Integrations
n8n
n8n with siati.ai: an OpenAI credential with siati.ai's base URL, the OpenAI Chat Model with the Responses API switched off, and embeddings in batches of 32.
Last updated: 2026-10-11
Credential
Create an OpenAI credential:
| Field | Value |
|---|---|
| API Key | your key, sk-… |
| Organization ID (optional) | empty |
| Base URL | https://api.siati.ai/v1 |
n8n checks the credential by reading https://api.siati.ai/v1/models.
OpenAI Chat Model
The OpenAI Chat Model node, under an AI Agent or a chain:
| Setting | Value |
|---|---|
| Credential | the one above |
| Model | By ID: apertus-70b-instruct, or another chat model of the catalogue |
| Use Responses API | off |
| Options → Maximum Number of Tokens | 8192 or less, or leave it unset |
From List shows every model of /v1/models, including those that do not
chat, such as bge-m3 and whisper-1. By ID avoids picking one of them.
For an AI Agent with tools, use a model that calls them: qwen3.8-27b,
qwen3.6-35b, qwen3-coder-30b, gpt-oss-120b, gemma-4-26b or
ministral-3-14b did on 11 October 2026.
Embeddings OpenAI
For a vector store, the Embeddings OpenAI node with the same credential:
| Setting | Value |
|---|---|
| Model | bge-m3 |
| Options → Batch Size | 32 |
The node sends 512 texts per request by default, and /v1/embeddings takes at
most 32. The vectors have 1,024 dimensions: set the vector store to match, and
leave Dimensions unset.
Limits
- Maximum Number of Tokens up to 8192. n8n allows up to 32,768; the API
refuses more than 8,192 with
422. - On
qwen3.8-27bthe reasoning counts against that maximum: a low value gives a cut or empty answer.