X 线索实战：OpenAI WebSocket + Claude 4.6 adaptive thinking 联合调优
Problem/Scenario: 长上下文任务延迟高且质量不稳定。Prerequisites: 同时配置OpenAI与Anthropic并可改模型参数。Steps: 1) 设置OpenAI `transport:auto`；2) 保持`openaiWsWarmup`；3) 按需启用`responsesServerCompaction`；4) Claude 4.6使用adaptive thinking；5) 用固定任务集做A/B评估。Key config: `transport`、`openaiWsWarmup`、`responsesServerCompaction`。Verification: p95延迟下降且复杂任务质量不回退。Risks/Boundaries: 网络波动时WS收益不稳定，需保留SSE回退。Source: 官方X帖 + providers/openai文档。
XDiscovered 2026-03-03Author @openclaw
Prerequisites
- OpenAI and Anthropic providers are both configured.
- Can modify model params and restart gateway.
Steps
- Set OpenAI transport to auto (WS first, SSE fallback).
- Keep WebSocket warm-up enabled for high-frequency models.
- Enable server-side compaction for long-context Responses workloads.
- Use Claude 4.6 adaptive thinking for complexity-varying tasks.
- Benchmark latency/cost/quality before rollout.
Commands
openclaw gateway statusopenclaw gateway restartVerify
A/B benchmark shows lower p95 latency and stable answer quality on hard prompts.
Caveats
- WebSocket-first does not guarantee lower latency on unstable links.
- Compaction threshold should be tuned per model context window（需验证）.
Source attribution
This tip is aggregated from community/public sources and preserved with attribution.
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