* feat(gateway): add OpenAI-compatible models and embeddings * docs(gateway): clarify model list and agent routing * Update index.md * fix(gateway): harden embeddings HTTP provider selection * fix(gateway): validate compat model overrides * fix(gateway): harden embeddings and response continuity * fix(gateway): restore compat model id handling
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summary, read_when, title
| summary | read_when | title | |
|---|---|---|---|
| Expose an OpenAI-compatible /v1/chat/completions HTTP endpoint from the Gateway |
|
OpenAI Chat Completions |
OpenAI Chat Completions (HTTP)
OpenClaw’s Gateway can serve a small OpenAI-compatible Chat Completions endpoint.
This endpoint is disabled by default. Enable it in config first.
POST /v1/chat/completions- Same port as the Gateway (WS + HTTP multiplex):
http://<gateway-host>:<port>/v1/chat/completions
When the Gateway’s OpenAI-compatible HTTP surface is enabled, it also serves:
GET /v1/modelsGET /v1/models/{id}POST /v1/embeddingsPOST /v1/responses
Under the hood, requests are executed as a normal Gateway agent run (same codepath as openclaw agent), so routing/permissions/config match your Gateway.
Authentication
Uses the Gateway auth configuration. Send a bearer token:
Authorization: Bearer <token>
Notes:
- When
gateway.auth.mode="token", usegateway.auth.token(orOPENCLAW_GATEWAY_TOKEN). - When
gateway.auth.mode="password", usegateway.auth.password(orOPENCLAW_GATEWAY_PASSWORD). - If
gateway.auth.rateLimitis configured and too many auth failures occur, the endpoint returns429withRetry-After.
Security boundary (important)
Treat this endpoint as a full operator-access surface for the gateway instance.
- HTTP bearer auth here is not a narrow per-user scope model.
- A valid Gateway token/password for this endpoint should be treated like an owner/operator credential.
- Requests run through the same control-plane agent path as trusted operator actions.
- There is no separate non-owner/per-user tool boundary on this endpoint; once a caller passes Gateway auth here, OpenClaw treats that caller as a trusted operator for this gateway.
- If the target agent policy allows sensitive tools, this endpoint can use them.
- Keep this endpoint on loopback/tailnet/private ingress only; do not expose it directly to the public internet.
See Security and Remote access.
Choosing an agent
No custom headers required: encode the agent id in the OpenAI model field:
model: "openclaw:<agentId>"(example:"openclaw:main","openclaw:beta")model: "agent:<agentId>"(alias)
Or target a specific OpenClaw agent by header:
x-openclaw-agent-id: <agentId>(default:main)
Advanced:
x-openclaw-session-key: <sessionKey>to fully control session routing.x-openclaw-message-channel: <channel>to set the synthetic ingress channel context for channel-aware prompts and policies.
For /v1/models and /v1/embeddings, x-openclaw-agent-id is still useful:
/v1/modelsuses it for agent-scoped model filtering where relevant./v1/embeddingsuses it to resolve agent-specific memory-search embedding config.
Enabling the endpoint
Set gateway.http.endpoints.chatCompletions.enabled to true:
{
gateway: {
http: {
endpoints: {
chatCompletions: { enabled: true },
},
},
},
}
Disabling the endpoint
Set gateway.http.endpoints.chatCompletions.enabled to false:
{
gateway: {
http: {
endpoints: {
chatCompletions: { enabled: false },
},
},
},
}
Session behavior
By default the endpoint is stateless per request (a new session key is generated each call).
If the request includes an OpenAI user string, the Gateway derives a stable session key from it, so repeated calls can share an agent session.
Why this surface matters
This is the highest-leverage compatibility set for self-hosted frontends and tooling:
- Most Open WebUI, LobeChat, and LibreChat setups expect
/v1/models. - Many RAG systems expect
/v1/embeddings. - Existing OpenAI chat clients can usually start with
/v1/chat/completions. - More agent-native clients increasingly prefer
/v1/responses.
Model list and agent routing
A flat OpenAI-style model list.The returned ids are canonical `provider/model` values such as `openai/gpt-5.4`.
These ids are meant to be passed back directly as the OpenAI `model` field.
No.
`/v1/models` lists model choices, not execution topology. Agents and sub-agents are OpenClaw routing concerns, so they are selected separately with `x-openclaw-agent-id` or the `openclaw:<agentId>` / `agent:<agentId>` model aliases on chat and responses requests.
Send `x-openclaw-agent-id: ` when you want the model list for a specific agent.
OpenClaw filters the model list against that agent's allowed models and fallbacks when configured. If no allowlist is configured, the endpoint returns the full catalog.
Sub-agent model choice is resolved at spawn time from OpenClaw agent config.
That means sub-agent model selection does not create extra `/v1/models` entries. Keep the compatibility list flat, and treat agent and sub-agent selection as separate OpenClaw-native routing behavior.
Use `/v1/models` to populate the normal model picker.
If your client or integration also knows which OpenClaw agent it wants, set `x-openclaw-agent-id` when listing models and when sending chat, responses, or embeddings requests. That keeps the picker aligned with the target agent's allowed model set.
Streaming (SSE)
Set stream: true to receive Server-Sent Events (SSE):
Content-Type: text/event-stream- Each event line is
data: <json> - Stream ends with
data: [DONE]
Examples
Non-streaming:
curl -sS http://127.0.0.1:18789/v1/chat/completions \
-H 'Authorization: Bearer YOUR_TOKEN' \
-H 'Content-Type: application/json' \
-H 'x-openclaw-agent-id: main' \
-d '{
"model": "openclaw",
"messages": [{"role":"user","content":"hi"}]
}'
Streaming:
curl -N http://127.0.0.1:18789/v1/chat/completions \
-H 'Authorization: Bearer YOUR_TOKEN' \
-H 'Content-Type: application/json' \
-H 'x-openclaw-agent-id: main' \
-d '{
"model": "openclaw",
"stream": true,
"messages": [{"role":"user","content":"hi"}]
}'
List models:
curl -sS http://127.0.0.1:18789/v1/models \
-H 'Authorization: Bearer YOUR_TOKEN'
Fetch one model:
curl -sS http://127.0.0.1:18789/v1/models/openai%2Fgpt-5.4 \
-H 'Authorization: Bearer YOUR_TOKEN'
Create embeddings:
curl -sS http://127.0.0.1:18789/v1/embeddings \
-H 'Authorization: Bearer YOUR_TOKEN' \
-H 'Content-Type: application/json' \
-H 'x-openclaw-agent-id: main' \
-d '{
"model": "openai/text-embedding-3-small",
"input": ["alpha", "beta"]
}'
Notes:
/v1/modelsreturns canonical ids inprovider/modelform so they can be passed back directly as OpenAImodelvalues./v1/modelsstays flat on purpose: it does not enumerate agents or sub-agents as pseudo-model ids./v1/embeddingssupportsinputas a string or array of strings.