add finishedWorkflow state and update on finishWorkflowNode

src/agents/workflows/orchestrator/nodes/finishWorkflowNode.ts

@@ -1,15 +1,32 @@
-import { AIMessage } from '@langchain/core/messages';
 import { createLogger } from '../../../../utils/logger.js';
 import { OrchestratorConfig, OrchestratorState } from '../types.js';
+import { finishedWorkflowParser } from './finishWorkflowPrompt.js';
+import { AIMessage } from '@langchain/core/messages';
 import { VectorDB } from '../../../../services/vectorDb/VectorDB.js';
-const logger = createLogger('workflow-summary-node');
+const logger = createLogger('finish-workflow-node');
+
+const parseFinishWorkflow = async (content: unknown) => {
+  const contentString = typeof content === 'string' ? content : JSON.stringify(content, null, 2);
+  if (typeof contentString === 'string') {
+    try {
+      return await finishedWorkflowParser.parse(contentString);
+    } catch (error) {
+      logger.error('Failed to parse workflow control. Applying fallback termination.', {
+        error,
+        content,
+      });
+      return { workflowSummary: 'Failed to parse workflow content' };
+    }
+  }
+  return { workflowSummary: 'Failed to parse workflow content' };
+};
 
 export const createFinishWorkflowNode = (
   { orchestratorModel, prompts }: OrchestratorConfig,
   vectorStore: VectorDB,
 ) => {
   const runNode = async (state: typeof OrchestratorState.State) => {
-    logger.info('Workflow Summary Node');
+    logger.info('Finish Workflow Node');
 
     const messages = state.messages
       .map(msg => {
@@ -26,14 +43,15 @@ export const createFinishWorkflowNode = (
     logger.info('Summarizing messages:', { messages });
 
     const result = await orchestratorModel.invoke(formattedPrompt);
+    const finishedWorkflow = await parseFinishWorkflow(result.content);
+
+    logger.info('Finished Workflow:', { finishedWorkflow });
 
-    const summary =
-      typeof result.content === 'string' ? result.content : JSON.stringify(result.content, null, 2);
+    await vectorStore.insert(JSON.stringify(finishedWorkflow));
 
-    logger.info('Workflow summary:', { summary });
-    await vectorStore.insert(summary);
     return {
-      messages: [new AIMessage({ content: `Workflow summary: ${summary}` })],
+      messages: [new AIMessage({ content: result.content })],
+      ...finishedWorkflow,
     };
   };
   return runNode;

src/agents/workflows/orchestrator/nodes/finishWorkflowPrompt.ts

@@ -1,23 +1,40 @@
 import { ChatPromptTemplate, PromptTemplate } from '@langchain/core/prompts';
 import { SystemMessage } from '@langchain/core/messages';
 import { config } from '../../../../config/index.js';
+import { StructuredOutputParser } from '@langchain/core/output_parsers';
+import { z } from 'zod';
 
 export const createFinishWorkflowPrompt = async (customInstructions?: string) => {
   const character = config.characterConfig;
 
+  const followFormatInstructions = `
+  IMPORTANT:
+  - Return ONLY the raw JSON data
+  - DO NOT include any markdown formatting, code blocks, or backticks
+  - DO NOT wrap response in code block markers
+  - Do not include any additional text or explanations
+  - The response should NOT start with \`\`\`json and end with \`\`\`
+  - The response should start and end with curly braces`;
+
   const workflowSummarySystemPrompt = await PromptTemplate.fromTemplate(
-    `Summarize the following messages in detail. This is being returned as a report to what was accomplished during the execution of the workflow.
+    `Summarize the following messages in detail. This is being returned as a report to what was accomplished during the execution of the workflow. Additionally, provide a recommendation for the next action to take when the workflow begins again and how long until the next workflow should begin.
 
     You have a personality, so you should act accordingly.
     {characterDescription}
     {characterPersonality}
 
     Custom Instructions:
-    {customInstructions}`,
+    {customInstructions}
+    
+    {followFormatInstructions}
+    Format Instructions:
+    {formatInstructions}`,
   ).format({
     characterDescription: character.description,
     characterPersonality: character.personality,
     customInstructions: customInstructions ?? 'None',
+    formatInstructions: finishedWorkflowParser.getFormatInstructions(),
+    followFormatInstructions,
   });
 
   const workflowSummaryPrompt = ChatPromptTemplate.fromMessages([
@@ -32,3 +49,22 @@ export const createFinishWorkflowPrompt = async (customInstructions?: string) =>
 
   return workflowSummaryPrompt;
 };
+
+const finishedWorkflowSchema = z.object({
+  workflowSummary: z.string().describe('A summary of the workflow.'),
+  nextRecommendedAction: z
+    .string()
+    .optional()
+    .describe(
+      'Given what was accomplished during the workflow and our overall goal,the next recommended action when the workflow begins again',
+    ),
+  secondsUntilNextWorkflow: z
+    .number()
+    .optional()
+    .describe(
+      'Given what was accomplished during the workflow and our overall goal, the recommended number of seconds until the workflow should begin again.',
+    ),
+});
+
+export const finishedWorkflowParser = StructuredOutputParser.fromZodSchema(finishedWorkflowSchema);
+export type FinishedWorkflow = z.infer<typeof finishedWorkflowSchema>;

src/agents/workflows/orchestrator/nodes/inputPrompt.ts

@@ -50,7 +50,6 @@ export const createInputPrompt = async (customInstructions?: string) => {
     [
       'human',
       `Based on the following messages, determine what actions should be taken.
-      Format your response as a JSON object with shouldStop (boolean) and reason (string).
 
       Messages: {messages}
       `,
@@ -61,8 +60,8 @@ export const createInputPrompt = async (customInstructions?: string) => {
 };
 
 const workflowControlSchema = z.object({
-  shouldStop: z.boolean(),
-  reason: z.string(),
+  shouldStop: z.boolean().describe('Whether the workflow should stop.'),
+  reason: z.string().describe('The reason for stopping the workflow.'),
 });
 
 export const workflowControlParser = StructuredOutputParser.fromZodSchema(workflowControlSchema);

src/agents/workflows/orchestrator/types.ts

@@ -5,7 +5,7 @@ import { ChatPromptTemplate } from '@langchain/core/prompts';
 import { config } from '../../../config/index.js';
 import { WorkflowControl } from './nodes/inputPrompt.js';
 import { LLMModelType } from '../../../services/llm/factory.js';
-
+import { FinishedWorkflow } from './nodes/finishWorkflowPrompt.js';
 export type OrchestratorPrompts = {
   inputPrompt: ChatPromptTemplate;
   messageSummaryPrompt: ChatPromptTemplate;
@@ -48,4 +48,8 @@ export const OrchestratorState = Annotation.Root({
     default: () => null,
     reducer: (_, update) => update,
   }),
+  finishedWorkflow: Annotation<FinishedWorkflow | null>({
+    default: () => null,
+    reducer: (_, update) => update,
+  }),
 });