# OpenAI advanced configuration > Prompt contribution, transport, Fast mode, compaction, and route compat - 网址：https://funcoding.ai/agents/openclaw/providers/openai/advanced/ - 来源：OpenClaw 官方文档原文（英文），MIT 许可，同步于 2026-10-11 - 官方原文：https://docs.openclaw.ai/zh-CN/providers/openai/advanced --- ## GPT-5 prompt contribution OpenClaw adds a shared GPT-5 prompt contribution to matching GPT-5 and GPT-6 OpenClaw-assembled prompts (`gpt-5*` and `gpt-6*`, such as the default `gpt-6-astra`). The OpenAI plugin setting below controls the friendly style on OpenAI-family routes. Older GPT-4.x, `gpt-oss`, o-series, and `codex-mini` model ids do not match. The native Codex app-server harness does not receive the persona/tool- discipline behavior contract or the friendly interaction-style overlay through developer instructions; native Codex keeps Codex-owned base, model, and project-doc behavior, and OpenClaw disables Codex's built-in personality for native threads so agent workspace personality files stay authoritative. OpenClaw contributes only runtime context to native Codex threads: channel delivery, OpenClaw dynamic tools, ACP delegation, workspace context, and OpenClaw skills. The heartbeat-guidance text from this same contribution is the one exception: native Codex heartbeat turns do get it, injected as dedicated collaboration instructions rather than through the shared prompt-contribution hook. The GPT-5 contribution adds a tagged behavior contract for persona persistence, execution safety, tool discipline, output shape, completion checks, and verification on matching OpenClaw-assembled prompts. Channel- specific reply and silent-message behavior stays in the shared OpenClaw system prompt and outbound delivery policy. The friendly interaction-style layer is separate and configurable. | Value | Effect | | ---------------------- | ------------------------------------------- | | `"friendly"` (default) | Enable the friendly interaction-style layer | | `"on"` | Alias for `"friendly"` | | `"off"` | Disable only the friendly style layer | **Config** ```json5 { plugins: { entries: { openai: { config: { personality: "friendly" }, }, }, }, } ``` **CLI** ```bash openclaw config set plugins.entries.openai.config.personality off ```
Values are case-insensitive at runtime, so `"Off"` and `"off"` both disable the friendly style layer.
The retired `agents.defaults.promptOverlays` key is no longer read; config validation rejects it, and `openclaw doctor --fix` migrates its personality value into `plugins.entries.openai.config.personality` when that key is unset.
## Advanced configuration The `transport` and `serviceTier` examples below are authored embedded-provider request settings, so an otherwise eligible `auto` route stays on OpenClaw instead of selecting Codex implicitly. Valid `fastMode` / `fast_mode` values and valid cutoff keys are typed agent-runtime controls and do not select a runtime. Runtime-specific examples therefore pin `agentRuntime.id` explicitly. The native Codex app-server harness owns its transport and request settings. Authored embedded-provider settings can therefore select the declared OpenClaw fallback even with explicit `agentRuntime.id: "codex"`; see [Runtime selection](https://funcoding.ai/agents/openclaw/concepts/agent-runtimes/#runtime-selection).
Transport (WebSocket vs SSE) Direct API-key requests use SSE by default. Set `params.transport` when you want Responses WebSocket mode on an eligible official OpenAI endpoint. | Value | Behavior | | --------------------- | -------- | | `"sse"` (default) | Stream each request over SSE | | `"auto"` | Prefer a session-cached WebSocket, with pre-dispatch SSE fallback | | `"websocket-cached"` | Explicitly use the session-cached WebSocket path, with the same pre-dispatch SSE fallback | | `"websocket"` | Use a transient WebSocket for the request, with pre-dispatch SSE fallback | Cached modes keep one eligible connection per session. When the prior request and response still match the current history, OpenClaw sends only the new input and references the prior response with `previous_response_id`. Otherwise it sends full history without that reference. A setup or handshake failure before request dispatch falls back to SSE; it is not retried or reconnected first. After dispatch, failures with an unknown outcome remain replay-unsafe and fail closed. The explicit server rejections `previous_response_not_found`, `websocket_connection_limit_reached`, and the Zero Data Retention `unsupported_parameter` rejection of `previous_response_id` are safe exceptions: OpenClaw closes the failed socket and retries that turn once over SSE with full history and no rejected `previous_response_id`. ```json5 { agents: { defaults: { models: { "openai/gpt-5.5": { agentRuntime: { id: "openclaw" }, params: { transport: "auto" }, }, }, }, }, } ``` ChatGPT Responses SSE turns may exceed 16 MiB in total. The parser bounds each buffered event to 16 MiB of bytes before decoding or parsing it, and cancels oversized events, including events without a closing delimiter. For cached ChatGPT Responses WebSocket requests, an explicit "Rustponses cannot replay" rejection before any response event triggers one retry on a fresh connection with full input instead of the cached response reference. The retry preserves reasoning, compaction, and completed tool results; it does not rerun tools. Rejections of full input and failures after response events remain terminal. Related OpenAI docs: - [Responses API WebSocket mode](https://developers.openai.com/api/docs/guides/websocket-mode) - [Streaming API responses (SSE)](https://platform.openai.com/docs/guides/streaming-responses)
Fast mode OpenClaw exposes a shared fast-mode toggle for `openai/*`: - **Chat/UI:** `/fast status|auto|on|off|ultrafast|default` - **Config:** `agents.defaults.models["/"].params.fastMode` Valid `params.fastMode` / `params.fast_mode` values and valid cutoff keys are typed runtime controls. They do not count as authored provider request params and do not select OpenClaw or Codex. The example below pins embedded OpenClaw because it describes a direct provider request. When enabled on the embedded runtime, OpenClaw maps fast mode to OpenAI API Fast mode (formerly Priority processing) and sends `service_tier = "priority"`. Explicit `/fast ultrafast` or `params.fastMode: "ultrafast"` sends `service_tier = "ultrafast"` instead. The selected account and model must support that tier; the provider can reject it or return a different effective tier. Fast mode does not rewrite `reasoning` or `text.verbosity`. `fastMode: "auto"` starts new model calls fast until the auto cutoff, then starts later retry, fallback, tool-result, or continuation calls without fast mode. The cutoff defaults to 60 seconds; set `params.fastAutoOnSeconds` on the active model to change it. For the embedded OpenClaw runtime, the Control UI uses provider model and route limits when offering Standard, Fast, and Ultrafast. This works for auth profiles, environment keys, and provider config (including SecretRefs). Models limited to Standard or Fast keep those restrictions. Custom endpoints and ChatGPT account catalogs retain their own tier policy. If a response to an Ultrafast request echoes a different `service_tier`, OpenClaw records a temporary observation for that credential, model, and route. Ultrafast stays selectable, and the composer's Speed tooltip shows the requested and served tiers. Later calls keep requesting the selected tier. A response honoring it clears the hint immediately; otherwise the observation expires five minutes after its latest occurrence. If the native OpenAI API explicitly rejects `service_tier` before output, tool activity, or active-response steering, OpenClaw automatically retries that request at a slower tier: Ultrafast → Fast → Standard. The hint records that recovery without changing saved preferences or later requests. It does not retry tier errors after cancellation or an ambiguous connection failure. Explicit low-level tier overrides are still sent as configured. Observations also clear on credential replacement, profile discovery refresh, or retirement of the prepared runtime, and are not persisted across restarts. ChatGPT-account availability remains based on authenticated account catalog discovery. ```json5 { agents: { defaults: { models: { "openai/gpt-5.5": { agentRuntime: { id: "openclaw" }, params: { fastMode: "auto", fastAutoOnSeconds: 30 }, }, }, }, }, } ```
The full precedence is inline message, stored session, per-agent default, global default, per-model `params.fastMode`, then off. `/fast default` clears only the session layer. `/status` reports the resolved OpenClaw policy and runtime, not the upstream service tier actually honored or returned. See [Thinking levels](https://funcoding.ai/agents/openclaw/tools/thinking/#fast-mode-%2Ffast) and [Codex harness](https://funcoding.ai/agents/openclaw/plugins/codex-harness/commands/#shared-fast-mode-and-codex-fast-mode).
Fast mode is premium-priced and model-specific. GPT-5.6 Sol API Fast mode currently costs 2× Standard token pricing, with long-context multipliers stacking as described in [context window defaults and long-context opt-in](https://funcoding.ai/agents/openclaw/providers/openai/setup/#context-window-defaults-and-long-context-opt-in). ChatGPT/Codex-credit Fast mode is a separate billing system: GPT-5.6 and GPT-5.5 currently consume 2.5× Standard credits, while API-key Codex runs use API token pricing. See [Fast mode](https://openai.com/api-priority-processing/), [API pricing](https://developers.openai.com/api/docs/pricing), and [Codex speed](https://learn.chatgpt.com/docs/agent-configuration/speed).
OpenAI API Fast mode with service_tier OpenAI now calls this API product Fast mode; it was formerly Priority processing. OpenClaw sends the wire value `service_tier = "priority"`. Set an explicit tier per model on the embedded OpenClaw runtime: ```json5 { agents: { defaults: { models: { "openai/gpt-5.5": { agentRuntime: { id: "openclaw" }, params: { serviceTier: "priority" }, }, }, }, }, } ``` Supported values: `auto`, `default`, `flex`, `priority`, `ultrafast`. Availability depends on the selected provider route, account, and model.
`params.serviceTier` is an authored embedded-provider setting, not native Codex app-server configuration. It is forwarded only by the embedded runtime on OpenAI Responses routes, including compatible base URLs, and native ChatGPT endpoints (`chatgpt.com/backend-api`). Compatible endpoints must honor the requested tier; a saved preference does not guarantee fulfillment. Configure the native harness separately with `plugins.entries.codex.config.appServer.serviceTier`; the shared Fast-mode run control can supersede that value.
Server-side compaction (Responses API) For store-capable direct OpenAI Responses models (`openai/*` resolved to `api.openai.com`), the OpenAI plugin's OpenClaw stream wrapper auto-enables server-side compaction: - Forces `store: true` (unless model compat sets `supportsStore: false`) - Injects `context_management: [{ type: "compaction", compact_threshold: ... }]` - Default `compact_threshold`: 70% of `contextWindow` (or `80000` when unavailable) The same resolved route and effective threshold gate the client preflight, so OpenClaw does not delay local compaction unless the transport will inject `context_management`. ChatGPT OAuth, custom proxies, and routes with `compat.supportsStore: false` are not store-capable and therefore ignore these server-compaction controls. This applies to the built-in OpenClaw runtime path and to OpenAI provider hooks used by embedded runs. The native Codex app-server harness manages its own context through Codex and is not affected by this setting. OpenAI emits the compacted state as an encrypted `compaction` output item. Keep that item opaque. For stateless continuation, carry the newest item forward and drop the earlier input prefix it replaces. OpenClaw does this automatically: it persists and replays the item only for the matching route, session, and auth identity, preserves it across worker transcript commits, and filters it from user-visible history and diagnostics. Never display or log the encrypted content. **Enable explicitly** Useful for store-capable endpoints like Azure OpenAI Responses. Setting this to `true` does not override endpoint or `supportsStore` capability: ```json5 { agents: { defaults: { models: { "azure-openai-responses/gpt-5.5": { params: { responsesServerCompaction: true }, }, }, }, }, } ``` **Custom threshold** ```json5 { agents: { defaults: { models: { "openai/gpt-5.5": { params: { responsesServerCompaction: true, responsesCompactThreshold: 120000, }, }, }, }, }, } ``` **Disable** ```json5 { agents: { defaults: { models: { "openai/gpt-5.5": { params: { responsesServerCompaction: false }, }, }, }, }, } ```
`responsesServerCompaction` only controls `context_management` injection. The public OpenAI Responses API also uses `/responses/compact` by default for budget-triggered compaction and for `/compact` without focus instructions. Set `params.responsesCompactEndpoint: false` to disable this separate endpoint. `/compact `, provider-confirmed overflow, and endpoint failures use client-side summarization. Direct OpenAI Responses models still force `store: true` unless compat sets `supportsStore: false`.
Strict-agentic GPT mode For `openai` provider GPT-5-family models run through OpenClaw's embedded runtime, OpenClaw already defaults to a stricter execution contract called `strict-agentic`. It auto-activates whenever the resolved provider is `openai` and the model id matches the GPT-5 family, unless config explicitly opts back out: ```json5 { agents: { defaults: { embeddedAgent: { executionContract: "default" }, }, }, } ``` Setting `"strict-agentic"` explicitly is a no-op on a supported lane (it is already the default) and inert on unsupported provider/model pairs. With `strict-agentic` active, OpenClaw: - Makes `progress_card` available for substantial work unless `tools.updatePlan` disables it - Retries structurally empty or reasoning-only turns with a visible-answer continuation - Uses explicit harness plan events when the selected harness provides them OpenClaw does not classify assistant prose to decide whether a turn is a plan, progress update, or final answer.
This contract lives entirely in OpenClaw's embedded agent runner. It does not apply to the native Codex app-server harness, which manages its own turn and plan behavior; the harness selection matters more than the execution-contract setting for native Codex runs.
Native vs OpenAI-compatible routes OpenClaw treats direct OpenAI, Codex, and Azure OpenAI endpoints differently from generic OpenAI-compatible `/v1` proxies: **Native routes** (`openai/*`, Azure OpenAI): - Keep `reasoning: { effort: "none" }` only for models that support the OpenAI `none` effort - Omit disabled reasoning for models or proxies that reject `reasoning.effort: "none"` - Default tool schemas to strict mode - Attach hidden attribution headers on verified native hosts only (Azure OpenAI does not get these headers, even though it is a native route) - Keep OpenAI-only request shaping (`service_tier`, `store`, reasoning-compat, prompt-cache hints) - Send tool-bearing turns for reasoning models configured with `openai-completions` on `api.openai.com` to `/v1/responses`, because Chat Completions rejects function tools with reasoning for current GPT models. Credentials, endpoint host, and proxy routes are unchanged. **Proxy/compatible routes:** - Use looser compat behavior - Strip Completions `store` from non-native `openai-completions` payloads - Accept advanced `params.extra_body`/`params.extraBody` pass-through JSON for OpenAI-compatible Completions proxies - Accept `params.chat_template_kwargs` for OpenAI-compatible Completions proxies such as vLLM - Do not force strict tool schemas or native-only headers If a usable tool schema is incompatible with requested strict mode, the request uses `strict: false`. Debug logs report the downgrade under `openai-transport`, with a bounded sample of incompatible tools. Built-in and managed Responses requests share duplicate suppression for the same model and schemas. Compatibility checks inspect schema constraints, not literal names in schema maps or annotation data such as examples and defaults.