Technical Guide2026-05-1722 min Read
Building AI Agents with Chinese LLMs
Technical guide to developing autonomous AI agents using function calling, tool use, and multi-step reasoning with Chinese models.
AI AgentFunction CallingTool UseAgentic AI
Agent Architecture Components
A production AI agent typically includes:
| Component | Function | Implementation |
|---|---|---|
| Planning | Task decomposition | Chain-of-thought prompting |
| Memory | Context retention | Vector + summary hybrid |
| Tools | External capabilities | Function definitions |
| Execution | Action loop | While/until conditions |
Best Chinese LLMs for Agents
Model selection impacts agent performance:
- DeepSeek R1: Best reasoning for complex task decomposition
- Qwen Plus: Strong function calling accuracy
- Yi-Large: Excellent tool selection
- GLM-4: Good balance of cost and capability
Tool Definition Best Practices
Define tools clearly for optimal performance:
Error Handling & Recovery
Production agents need robust error handling:
- Implement retry logic with exponential backoff
- Provide fallback responses for tool failures
- Log all actions for debugging and optimization
- Set maximum iteration limits to prevent loops