50-thinking-config.ts

/**
 * 50 - Thinking Config — enable extended reasoning for complex tasks.
 *
 * When `thinkingBudgetTokens` is set, the agent uses extended thinking
 * mode, allowing the LLM to reason step-by-step before responding.
 *
 * Requirements:
 *   - Conductor server with thinking config support
 *   - CONDUCTOR_SERVER_URL=http://localhost:8080/api
 *   - CONDUCTOR_AGENT_LLM_MODEL=openai/gpt-4o-mini
 */

import { Agent, AgentRuntime, tool } from '@io-orkes/conductor-javascript/agents';
import { llmModel } from './settings';

// -- Tool --------------------------------------------------------------------

const calculate = tool(
  async (args: { expression: string }) => {
    try {
      const fn = new Function(`return (${args.expression});`);
      return { expression: args.expression, result: fn() };
    } catch (e) {
      return { expression: args.expression, error: String(e) };
    }
  },
  {
    name: 'calculate',
    description: 'Evaluate a mathematical expression.',
    inputSchema: {
      type: 'object',
      properties: {
        expression: { type: 'string', description: 'A math expression to evaluate (e.g., \'2 + 3 * 4\')' },
      },
      required: ['expression'],
    },
  },
);

// -- Agent -------------------------------------------------------------------

export const agent = new Agent({
  name: 'deep_thinker_50',
  model: llmModel,
  instructions:
    'You are an analytical assistant. Think carefully through complex ' +
    'problems step by step. Use the calculate tool for math.',
  tools: [calculate],
  thinkingBudgetTokens: 2048,
});

// -- Run ---------------------------------------------------------------------

async function main() {
  const runtime = new AgentRuntime();
  try {
    const result = await runtime.run(
    agent,
    'If a train travels 120 km in 2 hours, then speeds up by 50% for ' +
    'the next 3 hours, what is the total distance traveled?',
    );
    result.printResult();

    // Production pattern:
    // 1. Deploy once during CI/CD (optional -- serve() below also deploys):
    // await runtime.deploy(agent);
    // CLI alternative:
    // conductor deploy --package examples/agents --agents deep_thinker_50
    //
    // 2. In a separate long-lived worker process (deploys + registers workers + starts polling):
    // await runtime.serve(agent);
  } finally {
    await runtime.shutdown();
  }
}

main().catch(console.error);