WIP - using deep agent to create complex workflow
This commit is contained in:
Francisco Gaona
@@ -1,8 +1,9 @@
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import { BadRequestException, Injectable, Logger } from '@nestjs/common';
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import { JsonOutputParser } from '@langchain/core/output_parsers';
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import { HumanMessage, SystemMessage } from '@langchain/core/messages';
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import { AIMessage, BaseMessage, HumanMessage, SystemMessage } from '@langchain/core/messages';
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import { ChatOpenAI } from '@langchain/openai';
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import { Annotation, END, START, StateGraph } from '@langchain/langgraph';
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import { createDeepAgent } from 'deepagents';
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import { ObjectService } from '../object/object.service';
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import { PageLayoutService } from '../page-layout/page-layout.service';
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import { TenantDatabaseService } from '../tenant/tenant-database.service';
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@@ -68,32 +69,275 @@ export class AiAssistantService {
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const prior = this.conversationState.get(conversationKey);
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const trimmedHistory = Array.isArray(history) ? history.slice(-6) : [];
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const initialState: AiAssistantState = {
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message: this.combineHistory(trimmedHistory, message),
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history: trimmedHistory,
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context: context || {},
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extractedFields: prior?.fields,
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};
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// Use Deep Agent as the main coordinator
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const result = await this.runDeepAgent(tenantId, userId, message, trimmedHistory, context, prior);
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const finalState = await this.runAssistantGraph(tenantId, userId, initialState);
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if (finalState.record) {
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// Update conversation state based on result
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if (result.record) {
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this.conversationState.delete(conversationKey);
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} else if (finalState.extractedFields && Object.keys(finalState.extractedFields).length > 0) {
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} else if ('extractedFields' in result && result.extractedFields && Object.keys(result.extractedFields).length > 0) {
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this.conversationState.set(conversationKey, {
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fields: finalState.extractedFields,
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fields: result.extractedFields,
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updatedAt: Date.now(),
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});
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}
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return {
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reply: finalState.reply || 'How can I help?',
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action: finalState.action,
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missingFields: finalState.missingFields,
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record: finalState.record,
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reply: result.reply || 'How can I help?',
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action: result.action,
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missingFields: result.missingFields,
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record: result.record,
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};
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}
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private async runDeepAgent(
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tenantId: string,
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userId: string,
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message: string,
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history: AiAssistantState['history'],
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context: AiAssistantState['context'],
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prior?: { fields: Record<string, any>; updatedAt: number },
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): Promise<AiAssistantReply & { extractedFields?: Record<string, any> }> {
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const openAiConfig = await this.getOpenAiConfig(tenantId);
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if (!openAiConfig) {
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this.logger.warn('No OpenAI config found; using fallback graph execution.');
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// Fallback to direct graph execution if no OpenAI config
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const initialState: AiAssistantState = {
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message: this.combineHistory(history, message),
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history: history,
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context: context || {},
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extractedFields: prior?.fields,
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};
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const graph = this.buildResolveOrCreateRecordGraph(tenantId, userId);
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const result = await graph.invoke(initialState);
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return {
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reply: result.reply || 'How can I help?',
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action: result.action,
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missingFields: result.missingFields,
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record: result.record,
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};
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}
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// Build the compiled subagent
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const compiledSubagent = this.buildResolveOrCreateRecordGraph(tenantId, userId);
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// Create Deep Agent with the subagent
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const mainModel = new ChatOpenAI({
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apiKey: openAiConfig.apiKey,
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model: this.normalizeChatModel(openAiConfig.model),
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temperature: 0.3,
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});
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const systemPrompt = this.buildDeepAgentSystemPrompt(context);
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const agent = createDeepAgent({
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model: mainModel,
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systemPrompt,
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tools: [],
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subagents: [
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{
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name: 'resolve-or-create-record',
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description: [
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'ALWAYS use this subagent for ANY operation involving CRM records (create, find, or lookup).',
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'',
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'This subagent handles:',
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'- Looking up existing records by name or other fields',
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'- Creating new records with the provided field values',
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'- Resolving related records (e.g., finding an Account to link a Contact to)',
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'- Validating required fields before creating records',
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'',
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'IMPORTANT: When invoking this subagent, include in your message:',
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'- The exact user request',
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'- The object type (Account, Contact, etc.) if known from context',
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'- Any previously collected information',
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'',
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'Example invocations:',
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'- "Create Account named Acme Corp" (objectApiName: Account)',
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'- "Create Contact John Doe" (objectApiName: Contact)',
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'- "Add phone number 555-1234 for Contact John" (objectApiName: ContactDetail)',
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].join('\n'),
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runnable: compiledSubagent,
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},
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],
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});
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// Convert history to messages format
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const messages: BaseMessage[] = [];
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if (history && history.length > 0) {
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for (const entry of history) {
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if (entry.role === 'user') {
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messages.push(new HumanMessage(entry.text));
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} else if (entry.role === 'assistant') {
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messages.push(new AIMessage(entry.text));
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}
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}
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}
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messages.push(new HumanMessage(message));
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// Include context information in the first message if available
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let contextInfo = '';
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if (context?.objectApiName) {
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contextInfo += `\n[System Context: User is working with ${context.objectApiName} object`;
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if (context.recordId) {
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contextInfo += `, record ID: ${context.recordId}`;
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}
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contextInfo += ']';
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}
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if (prior?.fields && Object.keys(prior.fields).length > 0) {
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contextInfo += `\n[Previously collected field values: ${JSON.stringify(prior.fields)}]`;
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}
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if (contextInfo && messages.length > 0) {
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const lastMessage = messages[messages.length - 1];
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if (lastMessage instanceof HumanMessage) {
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messages[messages.length - 1] = new HumanMessage(
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lastMessage.content + contextInfo,
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);
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}
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}
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try {
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console.log('=== DEEP AGENT: Starting invocation ===');
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console.log('Messages:', messages.map(m => ({ role: m._getType(), content: m.content })));
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const result = await agent.invoke({ messages });
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console.log('=== DEEP AGENT: Result received ===');
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console.log('Result messages count:', result.messages.length);
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// Look for subagent results in the messages
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let subagentResult: any = null;
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for (let i = result.messages.length - 1; i >= 0; i--) {
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const msg = result.messages[i];
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console.log(`Message ${i}:`, {
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type: msg._getType(),
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content: typeof msg.content === 'string' ? msg.content.substring(0, 200) : msg.content,
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additional_kwargs: msg.additional_kwargs,
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});
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// Check if this message has subagent output data
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if (msg.additional_kwargs?.action || msg.additional_kwargs?.record) {
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subagentResult = msg.additional_kwargs;
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console.log('Found subagent result in message additional_kwargs:', subagentResult);
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break;
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}
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}
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const lastMsg = result.messages[result.messages.length - 1];
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const replyText = typeof lastMsg.content === 'string'
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? lastMsg.content
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: 'How can I help?';
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console.log('Final reply text:', replyText);
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// If we found subagent results, use them; otherwise use defaults
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if (subagentResult) {
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console.log('=== DEEP AGENT: Using subagent result ===');
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return {
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reply: replyText,
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action: subagentResult.action || 'clarify',
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missingFields: subagentResult.missingFields || [],
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record: subagentResult.record,
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extractedFields: subagentResult.extractedFields,
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};
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}
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console.log('=== DEEP AGENT: No subagent result found, using defaults ===');
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return {
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reply: replyText,
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action: 'clarify',
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missingFields: [],
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record: undefined,
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};
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} catch (error) {
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this.logger.error(`Deep Agent execution failed: ${error.message}`, error.stack);
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// Fallback to direct graph execution
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const initialState: AiAssistantState = {
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message: this.combineHistory(history, message),
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history: history,
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context: context || {},
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extractedFields: prior?.fields,
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};
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const graph = this.buildResolveOrCreateRecordGraph(tenantId, userId);
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const result = await graph.invoke(initialState);
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return {
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reply: result.reply || 'How can I help?',
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action: result.action,
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missingFields: result.missingFields,
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record: result.record,
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};
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}
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}
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private buildDeepAgentSystemPrompt(context?: AiAssistantState['context']): string {
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const contextInfo = context?.objectApiName
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? ` The user is currently working with the ${context.objectApiName} object.`
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: '';
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return [
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'You are an AI assistant helping users interact with a CRM system through natural conversation.',
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'Your role is to understand user requests and coordinate with specialized subagents to fulfill them.',
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'',
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'Core Responsibilities:',
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'- Parse user requests to understand what records they want to create or find',
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'- Identify the record type (Account, Contact, ContactDetail, etc.)',
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'- Break down complex multi-step requests into manageable tasks',
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'- ALWAYS delegate to the "resolve-or-create-record" subagent for ANY record operation',
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'',
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'Understanding Record Relationships:',
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'- When user says "Create X under Y account":',
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' 1. X is NOT an Account - it is a Contact or child record',
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' 2. Y is the parent Account name',
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' 3. You must: (a) First ensure Y account exists, (b) Then create X as a Contact under Y',
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'- Accounts are top-level organizations/companies',
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'- Contacts are people/entities that belong to Accounts',
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'- ContactDetails are phone/email/address records for Contacts or Accounts',
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'',
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'Multi-Step Example:',
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'- User: "Create Chipi under Jeannete Staley account"',
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' Step 1: Invoke subagent to find/create Account "Jeannete Staley" (objectApiName: Account)',
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' Step 2: Once account exists, invoke subagent to create Contact "Chipi" linked to that Account (objectApiName: Contact)',
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'',
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'When invoking the subagent:',
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'- Include the record type in parentheses: "Find Account Jeannete Staley (objectApiName: Account)"',
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'- For child records: "Create Contact Chipi for Account <id> (objectApiName: Contact)"',
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'- Pass the user\'s full request with context',
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'',
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'DO NOT try to create records yourself - ALWAYS use the subagent for:',
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' * Finding existing records',
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' * Creating new records',
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' * Resolving related records',
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'',
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'Important Patterns:',
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'- When a user says "Create X under/for Y", this means:',
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' 1. You need to first find or verify record Y exists',
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' 2. Then create record X with a reference to Y',
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' Example: "Create Max under John Doe Account" means find the Account named "John Doe",',
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' then create a record named "Max" that references that Account.',
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'',
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'- For polymorphic relationships (records that can reference multiple types):',
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' * ContactDetail records can reference either Account or Contact',
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' * Infer the correct type from context clues in the user\'s message',
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'',
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'CRITICAL - Checking Results:',
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'- After the subagent responds, CHECK if it actually completed the action',
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'- Look for phrases like "I still need" or "missing fields" which indicate incomplete work',
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'- If the subagent asks for more information, relay that to the user - DO NOT claim success',
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'- Only report success if the subagent explicitly confirms record creation',
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'- DO NOT fabricate success messages if the subagent indicates it needs more data',
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'',
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'Response Style:',
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'- Be conversational and helpful',
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'- Confirm what you\'re doing: "I\'ll create Max as a Contact under the John Doe Account"',
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'- Ask for clarification when the request is ambiguous',
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'- Report success clearly ONLY when confirmed: "Created Contact Max under John Doe Account"',
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'- If the subagent needs more info, ask the user for that specific information',
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'',
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contextInfo,
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].join('\n');
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}
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async searchRecords(
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tenantId: string,
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userId: string,
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@@ -196,13 +440,13 @@ export class AiAssistantService {
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};
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}
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private async runAssistantGraph(
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private buildResolveOrCreateRecordGraph(
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tenantId: string,
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userId: string,
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state: AiAssistantState,
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): Promise<AiAssistantState> {
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) {
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const AssistantState = Annotation.Root({
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message: Annotation<string>(),
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messages: Annotation<BaseMessage[]>(),
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history: Annotation<AiAssistantState['history']>(),
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context: Annotation<AiAssistantState['context']>(),
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objectDefinition: Annotation<any>(),
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@@ -215,33 +459,174 @@ export class AiAssistantService {
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reply: Annotation<string>(),
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});
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// Entry node to transform Deep Agent messages into our state format
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const transformInput = async (state: any): Promise<AiAssistantState> => {
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console.log('=== SUBAGENT: Transform Input ===');
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console.log('Received state keys:', Object.keys(state));
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console.log('Has messages:', state.messages ? state.messages.length : 'no');
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// If invoked by Deep Agent, state will have messages array
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if (state.messages && Array.isArray(state.messages)) {
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const lastMessage = state.messages[state.messages.length - 1];
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const messageText = typeof lastMessage.content === 'string'
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? lastMessage.content
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: '';
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console.log('Extracted message from Deep Agent:', messageText);
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// Try to extract context from message (Deep Agent should include it)
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const contextMatch = messageText.match(/\[System Context: User is working with (\w+) object(?:, record ID: ([^\]]+))?\]/);
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const priorFieldsMatch = messageText.match(/\[Previously collected field values: ({[^\]]+})\]/);
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let extractedContext: AiAssistantState['context'] = {};
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let extractedFields: Record<string, any> | undefined;
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if (contextMatch) {
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extractedContext.objectApiName = contextMatch[1];
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if (contextMatch[2]) {
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extractedContext.recordId = contextMatch[2];
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}
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console.log('Extracted context from annotations:', extractedContext);
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} else {
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// Fallback: Try to infer object type from the message itself
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console.log('No context annotation found, attempting to infer from message...');
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// Check for explicit objectApiName mentions in parentheses
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const explicitMatch = messageText.match(/\(objectApiName:\s*(\w+)\)/);
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if (explicitMatch) {
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extractedContext.objectApiName = explicitMatch[1];
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console.log('Found explicit objectApiName:', extractedContext.objectApiName);
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} else {
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// Try to infer from keywords and patterns
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const lowerMsg = messageText.toLowerCase();
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// Pattern: "Create X under/for Y account" - X is NOT an account, it's a child record
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const underAccountMatch = messageText.match(/create\s+([\w\s]+?)\s+(?:under|for)\s+([\w\s]+?)\s+account/i);
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if (underAccountMatch) {
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// The thing being created is likely a Contact or ContactDetail
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console.log('Detected "under account" pattern - inferring child record type');
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// Check if it's a contact detail (phone/email)
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if (lowerMsg.includes('phone') || lowerMsg.includes('email') || lowerMsg.includes('address')) {
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extractedContext.objectApiName = 'ContactDetail';
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} else {
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// Default to Contact for things created under accounts
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extractedContext.objectApiName = 'Contact';
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}
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console.log('Inferred child object type:', extractedContext.objectApiName);
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} else if (lowerMsg.includes('account') && (lowerMsg.includes('create') || lowerMsg.includes('add'))) {
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extractedContext.objectApiName = 'Account';
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} else if (lowerMsg.includes('contact') && !lowerMsg.includes('contact detail')) {
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extractedContext.objectApiName = 'Contact';
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} else if (lowerMsg.includes('contact detail') || lowerMsg.includes('contactdetail')) {
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extractedContext.objectApiName = 'ContactDetail';
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} else if (lowerMsg.includes('phone') || lowerMsg.includes('email')) {
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extractedContext.objectApiName = 'ContactDetail';
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}
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if (extractedContext.objectApiName) {
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console.log('Inferred objectApiName from keywords:', extractedContext.objectApiName);
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} else {
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console.warn('Could not infer objectApiName from message!');
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}
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}
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}
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if (priorFieldsMatch) {
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try {
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extractedFields = JSON.parse(priorFieldsMatch[1]);
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console.log('Extracted prior fields:', extractedFields);
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} catch (e) {
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console.warn('Failed to parse prior fields');
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}
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}
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// Clean the message text from system context annotations
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const cleanMessage = messageText
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.replace(/\[System Context:[^\]]+\]/g, '')
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.replace(/\[Previously collected field values:[^\]]+\]/g, '')
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.replace(/\(objectApiName:\s*\w+\)/g, '')
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.trim();
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console.log('Final transformed state:', {
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message: cleanMessage,
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context: extractedContext,
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hasExtractedFields: !!extractedFields,
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});
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return {
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message: cleanMessage,
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messages: state.messages,
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history: [],
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context: extractedContext,
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extractedFields,
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} as AiAssistantState;
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}
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// If invoked directly (fallback or testing), use the state as-is
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console.log('Using direct state (not from Deep Agent)');
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return state as AiAssistantState;
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};
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const workflow = new StateGraph(AssistantState)
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.addNode('transformInput', transformInput)
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.addNode('loadContext', async (current: AiAssistantState) => {
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console.log('=== SUBAGENT: Load Context ===');
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return this.loadContext(tenantId, current);
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})
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.addNode('extractFields', async (current: AiAssistantState) => {
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console.log('=== SUBAGENT: Extract Fields ===');
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return this.extractFields(tenantId, current);
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})
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.addNode('decideNext', async (current: AiAssistantState) => {
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console.log('=== SUBAGENT: Decide Next ===');
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return this.decideNextStep(current);
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})
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.addNode('createRecord', async (current: AiAssistantState) => {
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console.log('=== SUBAGENT: Create Record ===');
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return this.createRecord(tenantId, userId, current);
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})
|
||||
.addNode('respondMissing', async (current: AiAssistantState) => {
|
||||
console.log('=== SUBAGENT: Respond Missing ===');
|
||||
return this.respondWithMissingFields(current);
|
||||
})
|
||||
.addEdge(START, 'loadContext')
|
||||
.addNode('formatOutput', async (current: AiAssistantState) => {
|
||||
console.log('=== SUBAGENT: Format Output ===');
|
||||
console.log('Final state before output:', {
|
||||
action: current.action,
|
||||
record: current.record,
|
||||
reply: current.reply,
|
||||
missingFields: current.missingFields,
|
||||
});
|
||||
|
||||
// Format the output for Deep Agent to understand
|
||||
const outputMessage = new AIMessage({
|
||||
content: current.reply || 'Completed.',
|
||||
additional_kwargs: {
|
||||
action: current.action,
|
||||
record: current.record,
|
||||
missingFields: current.missingFields,
|
||||
extractedFields: current.extractedFields,
|
||||
},
|
||||
});
|
||||
|
||||
return {
|
||||
...current,
|
||||
messages: [...(current.messages || []), outputMessage],
|
||||
} as AiAssistantState;
|
||||
})
|
||||
.addEdge(START, 'transformInput')
|
||||
.addEdge('transformInput', 'loadContext')
|
||||
.addEdge('loadContext', 'extractFields')
|
||||
.addEdge('extractFields', 'decideNext')
|
||||
.addConditionalEdges('decideNext', (current: AiAssistantState) => {
|
||||
return current.action === 'create_record' ? 'createRecord' : 'respondMissing';
|
||||
})
|
||||
.addEdge('createRecord', END)
|
||||
.addEdge('respondMissing', END);
|
||||
.addEdge('createRecord', 'formatOutput')
|
||||
.addEdge('respondMissing', 'formatOutput')
|
||||
.addEdge('formatOutput', END);
|
||||
|
||||
const graph = workflow.compile();
|
||||
return graph.invoke(state);
|
||||
return workflow.compile();
|
||||
}
|
||||
|
||||
private async loadContext(
|
||||
@@ -451,6 +836,8 @@ export class AiAssistantService {
|
||||
userId,
|
||||
);
|
||||
|
||||
console.log('record',record);
|
||||
|
||||
const nameValue = enrichedState.extractedFields.name || record?.name || record?.id;
|
||||
const label = enrichedState.objectDefinition.label || enrichedState.objectDefinition.apiName;
|
||||
|
||||
@@ -619,6 +1006,26 @@ export class AiAssistantService {
|
||||
const phoneField = fieldDefinitions.find((field) =>
|
||||
field.apiName.toLowerCase().includes('phone') || field.label.toLowerCase().includes('phone'),
|
||||
);
|
||||
|
||||
// Check for Account lookup field (for Contacts)
|
||||
const accountField = fieldDefinitions.find((field) =>
|
||||
field.apiName === 'accountId' || field.apiName.toLowerCase().includes('account'),
|
||||
);
|
||||
|
||||
// Pattern: "Create X under/for Y account" - extract name and account reference
|
||||
const underAccountMatch = message.match(/create\s+([^\s]+(?:\s+[^\s]+)?)\s+(?:under|for)\s+(.+?)\s+account/i);
|
||||
if (underAccountMatch && nameField) {
|
||||
const recordName = underAccountMatch[1].trim();
|
||||
const accountName = underAccountMatch[2].trim();
|
||||
|
||||
extracted[nameField.apiName] = recordName;
|
||||
|
||||
if (accountField) {
|
||||
// Store the account name for lookup
|
||||
extracted[accountField.apiName] = accountName;
|
||||
console.log('Extracted hierarchical pattern:', { name: recordName, account: accountName });
|
||||
}
|
||||
}
|
||||
|
||||
// Generic pattern matching for any field: "label: value" or "set label to value"
|
||||
for (const field of fieldDefinitions) {
|
||||
@@ -628,7 +1035,7 @@ export class AiAssistantService {
|
||||
}
|
||||
}
|
||||
|
||||
if (nameField) {
|
||||
if (nameField && !extracted[nameField.apiName]) {
|
||||
const nameMatch = message.match(/add\s+([^\n]+?)(?:\s+with\s+|$)/i);
|
||||
if (nameMatch?.[1]) {
|
||||
extracted[nameField.apiName] = nameMatch[1].trim();
|
||||
@@ -646,6 +1053,8 @@ export class AiAssistantService {
|
||||
extracted[nameField.apiName] = message.replace(/^add\s+/i, '').trim();
|
||||
}
|
||||
|
||||
console.log('Heuristic extraction result:', extracted);
|
||||
|
||||
return extracted;
|
||||
}
|
||||
|
||||
|
||||
Reference in New Issue
Block a user