Models

client.chat.completions.create posts to /v1/chat/completions. Required fields are model and messages; common options include temperature, max_tokens, tools, tool_choice, and response_format. The scope is model:invoke.

const completion = await client.chat.completions.create({
  model: "claude-opus-4-8",
  messages: [
    { role: "system", content: "You are concise." },
    { role: "user", content: "Name three primary colors." },
  ],
  max_tokens: 256,
});
console.log(completion.choices[0].message.content);

Pass stream: true and the call resolves to an AsyncIterable of chunks (the gateway responds with text/event-stream). Read chunk.choices[0].delta.content for each token.

const stream = await client.chat.completions.create({
  model: "claude-opus-4-8",
  messages: [{ role: "user", content: "Write a haiku about the sea." }],
  stream: true,
});
for await (const chunk of stream) {
  const delta = chunk.choices?.[0]?.delta?.content;
  if (delta) process.stdout.write(delta);
}

client.responses.create posts to /v1/responses (OpenAI-compatible Responses payload, passthrough). It also supports stream: true, returning an AsyncIterable of chunks.

const result = await client.responses.create({
  model: "gpt-5.5",
  input: "Summarize the SeaChat API in one paragraph.",
});

client.models.list() (GET /v1/models) lists available modalities/models. client.models.get(path) (GET /v1/models/{path}) reads a sub-resource; pass a modality such as "image" or "embedding" to enumerate that modality's deployment-specific model ids. Filter to availability.state === "live_ok" before using one.

curl https://seachat.ai/v1/models \
  -H "Authorization: Bearer $SEACHAT_API_KEY"