openclaw
Version:
Multi-channel AI gateway with extensible messaging integrations
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Markdown
---
summary: "Prompt contribution, transport, Fast mode, compaction, and route compat"
read_when:
- You are tuning transport, Fast mode, or service tier for openai/*
- You need stricter GPT-5 agent execution behavior
- You are debugging server-side compaction or OpenAI-compatible proxy behavior
title: "OpenAI advanced configuration"
sidebarTitle: "Advanced configuration"
---
## 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 |
<Tabs>
<Tab title="Config">
```json5
{
plugins: {
entries: {
openai: {
config: { personality: "friendly" },
},
},
},
}
```
</Tab>
<Tab title="CLI">
```bash
openclaw config set plugins.entries.openai.config.personality off
```
</Tab>
</Tabs>
<Tip>
Values are case-insensitive at runtime, so `"Off"` and `"off"` both disable the
friendly style layer.
</Tip>
<Note>
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.
</Note>
## 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](/concepts/agent-runtimes#runtime-selection).
<AccordionGroup>
<Accordion title="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)
</Accordion>
<Accordion title="Fast mode">
OpenClaw exposes a shared fast-mode toggle for `openai/*`:
- **Chat/UI:** `/fast status|auto|on|off|ultrafast|default`
- **Config:** `agents.defaults.models["<provider>/<model>"].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 },
},
},
},
},
}
```
<Note>
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](/tools/thinking#fast-mode-%2Ffast) and
[Codex harness](/plugins/codex-harness/commands#shared-fast-mode-and-codex-fast-mode).
</Note>
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](/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).
</Accordion>
<Accordion title="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.
<Warning>
`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.
</Warning>
</Accordion>
<Accordion title="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.
The next foreground turn waits for any pending local transcript projection
rebuild before reading the checkpoint. Request token counts need not fall
below the compaction threshold: instructions and tools are sent again, and
tool results or reasoning produced after the checkpoint remain in context.
To check replay, inspect item types rather than token totals: the newest
`compaction` item replaces the covered prefix, followed only by later items.
<Tabs>
<Tab title="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 },
},
},
},
},
}
```
</Tab>
<Tab title="Custom threshold">
```json5
{
agents: {
defaults: {
models: {
"openai/gpt-5.5": {
params: {
responsesServerCompaction: true,
responsesCompactThreshold: 120000,
},
},
},
},
},
}
```
</Tab>
<Tab title="Disable">
```json5
{
agents: {
defaults: {
models: {
"openai/gpt-5.5": {
params: { responsesServerCompaction: false },
},
},
},
},
}
```
</Tab>
</Tabs>
<Note>
`responsesServerCompaction` only controls `context_management` injection.
The public OpenAI Responses API also uses `/responses/compact` by default
for budget-triggered compaction. Set
`params.responsesCompactEndpoint: false` to disable this separate endpoint.
Provider-confirmed overflow and endpoint failures use client-side
summarization. Manual compaction keeps its existing behavior unless this
endpoint is explicitly enabled with `params.responsesCompactEndpoint: true`.
Direct OpenAI Responses models still force `store: true` unless compat
sets `supportsStore: false`.
</Note>
</Accordion>
<Accordion title="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.
<Note>
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.
</Note>
</Accordion>
<Accordion title="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.
</Accordion>
</AccordionGroup>