Setup Mastra AI Agent with Qwen 3

Initialize a Mastra AI project using TypeScript. Define a simple agent that uses Qwen 3 (via API call) to respond to basic queries. Create a custom tool, `fetchMarketData(category: string)`, that simulates fetching market data (e.g., return a JSON string for 'memory_chips' or 'ai_tools'). Integrate this tool into your Mastra agent. Show your `agent.ts` file setup.

```typescript
import { createAgent, Tool } from 'mastra';
import { QwenClient } from './qwen_client'; // Assume you have a client for Qwen API

const qwenClient = new QwenClient('YOUR_QWEN_API_KEY');

// Define a simulated tool to fetch market data
const fetchMarketData: Tool = {
  name: 'fetchMarketData',
  description: 'Fetches simulated market data for a given category (e.g., memory_chips, ai_tools).',
  inputSchema: { type: 'object', properties: { category: { type: 'string' } }, required: ['category'] },
  async handler(input: { category: string }): Promise<string> {
    if (input.category === 'memory_chips') {
      return JSON.stringify({
        'chip_production_2026': '100 units',
        'datacenter_demand_2026': '70%+ of total_production',
        'new_capacity_until_2027': 'little'
      });
    } else if (input.category === 'ai_tools') {
      return JSON.stringify({
        'adoption_rate': 'growing',
        'challenges': ['cost', 'integration'],
        'opportunities': ['automation', 'creativity']
      });
    } else {
      return JSON.stringify({ 'error': 'Category not found' });
    }
  },
};

// Your task: Create and export your Mastra agent, integrating Qwen 3 and fetchMarketData.
// export const marketAdvisorAgent = createAgent({
//   id: 'marketAdvisor',
//   llm: async (prompt) => qwenClient.generate(prompt),
//   tools: [fetchMarketData],
//   // ... further configuration for memory and behavior
// });
```