ai-agent-orchestrator

AI Agent Orchestrator

Build coordinated multi-agent systems for complex task automation.

Core Workflow

1. Define agents: Create specialized agents
2. Design workflow: Plan agent coordination
3. Implement handoffs: Agent-to-agent communication
4. Add shared memory: Persistent context
5. Create supervisor: Orchestrate execution
6. Monitor execution: Track agent activities

Agent Architecture

Agent Definition

// agents/base.ts
import { ChatOpenAI } from '@langchain/openai';
import { SystemMessage, HumanMessage, AIMessage } from '@langchain/core/messages';

export interface AgentConfig {
  name: string;
  role: string;
  systemPrompt: string;
  tools?: Tool[];
  model?: string;
}

export interface AgentResponse {
  content: string;
  toolCalls?: ToolCall[];
  nextAgent?: string;
  completed?: boolean;
}

export class Agent {
  private model: ChatOpenAI;
  private config: AgentConfig;
  private messageHistory: BaseMessage[] = [];

  constructor(config: AgentConfig) {
    this.config = config;
    this.model = new ChatOpenAI({
      modelName: config.model || 'gpt-4-turbo-preview',
      temperature: 0.7,
    });
  }

  async execute(input: string, context?: Record<string, any>): Promise<AgentResponse> {
    const systemMessage = new SystemMessage(
      this.buildSystemPrompt(context)
    );

    const messages = [
      systemMessage,
      ...this.messageHistory,
      new HumanMessage(input),
    ];

    const response = await this.model.invoke(messages, {
      tools: this.config.tools,
    });

    this.messageHistory.push(new HumanMessage(input));
    this.messageHistory.push(new AIMessage(response.content as string));

    return this.parseResponse(response);
  }

  private buildSystemPrompt(context?: Record<string, any>): string {
    let prompt = this.config.systemPrompt;

    if (context) {
      prompt += `\n\nContext:\n${JSON.stringify(context, null, 2)}`;
    }

    return prompt;
  }

  private parseResponse(response: any): AgentResponse {
    // Parse tool calls and determine next actions
    return {
      content: response.content as string,
      toolCalls: response.tool_calls,
      completed: response.content?.includes('[TASK_COMPLETE]'),
    };
  }

  clearHistory() {
    this.messageHistory = [];
  }
}