tinyagent-ts/dist/examples/react.js

Modern TypeScript framework for building AI agents with pluggable tools and ReAct reasoning

"use strict";
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Object.defineProperty(exports, "__esModule", { value: true });
exports.ReActAgent = void 0;
const dotenv = __importStar(require("dotenv"));
dotenv.config();
const zod_1 = require("zod");
const decorators_1 = require("../src/decorators");
const multiStepAgent_1 = require("../src/multiStepAgent");
/**
 * Example of a ReAct agent that demonstrates the Thought → Action → Observation loop
 * using JSON tool calls.
 */
let ReActAgent = class ReActAgent extends multiStepAgent_1.MultiStepAgent {
    /**
     * Simple echo tool that returns the input text
     */
    echo({ text }) {
        return `Echo: ${text}`;
    }
    /**
     * Simple calculator tool that evaluates a math expression
     */
    calculate({ expression }) {
        try {
            // WARNING: Never use eval in production code - this is just for demonstration
            const result = eval(expression);
            return `Result: ${result}`;
        }
        catch (error) {
            return `Error calculating: ${error instanceof Error ? error.message : String(error)}`;
        }
    }
};
exports.ReActAgent = ReActAgent;
__decorate([
    (0, decorators_1.tool)('Echo given text', zod_1.z.object({ text: zod_1.z.string() })),
    __metadata("design:type", Function),
    __metadata("design:paramtypes", [Object]),
    __metadata("design:returntype", String)
], ReActAgent.prototype, "echo", null);
__decorate([
    (0, decorators_1.tool)('Calculate math expression', zod_1.z.object({ expression: zod_1.z.string() })),
    __metadata("design:type", Function),
    __metadata("design:paramtypes", [Object]),
    __metadata("design:returntype", String)
], ReActAgent.prototype, "calculate", null);
exports.ReActAgent = ReActAgent = __decorate([
    (0, decorators_1.model)('openai/gpt-4.1')
], ReActAgent);
/**
 * Callback to display the ReAct steps in a readable format
 */
function displayReActSteps(pad) {
    const steps = pad.getSteps();
    const lastStep = steps[steps.length - 1];
    if (lastStep.type === 'thought') {
        console.log(`🤔 Thought: ${lastStep.text}`);
    }
    else if (lastStep.type === 'action') {
        if (lastStep.mode === 'json') {
            console.log(`🛠️  Action: ${lastStep.tool}(${JSON.stringify(lastStep.args)})`);
        }
        else {
            console.log(`🛠️  Action: [Code Action]`);
        }
    }
    else if (lastStep.type === 'observation') {
        console.log(`👁️  Observation: ${lastStep.text}`);
    }
}
async function runDemo() {
    if (!process.env.OPENROUTER_API_KEY) {
        console.error('💥 Error: OPENROUTER_API_KEY not set');
        process.exit(1);
    }
    console.log('🧠 Running ReAct Agent Demo...');
    const agent = new ReActAgent();
    // This query requires multiple steps to solve
    const question = 'Calculate 23 * 17 and then echo the result with a friendly message.';
    console.log(`❓ Query: "${question}"`);
    try {
        const result = await agent.run(question, {
            trace: true,
            onStep: displayReActSteps
        });
        // With the new final_answer workflow, result will be an object with answer property
        const answer = typeof result === 'object' && result && 'answer' in result
            ? result.answer
            : String(result);
        console.log(`✅ Final Answer: ${answer}`);
    }
    catch (error) {
        const message = error instanceof Error ? error.message : String(error);
        console.error(`❌ Error: ${message}`);
    }
}
if (require.main === module) {
    runDemo();
}
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