feat(agent): Implement simplified chat agent tools and state management
This commit is contained in:
Willie Zutz
parent
755e1de28b
commit
f6eab5a95a
27 changed files with 1929 additions and 2433 deletions
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@ -1,48 +1,19 @@
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import { Embeddings } from '@langchain/core/embeddings';
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import { BaseChatModel } from '@langchain/core/language_models/chat_models';
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import {
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BaseMessage,
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HumanMessage,
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SystemMessage,
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} from '@langchain/core/messages';
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import {
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BaseLangGraphError,
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END,
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GraphRecursionError,
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MemorySaver,
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START,
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StateGraph,
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} from '@langchain/langgraph';
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import { BaseMessage } from '@langchain/core/messages';
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import { EventEmitter } from 'events';
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import {
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AgentState,
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WebSearchAgent,
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AnalyzerAgent,
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SynthesizerAgent,
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TaskManagerAgent,
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FileSearchAgent,
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ContentRouterAgent,
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URLSummarizationAgent,
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} from '../agents';
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import { SimplifiedAgent } from './simplifiedAgent';
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/**
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* Agent Search class implementing LangGraph Supervisor pattern
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*/
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export class AgentSearch {
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private llm: BaseChatModel;
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private embeddings: Embeddings;
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private checkpointer: MemorySaver;
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private signal: AbortSignal;
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private taskManagerAgent: TaskManagerAgent;
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private webSearchAgent: WebSearchAgent;
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private analyzerAgent: AnalyzerAgent;
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private synthesizerAgent: SynthesizerAgent;
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private fileSearchAgent: FileSearchAgent;
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private contentRouterAgent: ContentRouterAgent;
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private urlSummarizationAgent: URLSummarizationAgent;
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private emitter: EventEmitter;
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private focusMode: string;
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// Simplified agent experimental implementation
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private simplifiedAgent: SimplifiedAgent;
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constructor(
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llm: BaseChatModel,
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embeddings: Embeddings,
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@ -52,117 +23,49 @@ export class AgentSearch {
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signal: AbortSignal,
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focusMode: string = 'webSearch',
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) {
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this.llm = llm;
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this.embeddings = embeddings;
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this.checkpointer = new MemorySaver();
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this.signal = signal;
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this.emitter = emitter;
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this.focusMode = focusMode;
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// Initialize agents
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this.taskManagerAgent = new TaskManagerAgent(
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// Initialize simplified agent (experimental)
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this.simplifiedAgent = new SimplifiedAgent(
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llm,
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emitter,
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systemInstructions,
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signal,
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);
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this.webSearchAgent = new WebSearchAgent(
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llm,
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emitter,
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systemInstructions,
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signal,
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embeddings,
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);
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this.analyzerAgent = new AnalyzerAgent(
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llm,
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emitter,
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systemInstructions,
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signal,
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);
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this.synthesizerAgent = new SynthesizerAgent(
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llm,
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emitter,
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personaInstructions,
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signal,
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);
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this.fileSearchAgent = new FileSearchAgent(
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llm,
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emitter,
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systemInstructions,
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signal,
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embeddings,
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);
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this.contentRouterAgent = new ContentRouterAgent(
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llm,
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emitter,
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systemInstructions,
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signal,
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);
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this.urlSummarizationAgent = new URLSummarizationAgent(
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llm,
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emitter,
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systemInstructions,
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signal,
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focusMode,
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);
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}
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/**
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* Create and compile the agent workflow graph
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* Execute the simplified agent search workflow (experimental)
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*/
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private createWorkflow() {
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const workflow = new StateGraph(AgentState)
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.addNode(
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'url_summarization',
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this.urlSummarizationAgent.execute.bind(this.urlSummarizationAgent),
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{
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ends: ['task_manager', 'analyzer'],
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},
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)
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.addNode(
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'task_manager',
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this.taskManagerAgent.execute.bind(this.taskManagerAgent),
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{
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ends: ['content_router', 'analyzer'],
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},
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)
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.addNode(
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'content_router',
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this.contentRouterAgent.execute.bind(this.contentRouterAgent),
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{
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ends: ['file_search', 'web_search', 'analyzer'],
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},
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)
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.addNode(
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'file_search',
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this.fileSearchAgent.execute.bind(this.fileSearchAgent),
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{
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ends: ['analyzer'],
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},
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)
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.addNode(
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'web_search',
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this.webSearchAgent.execute.bind(this.webSearchAgent),
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{
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ends: ['analyzer'],
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},
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)
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.addNode(
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'analyzer',
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this.analyzerAgent.execute.bind(this.analyzerAgent),
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{
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ends: ['url_summarization', 'task_manager', 'synthesizer'],
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},
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)
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.addNode(
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'synthesizer',
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this.synthesizerAgent.execute.bind(this.synthesizerAgent),
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{
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ends: [END],
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},
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)
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.addEdge(START, 'analyzer');
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async searchAndAnswerSimplified(
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query: string,
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history: BaseMessage[] = [],
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fileIds: string[] = [],
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): Promise<void> {
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console.log('AgentSearch: Using simplified agent implementation');
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return workflow.compile({ checkpointer: this.checkpointer });
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// Emit agent action to indicate simplified agent usage
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this.emitter.emit(
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'data',
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JSON.stringify({
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type: 'agent_action',
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data: {
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action: 'agent_implementation_selection',
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message: 'Using simplified agent implementation (experimental)',
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details: `Focus mode: ${this.focusMode}, Files: ${fileIds.length}`,
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},
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}),
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);
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// Update focus mode in simplified agent if needed
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this.simplifiedAgent.updateFocusMode(this.focusMode);
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// Delegate to simplified agent
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await this.simplifiedAgent.searchAndAnswer(query, history, fileIds);
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}
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/**
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@ -173,139 +76,7 @@ export class AgentSearch {
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history: BaseMessage[] = [],
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fileIds: string[] = [],
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) {
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const workflow = this.createWorkflow();
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const initialState = {
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messages: [...history, new HumanMessage(query)],
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query,
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fileIds,
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focusMode: this.focusMode,
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};
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const threadId = `agent_search_${Date.now()}`;
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const config = {
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configurable: { thread_id: threadId },
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recursionLimit: 18,
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signal: this.signal,
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};
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try {
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const result = await workflow.invoke(initialState, config);
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} catch (error: any) {
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if (error instanceof GraphRecursionError) {
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console.warn(
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'Graph recursion limit reached, attempting best-effort synthesis with gathered information',
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);
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// Emit agent action to explain what happened
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this.emitter.emit(
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'data',
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JSON.stringify({
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type: 'agent_action',
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data: {
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action: 'recursion_limit_recovery',
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message:
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'Search process reached complexity limits. Attempting to provide best-effort response with gathered information.',
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details:
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'The agent workflow exceeded the maximum number of steps allowed. Recovering by synthesizing available data.',
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},
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}),
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);
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try {
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// Get the latest state from the checkpointer to access gathered information
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const latestState = await workflow.getState({
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configurable: { thread_id: threadId },
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});
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if (latestState && latestState.values) {
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// Create emergency synthesis state using gathered information
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const stateValues = latestState.values;
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const emergencyState = {
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messages: stateValues.messages || initialState.messages,
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query: stateValues.query || initialState.query,
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relevantDocuments: stateValues.relevantDocuments || [],
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bannedSummaryUrls: stateValues.bannedSummaryUrls || [],
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bannedPreviewUrls: stateValues.bannedPreviewUrls || [],
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searchInstructionHistory:
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stateValues.searchInstructionHistory || [],
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searchInstructions: stateValues.searchInstructions || '',
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next: 'synthesizer',
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analysis: stateValues.analysis || '',
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fullAnalysisAttempts: stateValues.fullAnalysisAttempts || 0,
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tasks: stateValues.tasks || [],
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currentTaskIndex: stateValues.currentTaskIndex || 0,
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originalQuery:
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stateValues.originalQuery ||
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stateValues.query ||
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initialState.query,
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fileIds: stateValues.fileIds || initialState.fileIds,
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focusMode: stateValues.focusMode || initialState.focusMode,
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urlsToSummarize: stateValues.urlsToSummarize || [],
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summarizationIntent: stateValues.summarizationIntent || '',
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recursionLimitReached: true,
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};
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const documentsCount =
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emergencyState.relevantDocuments?.length || 0;
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console.log(
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`Attempting emergency synthesis with ${documentsCount} gathered documents`,
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);
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// Emit detailed agent action about the recovery attempt
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this.emitter.emit(
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'data',
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JSON.stringify({
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type: 'agent_action',
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data: {
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action: 'emergency_synthesis',
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message: `Proceeding with available information: ${documentsCount} documents gathered${emergencyState.analysis ? ', analysis available' : ''}`,
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details: `Recovered state contains: ${documentsCount} relevant documents, ${emergencyState.searchInstructionHistory?.length || 0} search attempts, ${emergencyState.analysis ? 'analysis data' : 'no analysis'}`,
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},
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}),
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);
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// Only proceed with synthesis if we have some useful information
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if (documentsCount > 0 || emergencyState.analysis) {
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await this.synthesizerAgent.execute(emergencyState);
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} else {
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// If we don't have any gathered information, provide a helpful message
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this.emitter.emit(
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'data',
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JSON.stringify({
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type: 'response',
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data: "⚠️ **Search Process Incomplete** - The search process reached complexity limits before gathering sufficient information to provide a meaningful response. Please try:\n\n- Using more specific keywords\n- Breaking your question into smaller parts\n- Rephrasing your query to be more focused\n\nI apologize that I couldn't provide the information you were looking for.",
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}),
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);
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this.emitter.emit('end');
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}
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} else {
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// Fallback if we can't retrieve state
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this.emitter.emit(
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'data',
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JSON.stringify({
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type: 'response',
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data: '⚠️ **Limited Information Available** - The search process encountered complexity limits and was unable to gather sufficient information. Please try rephrasing your question or breaking it into smaller, more specific parts.',
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}),
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);
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this.emitter.emit('end');
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}
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} catch (synthError) {
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console.error('Emergency synthesis failed:', synthError);
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this.emitter.emit(
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'data',
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JSON.stringify({
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type: 'response',
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data: '⚠️ **Search Process Interrupted** - The search encountered complexity limits and could not complete successfully. Please try a simpler query or break your question into smaller parts.',
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}),
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);
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this.emitter.emit('end');
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}
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} else if (error.name === 'AbortError') {
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console.warn('Agent search was aborted:', error.message);
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} else {
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console.error('Unexpected error during agent search:', error);
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}
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}
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console.log('AgentSearch: Routing to simplified agent implementation');
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return await this.searchAndAnswerSimplified(query, history, fileIds);
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}
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}
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