Messages. - Layer X1

Endpoint

POST /v1/messages

Authenticate with x-api-key: lx1_... (a bearer token also works). Any model in the catalog is valid in model.

Request parameters

Parameter	Type	Notes
`model`	string · required	Any catalog id, e.g. `lx1-sonnet-4.6`.
`max_tokens`	integer · required	Output ceiling. On reasoning models, hidden reasoning counts against it — budget generously.
`messages`	array · required	Alternating turns. Content is a string or an array of blocks: `text`, `image` (base64), `document` (PDF), `tool_result`.
`system`	string \| array	System prompt.
`tools`	array	Tool definitions with JSON-schema input. See Tool calling.
`tool_choice`	object	`{ "type": "auto" \| "any" \| "tool" }`.
`temperature`	number	Sampling temperature.
`top_p`	number	Nucleus sampling.
`stop_sequences`	string[]	Custom stop sequences.
`stream`	boolean	Anthropic SSE event stream when `true`.
`thinking`	object	`{ "type": "enabled" }` surfaces the model’s reasoning as a `thinking` block. See Reasoning.
`metadata`	object	`metadata.user_id` doubles as a conversation-stable cache-affinity hint. See Prompt caching.

Image blocks need a model that declares capabilities.vision, and PDF document blocks a model that declares capabilities.documents — both are short lists, so read them off GET /v1/models rather than guessing. A model that cannot read images rejects them with a 400. See Vision.

Example

curl https://api.layerx1.com/v1/messages \
  -H "x-api-key: $LAYERX1_API_KEY" \
  -H "content-type: application/json" \
  -d '{
    "model": "lx1-sonnet-4.6",
    "max_tokens": 512,
    "system": "You are concise.",
    "messages": [{ "role": "user", "content": "Say hi." }]
  }'

import anthropic

client = anthropic.Anthropic(
    base_url="https://api.layerx1.com",
    api_key="lx1_your_key",
)

msg = client.messages.create(
    model="lx1-sonnet-4.6",
    max_tokens=512,
    system="You are concise.",
    messages=[{"role": "user", "content": "Say hi."}],
)
print(msg.content[0].text)

import Anthropic from "@anthropic-ai/sdk";

const client = new Anthropic({
  baseURL: "https://api.layerx1.com",
  apiKey: process.env.LAYERX1_API_KEY,
});

const msg = await client.messages.create({
  model: "lx1-sonnet-4.6",
  max_tokens: 512,
  system: "You are concise.",
  messages: [{ role: "user", content: "Say hi." }],
});
console.log(msg.content[0].type === "text" ? msg.content[0].text : "");

Response (shape)

{
  "id": "msg_...",
  "type": "message",
  "role": "assistant",
  "model": "lx1-sonnet-4.6",
  "content": [{ "type": "text", "text": "Hi." }],
  "stop_reason": "end_turn",
  "usage": { "input_tokens": 14, "output_tokens": 3 }
}

Response fields

Field	Notes
`content`	Array of blocks — `text`, and `tool_use` when the model calls a tool.
`stop_reason`	`end_turn`, `max_tokens`, `stop_sequence`, or `tool_use`.
`usage`	Input and output token counts for the request.

Streaming

With stream: true the response is the Anthropic SSE event sequence — message_start, content_block_start, content_block_delta, content_block_stop, message_delta, message_stop — exactly what the Anthropic SDKs expect.

curl -N https://api.layerx1.com/v1/messages \
  -H "x-api-key: $LAYERX1_API_KEY" \
  -H "content-type: application/json" \
  -d '{
    "model": "lx1-gpt-oss-120b",
    "max_tokens": 256,
    "stream": true,
    "messages": [{ "role": "user", "content": "Count to five." }]
  }'

with client.messages.stream(
    model="lx1-gpt-oss-120b",
    max_tokens=256,
    messages=[{"role": "user", "content": "Count to five."}],
) as stream:
    for text in stream.text_stream:
        print(text, end="")

const stream = client.messages.stream({
  model: "lx1-gpt-oss-120b",
  max_tokens: 256,
  messages: [{ role: "user", content: "Count to five." }],
});
stream.on("text", (t) => process.stdout.write(t));
await stream.finalMessage();

Errors

Failures return standard status codes with Anthropic-shaped bodies ({ "type": "error", "error": { ... } }). Retry on 429/5xx with backoff and honor retry-after. Full reference: Errors.