Perplexica/src/lib/search/agentSearch.ts

137 lines
3.3 KiB
TypeScript
Raw Normal View History

import { Embeddings } from '@langchain/core/embeddings';
import { BaseChatModel } from '@langchain/core/language_models/chat_models';
import {
BaseMessage,
HumanMessage,
SystemMessage,
} from '@langchain/core/messages';
import { END, MemorySaver, START, StateGraph } from '@langchain/langgraph';
import { EventEmitter } from 'events';
import {
AgentState,
WebSearchAgent,
AnalyzerAgent,
SynthesizerAgent,
} from '../agents';
/**
* Agent Search class implementing LangGraph Supervisor pattern
*/
export class AgentSearch {
private llm: BaseChatModel;
private embeddings: Embeddings;
private checkpointer: MemorySaver;
private signal: AbortSignal;
private webSearchAgent: WebSearchAgent;
private analyzerAgent: AnalyzerAgent;
private synthesizerAgent: SynthesizerAgent;
constructor(
llm: BaseChatModel,
embeddings: Embeddings,
emitter: EventEmitter,
systemInstructions: string = '',
personaInstructions: string = '',
signal: AbortSignal,
) {
this.llm = llm;
this.embeddings = embeddings;
this.checkpointer = new MemorySaver();
this.signal = signal;
// Initialize agents
this.webSearchAgent = new WebSearchAgent(
llm,
emitter,
systemInstructions,
signal,
);
this.analyzerAgent = new AnalyzerAgent(
llm,
emitter,
systemInstructions,
signal,
);
this.synthesizerAgent = new SynthesizerAgent(
llm,
emitter,
personaInstructions,
signal,
);
}
/**
* Create and compile the agent workflow graph
*/
private createWorkflow() {
const workflow = new StateGraph(AgentState)
.addNode(
'web_search',
this.webSearchAgent.execute.bind(this.webSearchAgent),
{
ends: ['analyzer'],
},
)
.addNode(
'analyzer',
this.analyzerAgent.execute.bind(this.analyzerAgent),
{
ends: ['web_search', 'synthesizer'],
},
)
.addNode(
'synthesizer',
this.synthesizerAgent.execute.bind(this.synthesizerAgent),
{
ends: [END],
},
)
.addEdge(START, 'analyzer');
return workflow.compile({ checkpointer: this.checkpointer });
}
/**
* Execute the agent search workflow
*/
async searchAndAnswer(query: string, history: BaseMessage[] = []) {
const workflow = this.createWorkflow();
try {
const initialState = {
messages: [...history, new HumanMessage(query)],
query,
};
const result = await workflow.invoke(initialState, {
configurable: { thread_id: `agent_search_${Date.now()}` },
2025-06-10 00:12:45 -06:00
recursionLimit: 20,
signal: this.signal,
});
return result;
} catch (error) {
console.error('Agent workflow error:', error);
// Fallback to a simple response
const fallbackResponse = await this.llm.invoke(
[
new SystemMessage(
"You are a helpful assistant. The advanced agent workflow failed, so please provide a basic response to the user's query based on your knowledge.",
),
new HumanMessage(query),
],
{ signal: this.signal },
);
return {
messages: [...history, new HumanMessage(query), fallbackResponse],
query,
searchResults: [],
next: END,
analysis: '',
};
}
}
}