.summary)
-    .map((item) => `- ${item.id}: ${item.summary}`)
-    .join('\n');
-
-  if (!historySummary) {
-    return {
-      depends: [],
-      usage: {
-        inputTokens: 0,
-        outputTokens: 0
-      }
-    };
-  }
-
-  const prompt = `
-你是一个智能检索助手。现在需要执行一个新的步骤，请根据步骤描述和历史步骤的概括信息，判断哪些历史步骤的结果对当前步骤有帮助，并提取出来。
-
-【当前需要执行的步骤】
-步骤ID: ${step.id}
-步骤标题: ${step.title}
-步骤描述: ${step.description}
-
-【已完成的历史步骤概括】
-${historySummary}
-
-【任务】
-请分析当前步骤的需求，判断需要引用哪些历史步骤的详细结果。
-如果不需要任何历史步骤，返回空列表。
-如果需要，请返回相关步骤的ID列表。
-
-【返回格式】（严格的JSON格式，不要包含其他文字）
-\`\`\`json
-{
-  "needed_step_ids": ["step1", "step2"],
-  "reason": "当前步骤需要整合美食和天气信息，因此需要 step1 和 step2 的结果"
-}
-\`\`\``;
-  console.log('Get dependon prompt', prompt);
-  const { answerText, usage } = await createLLMResponse({
-    body: {
-      model: modelData.model,
-      messages: [{ role: 'user', content: prompt }],
-      stream: false
-    }
-  });
-
-  const params = parseToolArgs<{
-    needed_step_ids: string[];
-    reason: string;
-  }>(answerText);
-  if (!params) {
-    return {
-      depends: [],
-      usage
-    };
-  }
-
-  return {
-    depends: params.needed_step_ids,
-    usage
-  };
-};

 export const stepCall = async ({
  getSubAppInfo,
@@ -172,7 +98,6 @@ export const stepCall = async ({
    step
  });
  step.depends_on = depends;
-  console.log(step.title, depends);

  const requestMessages = chats2GPTMessages({
    messages: [
@@ -201,7 +126,7 @@ export const stepCall = async ({
    ],
    reserveId: false
  });
-  console.log('Step call requestMessages', JSON.stringify(requestMessages, null, 2));
+  // console.log('Step call requestMessages', JSON.stringify(requestMessages, null, 2));
  const { assistantResponses, inputTokens, outputTokens, subAppUsages, interactiveResponse } =
    await runAgentCall({
      maxRunAgentTimes: 100,
--- a/packages/service/core/workflow/dispatch/ai/agent/sub/plan/index.ts
+++ b/packages/service/core/workflow/dispatch/ai/agent/sub/plan/index.ts
@@ -20,6 +20,7 @@ import { PlanAgentAskTool, type AskAgentToolParamsType } from './ask/constants';
 import { PlanCheckInteractive } from './constants';
 import type { AgentPlanType } from './type';
 import type { GetSubAppInfoFnType } from '../../type';
+import { getStepDependon } from '../../common/dependon';

 type PlanAgentConfig = {
  model: string;
@@ -92,6 +93,8 @@ export const dispatchPlanAgent = async ({
    });
  }

+  console.log('Plan request messages');
+  console.dir(requestMessages, { depth: null });
  const {
    answerText,
    toolCalls = [],
@@ -205,11 +208,18 @@ export const dispatchReplanAgent = async ({
  plan: AgentPlanType;
 }): Promise<DispatchPlanAgentResponse> => {
  const modelData = getLLMModel(model);
-  const replanSteps = plan.steps.filter((step) => (plan.replan || []).includes(step.id));
-  if (replanSteps.length === 0) {
-    console.log(plan);
-    return Promise.reject('No replan steps');
-  }
+
+  // 获取依赖的步骤
+  const { depends, usage: dependsUsage } = await getStepDependon({
+    model,
+    steps: plan.steps,
+    step: {
+      id: '',
+      title: '重新规划决策依据：需要依赖哪些步骤的判断',
+      description: '本步骤分析先前的执行结果，以确定重新规划时需要依赖哪些特定步骤。'
+    }
+  });
+  const replanSteps = plan.steps.filter((step) => depends.includes(step.id));

  const requestMessages: ChatCompletionMessageParam[] = [
    {
@@ -238,15 +248,17 @@ export const dispatchReplanAgent = async ({
  } else {
    requestMessages.push({
      role: 'user',
+      // 根据需要 replanSteps 生成用户输入
      content: getReplanAgentUserPrompt({
-        task: plan.task,
-        steps: replanSteps,
+        task: userInput,
+        dependsSteps: replanSteps,
        background,
        referencePlans
      })
    });
  }

+  console.log('Replan call messages', JSON.stringify(requestMessages, null, 2));
  const {
    answerText,
    toolCalls = [],
--- a/packages/service/core/workflow/dispatch/ai/agent/sub/plan/prompt.ts
+++ b/packages/service/core/workflow/dispatch/ai/agent/sub/plan/prompt.ts
@@ -433,21 +433,21 @@ export const getReplanAgentUserPrompt = ({
  task,
  background,
  referencePlans,
-  steps
+  dependsSteps
 }: {
  task: string;
  background?: string;
  referencePlans?: string;
-  steps: AgentPlanStepType[];
+  dependsSteps: AgentPlanStepType[];
 }) => {
-  const stepsResponsePrompt = steps
+  const stepsResponsePrompt = dependsSteps
    .map(
      (step) => `步骤 ${step.id}:
 - 标题: ${step.title}
 - 执行结果: ${step.response}`
    )
    .join('\n');
-  const stepsIdPrompt = steps.map((step) => step.id).join(', ');
+  const stepsIdPrompt = dependsSteps.map((step) => step.id).join(', ');

  return `任务目标：${task}