Example: Research Assistant

import {
  defineAgent, defineTool, createLLM,
  InMemoryMemoryStore,
} from '@ahzan-agentforge/core';
import { z } from 'zod';

const searchTool = defineTool({
  name: 'web-search',
  description: 'Search the web for information',
  input: z.object({ query: z.string() }),
  output: z.object({
    results: z.array(z.object({
      title: z.string(),
      snippet: z.string(),
      url: z.string(),
    })),
  }),
  execute: async ({ query }) => {
    // Your search API integration
    return { results: [{ title: 'Example', snippet: 'Info...', url: 'https://example.com' }] };
  },
  cacheable: true,  // Cache identical searches
});

const agent = defineAgent({
  name: 'researcher',
  description: 'Researches topics and generates reports',
  tools: [searchTool],
  llm: createLLM({ provider: 'anthropic', model: 'claude-sonnet-4-20250514' }),
  systemPrompt: `You are a research assistant. When given a topic:
1. Search for relevant information using multiple queries
2. Synthesize findings into a structured report
3. Include citations for all claims`,
  maxSteps: 15,
  budget: { maxCostUsd: 0.50, warnThreshold: 0.7 },
  memory: {
    store: new InMemoryMemoryStore(),
    config: { autoCapture: true },
  },
});

// Stream results
for await (const event of agent.stream({
  task: 'Research the current state of AI agent frameworks in 2025',
})) {
  if (event.type === 'llm_token') {
    process.stdout.write(event.token);
  }
  if (event.type === 'tool_start') {
    console.log(`\nSearching: ${event.input?.query}`);
  }
}