Key takeaways
Structured output failures cause more production incidents than chat quality gaps. Treat JSON as a contract: schema → model mode → parse → validate → retry/failover. OpenAI-compatible endpoints vary on strict JSON and tool argument shapes—see /en/articles/china-llm-openai-compatible-sdk-2026 and agent guide.
Implementation pattern
Define JSON Schema or Zod/Pydantic models → ask for JSON only → enable vendor JSON mode when available → parse → validate → on failure, one repair prompt or switch vendor (/en/articles/china-llm-latency-failover-2026). Log raw text for debugging.
Vendor caveats
Do not assume GPT-identical strict mode. Test nested objects, enums, and empty arrays on DeepSeek, Qwen, GLM. Tool calling often needs separate tests from pure JSON chat (/en/articles/china-llm-agent-tool-calling-2026).
Next steps on Swift Horse
SDK /en/articles/china-llm-openai-compatible-sdk-2026 → agents /en/articles/china-llm-agent-tool-calling-2026 → pricing /en/articles/china-llm-api-pricing-2026 → access /en/articles/access-china-llm-api-overseas.
FAQ
Do Chinese LLMs support JSON mode?
Many expose JSON or schema-like controls—names differ. Verify on each vendor console and test nested schemas.
JSON mode vs tool calling?
JSON mode shapes assistant content; tools return function arguments. Pick based on whether you need side effects.
How to handle invalid JSON in production?
Validate, one repair retry, then failover model; never silently pass bad payloads downstream.
Is this official API documentation?
No—independent Swift Horse engineering guide. Defer to vendor docs for parameters.